i

The stability of tolerance of Sorghum spp to Striga asiatica

L. Kuntze under diverse conditions and existence of pre-

attachment resistance

Mandumbu Ronald (201317414)

A Thesis Submitted to the Faculty of Science and Agriculture in

Fulfillment of the Requirements of the Degree of Doctor of Philosophy

Department of Agronomy

Faculty of Science and Agriculture

University of Fort Hare

July 2017

ii

DECLARATION

I Ronald Mandumbu, declare that the work contained in this thesis is entirely my own work

and that all reference materials contained in this thesis have been duly acknowledged. This

thesis has not been previously submitted to this or any other University for the award of a

degree.

Signature………………………………………………

Date…………………………………………………….

iii

PUBLICATIONS

1. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2016). Existence of different

physiological strains of Striga asiatica (L.) Kuntze on Sorghum spp [Sorghum bicolor

and Sorghum arundinaceum (Desv) Stapf) in Zimbabwe. Research on Crops 17 (3):

468 – 478. DOI10.5958/2348-7542.2016.00077.2

2. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2017) The effect of witchweed

(Striga asiatica) infestation and moisture stress on selected morpho-physiological

traits of sorghum in Zimbabwe. Journal of Agronomy 16 (2): 65 - 75.

3. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2017) determination of resistance

to Striga asiatica (L.) Kuntze using agar jel analysis and sand culture in Sorghum

bicolor and Sorghum arundinaceum in Zimbabwe. Accepted by the Asian Journal of

Crop Science.

4. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2017) Response of Sorghum

bicolor (L) Moench and Sorghum arundinaceum (Desv) Stapf to Striga asiatica (L)

Kuntze infestation under mulch. Accepted by Tropical Agriculture .

5. Mandumbu R, Mutengwa C, Mabasa S and Mwenje E (2017). The Striga scourge

under changing climate in southern Africa: A perspective. Accpeted by Journal of

Biological Science.

6. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2017). Factors affecting the

success of resistance as a management strategy in Striga management: A review.

Under review with the Asian Journal of Plant Science.

iv

PREFACE

This thesis is presented in a form of a General Introduction (Chapter 1) and Literature

Review (Chapter 2) which introduces the reader to sorghum and Striga issues in Zimbabwe

and elsewhere in the world. Chapter three deals with the simultaneous effect of reduced water

availability and Striga asiatica infestation on the morpho-physiological attributes of

sorghum. Chapter four investigates the effect of mulching as a cultural practice on the

stability of tolerance by Sorghum spp to Striga asiatica. Chapter five focuses on the variable

effects of two Striga asiatica strains sourced from two distant places in Zimbabwe on

sorghum productivity and the stability of tolerance. Chapter 6 deals with the quantification of

strigolactones in Sorghum bicolor and Sorghum arundinaceaum and determines the

relationship between strigolactone quantities and sorghum tillering. Finally, the general

discussion, conclusions and recommendations are reported in the last chapter (Chapter 7).

This thesis was written in paper format and there is therefore unavoidable repetition of some

information, including references.

v

ABSTRACT

Sorghum is the fifth most important cereal in the world and a staple food for humans. It is

also a source of food and fodder for animals. In addition to the abiotic stresses such as

drought, parasitic weeds of the genus Striga cause losses in sorghum production in sub

Saharan Africa. Striga asiatica is a parasitic weed that attacks cereals in low input

agricultural systems and is distributed throughout semi- arid regions of Africa. Most sorghum

producing farmers rely on tolerance for their harvests in Striga infested fields yet the stability

of tolerance in the face of a changing climate (recurrent droughts), new farming systems

(mulch based agriculture) and existence of various Striga strains needs further investigation.

Reduced strigolactones production was also studied as a resistance mechanism.

The first study was focused on the determination of tolerance of Striga asiatica infested

sorghum under drought in a pot study. Five sorghum lines were subjected to infestation with

Striga and some were not infested while watering was done at 50 % field capacity (FC) and

100% FC. The results showed that the five sorghum lines differed significantly in chlorophyll

content and Normalised Differential Vegetation Index (NDVI). Infection did not lower

chlorophyll content when it co-occurred with drought across all sorghum lines. Drought and

infestation had mutually exclusive effects on chlorophyll content and NDVI. Under

infestation, internode length was similar both at 100 % FC and at 50 % FC while under

uninfested conditions, 100 % FC gave the longer internode compared to 50 % FC. Both

infestation and irrigation regime reduced the sorghum head weight, illustrating that the two

effects have synergistic effects on sorghum head weight.

The second study sought to determine the effects of mulching and infestation on sorghum spp

tolerance to Striga asiatica. The experiments were carried out in the seasons 2013/14 and

2014/15 summer seasons. The results indicated that mulching increased chlorophyll content

vi

in the 2014/15 season which was a drier season compared to 2013/14. In the 2014/15 season,

mulching increased chlorophyll content in all varieties except Ruzangwaya, Mukadziusaende

and SC Sila. When the same varieties were infested under mulch and infested without mulch,

the results showed that mulching overcomes the effects of infestation in some varieties.

Mulch also negates the effect of Striga parasitism and results in yield maintenance in

sorghum varieties.

The third study sought to determine the stability of sorghum lines when exposed to two

Striga asiatica lines sourced from two places which are 500 km apart in Zimbabwe. The two

strains were termed the Chiundura and Rushinga strains, based on where they were sourced.

The experiments were conducted at Henderson Research Station (HRS) at Mazoe and at

Bindura University of Science Education (BUSE). The results showed differential virulence

for some traits while the two strains were equally virulent for some traits. The two strains

were equally virulent on all sorghum lines with respect to chlorophyll content. The different

sorghum lines responded differently to the effects of the two strains. The effects of the two

strains were generally similar for head index, root index, and leaf index at all sites. Generally

the Chiundura strain was more virulent to sorghum lines compared to Rushinga strain,

confirming the existence of physiological strains of Striga in Zimbabwe. Therefore

physiological speciation of Striga asiatica exists and this adds a further dimension to the

complexity of Striga management in the smallholder sector.

Quantification of strigolactone production by different sorghum genotypes was conducted in

the laboratory using the agar gel assay. The genotype Mukadziusaende produced

significantly the least (P<0.01) quantities of strigolactones, as inferred from the maximum

germination distance (MGD) from the sorghum root. The MGD was negatively correlated to

tiller numbers illustrating that the more the strigolactones the less the tillering capacity. Tiller

numbers and MGD can therefore be used to select for reduced strigolactones production.

vii

Key words

Sorghum bicolor, Sorghum arundinaceum, Striga asiatica, resistance, tolerance, drought,

mulch, physiological speciation, strigolactones.

viii

DEDICATION

This study is dedicated to my wife, Virginia, my children, Praise, Gladiness, Anesu and Ruth,

my parents Ndedza and Enita Mandumbu.

ix

ACKNOWLEDGEMENTS

In a doctoral study, one is indebted to so many sources of assistance that it is practically

impossible to list them all. At the risk of omission, I would like particularly to thank the

people and institutions listed below.

I would like to thank my supervisors: Professor C.S. Mutengwa, Dr Stanford Mabasa and

Professor Eddie Mwenje for their guidance throughout the course of this work. This work

was made possible by the financial assistance from the Zimbabwe Manpower Development

Fund (ZIMDEF), the Research Council of Zimbabwe (RCZ) and the Research and Post

Graduate Centre of the Bindura University of Science Education (BUSE).

I want to thank Mr Chikaka, Mr Gochera, Zengeza Tapiwa, Chitaukire Charity and Maramba

Komborero, Mr Kufa Mutsengi and Munyati Vincent for the assistance of setting the

experiments and data collection. Mr Senga and Mr Kamhapa for the assistance in laboratory

work. Mr Parwada and Mr Mafuse for assembling at our reading hub as we had the same

challenges of coming up with a thesis. The Weed Research Team at Henderson Research

station is acknowledged for their assistance with space and data collection for the

experiments which were carried out there. I also want to thank the Mafirenyika family for

hosting me in East London every time I was in South Africa. They made my stay a

memorable experience with great dinners, break fast and sight seeing. I also want to thank my

brothers and sisters who include Tongai, Pesanai, Georgina, Tawanda, Solomon, Ruvarashe

and Chiedza and their families for inspiration. I also thank Diriri Simbarashe and family for

their support. My brother Zvamaida Gumbo is acknowledged for teaching me to read, I am

sure you also did not know it was coming to this. To Effort Macheza, Noel Gumbo and

Model Macheza, the button is now in your hands and the tracklines are open.

Never should I forget the Lord Jesus Christ for His unwarranted favour, for giving me

strength and wisdom to complete this study. Last but definitely not least I want to thank

Prophet Emmanuel Makandiwa, Prophetess Ruth Makandiwa and the whole United Family

International Church for the teachings, motivation and inspiration I got which have kept me

going and grounded in the word of God. And He said I give unto you POWER.

x

Table of Contents

PREFACE ................................................................................................................................. iv

ABSTRACT ............................................................................................................................... v

DEDICATION ....................................................................................................................... viii

ACKNOWLEDGEMENTS ...................................................................................................... ix

1.1 Statement of the problem ................................................................................................. 1

1.2 Justification of the study .................................................................................................. 5

1.3 Main objective .................................................................................................................. 7

1.4 Specific objectives............................................................................................................ 7

References .............................................................................................................................. 9

CHAPTER TWO: LITERATURE REVIEW ......................................................................... 15

2.1. Introduction to literature review .................................................................................... 15

2.2 Sorghum production in Zimbabwe ................................................................................. 15

2.3 The genus Striga............................................................................................................. 16

2.3.1 Striga hermonthica ................................................................................................... 17

2.3.2 Striga asiatica ........................................................................................................... 17

2.3.3 Striga gesneroides .................................................................................................... 18

2.4 Extent of the Striga problem in sub-Saharan Africa ...................................................... 19

2.5 Striga problem in the smallholder sector of Zimbabwe ................................................. 20

2.6 History and distribution of Striga asiatica in Zimbabwe ............................................... 24

2.7 Striga asiatica research in Zimbabwe ............................................................................ 24

2.8 Striga asiatica lifecycle .................................................................................................. 27

2.8.1 Dormancy and conditioning .................................................................................... 27

2.8.2 Germination ............................................................................................................. 28

2.8.3 Haustorium development ......................................................................................... 28

2.8.5 Establishment of parasitism and flowering ............................................................. 30

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2.9. Strigolactones in plants ................................................................................................. 31

2.10 The parasite as a sink ................................................................................................... 33

2.11 Mechanisms of sorghum tolerance to Striga asiatica .................................................. 33

2.11.1 Host photosynthesis ............................................................................................... 33

2.11.2 Sorghum tillering as Striga tolerance mechanism ................................................. 35

2.11.3 Environmental regulation of tillering ....................................................................... 36

2.12.1 Propensity to tiller ................................................................................................. 36

2.13 Host plant resistance against Striga ............................................................................. 37

2.13.1 Reduced host stimulant production ....................................................................... 37

2.13.2 Reduced haustorium inducing factors (Low haustorial factor) ............................ 38

2.13.3 Parasite establishment resistance ........................................................................... 39

2.13.4 Post-attachment resistance ..................................................................................... 39

2.13.5 Incompatible response (IR) ................................................................................... 39

2.13.6 Hypersensitive response ........................................................................................ 40

2.14 Managing Striga asiatica in sub-Saharan Africa ......................................................... 40

2.15. Sorghum response to drought stress ............................................................................ 42

2.16 Existence of Striga physiological speciation and differential virulence ...................... 43

2.17 Mulch effects on Striga asiatica incidence .................................................................. 44

2.18 Photosynthesis in a Striga-infested plant ..................................................................... 46

2.18.1 Stomatal conductance ............................................................................................ 47

Chapter Three: ......................................................................................................................... 68

The effect of witchweed (Striga asiatica L. Kuntze) and moisture stress on selected morpho-

physiological traits which impart tolerance to Sorghum spp ................................................... 68

3.1 Abstract .......................................................................................................................... 68

3.2 Introduction .................................................................................................................... 69

3.3 Methodology .................................................................................................................. 73

3.3.1 Experimental site ..................................................................................................... 73

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3.3.3 Experimental design and treatments ........................................................................ 73

3.3.5 Irrigation .................................................................................................................. 74

3.3.6 Data collection ......................................................................................................... 74

3.4 Results ............................................................................................................................ 75

3.4.1 Chlorophyll concentration and NDVI ......................................................................... 75

3.4.2 Dry matter traits ....................................................................................................... 81

3.5 Discussion ...................................................................................................................... 89

References ............................................................................................................................ 94

CHAPTER FOUR:................................................................................................................. 103

The response of tolerance traits of Sorghum bicolor (L) Moench and Sorghum arundinaceum

(Desv) Stapf to Striga asiatica (L) Kuntze infestation under mulch ..................................... 103

4.1 Abstract ........................................................................................................................ 103

4.3 Materials and methods ................................................................................................. 106

4.3.1 Experimental site ................................................................................................... 106

4.3.2 Experimental design and pot layout ...................................................................... 106

4.3.4 Source of Seeds ..................................................................................................... 107

4.4 Results .......................................................................................................................... 108

4.4.4 Plant height ............................................................................................................ 114

4.4.5 Grain yield ............................................................................................................. 119

4.5 Discussion .................................................................................................................... 121

6.0 References .................................................................................................................... 126

The existence of different physiological ‘strains’ of Striga asiatica (L.) kuntze on Sorghum

bicolor (L.) Moench and Sorghum arundinaceum (desv) Stapf in Zimbabwe ...................... 131

5.1 Abstract ........................................................................................................................ 131

5.2 Introduction .................................................................................................................. 132

5.3 Materials and Methods ................................................................................................. 134

5.3.1 Experimental sites.................................................................................................. 134

5.3.4 Experimental details .............................................................................................. 135

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5.3.5 Data Collection ...................................................................................................... 136

5.4 Results .......................................................................................................................... 136

5.4.1 Sorghum plant height............................................................................................. 136

5.4.3 Sorghum tillering ................................................................................................... 143

5.4.4 Sorghum dry matter traits ...................................................................................... 145

5.4.5 Sorghum head weight ............................................................................................ 148

5.4.6 Total dry weight..................................................................................................... 150

5.5 Discussion .................................................................................................................... 152

5.7 References .................................................................................................................... 156

CHAPTER SIX ...................................................................................................................... 161

Sorghum response to Striga asiatica based on maximum germination distance, Striga counts

and sorghum tillering in Zimbabwe ....................................................................................... 161

6.1 Abstract ........................................................................................................................ 161

6.2 Introduction .................................................................................................................. 162

6.3 Materials and methods ................................................................................................. 165

6.3.1 Experiment 1: Agar jel assays ................................................................................... 165

6.3.2 Sorghum germplasm and Striga asiatica seed sources ............................................. 165

6.3.3 Experimental design .................................................................................................. 165

6.3.4 Surface Sterilisation and sorghum seed germination ................................................ 165

6.3.5 Conditioning of Striga seed ................................................................................... 166

6.3.6 The assay set up ..................................................................................................... 166

6.5 Results .......................................................................................................................... 167

6.5.1 Maximum germination distance (MGD) ................................................................... 167

6.5.2 Tillering ..................................................................................................................... 168

6.5.3 Striga counts .............................................................................................................. 169

6.5.3 Correlations between maximum germination distance, tillering and Striga counts . 170

6.6 Discussion .................................................................................................................... 171

xiv

6.7 Conclusion .................................................................................................................... 173

6.8 References ............................................................................................................... 173

CHAPTER SEVEN: GENERAL DISCUSSION, CONCLUSIONS AND

RECOMMENDATIONS ................................................................................................... 178

7.1 Introduction .................................................................................................................. 178

7.2 Discussion .................................................................................................................... 178

7.3 Conclusions .................................................................................................................. 180

7.4. Recommendations for further research ....................................................................... 181

xv

List of tables

Table 2.1: Zimbabwe sorghum production by year from 2010 - 2014 .................................... 16

Table 2.2: The distribution and occurrence of Striga spp in sub-Saharan Africa .................... 18

Table 2.3: Agro-ecological regions of Zimbabwe and agricultural activities carried out in the

various regions. ........................................................................................................................ 22

Table 2.4: Different methods of controlling Striga asiatica ..................................................... 40

Table 3.1: Sorghum genotypes effects on chlorophyll content at 6 and 10 WACE ................ 76

Table 3.2: Moisture stress effects on NDVI at 6 and 10 WACE ............................................. 77

Table 3.3: Effect of S. asiatica infection on chlorophyll content of sorghum ......................... 79

Table 3.5: Effect of sorghum genotypes on head weight and head index ............................... 82

Table 3.6: The effect of infection on head weight and head index .......................................... 83

Table 3.6: The effect of water availability on head weight and head index across the two

experiments .............................................................................................................................. 83

Table 3.7: Effect of sorghum genotypes on leaf dry matter, leaf index, stem weight and index

and total dry matter in both experiments ................................................................................. 86

Table 3.8: The effect of infection on leaf weight and index, stem weight and index and total

dry matter in both experiments. ............................................................................................... 86

Table 3.9: The effects of water availability on leaf weight and index, stem weight and index

and total dry matter. ................................................................................................................. 87

Table 4.1: Sorghum genotypes tested for tolerance to Striga in the 2013/14 and 2014/15

seasons ................................................................................................................................... 107

Table 4.2: Effect of mulching on chlorophyll concentration for the 2013/14 and 2014/15

summer seasons ..................................................................................................................... 109

Table 4.6: Effect of sorghum variety on Striga counts .......................................................... 113

Table 4.7: Effects of infestation on plant height at 8 and 12 WACE in the year 2013/14 and

2014/15 seasons. .................................................................................................................... 117

Table 5.4: Effect of sorghum genotypes on head index, root index, stem index and leaf index

at BUSE and Henderson sites. ............................................................................................... 146

Table 5.5: Effect of Striga strains on head, root, stem and leaf index at BUSE and Henderson.

................................................................................................................................................ 147

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xvii

List of figures

Figure 2.1: The Natural Farming Regions of Zimbabwe ......................................................... 21

Figure 2.2: The life cycle of S. asiatica (Rich and Ejeta, 2007). ............................................. 27

Figure 3.1: Interaction effects of sorghum genotype and moisture availability on NDVI at 10

WACE in Experiment II. ......................................................................................................... 78

Figure 3.2: Interaction effects of sorghum genotypes and water availability on chlorophyll

concentration at 6 WACE in Experiment II. ............................................................................ 79

Figure 3.3: Effect of Striga infestation on internode length. ................................................... 80

Figure 3.4: Interaction effects of Striga infestation and water availability on sorghum

internode length. ...................................................................................................................... 81

Figure 3.3: The response of sorghum genotypes yield to moisture availability. ..................... 84

Figure3.6: Interaction effects of water availability and Striga infestation on leaf index. ....... 88

Figure 3.7: Interaction effects of sorghum genotypes and Striga asiatica infestation on stem

weight ....................................................................................................................................... 89

Figure 4.1: Effect of infestation on chlorophyll concentration at 6 WACE during the 2014/

15 season. ............................................................................................................................... 109

Figure 4.2: Interaction between variety and Striga infestation a) 6 WACE andvariety and

mulch b) 8 WACE on chlorophyll concentration ................................................................. 110

Figure 4.3: Effect of infestation status on stomatal conductance for the sorghum genotypes

during the 2013/14 season. .................................................................................................... 111

Figure 4.4: Effect of season on tiller numbers over two seasons........................................... 112

Figure 4.6: Interaction effects of sorghum genotype and S. asiatica infection on sorghum

height in the 2014/15 season at 8 and 12 WACE. ................................................................. 115

Figure 4.7: Interaction effects of sorghum genotype, mulching and infestation on plant height

in the 2014/15 season. ............................................................................................................ 116

Figure 4.8: Interaction effects of sorghum variety and infestation on plant height at 4, 8 and

12 WACE during the 2013 season. ........................................................................................ 118

Figure 4.9: Interaction effects of sorghum genotypes and infestation on sorghum yield for the

2013/14 season ....................................................................................................................... 119

Figure 4.10: Effect of sorghum genotypes, infestation and mulching on sorghum yield in the

2014/15 season ....................................................................................................................... 120

xviii

Figure 5.1: Interaction effects of sorghum genotypes and Striga strain on sorghum height at 6,

8 and 12 WACE at Henderson research station. .................................................................... 138

Figure 5.2: Interaction effects of sorghum genotype and Striga strains at 12 WACE at BUSE

................................................................................................................................................ 139

Figure 5.3: Interaction effects of sorghum genotype and Striga strains on chlorophyll content

at 10 WACE at both sites ....................................................................................................... 143

Figure 5.4: Effect of sorghum variety on tiller number at 12 WACE at both sites ............... 144

Figure 5.5: Effect of Striga strains on tiller number. ............................................................. 145

Figure 5.7: Interaction effects of sorghum genotypes and Striga strain at BUSE and

Henderson .............................................................................................................................. 149

Figure 5.8: Total dry matter of sorghum genotypes for BUSE and Henderson .................... 150

Figure 5.9: Interaction effects of sorghum genotype and Striga strain on total dry mass at

BUSE ..................................................................................................................................... 151

Figure 6.1: Maximumgermination distances for various sorghum genotypes……….….....168

Figure 6.2: Effect of Striga asiatica on tillering of sorghum genotypes ................................ 169

Figure 6.3: Effect of Sorghum genotypes on Striga counts ................................................... 169

Figure 6.4 : The relationship between germination distance and tiller numbers in

sorghum.................................................................................................................................170

Figure 6.5: Relationship between sorghum yield and tiller numbers………..…………..…171

xix

List of Acronyms

WACE – Weeks after crop emergence

FC – Field capacity

NDVI—Normalised vegetation difference index

BUSE – Bindura University of Science Education

HRS—Henderson research Station

MGD—Maximum germination distance

1

CHAPTER ONE: INTRODUCTION

1.1 Statement of the problem

Sorghum (Sorghum bicolor L. Moench) is an important crop in traditional farming systems

and in the diet of millions of people in the semi-arid tropics (Haussmann et al., 2001). It is an

annual C4 crop commonly consumed as human food and livestock feed and it feeds more than

500 million people in 98 countries in Africa, Asia and America (Pennissi, 2009). It is one of

the top five cereal grains produced worldwide (Burdette, 2007). In Zimbabwe, it is ranked the

third most important cereal after maize and wheat (FAO, 1996). It can maintain remarkable

yield potential in environments that are normally too extreme for other C4 plants (Tari et al.,

2013).One of the remarkable characteristics of sorghum is its drought tolerance, which has

made it an important cereal grown for food and beverages by resource poor farmers in sub-

Saharan Africa. . Sorghum represents a large proportion of the calorie intake of the people in

sub-Saharan Africa. White sorghum is ground into flour mostly for making sadza (a stiff

dumpling), beverages and porridge (Mutengwa, 2004). It can be popped like popcorn to

create a delicious snack food.

Among a myriad of factors constraining sorghum production, Striga is the major biological

constraint that hinders increased sorghum production in the small-holder sector of sub-

Saharan Africa. Striga species are a major parasitic weedy pest throughout the semi-arid sub-

Saharan Africa and many parts of Asia (Rubiales et al., 2009). Many cropping fields in

African countries including, Tanzania, Kenya, Malawi, Madagascar, Botswana, Zimbabwe,

Gabon, Nigeria, Ethiopia, Niger, Togo, Benin and Burkina Faso are highly infested with

Striga causing serious yield losses that are as high as 100 % at some sites (Lagoke et al.,

1988; Badu-Apraku et al., 2014; Bozkurt et al., 2014). In Kenya, crop losses have been

reported to be as high as 100 % in sorghum. For maize, losses of 50 % under ‘moderate’

2

infestation and 87 % under heavy infestation have also been reported (Manyong et al., 2007).

In Zimbabwe, complete crop failure has been reported by Mabasa (2003). The parasite is a

major constraint to subsistence agriculture in Africa such that resource poor farmers are

sometimes forced to abandon their fields with grave consequences to their families (Berner et

al., 1995; Ejeta, 2007). In particular, major crops that supply the bulk of the energy and

protein needs of the poor in the African savannah, namely maize, sorghum, millets, upland

rice and cowpeas have been severely vulnerable (Ejeta, 2005).

Losses from Striga are compounded because of the tendency of crops grown under severe

moisture and poor fertility conditions to show significant predisposition to Striga. According

to Timko et al., (2012), two thirds of the farmland under cultivation in sub-Saharan Africa is

infested with one or more Striga spp directly affecting livelihoods of more than 300 million

people in 25 countries. According to Scholes and Press (2008) and Ejeta (2007), over 50

million hectares of arable farmland under cultivation with cereals and legumes in sub-

Saharan Africa are infested with one or more Striga species. In many of these places, the

Striga has reached epidemic proportions presenting a desperate situation in subsistence

agriculture (Ejeta and Butler, 1993). The weed causes annual losses of yield estimated to be

in excess of US$10 billion (Ejeta, 2007). Striga spp affects the welfare and livelihoods of

over 100 million people in Africa (Rubiales et al., 2009). According to Parker (2009), the

weed has impacted on the sub-region’s economy. Striga spp stand as a major constraint that

prevents attainment of household food security for some of the world’s poorly resourced

people.

The Striga problem in sub-Saharan Africa is made worse by its exquisite adaptation to the

climatic conditions of the semi-arid tropics, its high fecundity and longevity of its seed

reserves in the tropical soils (Ejeta, 2007). The problem is tending to increase rather than

decrease as intensive land use and lack of fertilizers leads to continued decline in soil fertility

3

which greatly favours Striga (Parker, 2012). The climatic conditions of sub-Saharan Africa

permit timely break down of seed dormancy and conditioning of Striga seeds. Striga asiatica

has a high reproductive capacity, producing 10 000 to 20 000 seeds per plant (Hearne, 2009).

Striga seeds have very small dimensions (0.3 nm * 0.15 nm) and are light (4 – 7 ug) such that

they are easily dispersed by wind, water and animals. The viability of Striga seed goes

beyond 20 years in the soil and this creates seed banks that are difficult to manage.

The life cycle of the noxious cereal weed S.asiatica is complex and has co-evolved with

many hosts to comprise a series of discrete steps that are tightly coupled with the host’s

biochemistry, life cycle and genotype (Bouwmeester et al., 2003). The parasitic plant grows

underground for 4 – 7 weeks prior to emergence and utilizes host water, nutrients and

photosynthates (Jamil et al., 2012). Yoneyama et al., (2010) reported that seeds of parasitic

Striga only germinate after perceiving a germination stimulant (strigolactones) from their

host. The concentration of the stimulant required to initiate germination are as low as 10-18

M

soil solution (Stewart and Press, 1990, Yoneyama et al., 2007).

No single completely effective and practical method to eliminate Striga is known (Bozkurt et

al., 2014). Over the years, many promising Striga control strategies have been suggested in

various formats, with some suggestions appearing in multiple incarnations (Hearne, 2009).

Inspite of all this valuable work, adoption and utility of control methods is limited. The

control measures are neither fully effective nor easy to apply. Only marginal successes have

been obtained to date (Joel et al., 2006). As a result, yield loss attributable to Striga is acute,

as noted before (De Groote et al., 2008). Hence Striga continues to present a challenge for

the forseable future, not only in the areas already affected but also in terms of introduction

into new areas (Parker, 2012).

4

Host plant defense against Striga spp is the only sustainable route for Striga control. It

constitutes two complimentary mechanisms and these are resistance and tolerance. According

to Kim (1994) and Badu-Apraku et al., (2006) resistance to Striga refers to the ability of a

host plant to stimulate the germination of Striga seeds but prevent the attachment of the

parasite to its roots or kill the attached parasite. Host resistance is multi-dimensional with

both general and specific defence mechanisms that can disrupt critical steps throughout the

parasite’s life. Kim (1994) and Rodenburg and Bastiaans (2011) reported that a Striga

tolerant genotype germinates and supports many Striga plants as the intolerant ones, but

produces more grain and stover and shows fewer damage symptoms. Different cultivars may

differ in their capacity to tolerate the physiological and pathological effects caused by Striga

parasitism, finally resulting in milder or stronger impacts on crop yield (Cardoso et al., 2011).

There is only a marginal role of tolerance in the exploitation of host plant defense in sorghum

against Striga asiatica. Resistance is neither complete nor everlasting. The high level of

genetic variation in Striga populations, combined with typical high seed production rates

threatens the durability of resistance. The loss of resistance can be disastrous as the parasite

depends on the staple crops of rural farmers. Tolerance will act as a ‘safety net’ that prevents

a sudden and unforeseen collapse in food supply (Rodenburg and Bastiaans, 2011).

According to Gurney et al., (2003), the control of Striga has proved challenging, mostly as a

result of intricate life cycle of the parasite with the host. Much research has therefore focused

on the development of cereals resistant to infection as a sustainable long term solution.

Complete resistance has not been identified in sorghum although varieties differ in their

sensitivity to infection (Gurney et al., 1995). Therefore, the traits that reduce fitness impacts

of damage such as increased photosynthesis, compensatory growth, architecture of auxillary

buds and carbon storage organs are very critical in varietal selection under Striga infestation.

5

Understanding the mechanisms that plants use to defend themselves and the ecological

drivers thereof has been a major research problem (Hartmann, 2008; Agrawal, 2011).

1.2 Justification of the study

Despite cultivating the sorghum crop in S. asiatica infested fields, some level of yield has

been maintained in sorghum due to tolerance. Tolerance gives the ability to produce yield

despite Striga infestation. The stability of tolerance may be affected by exogeneous

environmental drivers such as athropogenically induced climate change, changes of farming

systems or cultural practices, or the existence of genetic variance in Striga asiatica virulence.

According to Stringer et al., (2009), agricultural systems face the increasing risk of water

stress and that can affect the nature of parasitism between Striga and its host. The stability of

tolerance may vary across genotypes and ecological contexts. The most common scenario is

for Sorghum to deal with both water stress and S. asiatica infestation. Given that global

change involves modification of a series of environmental factors concurrently and changes

in the severity of different stress factors, knowledge on how plants acclimate to multiple

successive or multiple combined stresses is of key significance in understanding the effects of

future climates on the parasite. A combination of two or more stresses such as drought and

Striga infestation is a common occurence to many agricultural areas around the world and

impacts negatively on crop productivity. According to Suzuki et al., (2014) there is an urgent

need to generate crops with enhanced tolerance to stress combinations. Information is limited

in literature on the stability of sorghum tolerance under both drought and Striga asiatica

stresses.

Additionally, human interventions to curb the effects of climate change can modify the

agricultural landscape to the demise or promotion of the parasite. Mulch based farming

systems being promoted as a component of conservation agriculture in sub Saharan Africa

may affect the expression of tolerance traits in some sorghum genotypes. Mulch increases

6

soil moisture and fertility, decreases soil temperature, light transmittance and these are

antagonistic to weed development (Carsky et al., 1994; Oswald et al., 2002). Information is

not available for Zimbabwe on the effects of this practice on the Striga epidemic and whether

it enhances the expression of tolerance in sorghum. Weed responses to such cultural practices

are usually species and genotype specific.

Sorghum arundinaceum (wild sorghum) is increasing in Zimbabwe’s cropping systems as a

weed and occurs in all crops, even where sorghum has never been grown. Near relatives of

cereals could provide new sources of tolerance and resistance (Ejeta et al., 2000, Gurney et

al., 2001, 2002). Studies done by Gurney et al., (2002) indicated that the Sorghum

arundinaceum strain they used demonstrated tolerance to infections by S. asiatica in terms of

growth, biomass accumulation and grain production and this contrasted with Sorghum

bicolor, in which infestations had deleterious effects. Such genotypes can be sources of

resistance and tolerance traits which can be exploited in breeding for elite genotypes. Mwenje

(2006) reported high cross compatibility between cultivated Sorghum spp and their wild

relatives. This provides the opportunity for gene flow between S. arundinaceaum and

cultivated sorghums. Rich et al., (2004) found wild sorghum lines that rarely stimulated the

development of haustoria in Striga. Currently it is not known whether the Zimbabwean wild

sorghum ecotypes are resistant, tolerant or susceptible to Striga species such that their role in

the spread of Striga species is unknown.

Genetic variation for virulence can enable the parasite to adapt to new host resistance alleles.

Hence a better understanding of the virulence variability of S. asiatica populations is essential

for deployment of resistant varieties in integrated Striga control. According to Bozkurt et al.,

(2014), geographic distance plays a more important role in population differentiation than

specialization to a host species. The high evolutionary potential of the parasite populations

was also reported by Karltz and Shykoff (1998). Information on the existence of

7

physiological speciation and the stability of tolerance to various S. asiatica accessions is

unavailable Zimbabwe but can enhance efforts to breed elite sorghum varieties with broad

spectrum and durable resistance through better understanding of the host parasite interactions.

Musimwa et al., (2001) observed wide genetic distance among S.asiatica strains sourced in

Zimbabwe.

Production of low germination stimulants results in low numbers of Striga asiatica

attachments, thus producing a resistant phenotype. Jamil et al., (2011) found significant

variation in strigolactones production in New Rice for Africa (NERICA) and the low

producers gave resistant phenotypes. Information is not available for Zimbabwe on the

resistance through reduced strigolactones production and the link between strigolactones and

tillering.

1.3 Main objective

The overall objective of this research was to examine the stability of tolerance of Striga

asiatica infested Sorghum spp under drought, mulch and different Striga strains. Also to

determine the existence of reduced strigolactones production as a resistance mechanism, and

establish its link to sorghum tillering.

1.4 Specific objectives

The objectives of this research were:

1. to determine the effect of drought stress and Striga asiatica infection on the stability

of morpho-physiological traits which impart tolerance to Sorghum bicolor and

Sorghum arundinaceum;

2. to determine the effect of mulching on Striga infected sorghum growth, tillering and

dry matter partitioning;

8

3. to determine the variable effects of two Striga asiatica strains on the stability of

tolerance of S. bicolor varieties and S. arundinaceaum; and

4. to quantify strigolactones produced in Sorghum bicolor and Sorghum arundinaceaum

and correlate it to sorghum tillering.

1.5 Alternate Hypothesis

1. Reduced water availability and Striga asiatica infestation have an effect on the

morpho-physiological traits of Sorghum bicolor and Sorghum arundinaceaum.

2. Mulch reduces S. asiatica incidence on S. bicolor and S. arundinaceaum and

enhances the expression of tolerance traits in sorghum.

3. There are variable effects of S. asiatica strains sourced from geographically distant

places on sorghum varieties and sorghum is able to maintain its tolerance in the face

of physiological speciation of S. asiatica.

4. There is pre-attachment resistance through reduced strigolactones production in

Sorghum bicolor varieties and Sorghum arundinaceaum.

9

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Functional Ecology 25: 420 – 432.

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selecting for improved grain yield in extra-early maize under Striga-infested and

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strigolactone production. New Phytologist 192: 964 – 975.

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24. Jamil M, Charnikhova T, Houshyani B, van Aast A, Bouwmeester HJ (2011). Genetic

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Omanya HD, Mignouna, Botanga M (2007). Baseline study of Striga control using IR

maize in western Kenya. http//aatf-africa.org.pdf

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inheritance studies of witch weeds (Striga asiatica Kuntze) resistance in Sorghum

bicolor. D. Phil Thesis, University of Zimbabwe, Crop science Department.

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31. Mwenje E (2006). Sorghum and its wild relatives: ecological implications in the

event of the release of transgenic sorghum in SADC region. Biotechnology, Biosafety

and Environment in South Africa 2: 5 - 6

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41. Stringer L.C, Dyer J.C, Read M.S, Dongil A.J, Twymen C, Mkwambisi D (2009).

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stress combinations. New Phytologist 203: 32 - 43

43. Tari, G; Lasckay G, Takacs Z, and Poor P (2013). Response of sorghum to abiotic

stresses: a review. Journal of Agronomy and Crop Science 199: 264 – 274.

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Striga-host plant interactions: a shifting balance of power. Weed Science 60: 307 –

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45. Yoneyama Kaori, Xie X, Kusumoto D, Sekimoto H, Sugimoto Y, Takeuchi Y and

Yoneyama Koichi (2007). Nitrogen deficiency as well as phosphorus deficiency in

sorghum promotes the production and exudation of 5-de-oxystrigol, the host

recognition signal for arbuscular mycorhizzal fungi and root parasites. Planta 227:

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physiology 51(7): 1095 – 1103

15

CHAPTER TWO: LITERATURE REVIEW

2.1. Introduction to literature review

The literature review provides a detailed background to the issues studied in this thesis. The

major aim of this study was determination of the stability of tolerance traits of Striga asiatica

infested Sorghum bicolor and Sorghum arundinaceaum under drought conditions, under

mulch, and under two different Striga asiatica strains sourced in Zimbabwe. The study also

sought to quantify strigolactones produced by sorghum varieties as a resistance mechanism

and also to find the relationship between strigolactones quantities and sorghum tillering. It

was thus necessary to explore literature on sorghum production in Zimbabwe, the genus

Striga, the extent of the S. asiatica problem in sub Saharan Africa and Zimbabwe, Striga

research in Zimbabwe, Striga life cycle and management and functions of strigolactones. The

mechanisms of resistance and tolerance were also explored, including Striga management,

sorghum response to stress and mulching. The discussions on Striga management were

biased towards subsistence agriculture as it was an important goal of this study to enhance

productivity in this agricultural sector.

2.2 Sorghum production in Zimbabwe

Sorghum bicolor is an important staple crop in Africa, Asia and central America. It is the fifth

major cereal crop after wheat, rice, maize and barley. Sorghum is adapted to tropical and

subtropical climates but the greatest area of the crop is cultivated in drought prone semi-arid

tropical environments with 400 – 600 mm rainfall that are too dry for maize (Mwenje, 2006).

Sorghum bicolor is one of the most drought tolerant small cereal grain crop grown under the

smallholder sector in Zimbabwe’s natural farming region III, IV and V (Mutengwa, 2004)

which covers more than 70 % of the area in Zimbabwe. These regions are the driest in

Zimbabwe, receiving less than 500 mm of rainfall per year. The crop is grown traditionally in

16

Zimbabwe to ensure food security even in drought years. Sorghum is therefore a calorie

source for the millions who reside in Zimbabwe’s semi-arid areas. The major producing areas

are Matebeleland North, Matebeleland South and Masvingo provinces. The Mashonaland

province produces only 10 % of the total tonnage in Zimbabwe. The production of sorghum

in Zimbabwe has been on the increase since 2010 for about five years (Table 2.1) with the

exception of 2012 when there was a decrease caused by reduced sorghum prices by the Grain

Marketing Board.

Table 2.1: Zimbabwe sorghum production by year from 2010 - 2014

Year Tonnage (MT) Growth rate (%)

2010 74 000 5.71

2011 95 000 28.38

2012 65 000 -31.58

2013 69 000 6.15

2014 95 000 37.68

Source: FAOSTAT 2015

2.3 The genus Striga

Striga is a latin word for ‘witch’ presumably because plants infested by Striga display stunted

growth and an overall drought like phenotype long before the weed appears. The genus was

previously grouped within the family Scrophulariaceae but more recent analysis has placed

Striga under the family Orobanchaceae (Ejeta, 2007; Spallek et al., 2013). Striga possibly

originates from a region between Semien mountains of Ethiopia and the Nubian Hills of

Sudan (Atera and Itoh, 2011). The same is the centre of cultivated sorghum which is the

major host species for several Striga spp (Spallek et al., 2013).

17

The main agriculturally important Striga spp in cereal crops are S. hermonthica (Del) benth

and S. asiatica (L.) Kuntze, while S. gesneroides (Willd) Vatke is a major pest in cowpeas.

Striga aspera (Willd) Benth and S. forbesii are also significant problems in cereals in limited

locations (Parker, 2009). The distribution of various Striga spp across the African continent

is shown on Table 2.2.

2.3.1 Striga hermonthica

This is the most damaging of all Striga spp affecting most staple cereal crops grown in

Africa. It has purple flowers. It is found mainly in the tropical and northern sub tropical

regions from Gambia to western Kenya, Tanzania and Ethiopia in the East (Parker, 2009).

According to Mohammed et al., (2001) S. hermonthica is widespread in sub Saharan Africa

and is found throughout west Africa to Ethiopia and east Africa.S. hermonthica is particularly

harmful to sorghum, maize and millet but is also found in sugarcane and rice fields (Atera

and Itoh, 2011).

2.3.2 Striga asiatica

Striga asiatica has red flowers and occurs sporadically across west Africa but becomes pre-

dominant species towards the east African coast, southwards to southern Africa (Parker,

2009). This is the Striga spp that wrecks havoc in Zimbabwe. Kroschel (1999) reported that a

countrywide survey in Malawi found 63 % of maize fields to be infested with this species. De

Groote et al., (2008) reported that 10 % and 25 % of the maize crop in Namibia and in

Angola, respectively, was infested with this species. A survey by Mabasa (1994) in

Zimbabwe found that 79 % of the farmers reported that this Striga species was present in

their fields.

18

2.3.3 Striga gesneroides

Striga gesneroides occur widely in Africa mainly on wild plants only although it has been

found in cowpeas in west Africa (Parker, 2009). It has been found in northern Zimbabwe

infesting cowpeas and weeds.

Table 2.2: The distribution and occurrence of Striga spp in sub-Saharan Africa

Striga spp Host Plants Distribution

Striga

asiatica

Rice, Sorghum and

maize

Angola, Lesotho, Malawi, Mozambique, Namibia,

Tanzania, Madagascar, South Africa, Zanzibar,

Zambia, Botswana, Burundi, DRC, Zimbabwe

Striga aspera Rice, maize, sorghum,

finger millet, wild

grasses and sugarcane

Burkina Faso, Cameroun, Central African republic,

Ethiopia, Gambia, Guinea, Cote’divoire, Nigeria,

Niger, Mali, Ghana, Senegal and Sudan

Striga

forbesii

Sorghum, sugarcane,

maize, rice

Angola, Botswana, DRC, Ethiopia, Kenya, Malawi,

Mozambique, South Africa, Sudan, Swaziland,

Tanzania, Uganda, Zambia, Zimbabwe

Striga

gesneroides

Cowpeas, and legumes,

Nicotiana spp,

Eurphobia spp and

Ipomoea spp

Angola, Botswana, Burkina Faso, Cameroun,

Central Africa Republic, DRC, Ethiopia, Sierra

Leone, Senegal, South Africa, Tanzania,

Zimbabwe, Gambia, Ghana, Kenya, Malawi, Mali,

Mozambique, Somalia, Nigeria, Rwanda, Uganda,

Zambia.

Striga

hermonthica

Maize, millet, rice,

sorghum,Pearl millet,

Fingermillet, sugarcane

Angola, Cameroun, Central Africa Republic,

Djibouti, Eritrea, Gambia, Guinnea Bissau,

Ethiopia, Nigeria

19

2.4 Extent of the Striga problem in sub-Saharan Africa

Parasitic weeds are fast becoming a major constraint to many crops in sub Saharan Africa and

yet the efficacy of available means to control them are minimal. Parasitic weeds have become

one of the greatest biological constraints to food production in the drier parts of Africa,

probably a more serious problem than insects, birds or plant diseases. The C4 cereals

consisting of maize, sorghum and millet are the preferred hosts and the infection of these

plants by Striga spp can result in severe grain losses. S hermonthica causes up to 100 % grain

yield losses. Losses associated with this pest are estimated to be more than US$7 billion in

sub Saharan Africa only (Berner et al., 1995) with most affected being the resource poor

subsistence farmers (Gurney et al., 2006). According to Rubiales et al., (2009), typical yield

losses vary from 15 to 20 % at a regional level, but can be more severe at local scales,

sometimes resulting in total crop failure. The losses largely depend on the level of infection,

stage of crop growth when infestation occurs, crop variety, soil fertility and rainfall (Menkir

and Kling, 2007).

In addition to the yield losses estimated to exceed US$7 billion in value, the weed also causes

adverse effects on the welfare and livelihoods of over 100 million people in Africa (Rubiales

et al., 2009). The most affected are the resource poor, small scale subsistence farmers and

severe infestations cause serious food shortages. There are contrasting statistics on the extent

of the Striga infestations by individual species but according to Mwakaboko (2003), 40 % of

arable land in sub Saharan Africa and 67 % of the 73 million hectares in cereal zones is

infested by Striga. Harsh conditions mean that few alternative crops can be grown, and the

use of high-cost inputs such as herbicides is generally not affordable to the resource poor

farmers. Sorghum is generally grown by small scale farmers whose cash investments in crop

production are low. According to Webb and Smith (1996), inputs are low, rainfall is erratic

and soils are poor. These conditions are likely to be the most suitable for the Striga epidemic.

20

In other areas, the weed has reached epidemic proportions, presenting a desperate scenario to

small scale farmers. Where the scenario has worsened to these proportions, the farmers are

left with no option except to abandon the land. According to Evans et al., (2012),

demographic pressure has led to monocropping, thus increasing the frequency of Striga spp

host crops in the cropping system, an ideal condition for Striga to thrive.

Ahmed et al., (2001) reported that research in Africa on the control of Striga has been going

on for >70 years and despite these efforts, limited success has been achieved. Effective

control of Striga has been elusive due to the fact that the weed produces thousands of seeds

that can remain viable in the soil for a long time, combined with the complicated mode of

parasitism where vascular connections occur underground (Midega et al., 2013). This is

partly due to the complex life cycle of Striga, which is intimately linked to its host and

depends on the response to chemical and tactile cues, posing a challenge to control both

before and after attachment to the host.

2.5 Striga problem in the smallholder sector of Zimbabwe

Zimbabwe is a land locked country which lies entirely in the tropics. It is situated between

15o30

I and 30

o05

I east longitudes. It has been divided into five agro-ecological zones- I, II.

III, IV and V defined largely by rainfall distribution (Figure 2.1) (Vincent and Thomas,

1961). The agricultural regions are therefore an indication of the agricultural potential of the

various regions in Zimbabwe (Table 2.2) (Rambakudzibga, 2000). A summary of the rainfall

characteristics of the five agro-ecological zones of Zimbabwe and the suitable agricultural

activities are shown in Table 2.3.

21

Figure 2.1: The Natural Farming Regions of Zimbabwe

22

Table 2.3: Agro-ecological regions of Zimbabwe and agricultural activities carried out

in the various regions.

Agro-

ecological

region

Area

(Km2)

% of

total

Rainfall characteristics Agricultural activities

I 7.000 2 More than 1050 mm per

annum with some rain in all

months

Specialized diversified farming region.

Suitable for forestry, temperate fruit

production and intensive livestock

production

II 58.

600

15 700 – 1050 mm confined to

summer. Infrequent heavy

rainfall. Subject to seasonal

droughts

Flue–cured tobacco, maize, soyabean, cotton,

sugar beans and coffee can be grown.

Sorghum, groundnuts, seed maize, wheat and

barley can be grown. Wheat and barley are

grown in winter under irrigation. Mixed

cropping with poultry, beef and dairy

production very common in the region.

III 72.

900

18 500 – 7000 mm per annum.

Infrequent heavy rainfall.

Subject to periodic seasonal

droughts, prolonged mid

season dry spells and

unreliable starts of the season.

A semi-intensive farming area. Smallholder

farmers occupied 39 % of this prior to land

reform and most of the land was used for

intensive ranching. Maize production

dominated commercial production. Irrigation

played an important role in sustaining crop

production in commercial farming areas

IV 147.

800

38 450- 600 mm per annum Suitable for intensive ranching and wild life

management. Too dry for successful crop

production and most crops suitable are

23

sorghum and millets and other drought

tolerant crops. Maize is commonly grown

under smallholder farmers. Sugarcane and

cotton are produced under irrigation in large

estates

V 104.

400

27 Normally less than 500 mm per

annum

Extensive ranching and wildlife management

are the most suitable activities

TOTAL 390.

700

100

Source: Rambakudzibga, 2000.

Zimbabwe is considered an agricultural country because the majority of the population

indirectly or directly depends on agriculture (Jasi and Mabasa, 2001). Prior to the land reform

program, most of the large scale commercial farmers were located in Natural Regions I and II

which are high potential areas for crop production. At independence, nearly 75 % of the

communal farmers were located in natural regions IV and V (Whitlow, 1980) and up to now

most of the communal areas are located in these regions. Crop production in these low

rainfall areas is risky, yields are low and they experience periodic crop failure.

Soils in the communal areas are mainly light sands with low fertility because they contain

low levels of nitrogen and phosphorus (Mashiringwani, 1983). Farmers in these areas have

limited access to capital for the purchase of inorganic fertilisers, pesticides and seed.

Agriculture in the small scale farming area is, therefore, characterized by unfavourable soil

and rainfall as well as constraints in input procurements. Striga is a problem mainly in this

farming sector.

24

2.6 History and distribution of Striga asiatica in Zimbabwe

Striga asiatica was first recorded in Zimbabwe in 1916 when it was found in farms around

Mazowe District (Weinmann 1972). Weinmann (1975) reported that 22 % of the total land

area in Mazowe District was infested between 1929 – 1930. A weed survey conducted in

1970 in the commercial farms showed that Striga asiatica was only a problem in isolated

areas in Mazowe (Thomas, 1970). Subsequent surveys done showed that Striga asiatica was

a problem in both the commercial sector (Chivinge, 1983) and the smallholder sector

(Chivinge, 1988; Mabasa, 1993).

In Zimbabwe, the weed is mostly found in the low rainfall areas where 75 % of the rural

farmers reside (Mabasa, 1993). In a survey done by Chivinge (1988), Striga asiatica was

found infesting maize, sorghum, pearl millet and finger millet in all the then eight provinces

of Zimbabwe. Chivinge (1988) reported the weed as the second most aggressive weed in

Mashonaland Central and third most aggressive in the Midlands and Masvingo Provinces in

the large scale commercial farms.

Another survey by Mabasa (1994) showed that 79 % of the farmers reported that Striga was

present in their fields. Mabasa (1993) noted that Striga is a significant production constraint

in three of the five agro-ecological regions (III, IV and V) where nearly 75 % of the

communal farmers are based. Efforts to combat the Striga should therefore be intensified to

come up with sustainable means of combating the weed.

2.7 Striga asiatica research in Zimbabwe

According to Timson (1945), Striga asiatica research in Zimbabwe dates back to the 1930s

and 1940s. After realizing the threat of Striga in the 1920s, an experimental farm was set up

in the Concession-Glendale area in the Mazowe valley in the 1930s with the aim of carrying

out both experimental and demonstrative work on Striga asiatica control (Anon, 1938).

25

Between 1945 and 1980, there was no research that was done on Striga because it was

assumed that the problem had been solved (Mabasa, 1993). This could be because research

by then targeted mostly white commercial farmers and neglected the black farmers who

might have been suffering due to the effects of the weed.

In 1986-87, the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT)

initiated Striga research and they specifically looked at the screening of sorghum cultivars for

resistance and tolerance to Striga forbesii (Mabasa, 1993). A survey done in 1988 by the

Weed Research Team (Agronomy Research Institute) found that 79 % of the interviewed

farmers reported that Striga was in their fields with the highest infestations in Zaka and

Chiwundura (Jasi and Mabasa, 2001).

Research was initiated on the management of Striga and agronomic trials were conducted by

the Weed Research Team on the effects of planting dates, herbicides (Dicamba), manure and

fertiliser on Striga in maize sorghum and millet. Early planted crops had the highest Striga

infestations than late crops and maize was found to tolerate Striga when manure was applied

at 30 tonsha-1

and nitrogen at 90 – 140 kgha-1

(Agronomy Institute, 1988/89). The level of

manure and fertiliser was found to be beyond the reach of Zimbabwe’s smallholder farmers.

The tested herbicide was Dicamba (3,6 dichloromethoxybenzoic acid) and it was found to be

effective in the control of Striga but it was unaffordable to the small scale farmers and the

numeracy that was needed for calibration made it complex for the smallholder farmers.

Maize cultivars that were tested for resistance were found to be susceptible. For sorghum,

cultivars SAR29, SAR33, SAR35, SAR37 and SAR16 supported low Striga asiatica counts

compared to SV1 and SV2 (Mabasa, 1996). However, their yields were very low. There was

therefore a need to improve the yielding capability of the resistant varieties which were

otherwise the least preferred by farmers.

26

A comprehensive study by Musambasi (1997) compared herbicide 2.4 dichlorophenoxyacetic

acids (2.4 D) and 3.6 dichloromethoxybenzoic acid (dicamba) to hand weeding at 2 and 5

weeks after crop emergence and found that dicamba resulted in the best control of Striga

asiatica and 2.4 D was effective in suppressing the weed at 12 weeks after crop emergence

and that hand weeding was uneconomic. In the same study, intercropping with Vigna

subterranean and Vigna unguiculata, field beans (Phaseolus vulgaris) and groundnut

(Arachis hypogeal) resulted in reduced Striga asiatica numbers. Another study by Mabasa

(2003) revealed that the source and timing of nitrogen application did not influence Striga

asiatica tolerance in maize and recommended supportive hand weeding to prevent build up of

seeds in the weed seed bank.

There are various constraints in the use of available technologies which should be taken into

account when working with smallholder farmers. Most technologies will need 3 – 4 years

before there is any appreciable reduction in Striga infestation. No technology has been able to

eliminate Striga hence research continues. Consequently, some farmers have come to accept

the problem as something they have to live with.

27

2.8 Striga asiatica lifecycle

Figure 2.2: The life cycle of S. asiatica (Rich and Ejeta, 2007).

2.8.1 Dormancy and conditioning

Striga seeds must go through a phase of conditioning before they can be able to germinate

(Spallek et al., 2013). If no strigolactone is received during this time, the Striga seeds will

eventually fall into secondary dormancy (Cardoso et al., 2011). Germination is linked to the

presence of the host that is nearby as the endosperm of Striga can sustain growth for only 3 –

7 days (Berner et al., 1995).

After ripened Striga seeds may not germinate until they have passed through a pre-

conditioning process (Figure 2.2). According to Ejeta and Butler (1993), peak germination of

S asiatica seed occurs in vitro after 10 – 15 days of soaking in water at a temperature of 28

oC. According to Sun et al., (2008), preconditioning strongly affects the responsiveness of

28

seeds to the stimulants. Pre-conditioning at 30oC releases the dormancy within 2 – 3 weeks

and increases the sensitivity to strigolactones by several orders of magnitude.

2.8.2 Germination

The biology of Striga parasitism at its various stages is a series of signal exchanges between

the host and the parasite that leads to successful establishment (Rich and Ejeta, 2008). The

germination of Striga is tightly defined by spatial relations with potential hosts. Striga seed

germination is reflected by the distance from the host root where strigolactones are still

active, that is, concentrated enough to elicit germination (Fate et al., 1990). Striga seeds can

not germinate without specific germination stimulants released by the potential host (Shen et

al., 2006). The strigolactone concentrations required to stimulate germination are in the

concentration range of 10-10

– 10-15

MoleM3 (Cechin and Press, 1994). Strigolactones have

been shown to induce germination of Striga at concentrations that are as low as 10-16

M

(Mussellman, 1980). Hearne et al., (2008) reported that the concentration dependent spatial

limitation of Striga seed germination ensures nearness to a potential host. This is critical

because once germinated, the seedlings will lose their capacity to form competent haustoria

within 3 – 7 days (Berner et al., 1995). This is because Striga seed has small amounts of food

reserves which can only support limited growth and the Striga would die in a few days

without attaching to the host (Shen et al. 2006).

2.8.3 Haustorium development

After seed germination has been triggered, the radicle of the germinating seed penetrates the

host root and forms haustoria to establish a xylem to xylem connection with the host to

withdraw water and nutrients (Jamil et al., 2011). A haustorium is a multifunctional organ

that attaches to a host, establishes a xylem and/or phloem continuum, a physiological bridge

between the parasite and its host, directs the unidirectional flow of resources to the parasite

and functions at multiple stages in the parasitism (Estabrook and Yoder, 1998). Generally,

29

haustorium formation consists of three phases, initiation (formation of the haustorium

primordial), invasion (the penetration of haustorium primordial) and maturation (the

establishment of xylem continuum linking the host to the parasite vacular systems

(Musselman and Dickison, 1975). The radicle tip grows chemotropically towards potential

host roots after germination.

Haustoria are the invasive structures that develop at the tips of Striga radicle in response to a

host root contact. Certain phenolics, flavonoids and quinines have been identified that induce

haustorium development when added to the parasite in vitro (Riopel and Timko, 1995).

Chang and Lynn (1986) reported that the only haustorium inducing factor isolated directly

from the host root is 2.4-dimethoxy-p-benzoquinone (DMBQ). DMBQ is a product of lignin

oxidation and decarboxylation of phenolic acids found in plant cell walls (Spallek et al.,

(2013). Within hours after the parasite roots come into contact with haustorial initiation

factors, the growth and division of cortical cells is altered, resulting in localized swelling that

develops into haustorium (Yoder, 1999). Xylem formation only occurs upon contact with the

host stele (Yoder, 1998). Striga therefore elicits the host to produce a signal necessary for

parasite development in the process called semagenesis (Keyes et al., 2007). A synthetic

haustorium initiation factor known as syringic acid has been made in the laboratory. Within

24 hours after contact, rapid cell division of the radical tip stops and a hypertrophic growth

phase begins (Hood et al., 1998). Penetration of the host epidermis is mediated by the

elongation of distal cells in the protoderm or epidermis and the underlying tissue, followed by

rounds of periclinal and anticlinal divisions of the cells leading to the growth into the cortex

of the host plants (Spallek et al., 2013).

The haustorium is a physical and physiological connection between the parasite and its host

and its interaction with host tissues is important in the translocation of molecules (Aly, 2013).

The haustoria initially adheres to the host root by a secreted, mucilaginous substance (Joel

30

and Kesner-Gashen, 1974) and penetrates by pushing between the host cells. Penetration is

aided by digestive enzymes secreted by the parasite that include pectin methylesterase,

polygalacturonase and endocellulase (Benhod et al., 1993, Losner-goshen et al., 1998). In

general, penetration is completed 40 – 72 hours after contact with a host root (Hood et al.,

1998). Molecular translocation between host and parasite ranges from the movement of sugar

(Aber et al., 1983), herbicides (Joel et al., 1995, Nandular et al., 1999) to movement of

proteins (Hamamouch et al., 2005; Aly, 2007).

2.8.4 Nutrient transfer

Hibberd and Jeschke (2001) reported that most of the parasitic plants make a beeline for their

host’s vascular system and they are able to tap into a large flux of amino acids, organic

sugars, ions and water in the host’s xylem vessels or sugars, ions or amino acids in the host’s

phloem. Press and Whittaker (1993) found that most of the hemi-parasites have very high

transpiration rates and that can be double that of their host especially under low moisture

availability. This then creates a strong mass flow that facilitates transfer of water, carbon,

nitrogen and mineral nutrients from the host plant. Shen et al., (2006) reported that the

stomata of the parasite remains more open than that of the host and results in higher

transpiration rates and lower water potentials in the parasite than the host. This was also

confirmed by Press (1995). Low water potentials are maintained by the biosynthesis of

polyhydric alcohols like mannitol (Press and Graves, 1995) in the parasite.

2.8.5 Establishment of parasitism and flowering

Once xylem to xylem connections are established, the cotyledons of Striga enlarge and break

free from the seed coat within 24 hours (Hood et al., 1998). The Striga grows adventitious

roots and are able to form secondary haustoria on the same host. Once a strong sink has

developed between the host and the parasite, water and nutrients begin to flow and this

31

damages the crops’ development by reducing crop yield. When the Striga plant starts to

photosynthesise, the low carbon dioxide fixation and high dark respiration rates of Striga

asiatica result in negative carbon gain over a 24 hour period, thus making the weed

dependent on the host when growing above ground (Press et al., 1987). Striga leaves are

characterised by degenerated palisade cell layers and a relatively small number of

chloroplasts per cell (Spallek et al., 2013). This leads to lower photosynthetic rates by Striga.

A stem develops and emerges above ground to flower and disseminate seed after

approximately 4 – 7 weeks of growth (Aly, 2013). Flowers of Striga asiatica are red and after

pollination, seeds mature within 4 weeks in seed pods, which contain 250 – 500 of dust-like

seeds of 200 – 300 µm in size. According to Berner et al., (1995) under optimal conditions

each Striga plant can produce between 50 000- 500 000 seeds. Eventually the seed pods open

up and the seeds spread on the soil adding to the seed bank.

2.9. Strigolactones in plants

The frequently asked question is why plants exude strigolactones that enables their

locationby parasitic plants. Xie et al., (2010) concluded that the strigolactones may

have other roles that outweigh the risks of parasitism. According to Akiyama et al.,

(2005), Akiyama and Hayashi (2006) and Akiyama et al., (2007) strigolactones

function as branching factors for the symbiotic abuscular mycorrhizae (AM) fungi

from which plants benefit. The AM fungi are soil inhabiting microorganisms that

form symbiotic associations with plants. The fungi penetrate and colonise plant roots

where they develop highly branched arbuscules which serve as nutrient exchange

sites. According to Xie et al., (2010) the fungi supply their host with water and

nutrients, especially nitrogen and phosphorus that are obtained through the hyphae

that is found on the outside in the soil.

32

In the absence of the host, the AM hyphae differentiate into morphological structures

characterized by extensive branching (Buee et al., 2000). Strigolactones therefore appear to

trigger a cascade of molecular and cellular events necessary for hyphae to become more

effective. In host plants, production of strigolactones is stimulated by phosphate shortages

(Yoneyama et al., 2007a). This demonstrates that strigolactones are molecules for use in the

successful establishment of plants with hyphal fungi- plant symbiosis.

Strigolactones have also been implicated in fungal/host shoot branching (Umehara et al.,

2008). When there is a host plant root in the vicinity of the germinating spores, signaling

molecules are released by the roots into the rhizosphere and they reach the hyphae and the

fungus responds to this with increased growth and intensive hyphal branching.

During symbiosis, the AM fungi obtain carbohydrates from the host plant and at the same

time the host obtains water and minerals from their fungal partners enabling them to perform

better under stressful conditions (Lopez Raez, et al., 2008a). This probably explains why

strigolactones are produced inspite of the risk of infection by parasitic plants. It is likely that

the parasitic plant has evolved the capacity to perceive the presence of a host plant by taking

advantage of the already existing signaling between plants and AM fungi.

Strigolactones have been classified as a new group of plant hormones that inhibit shoot

branching by preventing the outgrowth of leaf auxiliary buds. Like other plant hormones, the

strigolactones require a receptor in order to exert their activity; they are active at low

concentrations and can be transported over some distance (Umehara et al., 2008). Increased

synthesis of strigolactones under low phosphate and nitrogen conditions leads to the

proposition that under low inorganic phosphate conditions, plants increase biosynthesis of

33

strigolactones to reduce shoot branching and increase root growth to maximize interactions

with AM fungi to facilitate the uptake of mineral nutrients (Lopez Raez et al., 2008b).

2.10 The parasite as a sink

There is evidence that parasitic plants generally obtain carbon and nitrogen from their hosts

(Press, 1989; Press, 1995). However, the level of dependence may differ. For example hemi-

parasitic species that are facultative can survive in the absence of a host whilst holo-parasitic

angiosperms rely exclusively on their hosts for their carbon and nitrogen supplies (Press,

1995). The Striga parasite has roots and pigmented leaves and that suggests that the root

hemi-parasite may receive and incorporate water and solutes from both autotrophic and

heterotrophic sources (Press, 1996).

Mabasa (2003) reported that the rates of photosynthesis in hemi-parasites are generally

towards the low end as observed in C3 species and are usually lower than those of their hosts.

Lowly concentrated chlorophyll, poorly developed mesophyll cells and fewer air spaces

between the spongy mesophyll cells (Press et al., 1988) and low levels of ribulose 1,5-

biphosphate carboxylase (Press et al., 1986) in some root hemi-parasite may account for the

low rates of carbon dioxide fixation. According to Graves et al., (1989), carbon budget

models suggest that S hermonthica would be unable to maintain any appreciable positive

carbon balance in the absence of carbon from the host. This makes the parasite a strong sink

for the carbohydrates manufactured by the hosts.

2.11 Mechanisms of sorghum tolerance to Striga asiatica

2.11.1 Host photosynthesis

Host responses to infestation cannot be attributed solely to resource competition between the

host and the parasite (Gurney et al., 1999). Differences in dry matter accumulation between

34

infested and uninfested plants partly results from the parasite acting as a sink for carbon,

inorganic solutes and water, particularly in the later stages of infection, but also lower rates of

carbon gain by the infested cereals (Cechin and Press, 1993; Gurney et al., 1995; Smith et al.,

1995).

A study by Gurney et al., (2002) found lower rates of photosynthesis for all parasite-host

associations. However, the same study revealed that the tolerant Sorghum arundinaceaum

was not affected by the parasite with respect to dry matter accumulation. This demonstrated

the uncoupling of photosynthesis and biomass accumulation as was observed by Frost et al.,

(1997) in some sorghum–Striga associations.

In a study by Van Aast and Bastiaans (2006), it was found that two sorghum varieties

Tiemarifing and CK60-B had differential response to infection by Striga asiatica.

Tiemarifing’s reduction in panicle weight was proportional to overall reduction in total plant

dry weight but for CK60-B panicle weight was much more strongly reduced in total weight

than total dry mass. It was then concluded that the ability to maintain a constant harvest index

under Striga infestation conditions might be another aspect of tolerance in this cultivar.

According to Haussmann et al., (2001), genetic variation for tolerance to Striga under field

conditions exist in cultivated sorghum especially in local African cultivars. The different

responses of wild sorghum to infection by S. hermonthica and S. asiatica suggest that these

Striga spp possibly influence host growth through different mechanisms or differential

disruption of host metabolism.

Aly (2007) reported export of proteins from the host plant to the parasite. This movement of

may lower protein availability hence chlorophyll.Therefore the ability of a genotype to

maintain chlorophyll content irrespective of the infection is key to tolerance. Since

chlorophyll concentration is connected to nitrogen availability, chlorophyll concentration

35

becomes a key parameter in the measurement of plant canopies and subsequently

carbohydrate accumulation.

2.11.2 Sorghum tillering as Striga tolerance mechanism

Tillering is generally recognized as one of the most plastic traits affecting accumulation of

biomass and ultimately grain yield in many field crops (Kim et al., 2010a). Tillering is one of

the most important agronomic traits in poaceous crops and plays a major role in determining

plant architecture and grain yield (Wu et al., 1998). Tillering confers environmental plasticity

to grain crops. High tiller production capacity improves the chances of persistence after

periods of unfavourable conditions during which a plant may experience biotic and abiotic

stress (Assuero and Togretti, 2010). According to Bartholomew (2009), when a tiller dies as a

consequence of stress, it is replaced by another tiller in order to keep forage production. The

control of tillering is affected by endogeneous factors and environmental supplies (Mcsteen,

2009). According to Hammer et al., (2006), genetic variation in tillering affects the dynamics

of canopy development. Yoshida (1976) reported that one of the most critical characteristics

of successful high yielding varieties for rice and wheat is a semi-dwarf plant type with high

tillering ability.

Although tillering is considerably less in Sorghum bicolor, it nonetheless has a major

influence on plant leaf area development (Larfage et al., 2002). Modern sorghum hybrids

produce from zero to four fertile tillers under field conditions such that at plant densities

below 4 m-2

, around 70 – 80 % of the total plant leaf area and grain yield is attributable to

tillers. Kim et al., (2010a) asserted that the differences in tillering could be associated with

differences in carbon supply-demand balance and the propensity to tiller could possibly be

associated with hormonal signaling. Differences in tillering could be caused by differences in

hormonal signaling or responsiveness to sugar level. Studies done have found novel

hormones that trigger branching and are known to affect tiller growth in sorghum (George-

36

Jaeggli, 2009). Therefore, the capacity of a variety to produce tillers is important when

considering tolerance to Striga.

2.11.3 Environmental regulation of tillering

Studies by Kim et al., (2010b) found that the rate of appearance of successive leaf tillers and

the leaf appearance rate were similar to the appearance rate of leaves of the main shoot.

Therefore, the environmental effects on plant phenology can be important in explaining

tillering dynamics in terms of topological location, appearance and fertility frequency.

Environmental conditions affect tillering through their effects on the carbohydrate

supply/demand framework. Environmental effects on sorghum tillering have been reported

by Kaitaniemi et al., (1999) and were due to changes in leaf elongation rate in response to

temperature, vapour pressure deficit and water availability. In sorghum that is under parasite

attack, there is intense nitrogen competition and carbon usage is more prominent. For a

variety that uses tillering as a tolerance mechanism, the tillers should therefore appear after

the Striga has completed its life cycle. Striga generally takes a total of 10 – 12 weeks to

complete its life cycle. Once the Striga is dead and new tillers come up they are likely to

result in more yield as there is an extensive root system that will have been established.

Assuero et al., (2000) found that tiller number was reduced by endophyte infection in two

Fastuca arundinacea that had been infested by two fungal endophyte strains Neotyphodium

coenophilum strains. The same should be applied to plants parasitised by Striga as they lead

to resource competition.

2.12.1 Propensity to tiller

Studies by Kim et al., (2010b) revealed that high tillering was also associated with the

propensity to tiller. This is associated with hormonal signaling and responsiveness to sugar

level. Umehara et al., (2008) identified the hormone strigolactone that triggers branching.

37

The hormones are known to affect tiller outgrowth in sorghum (George-Jaeggli, 2009).

Research by Jamil et al., (2011) in rice cultivars found that low tillering rice cultivars have

lower strigolactones in the root exudates compared to high tillering.

2.13 Host plant resistance against Striga

Host resistance to parasitic plants is a multicomponent process that occurs at different stages

of a parasite’s life cycle (Estabrook and Yoder, 1998). Rich and Ejeta (2008) reported that the

biology of Striga at its various stages is a series of signal exchanges between host and

parasite that leads to successful establishment. Yoder and Scholes (2010) combined the

various stages of parasite development into the three general periods: pre-attachment, parasite

establishment and post attachment maturation. Parasitic plants use chemical communication

in the rhizosphere to trigger certain stages to occur in their life cycle. Therefore any genetic

differences in the biosynthesis or release of signaling molecules can reduce parasite viability.

The types of resistance occurring in parasitic plant hosts are classified into reduced host

germination stimulant production, reduced haustorium initiation factor production, host

resistance to parasite establishment and host resistance after parasite establishment.

2.13.1 Reduced host stimulant production

According to Jamil et al., (2011), there is a promising opportunity to minimize losses through

avoiding triggering of Striga seed germination through reduced strigolactone production.

Low production of host plant root exudates compounds that are essential for Striga

germination is the understood mechanism for Striga resistance (Lynn and Chang, 1990). In a

study by Sun et al., (2008), and Jamil et al., (2011), germination of Striga hermonthica seed

was dependent upon the quantity and quality of strigolactone production and any genetic

variation in this trait could potentially confer pre-attachment resistance. In a study by Jamil

et al., (2011), rice varieties CG14, WAB56-104 and NERICA 1 produced the smallest

amounts of strigolactones. The same varieties were shown to have differences in the

38

composition of the strigolactone blend. In another study, Jamil et al., (2011b) found that the

concentration of strigolactones in root exudates varied strongly in rice cultivars and that in

the study, Super Basmati, TN1, Anakila and Agee produced the least strigolactones. Low

germination stimulant genotypes of sorghum have enhanced resistance to Striga because of

the reduction in Striga germination (Ejeta, 2007). Low germination stimulant was also

implicated in some legume and sunflower accessions that showed enhanced resistance to

Orobanche species.

According to Ejeta et al., (2001) all susceptible Sorghum spp appear to be high stimulant

producers. Vogler et al., (1996) found that low germination stimulant (lgs) production of

sorghum is controlled by a single recessive gene. According to Ejeta et al., (1997), the lgs

gene found in a source germplasm has been transferred into high yielding and broadly

adapted sorghum cultivars.

2.13.2 Reduced haustorium inducing factors (Low haustorial factor)

Haustoria are the structures that invade the host root and causes the formation of xylem-

xylem connections. Riopel and Timko (1995) identified that phenolics, flavonoids and

quinones as compounds that induce haustorial development.

The success of parasitic plants results largely from strategies that tightly couple

developmental transitions with host recognition signals. This means in the absence of specific

signals by a potential host, successful infestation by the parasite is prevented. Studies by

Gurney et al., (2003) found that Tripscum dactyloides, a wild relative of maize does not

produce primary haustorium inducing factors as a small number of parasites initiated

haustorial formation. Rich and Ejeta (2004) found sorghum lines that rarely developed

haustoria.

39

Low haustorial factor (Lhf) is inherited as one dominant gene. According to Ejeta (2005) the

lhf gene found in sorghum has been transferred into improved sorghum cultivars and has

been pyramided with other resistant genes.

2.13.3 Parasite establishment resistance

In some cultivars, the parasite penetrates the host root cortex but is unable to form vascular

continuity with the host and it dies (Gurney et al., 2005). The same study revealed that by day

9 after infection, the parasite could not form a parasite-host xylem-xylem connection. In

many cases, the endophyte passed straight through the root cortex and emerged from the

other side of the root. Vascular continuity allows movement of water and nutrients from host

to parasite. It also provides factors required for further differentiation of the haustorium.

In a study by Gurney et al., (2006), the haustorium of parasites attached to the sorghum

variety Noponbare did not mature and differentiate. Their results indicated that by day 21, 49

% of the attached parasites were either dead or showed signs of necrosis. In other sorghum

varieties (Framida and Dobbs), a proportion of the parasites died owing to the onset of the

rapid hypersensitive reaction (Mohamed et al., 2003).

2.13.4 Post-attachment resistance

Resistance can occur following successful connection of parasites to the host vascular system

(Yoder and Scholes, 2010). Perez-de-Luque et al., (2006) found that in some pea genotypes,

host vascular cells fill with mucilage-like compounds that block the transport of nutrients to

the parasite leading to death of tubercules.

2.13.5 Incompatible response (IR)

This response is similar to the hypersensitive response in that it discourages the development

of Striga beyond attachment. There is however no apparent necrosis in host root tissue

surrounding the attachment site. In the IR based resistance, Striga seedlings that penetrated

40

the host tissue may not develop beyond first emergence of leaf primordia (Ejeta, 2005). Some

Striga appear to develop normally at first but show signs of stunted growth with time.

2.13.6 Hypersensitive response

In some sorghum genotypes, necrotic areas appear on roots at the site of Striga attachment.

Ejeta (2005) reported that necrotic lesions start as red becoming brownish with time and can

spread to 2 mm from the centre of attachment but most remain more localized. This

discourages further advancement of attached Striga which does not develop normally and

eventually dies on the host. Sorghum varieties with this phenomenon have been observed and

they include Framida, CK32 and CK33 (Ejeta, 2005). Hypersensitive reaction is conditioned

by two complementary dominant genes.

2.14 Managing Striga asiatica in sub-Saharan Africa

Despite the concerted efforts to come up with a sustainable method of Striga asiatica control,

there is no sustainable control method available for managing the parasite. It remains as the

number one biological constraint limiting the production of cereal grains in sub-Saharan

Africa. Several methods have been studied but have been accompanied by minimum success.

The numerous methods that have been suggested or developed together with their technical

limitations are shown in Table 2.4.

Table 2.4: Different methods of controlling Striga asiatica

Control

strategy

Mechanism Limitation References

Increased soil

fertility

Shortage of nitrogen

and phosphorus leads to

more active production

of strigolactone to

Most of the

affected farmers

cannot afford the

levels of fertiliser

Williams (1961), Raju et al., (1990)

Mabasa (2003), Jamil et al., (2011),

Lopez-Raez et al., (2008),

Yoneyama et al., (2007a, 2007b))

41

attract mychorhizal

fungi for increased

nutrient absorption.

required to reduce

production of

strigolactones

Intercropping

with legumes

The mechanism

according to Fernandez-

Aparicio et al., (2011)

involves smothering by

cover crops and

increase in soil moisture

and fertility for legumes

and decrease soil

temperature.

Jasi and Mabasa (2001),

Rambabkudzibga and Mabasa

(1993), Kabambe (1991),

Musambasi (1997), Kasembe

(1995), Mbwaga (1995), Adipala et

al., (1997), Kuchinda et al., (2003),

Carsky et al., (1994), Oswald et al.,

(2002), Khan et al., (2006), Midega

et al., (2010), Picket et al., (2010),

Khan et al., (2008) Tsanuo et al.,

2003; Hooper et al., 2010.

Trap crops These crops stimulate

germination of the

parasitic weed but is not

compatible with

subsequent infection

process

Trap crops cannot

exhaust the seed

banks and their

cultivation may not

be economic.

Rao and Gacheru (1998), Oswald et

al., (1996), Odhiambo and Ransom

(1996).

Catch crops These are true hosts that

promote Striga

germination but will be

burnt or chopped down

as soon as Striga

germinates

Not economic for

the farmer

Oswald et al., (1997)

Host

resistance or

Low strigolactone

production, low

This is a

sustainable

Jamil et al., (2011), Gurney et al.,

(2003), Rich and Ejeta (2008), El

42

tolerance haustorial initiation

factors, plugging of

xylem-xylem

connection between

host and parasite and

antibiosis.

approach but not

even one sorghum

cultivar has shown

complete

resistance.

Heweris (1987).

Herbicide

seed dressing

Herbicide coated seed

maize uses germplasm

resistant to

Imidazolinone group of

accetolactate synthase

(ALS) inhibiting family

of herbicides.

Successful so far Samb and Chamel (1992), Chivinge

et al., (1999), Odhiambo and

Ransom (1993), Kanampiu et al.,

(1997), Manyong et al., (2008),

Kanampiu et al., (2002)

2.15. Sorghum response to drought stress

About a third of the world’s agricultural land currently suffers from chronically inadequate

water availability (Ghannoun, 2009). Adaptations to drought is a quantitative trait controlled

by many genes (Fenta et al., 2012). According to Mitchell et al., (2013), plants exposed to

low intensity but long duration droughts may maintain water status above the critical water

potential thresholds but deplete stored carbohydrates. High intensity drought and incapability

to regulate plant water status above critical thresholds will lead to plant death. The ability of a

plant to maintain high rates of photosynthesis is an important determinant of the ability of a

crop plant to maintain growth and indicates tolerance of a crop to drought and Striga

infections.

Fenta et al., (2012) found differences in root biomass under water replete conditions with one

variety showing the greatest biomass accumulation. The same trend was demonstrated for

43

root biomass while no differences were shown in shoot/root biomass. The same study found

that tolerance was often concentrated largely on shoot parameters, particularly those

associated with photosynthesis. Gilbert et al., (2011) found that considerable genetic

differences exist in the ability of soyabeans to maintain high water use efficiency and

photosynthesis during drought. Genetic differences in stomatal conductance are considered to

exert the greatest effect on the intrinsic water use efficiency (Gilbert et al., 2011). The

stability of photosynthesis under conditions of water deprivations is also considered to be an

important aspect of drought tolerance.

The sorghum plant has the capability of withstanding drought conditions through adjustments

in stomatal aperture, maintenance of cell turgor, hydraulic conductivity and maintenance of

cell photosynthesis. However, the introduction of an extra sink from the parasite may alter

this delicate balance. Even if sorghum varieties may be tolerant to drought, the occurrence of

drought to a host attached to the parasite may aggravate the situation. The ability of a

sorghum plant to withstand both the parasite and drought may be compromised.

2.16 Existence of Striga physiological speciation and differential virulence

A lot of Striga management systems have been suggested, including introduction of resistant

sorghum varieties. According to Mohammed et al., (2007), crops with some measure of

resistance have been integrated into Striga management programmes and the new material

gets challenged by the Striga seed bank. The newly introduced sorghum variety must be able

to cope with the great potential genetic diversity in the seed bank. One of the major problems

in Striga control is the possible existence of physiological speciation within the species of

Striga as was first suggested by Jones (1955). Ten years later, Doggett (1965), was the first

one to report varietal differences in sorghum susceptibility to Striga hermonthica in east

Africa. It was observed that varieties of sorghum that were resistant in one location became

susceptible in another suggesting the existence of physiological strains of the parasite.

44

According to Bozkurt et al. (2015), genetic variation for virulence can enable the parasite to

adapt to new host resistance alleles and several studies have been undertaken to understand

the parasite’s genetic diversity and variability for virulence.

Rao and Musselmann (1987) suggested the possible causes of the differential response to be

Striga intensity differences, instability of host resistance or other several soil and

environmental factors which affect resistance of the host cultivars. Bebawi (1981)

investigated the germination response of eleven Striga hermonthica samples from sorghum

and pearl millet exudates of 27 sorghum cultivars and confirmed the suspiscions of

physiological speciation in Striga which had been alluded to by Parker and Reid (1979).

Botanga and Timko (2006), suggested that geographical isolation and host driven selection

are important factors in the formation of races of Striga gesneriodes in West Africa. In Striga

asiatica and Striga hermonthica populations from Kenya, 96.8 % and 84 % of the Amplified

fragment length polymorphism (AFLP) bands were polymorphic respectively (Gethi et al.,

2005). The observed polymorphism indicated that different strains were in each of the Striga

populations. A study in Benin discovered a high degree of host speciation within the 14

analysed Striga asiatica populations (Botanga et al., 2002). According to Spallek et al.,

(2013), Striga asiatica isolated from wild grasses species were unable to successfully

parasitise sorghum and maize plants susceptible to other Striga asiatica collections. The same

authors found a significant relationship between genetic and geographic distances in Striga

species.

2.17 Mulch effects on Striga asiatica incidence

There is a growing worldwide concern about soil health, usage of fossil fuels and overall

economics of field crop production. Conservation agriculture (CA) is being promoted

45

globally as a farming system that can address many of those concerns and increase the overall

economic productivity of mechanised agriculture (Norsworthy and Oleivera, 2007; Hobbs et

al., 2008; Sanyal et al., 2008). Conservation agriculture is a broad term, which encompasses

activities such as minimum and zero tillage, tractor powered, animal powered and manual

methods, integrated soil and water management and includes conservation farming. It is

generally defined as any tillage sequence that minimises soil and water loss and achieves at

least 30 % soil cover by crop residues.

According to Bilalis et al., (2003), the correct use of residues helps to conserve moisture and

deal with weeds while improving soil structure. Teasdale and Mohler (1993) indicated that

annual weed infestation decreases as crop residues increase on the soil surface offering direct

evidence that crop residues control weed emergence. The effect of the surface mulch on weed

seedling emergence is controlled by several factors such as quality of residue, weed species,

position in the soil, soil type and environmental conditions. According to Liebman et al.,

(2001), the mechanisms for weed suppression include changes in soil moisture, reduced

temperatures at the soil surface, physical impedance and allelopathy.

Weed response to residue depends on quality, quantity of residue and biology of a particular

weed. Residues of small grains have been shown to inhibit weed emergence and growth in

cropping systems (Putnam et al., 1983). Mulch therefore exerts a selection pressure on weeds

and the weeds that possess traits that enable them to germinate on the surface will increase in

numbers.

Crop residues used as mulch substantially decrease maximum daily soil temperature (Mohler

and Teasdale, 1993). Differences in temperature between mulched and unmulched plots can

be as great as 14 oC. Mulch shades weed seeds from light and prevents shoot growth. The

presence of light might indicate proximity to the soil surface or absence of overstorey canopy

46

and assurance for successful establishments and growth. Mohler and Teasdale (1993)

reported that large quantities of residues were needed to effect weed control as total weed

emergence paralleled light transmittance through the residues. The ability of mulch to

suppress weeds is also correlated to light extinction coefficient of the mulch. However no

study has sought to determine the effects of mulch on Striga asiatica establishments.

2.18 Photosynthesis in a Striga-infested plant

According to Gurney et al., (1999), an increased understanding of the parasitic mode of

nutrition has demonstrated that host response to infestation cannot be attributed to more

competition between the host and the parasite. Reduced photosynthesis may account for the

lower rates of host productivity. Graves et al., (1989) found that 80 % of the biomass not

accumulated by the host compared with uninfested plants can be accounted for by lower

carbon fixation in infested plants compared to controls. Gurney et al., (2002) suggested that

an ability to maintain high rate of photosynthesis while infested may be an important factor

of tolerance to the parasite.

According to Frost et al., (1997) lower rates of photosynthesis are a consequence of lower

stomatal conductance, particularly in the early stages of infection. Increased levels of the

plant growth regulator abscissic acid in infested plants cause stomatal closure (Taylor et al.,

1996; Gurney et al., 1997). The effects of plant parasites on their hosts vary from

undetectable levels where a plant proceeds to reproduction as if there is no pest to extreme

cases where the host dies. Some Striga-cereal associations result in stunting of the internode

elongation leading to unpacking of the leaves within the canopy (Walting and Press, 1997,

1998).

47

2.18.1 Stomatal conductance

One of the shoot related physiological traits that may affect stress tolerance is the decline in

whole plant water use during soil water deficit events (Manavalan et al., 2009). In most

cases, stomatal conductance affects leaf gas and water vapour exchange. According to Liu et

al., (2003), drought stress decreases relative leaf expansion rate, stomatal conductance and

leaf turgor whereas it increases abscissic acid content in the leaf and xylem. There are

obviously genetic differences in the ability to keep stomata open despite the presence of

stress in some plants. The control of stomatal conductance under stress is a physiological trait

that can be exploited when developing drought resistant materials in sorghum.

Adjustments in stomatal arpeture act to reduce transpiration in response to the declining

hydraulic conductance and/or reductions in leaf turgor and help plants to avoid water

potentials that can induce hydraulic failure (Sperry, 2000). Phosphorus and potassium are the

most essential nutrients. Ruiz-Lozamo et al., (1995) asserted that in particular, potassium

plays a key role in plant water stress and has been found to be the cationic solute responsible

for stomatal movement. Ge et al., (2012) found that the decline in nutrient uptake especially

P and K was because of low transpiration rate under soil water deficit. This had earlier been

observed by Sinha (1978) that stress tolerant wheat varieties can accumulate more potassium

than susceptible ones and that plants well supplied with potassium have higher stomatal

resistance which resulted in low transpiration rates.

2.19 Conclusions

A comprehensive up-to-date review of literature was conducted. In this review, Striga was

found to cause devastating effects on sorghum production. The life cycle of Striga spp was

discussed paying attention to its multi-stage nature, and depedance on host signals. The

current management methods were reviewed together with the limitations of each of them.

48

Tolerance was determined as central to Striga management since there is no single genotype

that has been found to be completely resistant. However, there is limited information on the

response of sorghum spp to various ecological factors such as mulching, drought and the

existence of physiological speciation in Striga.

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Chapter Three:

The effect of witchweed (Striga asiatica L. Kuntze) and moisture

stress on selected morpho-physiological traits which impart

tolerance to Sorghum spp

3.1 Abstract

Sorghum production is hampered by the parasite Striga asiatica and recurring droughts.

However, the morpho-physiological effects of these combined stresses on tolerance of

sorghum traits are poorly understood. Two pot experiments were set up to determine the

effects of the two stresses on morpho-physiological traits of sorghum. A 2 * 2 * 5 factorial

experiment laid down as a completely randomised design replicated three times was carried

out twice at Bindura University of Science Education (BUSE) nursery. The first factor was

water availability at two levels: 50 % field capacity (FC) and 100 % FC. Infection was the

second factor at two levels: infested and uninfested, and all these were imposed on five

sorghum lines, including wild sorghum (Sorghum arundinaceaum). Sorghum chlorophyll

content, normalized difference vegetation index (NDVI) and dry matter traits were analysed

using Genstat version 14 to compare treatment effects. Watering at 100 % FC gave the higher

(P<0.01) NDVI across all the measured periods compared to 50 % FC. The results indicated

that sorghum genotypes differed sharply with respect to chlorophyll content and the NDVI

with the genotype Mukadziusaende having the most chlorophyll and NDVI (P<0.05), whilst

the least was wild sorghum. Chlorophyll content and NDVI differed significantly among

genotypes while limited water availability did not reduce chlorophyll content of

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Mukadziusaende, wild sorghum and Chiredhi. Striga infection when it co-occurred with

water stress did not affect chlorophyll content. Mukadziusaende had the highest (P<0.05)

head weight and head index. Infestation with Striga significantly reduced (P<0.05) head

weight across all treatments. Drought stress and Striga infection had mutually exclusive

effects on chlorophyll content and NDVI. However, both infection and drought stress reduced

head weight illustrating the two factors were synergistic on their effects on sorghum head

weight.

3.2 Introduction

Sorghum is an important cereal crop that feeds more than a third of the population in southern

Africa. One of the remarkable characteristics of sorghum is its drought tolerance, that has

made it an important cereal grown for food and beverages in sub-Saharan Africa (SSA).

Among the major constraints of sorghum production are drought and infestation with Striga

asiatica. Striga is a parasitic weed that attaches itself to the roots of sorghum from where it

draws its moisture and nutrient requirements thus inhibiting host plant growth, reducing yield

and in severe cases, causing plant death. Striga affects the major crops that supply the bulk of

the carbohydrate and protein needs of the poor who reside in SSA (Ejeta, 2005). Scholes and

Press (2008) and Ejeta (2007) reported that over 50 million hectares of arable farmland under

cultivation with cereals and legumes are infested with one or more Striga species in SSA.

About a third of the world’s agricultural land currently suffers from chronically inadequate

water availability (Ghanounn et al., 2009) and this situation is predicted to worsen (Jury and

Vaux, 2007) due to climate change. Global warming, changes in rainfall abundance and

frequency and severity of rainfall events may exert a significant pressure on agricultural

water use, with several regions currently experiencing water deficits likely to face further

shortages (Padgam, 2009). Infact, many of the world’s poorest people farm in areas with

inadequate and unreliable rainfall. Even in traditionally irrigated areas, water stress is

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becoming a serious threat to crop production due to water scarcity resulting from the growing

and competing demands for water uses. Despite all this, agricultural productivity must be

increased to provide food for the world’s ever increasing population. Future food demand for

the rapidly increasing population pressures is likely to further aggravate the effects of drought

(Somerville and Briscoe, 2001).

Under natural conditions, a combination of two or more stresses such as drought, salinity and

heat are common to many agricultural areas around the world and negatively impacts crop

productivity (Suzuki et al., 2014). Information on plant performance under a more complex

environment where multiple stresses co-occur is fragmentary (Farooq et al., 2010). Cramer et

al., (2011) asserted that the major crops of the world are likely to be exposed to a wide range

and a number of abiotic and biotic stress conditions as well as their combinations. Stress

combinations represent one of the most critical challenges facing sorghum production today

and improved theory and practice are needed for quantification of genotype responses. As an

example, studies done elsewhere have revealed that the molecular responses of plants to a

combination of heat stress and drought is unique and cannot be directly extrapolated from the

response of plants to stresses such as drought or heat when applied individually (Rhizhsky et

al., 2002, Suzuki et al., 2005; Mittler et al., 2006).

There has been contrasting responses of different plants to different stress combinations.

Demirevska et al., (2010) found that tobacco showed the same physiological responses to

drought and heat and their combinations. In barley, the effect of drought or heat stress

reduced plant growth with a more severe effect coming from drought. The combination of

drought and heat stress reduced plant growth to a much greater extent than drought or heat

applied individually (Suzuki et al., 2014). However, Iyer et al., (2013) reported that

Medicago truncatula showed contrasting responses to a combination of ozone and drought

stress. Ozone stress caused development of chlorotic and necrotic tissue and drought alone

71

caused wilting and collapse of leaves but a combination of the two stresses cancelled the

effects of both stresses. Drought leads to stomatal closure and reduce the uptake of pollutants

via stomata thereby ameliorating the effect of gaseous pollutants like ozone (Olinger et al.,

1997; Low 2006). Actually, Suzuki et al., (2014) posited that some stress combinations might

have beneficial effects compared with the occurrence of separate stresses. Understanding the

limits of stress tolerance and acclimation to stress is of great importance and practical value

in predicting the potential limit of plant productivity (Isebrands et al., 2000).

Wahid and Rasul (2005) found that the major effect of drought is reduction in photosynthetic

machinery and pre-mature leaf senescence culminating in reduction of food production.

Drought stress produces changes in photosynthetic pigments and components (Anjom et al.,

2003) and diminishes the activities of the Calvin cycle enzymes which reduce yields (Fu and

Huang, 2001). According to Cramer et al., (2011), the hormones abscisic acid (ABA) and

ethylene have been found to be important regulators of plant responses to both abiotic and

biotic stresses. Striga has been shown to increase ABA in infested maize and sorghum plants

(Frost et al., 1997; Taylor and Frost, 1997). ABA induces stomatal closure which allows a

reduction in water loss and as a consequence, the maintenance of beneficial water potential.

Farooq et al., (2010) reported that the stoma close gradually as drought progresses, followed

by the parallel decline in net photosynthesis. Studies done on maize have shown that drought

stress leads to morphological, physiological and biochemical changes, including reduced

photosynthesis (Pervez et al., 2004; Zhao et al., 2010). Drought stress frequently enhances

allocation of dry matter to the roots which enhance water uptake (Leport et al., 2006).

Although the sorghum crop has evolved appropriate stress tolerance strategies, they are

largely incompatible with the exploitative root parasitic strategy of Striga species (Tesitel et

al., 2015). Given that global change involves a series of environmental factors occurring

concurrently and changes in the severity of different stress factors; knowledge on how plants

72

acclimate to multiple stresses is of key importance in understanding the effects of the future

climate on crops (Niinemets, 2010). An urgent need to generate crops with enhanced

tolerance to stress combinations therefore exists (Suzuki et al., 2014). It is necessary to select

for sorghum genotypes with enhanced tolerance to Striga asiatica, drought, and a

combination of the stresses. To determine the response of sorghum to a combination of

abiotic and biotic stresses applied simultaneously, the effects of Striga asiatica parasite and

drought on chlorophyll content, internode length, dry matter traits and productivity of

sorghum were studied. A combination of drought and Striga stress represent conditions

encountered by many cereal crops growing in the semi-arid environments of the sub tropical

regions of Africa. It becomes necessary to select for sorghum genotypes with enhanced

tolerance to drought and Striga asiatica and their combinations to ensure food security for the

poorly resourced farmers. The objectives of this study were:

i) To determine the effect of Striga infestation and reduced water availability on

normalized difference vegetation index (NDVI), chlorophyll concentration and

sorghum height as tolerance parameters to Striga.

ii) To determine the effects of Striga asiatica infestation and water availability on

sorghum yield and dry matter partitioning of sorghum.

The associated alternate hypotheses were:

i) Striga infestation and reduced water availability, lower chlorophyll content, NDVI

and sorghum height.

ii) Striga infestation and reduced water availability reduces sorghum yield and alters dry

matter partitioning of the host species.

73

3.3 Methodology

3.3.1 Experimental site

The pot experiments were carried out at Bindura University of Science Education (BUSE)

Astra Campus nursery, Bindura (17o 18

1 58

11 S and 31

o 19

1 23

11 East). Bindura is located 89

km north of the city of Harare. The soil type used was sandy, with 4.3 % clay content and a

pH of 4.4. The area receives an annual rainfall of about 700 mm per annum, with an average

temperature of 25 oC in the summer months.

3.3.2 Seed sources

Striga asiatica seeds were obtained from Henderson Research Station (Weed Research team)

at Mazowe in Zimbabwe. The seeds had been collected from Chiwundura communal lands in

the Midlands Province in Zimbabwe from farmers’ fields in the 2009 summer season.

Sorghum seed was obtained from the gene bank at the Department of Research and Specialist

Services in Harare. Wild sorghum seeds were collected from Gwebi Agricultural College

fields, 27 km west of Harare.

3.3.3 Experimental design and treatments

The experiment was a 2 * 2 * 5 factorial experiment laid down as a randomized complete

block design replicated three times. The first factor was sorghum genotype at five levels, the

second factor was infestation at two levels, infested and uninfested. The third factor was

irrigation at two levels, 50 % and 100 % of field capacity. The moisture level of 50 % Field

Capacity (FC) was included to mimic the low rainfall areas in SSA where total rainfall is

usually below 400 mm and that is where Striga has deleterious effects. Irrigation scheduling

was done using the 100 % field capacity application. The experiment was repeated twice over

time, and denoted as experiments I and II.

74

3.3.4 Experimental procedures

Plastic pots with a height of 27 cm and diameters of 25 cm and 17.5 cm for the top and

bottom, respectively, were filled with 8 kg of soil. All pots had six drainage holes at the

bottom. Half the pots were infested with 1 gram of Striga asiatica seeds and mixed with the

top 10 cm of the soil. Fertilizer was applied at a rate of 5 g maizefert (8 N: 14 P2O5: 7 K2O)

per pot. Top dressing was done at 4 weeks after crop emergence (WACE) by applying 2.5

grammes of ammonium nitrate (34.5 % N). Ten sorghum seeds were planted and germinated

after 6 days and were thinned to one plant per pot at 2 WACE. Weeds other than Striga were

hand pulled as soon as they emerged.

3.3.5 Irrigation

The soil had its water holding capacity determined and half the pots were watered with water

that gave the field capacity (FC) and the other by half that amount. To determine field

capacity, five pots with the same oven dried soil were weighed and gradually filled with

water until the addition of any extra water created a tiny flood layer. The pots were then left

to drain freely for 48 hours and weighed again. This method was according to Kabiri et al.,

(2014). The amount required to reach field capacity was 1.5 litres per pot. The pots were

irrigated to a moisture content of 100 % and 50 % field capacity according to Webster and

Grey (2008) and Chauhan and Johnson (2010).

3.3.6 Data collection

Data collected during crop growth were: normalized difference vegetation index (NDVI),

chlorophyll content and sorghum internode length. The NDVI was measured using a

handheld green-seeker optical sensor unit (NTech industries, Inc, USA). Chlorophyll content

was measured using a chlorophyll meter (SPAD 502, KONICA MINOLTA Incl) starting

75

from 6 WACE. At the end of the experiment, head weight and total dry matter were

determined using a sensitive scale. At crop maturity, the sorghum plants were harvested and

partitioned into roots, leaves and stems. They were put in the drier at 104 oC for 48 hours for

dry matter determination using a sensitive weight scale. Total dry matter constituted the total

weights of roots, leaves, stems and head for each treatment. Head, stem, leaf and root indices

were computed as follows:

Part (e.g. roots, leaves stems) Index = Part weight/Total dry weight.

3.3.7 Statistical analysis

Data was assessed by analysis of variance using Genstat version 14. Means that were

significantly different were separated using LSD at 0.05 probability level.Barlett’s test was

applied and variances for the two experiments were not homogeneous, hence the data were

analysed separately.

3.4 Results

3.4.1 Chlorophyll concentration and NDVI

Sorghum varieties differed sharply with respect to chlorophyll concentration (P<0.01).

Across all the measured periods (6 and 10 WACE) in both experiments, the sorghum

genotype Mukadziusaende gave the highest chlorophyll content and the least was recorded

for wild sorghum (Table 3.1).

76

Table 3.1: Sorghum genotypes effects on chlorophyll content at 6 and 10 WACE

Experiment I

Chlorophyll concentration

(mmolcm-2

)

Experiment II

Chlorophyll concentration

(mmolcm-2

)

Sorghum

genotype

6 WACE 10 WACE 6 WACE 10 WACE

SC Sila 40.21±2.14a 40.5±2.025

a 38.39±2.035

a 31.04±3.152

a

Mukadziusaende 43.00±2.14a 47.23±2.025

b 42.33±2.035

b 33.55±3.152

a

Wild Sorghum 34.9±2.14b 36.3±2.025

c 32.39±2.035

c 29.78±3.152

a

Chiredhi 40.07±2.14a 42.09±2.025

a 38.49±2.035

a 32.95±3.152

a

Isifumbathe 43.77±2.14a 41.46±2.025

a 39.8±2.035

a 31.97±3.152

a

At increased moisture availability, there were significantly higher (P<0.005) NDVI values

compared to 50 % FC across the measured periods in both experiments (Table 3.2).

77

Table 3.2: Moisture stress effects on NDVI at 6 and 10 WACE

Experiment I Experiment II

6 WACE 10 WACE 6 WACE 10 WACE

100 % FC 0.525±0.067a 0.594±0.0242

a 0.59±0.0242

a 0.528±0.0267

a

50 % FC 0.464±0.067b 0.523±0.0242

b 0.523±0.0242

b 0.464±0.0267

b

At 10 WACE in experiment II, there was a significant interaction of genotype and water

availability on NDVI (Figure 3.1). For the genotype Chiredhi, higher NDVI were found at

100 % FC compared to 50 % FC. All the other genotypes had similar NDVI despite different

moisture availabilities (Figure 3.1).

78

Sorghum varieties

SC Sila

Mukadziusaende

Wild SorghumChiredhi

Isifumbathe

ND

VI

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7100 %

50 %

Figure 3.1: Interaction effects of sorghum genotype and moisture availability on NDVI at 10

WACE in Experiment II.

Chlorophyll content was not significantly affected by infection except at 6 WACE in

Experiment II (Table 3.3). Infection did not affect chlorophyll content in Experiment I and at

10 WACE in Experiment II. At 6 WACE, uninfested sorghum had a significantly higher

chlorophyll content compared to infested (Table 3.3).

79

Table 3.3: Effect of S. asiatica infection on chlorophyll content of sorghum

Chlorophyll content (mmolcm-2

)

Experiment I Experiment II

6 WACE 10 WACE 6 WACE 10 WACE

Infected 40.99±1.359a 41.54±1.295

a 36.73±1.458

a 31.35±1.994

a

Uninfected 39.79±1.359a 41.59±1.295

a 39.8±1.458

b 32.37±1.994

a

Figure 3.2: Interaction effects of sorghum genotypes and water availability on chlorophyll

concentration at 6 WACE in Experiment II.

The genotypes Mukadziusaende, Wild sorghum and Chiredhi maintained their chlorophyll

content despite variations in moisture availability. The chlorophyll concentration of

genotypes Isifumbathe and SC Sila was significantly (P<0.05) lowered by reduced moisture

availability (Figure 3.2).

80

Sorghum genotypes

Sc Sila

Mukadziusaende

Wild

Sorghum

Chiredhi

Isifumbathe

Ch

loro

ph

yll

co

nte

nt (m

mo

lcm

-2)

0

10

20

30

40

50

60

100 % FC

50 % FC

Figure 3.2: Interaction effects of sorghum genotypes and water availability on

chlorophyll concentration at 6 WACE in experiment II.

3.4.2 Internode length

Sorghum internode length was significantly lowered by infection (P<0.01). The uninfested

sorghum genotypes gave longer internode lengths compared to infested ones (Figure 3.3).

Infestation status

Infested Uninfested

Inte

rnod

e le

ngth

(cm

)

0

2

4

6

8

10

Figure 3.3: Effect of Striga infestation on internode length.

81

A significant interaction of infection and drought (P<0.01) showed that under Striga

infestation, internode length was the same both for 100 % FC and 50 % FC, whilst under non

infested conditions, 100 % FC increased sorghum internode compared to 50 % FC (Figure

3.4)

Infection status

Infested Uninfested

Inte

rnod

e leng

th (

cm

)

0

2

4

6

8

10

12

100 % FC

50 % FC

Figure 3.4: Interaction effects of Striga infestation and water availability on sorghum

internode length.

3.4.2 Dry matter traits

Striga infested sorghum significantly (P<0.05) increased both root weight and root index in

experiment I. In experiment II, infestation did not affect either root weight or root index

(Table 3.4). In both experiments, irrigation at 100 % FC increased root weight compared to

50 % FC.

82

Table 3.4: Effect of infestation and moisture availability on root weight and root index

Experiment I Experiment II

Root weight (g) Root Index Root weight Root index

Striga infested 39.6±4.53a 0.489±0.029a 34±3.99a 0.479±0.028a

Uninfested 29.4±4.53b 0.429±0.029b 28.8±3.99a 0.426±0.028a

100 % FC 41.4±4.53a 0.464±0.029a 37.4±2.28a 0.448±0.028a

50 % FC 27.6±4.53b 0.453±0.029a 25.4±2.28b 0.457±0.028a

Head weight and head index were significantly affected by sorghum genotype across the two

experiments (Table 3.4).

Table 3.5: Effect of sorghum genotypes on head weight and head index

Experiment I Experiment II

Sorghum

genotype

Head weight (g) Head index Head weight (g) Head index

SC Sila 4.04±1.304a 0.056±0.0266

a 5.52±1.228

a 0.0659±0.0211

a

Mukadziusaende 8.12±1.304b 0.165±0.0266

b 8.05±1.228

b 0.1446±0.0211

b

Wild Sorghum 0.44±1.304c 0.005±0.0266

a 1.96±1.228

c 0.0207±0.0211

c

Chiredhi 3.22±1.304a 0.0544±0.0266

a 3.4±1.228

c 0.0486±0.0211

ac

Isifumbathe 1.85±1.304ac

0.0339±0.0266a 1.94±1.228

c 0.0268±0.0211

dc

83

Head weight was highest on the genotype Mukadziusaende, which had head indices of 0.16

and 0.45 in experiment I and II respectively. The least head weight and head index were

recorded for wild sorghum in both experiments (Table 3.5).

Table 3.6: The effect of infection on head weight and head index

Experiment I Experiment II

Head weight (g) Head index Head weight (g) Head index

Infested 2.31±0.825a 0.0385±0.0168

a 2.83±0.777

a 0.0432±0.0134a

Uninfested 4.76±0.825b 0.0874±0.0168

b 5.52±0.777

b 0.0795±0.0134

b

The results revealed that infestation significantly reduced head weight and head index in both

experiments. Non infestation led to increase in head weight and head index in both

experiments (Table 3.6).

Table 3.6: The effect of water availability on head weight and head index across the two

experiments

Experiment I Experiment II

Head weight (g) Head index Head weight (g) Head index

100 % FC 4.93±0.825a 0.0755±0.034

a 6.14±0.777

a 0.777±0.0133

a

50 % FC 2.14±0.825b 0.0504±0.034

a 2.21±0.777

b 0.045±0.0133

b

84

Increased water availability significantly increased head weight and head index in both

experiments except head index in experiment I (Table 3.6). Increased moisture availability

significantly increased (P<0.05) head weight for SC Sila and Mukadziusaende, whilst the rest

of the sorghum genotypes did not respond to moisture availability (Figure 3.3).

Sorghum genotypes

Sc Sila

Mukadziusaende

Wild

Sorghum

Chiredhi

Isifumbathe

So

rgh

um

yie

ld (

g)

0

2

4

6

8

10

12

14

16

100 % FC

50 % FC

Figure 3.3: The response of sorghum genotypes yield to moisture availability.

The yields of wild sorghum, Chiredhi and Isifumbathe were not affected by water

availability. However, yields of SC Sila and Mukadziusaende were lowered by reduced

moisture availability although they remained higher than the other genotypes (Figure 3.5).

The yield of Mukadziusaende at 50 % water availability was still higher compared to wild

sorghum at 100 % FC (Figure 3.5).

In experiment II, leaf index, stem weight and stem indices were significantly affected by

sorghum genotypes (Table 3.7). However, SC Sila had a significantly (P<0.01) higher dry

weight and the least was Mukadziusaende. This trend was repeated for Experiment 11 (Table

85

3.7). Infestation did not affect leaf weight, leaf index, stem weight and stem index and total

dry matter for both experiments (Table 3.8). However, irrigation at 100 % field capacity gave

a significantly higher leaf weight, leaf index, stem weight, stem index and total dry matter in

both experiments (Table 3.9).

86

Table 3.7: Effect of sorghum genotypes on leaf dry matter, leaf index, stem weight and index and total dry matter in both experiments

Experiment I Experiment II

Sorghum genotype Leaf Index Leaf dry matter

(g)

Stem weight

(g)

Stem index Total dry

matter (g)

Leaf weight (g) Leaf index Stem weight

(g)

Stem index Total dry matter

(g)

Sc Sila 0.197±0.028a 14.54±1.754a 21.2±3.2a 0.284±0.032a 78.4±9.21a 14.92±1.684a 0.2055±0.024a 19.0±2.91a 0.262±0.034a 75.8±7.83a

Mukadziusaende 0.1888±0.028a 9.20±1.754b 15.9±3.2a 0.312±0.032a 49.7±9.21b 8.85±1.684b 0.1767±0.024a 14.84±2.91a 0.291±0.034a 49.8±7.83b

Wild sorghum 0.2028±0.028a 16.81±1.754a 18.4±3.2a 0.248±0.032a 76.3±9.21a 15.7±1.684a 0.2314±0.024a 17.12±2.91a 0.238±0.034a 71.5±7.83a

Chiredhi 0.1972±0.028a 14.62±1.754a 22.9±3.2a 0.293±0.032a 77.9±9.21a 13.32±1.684a 0.1954±0.024a 21.27±2.91a 0.303±0.034a 71.4±7.83a

Isifumbathe 0.222±0.028a 15.94±1.754a 18.4±3.2a 0.248±0.032a 74.1±9.21a 12.91±1.684a 0.1925±0.024a 19.3±2.91a 0.292±0.034a 66.7±7.83a

Table 3.8: The effect of infection on leaf weight and index, stem weight and index and total dry matter in both experiments.

Experiment I Experiment II

Leaf weight (g) Leaf index Stem weight (g) Stem index Total dry matter

(g)

Leaf weight (g) Leaf index Stem weight (g) Stem Index Total dry matter

(g)

Infested 14.63 0.205±0.018a 19.4±2.03a 0.267±0.014a 75.9±5.82a 13.48±1.06a 0.2028±0.015a 17.99±1.84a 0.269±0.02a 68.3±4.95a

Uninfested 13.82 0.197±0.018a 19.3±2.03a 0.287±0.014a 66.7±5.82a 12.8±1.06a 0.1978±0.015a 18.62±1.84a 0.285±0.02a 65.7±4.95a

87

Table 3.9: The effects of water availability on leaf weight and index, stem weight and index and total dry matter.

Experiment I Experiment II

Water

availability

Leaf weight (g) Leaf index Stem weight (g) Stem Index Total dry

matter (g)

Leaf weight (g) Leaf Index Stem weight (g) Stem index Total dry

matter (g)

100 % FC 15.81±1.109a 0.1947±0.0176a 22.1±2.03a 0.266±0.302a 84.2±5.82a 15.08±1.065a 0.1943±0.015a 21.3±1.842a 0.269±0.02a 79.9±4.95a

50 % FC 12.64±1.109b 0.1922±0.0176a 16.6±2.03b 0.287±0.302b 58.4±5.82b 11.20±1.065b 0.2063±0.015a 15.32±1.842b 0.285±0.02a 54.1±4.95b

88

There was a significant effect of infection and drought on leaf index (P<0.05) (Figure 3.7)

Infestation status

Infested Uninfested

Leaf

inde

x

0.00

0.05

0.10

0.15

0.20

0.25

0.30

100 % irrigation

50 % Irrigation

Figure3.6: Interaction effects of water availability and Striga infestation on leaf index.

Under infestation, 100 % irrigation had a lower leaf index compared to 50 % and under

infestation there were no significant differences (Figure 3.7). There was a significant

interaction of variety and infection on stem dry matter (P <0.05). Stem weight of wild

sorghum was reduced by Striga infestation (P<0.05) whilst it was vice versa for Chiredhi

(Figure 3.7).

89

Sorghum genotypes

Sc Sila

Mukadziusaende

Wild sorghumChiredhi

Isifumbathe

Stem

weig

ht (g

)

0

5

10

15

20

25

30

35

Infested

Uninfested

Figure 3.7: Interaction effects of sorghum genotypes and Striga asiatica infestation on stem

weight

3.5 Discussion

The objective of the study was to determine the effects of Striga asiatica and water stress

occurring simultaneously on sorghum productivity. The sorghum genotype Mukadziusaende

had the highest chlorophyll concentration of 47.33 mmolcm-2

, and the least was recorded for

wild sorghum, with 29.78 mmolcm-2

. This trend for chlorophyll concentration was the same

for both experiments. These values are in the range commensurate with Gurney et al.,

(2002)’s findings, where a maximum of 47.44 and a minimum of 32.33 mmolcm-2

were

reported.

Chlorophyll concentration was lowered by moisture deficit when irrigated at 50 % FC

compared to 100 % FC (Table 3.2) but was not affected by infection (Table 3.4). This

contrasts with the findings of Gurney et al., (2002), where Striga asiatica infection alone

90

reduced chlorophyll concentration. Similar results were also found by Wahid and Rasul

(2005) and Fu and Huang (2001) who reported that drought impaired the photosynthetic

machinery of the plant which eventually reduces food production. Likewise, Anjum et al.

(2003) also reported changes in photosynthetic pigments and their components as a result of

drought. According to Niinemets et al., (2010), measurements of chlorophyll provides an

important tool to gaining insight into modifications of foliage physiological activity. The

sensitivity of photosynthesis to both biotic and abiotic stresses varies with plant genotype

tolerance. This study revealed that sorghum genotypes vary greatly with respect to

chlorophyll concentration when exposed to the same environmental limitations. Palta et al.,

(1994) and Zhang et al., (1998) reported that water deficits result in early senescence which

results in reduced chlorophyll concentrations. The results of this study suggested that drought

stress takes precedence over Striga asiatica stress when they co-occur in sorghum. This may

be attributed to the fact that water has to be available prior to Striga asiatica infection in

sorghum. The results may also suggest that the two are mutually exclusive on their effects on

chlorophyll concentration in sorghum.

The responses of sorghum genotypes to chlorophyll content under 50 and 100 % FC tended

to differ (Figure 3.2). The genotypes Mukadziusaende, wild sorghum and Chiredhi had

similar chlorophyll content at both irrigation regimes. However, reduced water availability

lowered the chlorophyll content of genotypes SC Sila and Isifumbathe. Similar results were

found by Gurney et al., (2002) who reported a maize variety, ‘Staha’, whose foliar

chlorophyll concentration was unaffected by the parasite. In the current study, it was

hypothesized that the genotypes Mukadziusaende, wild sorghum and Chiredhi showed

resilience to both stresses hence photosynthesis was maintained in these genotypes despite

the presence of both stresses, which may help maintain sorghum productivity. This may be

due to the limited sensitivity of the genotypes towards drought. According to Cameron et al.,

91

(2006), it is known that the responses of the genotypes to reduced water availability might be

high osmotic adjustments that help maintain leaf water potential. Bloom et al., (1985)

reported that even in limited supply of resources, plants have to maintain a balanced

investment such that all functions and organs are limited to the same degree. Across all the

two experiments, NDVI was higher at 100% compared to 50 %. NDVI is a measurement of

amalgamated plant growth that reflects the effects of various plant growth factors and is

highly correlated with plant available soil moisture (Verhulst and Govaerts, 2010). For the

genotypes SC Sila, Mukadziusaende, wild sorghum and Isifumbathe, NDVI was lowered by

drought treatments. Bjorkman and Powles (1984) reported that the effect of S. asiatica on

both photosynthetic performance and photo-inhibition of maize plants under light conditions

is similar to the effects observed when abiotic factors such as water shortage are imposed. For

the genotype Chiredhi, NDVI was higher at 100 % moisture compared to 50 %, whilst the

rest of the genotypes were not affected. Irrigation at 50 % of field capacity could have limited

nitrogen assimilation and consequently lowered chlorophyll concentration in the affected

genotypes.

Under infested conditions, moisture availability did not affect internode length. However, 100

% FC under uninfested conditions increased internode length (Figure 3.4). The fact that

drought reduced internode length in sorghum is in tandem with Deligoz and Gur (2015)’s

findings who reported that drought stress causes physiological and metabolic changes which

negatively affects growth and development of plants. Actually, Farooq et al., (2009) reported

that growth is accomplished by cell division, enlargement and differentiation. Nonami (1998)

posited that under water deficient conditions, cell elongation can be inhibited by interruption

of water flow from xylem vessels to surrounding cells. This study revealed that in relation to

internode length, the effect of reduced water availability is equal to the effect of Striga.

92

Under 50 % FC, non infested sorghum had limited growth and it only grew when water was

made available at 100 % FC.

Striga infestation increased dry matter allocated to the roots in Experiment I, but had no

effect on experiment II. This agrees with Poorter et al., (2011), who reported that plants

allocate more dry matter to the roots as the limiting factor is below the ground. Similar results

were also found by Farooq et al., (2009 and Liu et al., (2011). The results indicated that root

dry mass decreased under drought, which was also reported by Luttschwager et al., (2016),

who found decreased root mass under drought in Populus tremula.

Head weight and head index were lowered by S. asiatica infestation and drought (Tables 6

and 7). The results are in tandem with the findings of Baker et al., (1996) and Vasey et al.,

(2005) in which infestation reduced dry matter allocated to the head. Similar results were

found by Pandey et al., (2000) who found that the harvest index was lowered by increased

water stress. Groene (2008) concurs with the assertions and reported that drought has an

effect on pollen viability, pollen tube germination and increases in ovule abortion rates as a

result of reduction in assimilate supplies which are required for grain development.

According to Ober et al., (1991), water stress resulted in diminished grain set and kernel

growth in wheat and decreased rate of endosperm cell division. Striga asiatica causes

increases in abscissic acid (Taylor et al., 1996; Frost et al., 1997). Also, increases in ABA

concentration as a result of drought had been previously documented by Aldesuquy and

Ibrahim, (2001) and Gniazdowska et al., (2007). Cramer et al., (2011) asserted that ABA is

an important regulator of plant responses to both abiotic and biotic stresses. Both drought and

Striga infestation have been reported to lead to an increase in ABA production and

consequently cause stomatal closure reducing carbon dioxide entrance into the leaf, hence

reduced productivity.

93

Leaf and stem indices were not affected by sorghum genotypes (Table 3.8) and infestation

(Table 3.9) whereas they were both reduced by irrigation at 50 % of field capacity. These

results are in disagreement with the findings of Aflakpui et al., (1998), who found that Striga

infestation reduced leaf and stem indices. However, their study on maize was subjected to

Striga only whereas in this study, drought was also a factor that was added to S. asiatica

infection. Taken together, these results indicated that the response of sorghum to S. asiatica

and drought is complex and cannot be extrapolated from the results of each stress applied

singly. This confirms the assertion by Mittler (2005) that two or more stresses may require a

unique response on the hosts and that the responses may have synergistic or antagonistic

effects on each other. From the results, drought effects got preference when they co-existed

with Striga infestation. The simultaneous occurrence of different biotic and abiotic stresses

was shown to result in a high degree of complexity in plant responses as the responses to

these combined stresses are largely controlled by different signaling pathways that may

interact or inhibit one another (Artkinson and Urwin, 2012; Rasmussen et al., 2013).

Consequently, the fact that drought only had a significant influence on leaf and stem biomass

indicated that its influence was greater than that of S. asiatica or the response pathways to

drought suppresses the effects of S. asiatica. The effects of S. asiatica are inhibited when it

co-exists with drought in sorghum. Results from this study confirmed the findings of

Artkinson and Urwin (2012), who reported that plants respond in a specific manner when

they have to face more than one stress simultaneously, and the response cannot be predicted

based on the plant’s response to the individual stresses.

Leaf index was higher under infested conditions at 50 % irrigation compared to uninfested

conditions (Figure 3.4). This demonstrated that the two stresses resulted in more dry matter

94

being channeled to the leaves. These results confirmed the assertion by Suzuki et al., (2014)

that stress combinations might have beneficial effects on plants compared to each stress

applied separately.

Stem weight was not significantly affected by infections for all varieties except for wild

sorghum where infection lowered stem weight but increased stem weight for Chiredhi.

Reduced allocation of dry matter to the stems combined with increased allocation to the roots

was reported by Frost et al., (1995) and Graves et al., (1990). It is now known that the

parasite acts as a sink for carbon, inorganic solutes and water and also because of the reduced

carbon gain in infested hosts as reported by Smith et al., (1995) and Cechin and Press (1993).

Under infestation, reduced water availability increased leaf index and this is likely an issue of

overcompensation.

3.5 Conclusions

The study found that with respect to chlorophyll content, reduced water availability and

infestation were mutually exclusive. With respect to sorghum internode length, the resilience

of sorghum to Striga asiatica is reduced when sorghum is affected by drought which shows

synergistic effects of drought and S. asiatica infestation..

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CHAPTER FOUR:

The response of tolerance traits of Sorghum bicolor (L) Moench

and Sorghum arundinaceum (Desv) Stapf to Striga asiatica (L)

Kuntze infestation under mulch

4.1 Abstract

The production of sorghum is hampered by the parasitic weed Striga asiatica. Studies are

lacking on the effect of cultural techniques of managing the weed such as mulching.

Mulching is promoted as a component of the conservation agriculture systems in sub Saharan

Africa. Nine Sorghum bicolor cultivars and one Sorghum arundinaceum line were evaluated

under Striga infestation and under Striga free conditions with half being mulched and the

other half unmulched for two years at Bindura University of Science Education (BUSE)

nursery in Zimbabwe. The objective was to assess the effects of mulching and infestation on

the tolerance of Sorghum bicolor and Sorghum arundinaceum to Striga asiatica. The

experiment was a 2*2*10 factorial, replicated three times in both seasons and arranged as a

completely randomized design. Results indicated that mulching increased chlorophyll content

in the 2014/15 season compared to 2013/14. Infestation reduced chlorophyll content in both

seasons. For the 2014 season, mulching increased chlorophyll content in all varieties except

Ruzangwaya, Mukadziusaende and SC Sila. Stomatal conductance and tiller numbers were

higher (P<0.01) in uninfested sorghum compared to infested in both seasons. The varieties

Mukadziusaende, Chiredhi and Hlubi were able to maintain height despite infestation by

Striga. When the same varieties were infested under mulch and infested without mulch, the

104

results showed that mulching overcomes the effect of infestation in some varieties. Varieties

Chiredhi, Mukadziusaende and Mashava were able to maintain yield despite infestation by

Striga in the 2013 season. Wild sorghum was highly susceptible to Striga. Mulching negates

the effect of Striga parasitism in the drier season compared to wetter season and results in

yield maintenance in some varieties.

4.2 Introduction

Sorghum (Sorghum bicolor L) is a multipurpose crop belonging to the Poaceae family, which

are C4 carbon cycle plants with high photosynthetic efficiency and productivity (Tari et al.,

2013). Sorghum is a preferred crop in sub tropical Africa as it can maintain yields in

environments normally regarded as too hostile for other crops such as maize. Many people in

Southern Africa live in chronic food deficit regions including the semi-arid zones where

rainfall shortage causes recurring food shortages and consequent malnutrition. In these

regions, sorghum is a critical strategic grain crop for a vast number of farmers. It is an

essential component of sustainable agricultural systems in the region’s extensive semi-arid

areas. Improvement of sorghum productivity is an immediate priority in these areas.

Striga species are obligate hemi-parasitic plants that attach to the root of the host to obtain

water, nutrients and carbohydrates (Parker and Riches, 1993). The life cycle of Striga

asiatica is complex, and co-evolved with many hosts to comprise a series of discrete steps

that are tightly coupled to the host’s biochemistry and life cycle (Bouwmeester et al., 2003).

The parasite grows underground for 4 – 8 weeks prior to emergence (Jamil et al., 2013). The

severe infestations appear to render African farmers helpless even though they are otherwise

very resilient and adaptive (Ejeta, 2007). The extent and intensity of Striga species

infestations has rapidly increased and become a threat to food production in practically the

entire semi-arid region farming systems of southern Africa.

105

Effective control of S asiatica has proved challenging, mostly as a result of the intricate life

cycle of the parasite (Gurney et al., 2003). Complete resistance has not been identified in

sorghum although varieties vary in their sensitivity to the parasite (Gurney et al., 1995).

Therefore, the traits that reduce fitness impacts of damage such as maintenance of

chlorophyll, increased photosynthesis, compensatory growth and tiller production despite

infection are very critical in varietal selection under Striga infestations. Also, any cultural

practice that negates Striga parasitism is critical to sorghum productivity.

Cultural practices like mulching may enable expression of tolerance since the parasite affects

the water economy of the plant. Mulch tends to develop and strengthen the top soil structure

through soil protection, microfauna activities and the incorporation of organic matter which

usually provides a high infiltration rate (Rao et al., 1998, Scopel et al., 1998). Mulch reduces

surface runoff due to increased roughness (Gilley et al., 1991; Gilley and Kottwitz, 1992).

Adekalu et al., (2007) reported increased water infiltration with increasing levels of mulch.

The same mulch has low thermal conductivity such that soil temperature is reduced

sometimes with consequent decrease in root development (Riddle et al., 1996). Generally

mulching is known to reduce weeds through physical effects and allelopathy. However, this

information relates to non-parasitic weeds and there is limited information on the effects of

mulching on Striga incidence and parasitism.

Sorghum arundinaceum is increasing in Zimbabwe’s cropping systems as a weed and occurs

in all crops. Studies by Gurney et al., (2002) and Rich et al., (2004) found a Sorghum

arundinaceum strain that was tolerant to Striga. In Zimbabwe, Mwenje (2006) reported high

compatibility between cultivated sorghum and its wild relatives. Therefore, the objectives of

this study were:

106

i) To determine the effect of mulching and Striga infestation on sorghum chlorophyll

concentration, stomatal conductance, sorghum height and Striga counts.

ii) To determine the effect of mulching and Striga infestation on sorghum grain yield and

dry matter traits.

The corresponding alternative hypothesis were

i) Mulching and Striga infestation affect the expression of tolerance traits of sorghum

genotypes with respect to chlorophyll concentrations, stomatal conductance,

sorghum height and Striga counts.

ii) Mulching and Striga infestation affect the expression of tolerance traits in sorghum

with respect to sorghum grain yield and dry matter partitioning.

4.3 Materials and methods

4.3.1 Experimental site

The pot experiments were carried out at Bindura University of Science Education (BUSE)

Astra Campus nursery, Bindura (GPS coordinates: 17o 181 5811 S and 31

o 19

1 2311 East) during

the 2013/14 and 2014/15 summer seasons. The area is located in agro-ecological region 11b

according to the Zimbabwean classification system (Vincent and Thomas, 1961) and it

receives a total of 800 mm of rainfall per season from November to April. The pot

experiment was done in medium grained sands with a pH of 4.2.

4.3.2 Experimental design and pot layout

For both seasons, the experiment was 2*2*10 factorial experiment. The first factor was

mulch at two levels: mulched at a rate equivalent to 3 t ha-1

and 0 t ha-1

. The second factor

was infestation at two levels: infested and uninfested. The third factor was sorghum genotype

107

at 10 levels (Table 4.1). The experiment was laid down as a completely randomized design

replicated three times.

Table 4.1: Sorghum genotypes tested for tolerance to Striga in the 2013/14 and 2014/15

seasons

Sorghum variety/code* Region Collected/grown Local name

1551 Matebeleland Isifumbathe

1773 Chiredzi Chiredhi

1836 Mrewa Mashava

1555 Matebeleland Tswetha

1556 Matebeleland Hlubi

1697 Masvingo Mukadziusaende

1669 Matebeleland Zambia

4487 Masvingo Ruzangwaya

SC Sila Zimbabwe

Wild sorghum Mashonaland West

*Codes refer to accession numbers at the Department of Research and Specialist Services,

gene bank in Harare, Zimbabwe

4.3.4 Source of Seeds

Sorghum and S. asiatica seeds were obtained from a source as stated in Section 3.3.2.

4.3.5 Experimental details

The soil was obtained from a farmer’s field where no Striga was reported before. The pots

were filled with soil and the top 10 cm of the soil was thoroughly mixed with 5.7 g of maize

fert (7N: 14 P2O5: 7 K2O) compound fertiliser and 1 g of conditioned S. asiatica seed. The

soil/S. asiatica mixture was placed back into the bucket after mixing thoroughly. Ten

108

sorghum seeds were planted in the bucket at a depth of 0.5 cm. The pot filling and planting

process was started on the uninfested pots to avoid contamination. The experiment was rain-

fed and the sorghum seedlings were thinned to one plant per pot at two weeks after crop

emergence (WACE). Sorghum plants were top-dressed by applying 3 grams of ammonium

nitrate (34.5 % N) per pot representing 90 kg ha-2

at 4 WACE. Non Striga weeds which

emerged were manually pulled and this was done continuously throughout the experimental

period.

4.3.6 Data collection

Height of the plants was measured and tiller number counted at 8 and 12 weeks after crop

emergence. Chlorophyll content was measured by a chlorophyll meter (SPAD-502 KONICA

MINOLTA INCL) at 6, 8 and 12 WACE. Sorghum yield was estimated by harvesting the

head when the sorghum plant had reached maturity and was weighed using a sensitive scale.

Stomatal conductance was measured using a porometer (DECAGON INCL).

4.3.7 Data analysis

Analysis of variance was performed to examine the effects of treatments and their

interactions on chlorophyll content, stomatal conductance, plant height and yield. The

Bartlett’s test for homogeneity of variance procedure showed that variances were not

homogeneous and hence, the data were analysed separately. The analysis was performed

using Genstat statistical software, Version 14. S. asiatica counts were subjected to square root

transformation prior to analysis.

4.4 Results

4.4.1 Chlorophyll content

109

Mulching increased (P<0.001) chlorophyll concentration at 6, 8 and 12 WACE for the

2014/15 season while it had no significant effect (P>0.05) during the 2013/14 season (Table

4.2).

Table 4.2: Effect of mulching on chlorophyll concentration for the 2013/14 and 2014/15

summer seasons

Condition Chlorophyll content for the 2013/2014

summer season

Chlorophyll content (mmolcm-2

) for 2014/2015 summer

season

6 WACE 8 WACE 12 WACE 6 WACE 8 WACE 12 WACE

Mulched 19.83a 31.62

a 41.06

a 20.69±0.883

a 46.25±1.014

a 37.69±1.376

a

Unmulched 20.3a 31.55

a 39.87

a 17.11±0.883

b 39.23±1.014

b 31.09±1.376

b

Infestation also lowered chlorophyll concentration at 6 WACE in the 2014/15 season but was

not significant at 8 and 12 WACE during the same season (Figure 4.1).

Figure 4.1: Effect of infestation on chlorophyll concentration at 6 WACE during the 2014/

15 season.

110

Sorghum genotypes

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

TshwethaSc Sila

Wild Sorghum

Chl

orop

hyll

conc

entr

atio

n (m

mol

cm-2

)

5

10

15

20

25

30

35

Infested

Uninfested

8 WACE in 2014 season

Sorghum genotypes

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

TshwethaSc Sila

Wild Sorghum

Chl

orop

hyll

conc

entra

tion

(mm

olcm

-2)

20

25

30

35

40

45

50

55

60 Mulched

Unmulched

Figure 4.2: Interaction between variety and Striga infestation a) 6 WACE andvariety and

mulch b) 8 WACE on chlorophyll concentration

There was a significant interaction of variety and mulching on chlorophyll content in the

2013/14 season (P<0.01) (Figure 2) and variety and Striga infestation (P<0.001).

111

At 6 WACE in the 2013, infestation significantly (P<0.05) lowered chlorophyll content of SC

Sila whilst all the other varieties were not affected. At 6 WACE in the 2014/15 season,

Isifumbathe, Chiredhi, Zambia and Wild sorghum had their chlorophyll concentration

significantly lowered by infection. Mulching significantly increased (P<0.01) chlorophyll

content in all varieties except Ruzangwaya, Mukadziusaende, Mashava and SC Sila. At 8

WACE, infestation lowered chlorophyll content (P<0.05) of wild sorghum whilst the content

for Tshwetha was not affected.

Figure 4.3: Effect of infestation status on stomatal conductance for the sorghum genotypes

during the 2013/14 season.

There was a significant effect of infection on stomatal conductance (P<0.001) (Figure 4.3).

The results revealed lowered stomatal conductance due to infestation compared to uninfested

conditions.

4.4.2 Tillering

112

The results showed that Mukadziusaende, Mashava and Isifumbathe had the highest tillers in

the 2013/14 summer season. The same varieties had the highest tiller numbers in the 2014/15

season. The 2013/14 season had less tillers for Chiredhi than 2013/14 season while 2014/15

had more tillers for Mukadziusaende and the same was true for Tshwetha (Figure 4.4).

Sorghum genotype

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

TshwethaSC Sila

Wild Sorghum

Till

er n

umbe

rs

0

1

2

3

4

5

2014 -15 season

2013 - 14 season

Figure 4.4: Effect of season on tiller numbers over two seasons.

Infestation status

Infested Uninfested

Till

er

nu

mb

er

0

1

2

3

4

Figure 4.5: Effect of infestation status on tiller numbers

113

For the variety Mukadziusaende and Tswetha, tiller number was significantly higher in the

2013/14 season compared to the 2014/15. Also infestation significantly (P<0.001) lowered

tillering across all the sorghum genotypes (Figure 4.5).

Sorghum genotypes differed significantly (P <0.05) at 10 WACE with regard to S. asiatica

incidence. The sorghum genotype Hlubi supported the highest number of S. asiatica plants

while Isifumbathe and Mukadziusaende supported the lowest at 10 WACE during both

seasons (Table 4.6).

Table 4.6: Effect of sorghum variety on Striga counts

Sorghum variety Striga counts at 10 WACE in 2013-

14 season

Striga counts at 10 WACE in 2014-

15 season

Hlubi 3.4 (12.88)±0.632d 5.08 (29.5)±0.71

e

Isifumbathe 1.28 (3.5)±0.632a 2.59 (8.2)±0.71

ab

Ruzangwaya 1.85 (4.67)±0.632abc

4.11 (21.7)±0.71cde

Chiredhi 1.73 (4.33)±0.632abc

2.34 (6.8)±0.71a

Mukadziusaenda 1.49 (3.67)±0.632ab

2.29 (5.5)±0.71a

Mashava 2.81 (8.67)±0.632cd

3.54 (13.7)±0.71abcd

Zambia 2.02 (4.17)±0.632abc

2.77 (8.5)±0.71abc

Tswetha 2.19 (5.87)±0.632abc

4.68 (23.2)±0.71de

SC Sila 2.66 (7.5)±0.632bcd

3.82 (14.8)±0.71bcde

Wild Sorghum 1.72 (5)±0.632abc

3.65 (13.5)±0.71abcd

The numbers in brackets represent the actual counts and those not in brackets are figures after square root transformation.

114

4.4.4 Plant height

The effects of Striga infection on sorghum height are shown in Figure 4.6. At 6 WACE,

Striga infection significantly reduced the height of some sorghum varieties. It was clear that

the impact of Striga infection on sorghum height was different among sorghum varieties at 12

WACE. It was interesting to note that Striga infection did not significantly reduce the

heights of Isifumbathe, Mukadziusaende and Chiredhi. In contrast, Striga infection reduced

the height of other sorghum cultivars (Figure 4.6).

8 wace in 2014 - 15 season

Sorghum genotype

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

TshwethaSC Sila

Wild Sorghum

Sor

ghum

hei

ght (

cm)

20

30

40

50

60

70

80

90

Infested

Uninfested

115

Sorghum genotypes

N.a.N.Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

TshwethaSC Sila

Wild Sorghum

So

rghu

m h

eig

ht (

cm)

0

20

40

60

80

100

120

140

Infested

Uninfested

Figure 4.6: Interaction effects of sorghum genotype and S. asiatica infection on sorghum

height in the 2014/15 season at 8 and 12 WACE.

The interaction revealed that all varieties, except Tshwetha, maintained their plant height

when infested pots were compared with uninfested ones. There was a significant interaction

of variety, mulching and infestation. Sorghum varieties responded differently to mulching

and infestation. Variety Isifumbathe had the least height under unmulched and infested

treatments (Figure 4.7). For SC Sila, plant height under mulched and infested pots was

significantly (P<0.05) taller than under unmulched uninfested plants (Figure 4.7).

116

Sorghum genotypes

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

TshwethaSC Sila

Wild Sorghum

Pla

nt heig

ht (c

m)

0

20

40

60

80

100

120

140

160

180

Mulched infested

Mulched uninfested

Unmulched infested

Unmulched uninfested

Figure 4.7: Interaction effects of sorghum genotype, mulching and infestation on plant height

in the 2014/15 season.

For the varieties Ruzangwaya, Tshwetha and SC Sila, mulched and infested pots gave taller

plants compared to unmulched and infested pots (Figure 4.7). For the variety Isifumbathe,

mulched and infested pots were taller better compared to infested but unmulched pots in the

2014/15 season (Table 4.7).

In the 2013/14 season infestation significantly (P<0.001) reduced affected plant height.

117

Table 4.7: Effects of infestation on plant height at 8 and 12 WACE in the year 2013/14

and 2014/15 seasons.

Infestation 2013/14 8 WACE 12 WACE 2014/15 8 WACE 12WACE

Infested 53.24±1.995a 97.3±6.61

a 48.94±1.955

a 79.5

a

Uninfested 60.68±1.995b 125.4±6.61

b 54.5±1.955

b 78.1

a

In the 2013/14 season there were significant interactions between variety and infestation at 6,

8 and 12 WACE.

Sorghum genotypes

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

Mashava

Zambia

Tshwetha

SC Sila

Sc Sila

Sor

ghum

hei

ght (

cm)

0

10

20

30

40

50

60

Infested

Uninfested

118

Sorghum genotypes

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

TshwethaSC Sila

Sc Sila

Sor

ghum

hei

ght (

cm)

0

20

40

60

80

100

Infested

Uninfested

Sorghum genotypes

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

TshwethaSC Sila

Sc Sila

Sorg

hum

hei

ght (

cm)

0

50

100

150

200

Infested

Uninfested

Figure 4.8: Interaction effects of sorghum variety and infestation on plant height at 4, 8 and

12 WACE during the 2013 season.

At 6 WACE, uninfested pots of Hlubi, Chiredhi, Mukadziusaende, Zambia and Tshwetha had

taller plants compared to infested ones. The results showed that infestation lowered plant

height for the majority of the sorghum genotypes except for Chiredhi, Mukadziusaende,

Zambia and Tshwetha at 8 WACE. At 8 WACE, Ruzangwaya, Chiredhi, Mukadziusaende

119

and SC Sila were not significantly affected by infestation (Figure 4.8). Isifumbathe,

Mukadziusaende and SC Sila resisted the dwarfing effects of Striga at 12 WACE.

4.4.5 Grain yield

The interaction of sorghum variety and Striga infection was significant (P<0.01) on sorghum

grain yield (P < 0.05). Striga infection significantly reduced the grain yield for most of the

sorghum varieties with the exception of Chiredhi, Mukadziusaenda and Mashava (Fig 4.9). In

fact, Mukadziusaende had significantly higher grain yield in the Striga infected plants

compared to uninfected plants (P < 0.05) for the 2013/14 season (Figure 4.9).

Sorghum varieties

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

Tswetha

SC Sila

Wild Sorghum

Sorg

hum

yie

ld (g

plan

t-1)

0

20

40

60

80

100

Infested

Uninfested

Figure 4.9: Interaction effects of sorghum genotypes and infestation on sorghum yield for the

2013/14 season

Uninfested pots had a higher head weight (P<0.05) compared to infested pots for Hlubi,

Isifumbathe, Ruzangwaya, Zambia, Tswetha and wild sorghum (Figure 4.10). Chiredhi and

Mashava maintained their yield despite infection. For the 2014/15 season head weight was

120

significantly affected by sorghum variety (P<0.001), infestation (P<0.001) and mulch (P=

0.001) (Figure 4.10).

sorghum yield in 2014 - 15 season

Infestation

Infested Uninfested

So

rgh

um

yie

ld (

g/p

lan

t)

0

10

20

30

40

2014 - 15 season

Mulching status

Mulched Unmulched

Yie

ld (

g/p

lan

t)

0

10

20

30

40

50

Yield for the 2014 - 15 season

Sorghum varieties

Hlubi

Isifumbathe

Ruzangwaya

Chiredhi

Mukadziusaende

MashavaZambia

TshwethaSC Sila

Wild Sorghum

Sorg

hum

yie

ld (g

/pla

nt)

0

10

20

30

40

50

60

Figure 4.10: Effect of sorghum genotypes, infestation and mulching on sorghum yield in the

2014/15 season

It was noted that whilst there were no significant interactions on yield, infestation reduced

yield while mulching increased yield (Figure 4.10). The sorghum genotypes Isifumbathe and

SC Sila had the highest yield. Mulching significantly (P<0.001) increased yield in the

2014/15 season.

121

4.5 Discussion

In this study, chlorophyll concentration was reduced by infection with S. asiatica.

Chlorophyll concentration is indicative of photosynthetic functioning and potential maximum

carbon dioxide assimilation rates. The fact that chlorophyll concentration was reduced by

infection is in agreement with the findings of Gurney et al., (2011) who found lower

chlorophyll content in Striga infested maize than uninfested susceptible maize genotypes.

Mulching increased chlorophyll concentrations at 6, 8 and 12 WACE for the 2014/15 season

which was not the case for 2013/14 season. The 2013/14 season was a wet season whilst the

2014/15 season had less rainfall with a lot of mid-season droughts. According to Chakraborty

et al., (2008), mulching is a suitable agronomic practice for conserving soil and water and

controlling soil temperature regimes. Mupangwa et al., (2012); Rao et al. (1998); Scopel et

al., (1998); and Adekalu et al., (2007) reported that the presence of mulch residue at the soil

atmosphere interface has a direct influence on infiltration of rainwater into the soil and

evaporation from the soil leading to improved water supply for crops. The advantage of

mulching with respect to chlorophyll content was apparent in the 2014/15 season which had

erratic rainfall.

Chlorophyll concentration is connected to nitrogen availability and is a key parameter in

measurement of plant canopies (Gitelson et al., 2003). Any perturbations in nitrogen

assimilation as a result of water limitations could in turn lower chlorophyll content as

reflected by the results of this study. The rest of the varieties whose chlorophyll content was

not affected by mulching may have high osmotic adjustment that helps maintain higher leaf

water potential. Blum (2005) reported that osmotic adjustment helps to sustain growth while

the plant is meeting transpirational demand by reducing its leaf water potential.

122

Stomatal conductance was lower in infested compared to uninfested sorghum genotypes. The

reduced stomatal conductance was probably caused by changes in the concentrations of

growth regulators in the host which are stimulated by Striga infestations (Frost et al., 1997).

Taylor and Frost (1997) revealed that increased levels of abscissic acid (ABA) in infested

plants resulted in stomatal closure. The wide variations of stomatal conductance following

infection across different varieties were probably a reflection of variable responses to ABA

accumulation in the plant.

The genotypes that maintain higher stomatal conductance are likely going to maintain

photosynthesis despite Striga infection. The varieties Chiredhi, Zambia and Wild sorghum

for the 2013/14 season and Hlubi, SC Sila and Tshwetha for the 2014/15 season maintained

opening of stoma under infestation and this is a useful trait for maintenance of

photosynthesis. It therefore enhances tolerance of the genotype to Striga infestations.

The genotypes that had the highest tiller numbers were Mukadziusaende, Mashava,

Isifumbathe and Ruzangwaya for both seasons. Tillers were more in infested sorghum

cultivars compared to uninfested ones. Tillering is one of the most important agronomic traits

in poaceous crops and plays a major role in determining plant architecture and grain yield

(Wu et al., 1998). According to Assuero and Tognetti (2010), high tiller production capacity

improves the chances of persistence after periods of unfavourable environmental conditions

during which a plant can experience biotic or abiotic stress. It means that there are higher

chances of survival after a biotic stress as one or more tillers can take over after stress has

affected the initial stems.

Strigolactones are involved in the regulation of above ground plant architecture by inhibiting

tiller development or shoot branching (Umehara et al., 2010). Jamil et al., (2011) found an

inverse relationship between number of tillers per plant and strigolactone production. This

123

may mean that high tillering varieties are producers of low strigolactones which gives an

advantage of supporting a lower number of S. asiatica parasites. Tillering therefore becomes

a useful trait that can be incorporated into other cultivars. According to Khush et al., (1999),

tillering increased the widespread adoption of wheat and rice varieties in the 1960s because

the altered plant architecture averted severe food shortages and was an essential component

of the green revolution. Jahn et al., (2011) found that continuous tillering is associated with

high grain yield and is characteristically selected for in advanced varieties in most crops. This

study showed that tillering was higher in uninfested pots than infested ones. This coincides

with the findings of Cruz and Boval (2000) who found a positive effect of nitrogen

availability on tillering in Lolium perenne. In this study, it could be possible that the nitrogen

levels in the Striga infested pots were not sufficient to sustain the direct demands of the

parasite and the tillering processes of the sorghum plants.

The germination of S. asiatica is elicited by strigolactones from the hosts. Therefore the

number of Striga attached is a reflection to some extent of the quantity of strigolactones

produced by the host. In a study by Jamil et al., (2011), the germination of Striga was

dependent on the quantity and quality of strigolactones produced by the host. As a result, any

genetic variation in this trait could potentially confer pre-attachment resistance. Varieties

Hlubi, Mashava, Ruzangwaya and Tshwetha are likely to be high strigolactone producers as

they stimulated a lot of seeds to germinate. Mukadziusaende and Chiredhi are likely to be

low strigolactone producers as they elicited the germination of a few parasites.

The heights of varieties Chiredhi, Mukadziusaende and Isifumbate were not significantly

lowered by Striga infestation. Mukadziusaende and Chiredhi resisted the dwarfing effects of

S. asiatica. Reduction in plant growth rate is caused by changes in the growth regulators in

the host (Frost et al., 1997). Taylor et al., (1996) reported that the increased levels of the

plant growth regulator, ABA in infested plants may result in stomatal closure. The reduction

124

in photosynthesis and ultimately growth would explain the reduction in height of infested

plants that was observed in this study.

The differences in plant height observed between infested and uninfested genotypes for some

varieties reflected that the parasite acted as a sink for carbon, inorganic solutes and water.

This was confirmed by Gurney et al., (2002), Cechin and Press (1993), and Gurney et al.,

(1995). The sorghum genotypes that maintained plant height irrespective of infestation

demonstrated tolerance. The results showed that at 6, 8 and 12 WACE for the 2013/14

season, the varieties Mukadziusaende, Chiredhi and Isifumbathe maintained their plant

height. The same genotypes were able to maintain high chlorophyll content, were

independent of mulch and infection with respect to chlorophyll content, maintained high

stomatal conductance and supported low Striga numbers. The first two parameters constitute

the photosynthetic machinery, implying that photosynthesis was not affected by infection in

those genotypes and hence they were able to maintain plant height despite the parasite load.

For the varieties Tshwetha, SC Sila and Ruzangwaya, mulched and infested pots had taller

plants than unmulched and uninfested ones demonstrating that in drier seasons, moisture

availability can negate the effects of infestation. The absence of mulch caused the plant to be

affected more than by infection alone. Despite the fact that sorghum is a drought tolerant

crop, absence of mulch which regulates soil temperature and conserve soil moisture had

deleterious effects on plant height. This is supported by Chakraborty et al., (2008) and

Mupangwa et al., (2012) who reported the merits of mulching in moisture conservation and

temperature regulation in hot and dry environments.

The ability of the varieties to maintain grain yield when infested by Striga asiatica may result

from the ability of the cultivars to maintain higher rates of photosynthesis (Gurney et al.,

2002). Striga asiatica therefore has little effect on the physiology of these varieties. Infact,

125

Mukadziusaende had higher yields in infested than uninfested pots, a phenomenon that was

attributed to profuse tillering. Jahn et al., (2011) reported on rice varieties that continued to

tiller after the main stem begins senescence. Striga spends about 7 weeks underground and

about 3 weeks above ground, after which it sets seed and dies. Mukadziusaende and Chiredhi

matured early and the main stem dried, many tillers formed and these matured very early

which lead to increased yield. Tillering seems to be the major parameter for tolerance under

infested conditions. Mukadziusaende had the highest number of tillers and chlorophyll

content and all these added together may provide a suite that overcompensates for Striga

infestation to the extent that yield becomes higher under infested than uninfested conditions.

The ability to tiller when the main stem approaches senescence therefore becomes a

beneficial trait in response to Striga infestation.

Varieties Isifumbathe, Mukadziusaende and Mashava had the highest number of tillers. The

same varieties supported the least number of S. asiatica. The data showed that there was an

inverse relationship between the number of tillers per plant and S. asiatica parasitism. Similar

results were found by Jamil et al., (2011) in rice cultivars where there was an inverse

relationship between number of tillers in rice and the number of Striga supported. Their study

quantified strigolactones and found that they were also inversely related to tillering in rice

cultivars. This research did not quantify strigolactones but their quantities can be inferred

from the Striga asiatica attached together with tillering of sorghum. The results imply that

Mukadziusaende is a low strigolactone producer which is why it had the highest tiller

number. Hlubi, Ruzangwaya and SC Sila supported the highest number of Striga asiatica and

had lower number of tillers so they are likely to be producers of low quantities of

strigolactones. The tillering of sorghum can therefore be used as a measure of sorghum

tolerance when selecting genotypes for use. Chlorophyll content and growth rate can be used

126

as parameters for tolerance to Striga. When all these traits are combined, they can

characterise a sorghum variety in terms of its ability to resist and tolerate Striga.

This study demonstrated substantial sorghum genetic variation for chlorophyll content, Striga

number, tillering, stem height, internode length and grain yield in response to mulching. The

sorghum varieties Mukadziusaende and Chiredhi were Striga tolerant, because of their ability

to maintain high chlorophyll content, stem height, high internode length values, high grain

yields and supporting low Striga attachments. The other two sorghum varieties were

Ruzangwaya with high chlorophyll content and maintenance of stem heights under Striga

infection, and Mashava with high tillering ability and high grain yield production. The results

clearly indicated that varieties Mukadziusaende and Chiredhi were able to perform well in

parasite infested pots.

4.6 Conclusions

Mulching increased chlorophyll content and sorghum height in the drier season of 2014/15

compared to the 2013/14 wetter season. Yield and dry matter traits were maintained under S.

asiatica infestation in the drier season of 2014/15. Therefore, mulching negated the effects of

drought spells in the drier seasons. In the wetter season the effects of mulching were not

apparent.

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Gurney AL, press, MC and Scholes JD (2002). Can wild relatives of sorghum provide new

sources of resistance or tolerance against Striga spp. Weed Research 42: 317 - 324

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(2011). Genetic variation in biomass traits among 20 diverse rice varieties. Plant Physiology

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diammonium phosphate application on strigolactone production and Striga hermonthica

infection in three sorghum cultivars. Weed Research 53: 121 – 130.

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Research 132: 139 - 148

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release of transgenic (herbicide/Bt) sorghum in the SADC region. Biotechnology, biosafety

and Environment in Southern Africa 2: (1): 5 - 6

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International, Wallingford, UK.

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and runoff from an alfisol in semi-arid india. 1. No till systems. Soil and Tillage Res 48: 51 -

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microclimatic modeling. Agric for Meteorology 78: 67 - 81

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Scopel E, Muller, B, Areola Tostado J, Chavez Guera E, Maraux F (1998). Quantifying and

modeling the effects of a light crop residue on the water balance: an application to rainfed

maize in western Mexico. World congress on soil science, France

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review. Journal of Agronomy and Crop Science 199: 264 – 274.

Taylor A, Martin J, Seel WE (1996). Psychology of the parasitic association between maize

and witch weed Striga hermonthica; Is ABA involved. Journal of Experimental Botany 47:

1057 - 1065

Umehara M, Hanada A, Yoshida S, Akiyama K, Arite T, Takeya-Kamiya N, Magome H,

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branching branching by new terpenoid plant hormones. Nature 455: 195 – 200.

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Agroecological regions survey. Salisbury. Rhodesia. Ministry of Agriculture.

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131

CHAPTER FIVE

The existence of different physiological ‘strains’ of Striga asiatica

(L.) kuntze on Sorghum bicolor (L.) Moench and Sorghum

arundinaceum (desv) Stapf in Zimbabwe

5.1 Abstract

A better understanding of the virulence variability of S. asiatica populations and host parasite

interactions is essential for more efficient resistant material deployment. This study was

stimulated by the observation that sorghum that is tolerant to Striga asiatica in a particular

area could still lack the same tolerance to a strain native to remote areas.Therefore an

experiment was designed with the objective of determining the stability of Sorghum spp

tolerance to two Striga strains. Nine Sorghum bicolor and one Sorghum arundinaceaum

(Wild sorghum) genotypes were subjected to two Striga asiatica strains sourced from

Rushinga and Chiundura, which are 500 km apart, and a control. A 3*10 factorial experiment

was set up, arranged in a completely randomized design with three replications at two sites.

The data collected were sorghum height, chlorophyll content, tiller number and dry matter

traits. The results showed that sorghum genotypes differed significantly (P<0.05) in their

response to the stunting effects of Striga strains at both sites. The Chiundura strain was more

virulent to Isifumbathe, Zambia, Wild sorghum and Mashava at Henderson research station

whilst at BUSE, the Chiundura strain was more virulent on wild sorghum and Mashava. The

two Striga strains were generally similar on their effects on chlorophyll content. At

Henderson, the Chiundura strain reduced chlorophyll content of Chiredhi, Zambia, Tshwetha

and SC Sila. At BUSE both strains were not significantly different (P<0.01) from each other

132

at 10 weeks after crop emergence (WACE). The effects of the two strains were similar for

head index, root index, stem index and leaf index at both sites. The Chiundura strain reduced

the total dry weight at BUSE but not at Henderson. Overally, the Chiundura strain had more

deleterious effects on sorghum traits compared to the Rushinga strain confirming the

existence of physiological speciation on Striga asiatica in Zimbabwe.

Key words: Striga asiatica, sorghum, Striga strains, dry matter partitioning

5.2 Introduction

Sorghum (Sorghum bicolor) is an important food crop in sub Saharan Africa where plant

available water is often a limiting factor for crop production. Sorghum allows for

maintenance of yield stability in arid environments. Despite cultivating the crop in more than

60 % of the world hectarage, African sorghum constitutes 37 % of the world’s production and

the average yield in most African countries is about 0.9 tha-1

which is substantially lower than

the world average of 1.4 t ha-1

(Jamil et al., 2012). The major biotic constraint to sorghum

production in the southern Africa sub-region is Striga asiatica, a hemi-parasitic weed. Striga

competes effectively with the host for carbon, nitrogen and inorganic solutes (Gurney et al.,

1999) and also causes phytotoxic effects on the host plants within days of attachment (Frost

et al., 2005; Frost et al., 1997). The witchweeds are obligate hemi-parasites and although

they contain some photosynthetic capacity, Striga species have an absolute requirement for

the host in order to develop and complete their life cycle (Aly, 2007).

Host resistance to Striga has been proposed as the best method of control. According to

Mohammed et al., (2007), crops with some measure of resistance have been integrated into

Striga management programmes and the new material got challenged by the Striga seed

bank. The newly introduced sorghum genotype must be able to cope with the great potential

genetic diversity in the seed bank. Lewin (1939) was the first to observe the possible

133

existence of biological strains in Striga to explain the differential damage and distribution of

Striga on wild and cultivated hosts in sub Saharan Africa. Jones (1955) reported that the

major problem in Striga control is the possible existence of physiological speciation within

the species. Ten years later, Doggett (1965), reported varietal differences in sorghum

susceptibility to Striga hermonthica sourced from different places in east Africa. It was

observed that varieties of sorghum resistant in one location became susceptible in another

location thus suggesting the existence of physiological strains of the parasite.

Some workers have reported that resistance could be dependent on the virulence of the Striga

strains (Parker and Reid, 1979; Ramaiah, 1987). A study by Riches et al., (1992) on cowpeas

found occurrence of distinct varietal specificity among races of the S. gesneroides. This

meant existence of genetic divergence in Striga. Reda et al., (2010) found that there were

populations of Striga that represented a threat to resistant varieties. Virulence could depend

on the history of agriculture and specific characteristics of the source environment

(Polniaszek et al., 1991).

Botanga and Timko (2006) suggested that geographical isolation and host driven selection are

important factors in the formation of races of Striga gesneriodes in West Africa. S. asiatica

and S. hermonthica populations from Kenya were respectively polymorphic for 96.8 % and

84 % of the amplified fragment length polymorphic (AFLP) bands that were assessed (Gethi

et al., 2005). A study in Benin discovered a high degree of host speciation within the 14 S.

asiatica populations that were analysed (Botanga et al., 2002). According to Spallek et al.,

(2013), S. asiatica isolated from wild grasses spp were unable to successfully parasitise

sorghum and maize plants susceptible to other Striga asiatica collections.

134

In Zimbabwe, studies conducted by Musimwa et al. (2001) using RAPD-PCR markers found

great genetic distances among Striga from three places which are sparsed from one another

by about 400 kilometres.

The objective of this study were

i) to determine the differential virulence effects of two srains of S. asiatica to sorghum

genotypes with respect to growth and dry matter traits in sorghum.

ii) to establish the existence of different strains of S. asiatica in Zimbabwe

There the alternative hypothesis were

i) the two S. asiatica strains were differentially virulent on sorghum growth and

dry matter parameters.

ii) there exists physiological strains in S. asiatica in Zimbabwe

5.3 Materials and Methods

5.3.1 Experimental sites

Two experiments were carried out at Henderson Research Station in Mazowe and the other

one at Bindura University of Science Education (BUSE) nursery. Henderson Research station

is located at latitude17.340S and longitude 30.58

0E. BUSE is located at the coordinates: 17

o

18I 58II S and 31o 19

I 23IIE. The two sites are located in agro-ecological region IIa of

Zimbabwe (Vincent and Thomas, 1961) and receive about 800 mm rainfall per annum. The

average temperature for both areas was 25oC. The experiments were conducted in the 2013 -

14 cropping season. The soil used at both sites was medium grained sands with a pH of 4.1

(CaCl2) and with a phosphorus content of 20 parts per million (ppm), 4 ppm nitrogen.

135

Exchangeable cations in milligram equivalent per 100 g of soil were 0.06 for potassium, 0.67

calcium and 0.48 magnesium.

5.3.2 Source of sorghum genotypes and Striga asiatica strains

Sorghum bicolor genotypes were sourced from the gene bank at the Department of Research

and specialist services, Harare research station, Zimbabwe. The Chiundura S. asiatica strain

was sourced from the Midlands province of Zimbabwe, which is 500 km from Rushinga in

Mashonaland province where the Rushinga strain was sourced. Sorghum arundinaceum seed

was collected in arable lands at Gwebi Agricultural College, 27 km west of Harare.

5.3.3 Experimental design

The experiments were conducted in pots with a 3*10 factorial treatment structure. The

sorghum genotypes that were used are shown in Section 4.3.2.

5.3.4 Experimental details

Medium grained sandy soil was obtained from the top 15 cm of a farmer’s field where Striga

has never been reported. Six litre plastic pots with six drainage holes at the bottom were filled

with the soil, and the top 10 cm of the soil were thoroughly mixed with 5.7 g of Compound D

fertilizer (8%N, 14% P2O5, 7 K2O) and 1 g of Striga asiatica seed. Ten sorghum seeds were

planted in the plastic pots at a depth of 0.5 cm and watered. The two strains were each used

to infest a third of the buckets and the other third was uninfested. The pot filling and planting

process started with the uninfested pots to avoid contamination. The sorghum seedlings were

thinned to one plant/pot at two WACE. The sorghum plants were topdressed at a rate of 3 g

per pot using ammonium nitrate (34.5 %N) at 4 WACE.

136

5.3.5 Data Collection

Height of the sorghum plants was measured using a metre ruler from the soil level to the

growing point. Tiller number was counted on each plant. Chlorophyll content was measured

by a chlorophyll meter (SPAD-502 KONICA MINOLTA INCL) at 6, 8 and 12 WACE.

Striga numbers were determined by counting the number of Striga plants that emerged from

the pots. The whole sorghum plant was carefully uprooted at maturity and the total dry matter

was separated into roots, leaves and stems. Head weight was determined by drying the

sorghum head in the sun until moisture content was 14 %. Roots, leaves and stems were dried

in an oven at 78oC for 48 hours for dry mass determination. Various indices were calculated

by dividing mass of the part, like leaf mass, by total mass.

5.3.6 Data Analysis

Barlett’s test for homogeneity of variance was done and the variances were not

homogeneous. Hence, the data from the two sites were analysed separately. Data was

subjected to analysis of variance (ANOVA) to determine the treatment effects using Genstat

release 14 (VSN International, UK).

5.4 Results

5.4.1 Sorghum plant height

Sorghum genotypes differed significantly (P< 0.01) in plant height in response to the two

different Striga strains. There was a significant interaction (P<0.05) of Striga strain and

sorghum genotype. The Chiundura strain lowered the height of Isifumbathe, Zambia and wild

sorghum 6 WACE at Henderson research station (Figure 5.1).

137

Henderson plant height at 6 WACE

Sorghum genotypes

ChiredhiHlubi

IsifumbatheZambia

Tshwetha

Mukadziusaende

RuzangwayaSC Sila

Wild Sorghum

Mashava

Sor

ghum

hei

ght (

cm)

15

20

25

30

35

40

45

50

Rushinga

Chiundura

Uninfested

138

Sorghum genotypes

ChiredhiHlubi

IsifumbatheZambia

Tshwetha

Mukadziusaende

RuzangwayaSC Sila

Wild Sorghum

Mashava

Pla

nt h

eigh

t (cm

)

10

20

30

40

50

60

70

80

90

Rushinga

Chiundura

Uninfested

Sorghum genotypes

ChiredhiHlubi

IsifumbatheZambia

Tshwetha

Mukadziusaende

RuzangwayaSC Sila

Wild Sorghum

Mashava

Pla

nt h

eigh

t (cm

)

0

20

40

60

80

100

120

140

160

180

200

220

Rushinga

Chiundura

Uninfested

Figure 5.1: Interaction effects of sorghum genotypes and Striga strain on sorghum

height at 6, 8 and 12 WACE at Henderson research station.

139

At 8 WACE, the Chiundura strain significantly lowered the height of genotype Isifumbathe.

At 12 WACE, the same strain significantly lowered the height of Zambia, Wild sorghum and

Mashava genotypes compared to Rushinga strain and uninfested genotypes. The Rushinga

strain significantly (P<0.05) dwarfed Tshwetha compared to Chiundura and uninfested pots

(Figure 5.1). Mukadziusaende and Ruzangwaya genotypes resisted the dwarfing effects of the

Striga strains. The two strains had similar effects on Chiredhi and Isifumbathe genotypes

(Figure 5.1).

Sorghum genotype

Chiredhi

Hlubi

Isifumbathe

Zambia

Tshwetha

Mukadziusaende

Ruzangwaya

SC Sila

Wild Sorghum

Mashava

Pla

nt h

eigh

t (cm

)

-50

0

50

100

150

200

250

Rushinga

Chiundura

Uninfested

Figure 5.2: Interaction effects of sorghum genotype and Striga strains at 12 WACE at BUSE

A significant interaction (P<0.05) of sorghum genotype and Striga strains was observed for

plant height. The Chiundura strain dwarfed wild sorghum and Mashava genotypes compared

to Rushinga and the control at BUSE. Rushinga lowered the height of Tshwetha genotype

compared to Chiundura strain (Figure 5.2).

140

Table 5.2: Effect of Striga strain on plant height at 6 and 12 WACE at Henderson and

BUSE

6 WACE 12 WACE

Henderson BUSE Henderson BUSE

Rushinga 32.67±1.029a 32.51

a 114.6±2.461

a 101.4±9.58

a

Chiundura 28.00±1.029b 30.62

a 111.6±2.461

a 98.9±9.58

a

Uninfested 34.23±1.029c 33.86

a 138.3±2.461

b 122.9±9.58

b

Values followed by different superscripts are significantly different at P<0.05

Across the measured periods Chiundura elicited the lowest sorghum height at all sites (Table

5.2).

5.4.2 Chlorophyll concentration

Chlorophyll content was significantly affected (P<0.001) by Striga strains at 8 and 12 WACE

(Table 5.3). The results revealed that the two strains were equally virulent on chlorophyll

content but were significantly lower compared to uninfested pots at both sites at 8 and 12

WACE (Table 5.3)

141

Table 5.3: Effect of Striga strains on chlorophyll content at 8 and 12 WACE

Chlorophyll content (mmolcm-2

)

Accesions 8WACE 12 WACE

BUSE Henderson BUSE Henderson

Rushinga 26.48±0.749a 35.67±0.815

a 29.54±0.784

a 30.66±0.975

a

Chiundura 26.56±0.749a 34.53±0.815

a 30.74±0.784

a 31.21±0.975

a

Uninfested 29.45±0.749b 40.16±0.815

b 33.01±0.784

b 37.45±0.975

b

Values followed by different superscripts are significantly different at P<0.001

The genotype Mukadziusaende resisted the effects of the two strains with respect to

chlorophyll content (Figure 5.3). The two strains were equally virulent on Hlubi, SC Sila,

Mashava and Ruzangwaya (Figure 5.3) and the results were similar at both sites. The

Rushinga strain elicited the lowest chlorophyll content (Figure 5.3) across all sorghum

genotypes.

142

Sorghum genotypes

Chiredhi

Hlubi

Isifumbathe

Zambia

Tshwetha

Mukadziusaende

Ruzangwaya

SC Sila

Wild Sorghum

Mashava

Chl

orop

hyll

cont

ent (

mm

olcm

-2)

0

10

20

30

40

50

60Rushinga

Chiundura

Uninfested

143

Sorghum genotypes

Chiredhi

Hlubi

Isifumbathe

Zambia

Tshwetha

Mukadziusaende

Ruzangwaya

SC Sila

Wild Sorghum

Mashava

Chl

orop

hyll

cont

ent (

mm

olcm

-2)

0

10

20

30

40

50

Rushinga

Chiundura

Uninfested

Figure 5.3: Interaction effects of sorghum genotype and Striga strains on chlorophyll

content at 10 WACE at both sites

5.4.3 Sorghum tillering

At 8 WACE, tiller number was significantly (P<0.001) affected by sorghum genotype and by

Striga strain (P<0.05) (Figure 5.4). The genotypes Chiredhi, Ruzangwaya and Mashava had

the biggest tiller numbers, while Hlubi, Zambia and SC Sila had the least.

144

Sorghum varieties

Chiredhi

Hlubi

Isifumbathe

Zambia

Tswetha

Makadziusaende

RuzangwayaSC Sila

Wild Sorghum

Mashava

Tille

r num

ber

0

2

4

6

8

10

Sorghum varieties

ChiredhiHlubi

IsifumbatheZambia

Tswetha

Makadziusaende

RuzangwayaSC Sila

Wild Sorghum

Mashava

Tille

r num

ber

0

2

4

6

8

10

12

Figure 5.4: Effect of sorghum variety on tiller number at 12 WACE at both sites

At Henderson research Station, the sorghum genotypes with the highest tiller numbers were

Chiredhi, Ruzangwaya, Mashava and Wild sorghum. At BUSE, Wild sorghum, Mashava and

Ruzangwaya had the highest tiller numbers. At both sites the lowest tillers were on genotypes

Zambia and SC Sila. The Chiundura strain elicited the highest number of tillers compared to

infestation using Rushinga strain and uninfested sorghum genotypes (Figure 5.5).

145

Striga strains

Rushinga Chiwundura Uninfested

Tille

r num

ber

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Figure 5.5: Effect of Striga strains on tiller number.

5.4.4 Sorghum dry matter traits

Sorghum genotype had a significant (P<0.001) effect on head, root, stem and leaf indices at

both sites (Table 5.4)

146

Table 5.4: Effect of sorghum genotypes on head index, root index, stem index and leaf index at BUSE

and Henderson sites.

Head Index Root Index Stem Index Leaf Index

Sorghum

variety or

landrace

Henders

on

BUSE Henders

on

BUSE Henders

on

BUS

E

Henders

on

BUSE

Chiredhi 0.31d 0.40

e 0.19

a 0.29

a 0.42

c 0.23

bc 0.074

a 0.073

b

c

Hlubi 0.18b 0.21

c 0.29

bcd 0.48

cd 0.458

cd 0.24

bc 0.069

a 0.074

b

c

Isifumbathe 0.24c 0.319

d 0.287

abcd 0.413

b 0.412

bc 0.216

bc

0.057a 0.051

a

Zambia 0.208bc

0.239c 0.207

ab 0.367

a 0.497

cd 0.289

c

0.088b 0.104

e

Tshwetha 0.089a 0.142

a 0.315

cd 0.531

d 0.527

d 0.244

bc

0.068a 0.082

c

d

Mukadziusaen

de

0.232bc

0.315

5d

0.287abcd

0.409b 0.394

bc 0.215

bc

0.066a 0.06

ab

Ruzangwaya 0.171b 0.200

c 0.342

d 0.498

b

cd

0.392b 0.207

b

0.094b 0.094

d

e

SC Sila 0.1881b 0.185

b 0.285

abcd 0.514

c

d

0.408bc

0.176d

0.118c 0.1230

e

Wild Sorghum 0.077a 0.082

7a

0.493ef 0.676

e 0.32

b 0.161

a

0.108bc

0.079b

cd

Mashava 0.168b 0.119

a 0.518

f 0.688

e 0.213

a 0.118

a

0.10b 0.074

b

c

Sed 0.023 0.037 0.05 0.048 0.053 0.037 0.009 0.01

Means followed by different superscripts in the same column are significantly different at P<0.001.

Head index was significantly higher on Chiredhi, Isifumbathe, Zambia and Mukadziusaende

while the lowest indices were recorded for Tshwetha and wild sorghum genotypes at both

sites. Root index was highest on Tshwetha, Mashava and wild sorghum genotypes (Table 5.4)

whilst the lowest were Chiredhi, Mukadziusaende, Zambia and SC Sila genotypes (Table

5.4). Stem index was lowest on Mukadziusaende, Ruzangwaya and Wild sorghum genotypes.

The Striga strains significantly affected the four indices at Henderson but not at BUSE (Table

5.5).

147

Table 5.5: Effect of Striga strains on head, root, stem and leaf index at BUSE and

Henderson.

Head Index Root index Stem index Leaf index

Striga

strain

Henderson BUSE Henderson BUSE Henderson BUSE Henderson BUSE

Rushinga 0.1658±0.0123a 0.1785±0.02a 0.388±0.027a 0.566±0.027a 0.37a 0.181±0.029a 0.076±0.005a 0.0741a

Chiundura 0.1861±0.0123a 0.213±0.02a 0.349±0.027a 0.516±0.027a 0.366a 0.185±0.029a 0.1±0.005b 0.0856a

Uninfested 0.2151±0.0123b 0.272±0.02b 0.229±0.027b 0.377±0.027b 0.477b 0.2646±0.029b 0.078±0.005a 0.0857a

Means followed by different letters are significantly different at P<0.001

Both strains led to more dry matter being allocated to the root at both sites. The two Striga

strains reduced the biomass allocated to the stems at both sites compared to uninfested hosts.

Head index was also lowered by Striga infestations. Leaf index was independent of Striga

strain at BUSE but it increased significantly (P<0.001) under the Chiundura strain compared

to Rushinga strain and uninfested genotypes.

There was a significant interaction (P<0.05) of sorghum genotype and Striga strain on leaf

index at the Henderson site (Figure 5.6).

148

. Sorghum genotypes

Chiredhi

Hlubi

Isifumbathe

Zambia

Tshwetha

Mukadziusaende

Ruzangwaya

SC Sila

Wild Sorghum

Mashava

Leaf

inde

x

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

Rushinga

Chiundura

Uninfested

Figure 5.6: Interaction effects of sorghum genotype and Striga strains at Henderson.

Leaf indices were similar for Chiredhi, Hlubi, Isifumbathe, Zambia, Mukadziusaende and

Ruzangwaya genotypes. The genotypes SC Sila, Wild sorghum and Mashava increased their

leaf indices under infestation by Chiundura strain compared to uninfested sorghum

genotypes. The Chiundura strain stimulated formation of more leaf tissue in wild sorghum

and SC Sila because of the higher leaf indices observed for these genotypes (Figure 5.6).

5.4.5 Sorghum head weight

There was a significant (P<0.05) interaction of Striga strain and sorghum genotype on

sorghum head weight at Henderson research Station and at BUSE (P<0.05) (Figure 5.7).

149

Sorghum genotypes

Chiredhi

Hlubi

Isifumbathe

Zambia

Tshwetha

Mukadziusaende

Ruzangwaya

SC Sila

Wild Sorghum

Mashava

Hea

d w

eigh

t (g)

0

10

20

30

40

50

60

70

Rushinga

Chiundura

Uninfested

Head weight at BUSE

Sorghum genotypes

ChiredhiHlubi

IsifumbatheZambia

Tswetha

Mukadziusaende

RuzangwayaSC Sila

Wild Sorghum

Mashava

Sor

ghum

hea

d w

eigh

t (g)

0

10

20

30

40

50

60

70

Rushinga

Chiundura

Uninfested

Figure 5.7: Interaction effects of sorghum genotypes and Striga strain at BUSE and

Henderson

150

At both sites, the head weight of Hlubi, Mukadziusaende and Wild sorghum genotypes were

not affected by the Striga strains. The effects of Rushinga and Chiundura strains were similar

for Ruzangwaya and SC Sila genotypes and they were lower than uninfested genotypes

(Figure 5.7).

5.4.6 Total dry weight

The total dry weight was significantly affected by Striga strain (P<0.05) at BUSE, but was

not affected at Henderson Research Station (Figure 5.8). The Rushinga strain gave the

highest total dry weight at BUSE compared to the Chiundura strain and uninfested genotypes.

At Henderson, the total dry weight was not affected by the Striga strains (Figure 5.8).

Striga strains

Rushinga Chiundura Uninfested

Tota

l dry

mat

ter (

g)

0

50

100

150

200

250

BUSE

Henderson

Figure 5.8: Total dry matter of sorghum genotypes for BUSE and Henderson

151

total dry mass at BUSE

Sorghum genotype

ChiredhiHlubi

IsifumbatheZambia

Tswetha

Mukadziusaende

RuzangwayaSC Sila

Wild Sorghum

Mashava

Tota

l dry

mass

(g)

0

50

100

150

200

250

300

350

Rushinga

Chiundura

Uninfested

Figure 5.9: Interaction effects of sorghum genotype and Striga strain on total dry mass

at BUSE

There was a significant interaction (P <0.05) between variety and Striga strain for total dry

matter. Uninfested Isifumbathe, Zambia, Ruzangwaya, SC Sila and Mashava genotypes had

significantly higher (P<0.05) head weight compared to infested genotypes. The Chiwundura

strain had higher virulence on head weight for the varieties Mashava, Zambia and Chiredhi.

The head weight of genotypes Hlubi, Tshwetha, Mukadziusaende, Ruzangwaya and wild

sorghum was not significantly reduced by the Striga strains (Figure 5.9).

Total dry matter was not significantly (P >0.05) affected by both Striga strains for the

genotypes Chiredhi, Hlubi, Isifumbathe, Zambia, Tshwetha, Hlubi, Isifumbathe,

152

Mukadziusaende, Ruzangwaya and SC Sila. The Chiwundura strain significantly (P<0.05)

lowered the total dry matter of the genotypes wild sorghum and Mashava.

5.5 Discussion

The objective of this study was to determine the stability of sorghum tolerance when infested

with two Striga asiatica strains. The ability to express tolerance in a wider range of

environments indicates plasticity which is an important component for yield maintenance.

According to Poorter et al., (2012), the plant has to balance the allocation of dry matter to

leaves, stems and roots in a way that matches the physiological activities and functions

performed by these organs.

Generally, the Chiundura strain was more virulent in dwarfing the sorghum genotypes

compared to the Rushinga strain. The sorghum genotypes which resisted the dwarfing effects

of the Striga were Hlubi, Zambia, Mukadziusaende, and Ruzangwaya. The two strains

differed in their effects on sorghum lines. The results concur with the findings of Campos et

al., (2004) who reported that the response of plants to stress is genotype specific. Other

studies by Taylor et al., (1996) found that the plant growth regulator abscissic acid (ABA)

increases in Striga infested plants and this leads to a reduction of stomatal conductance which

consequently reduced carbon assimilation. In tolerant maize genotypes, Gurney et al., (2002)

found two maize varieties in which Striga had limited effect on photosynthesis despite

infection. In this study, failure by the Striga strains to dwarf Zambia, Mukadziusaende and

Ruzangwaya may be a demonstration that the genotypes are less responsive to ABA hence

may be labelled as tolerant with respect to height. In sorghum genotypes such as Mashava,

wild sorghum, SC Sila and Chiredhi, differential effects of the Striga strains were observed.

Flexas et al., (2006) attributed reduction in plant growth from imposition of stress to changes

in the partitioning of assimilates between different organs and the balance between

photosynthesis and respiration.

153

The differential effects of the Striga strains on plant height was demonstrated in this study.

In this case, the Chiundura strain was the more virulent than the Rushinga strain. However,

Richards et al., (2006) asserted that a given host genotype may be plastic for a certain trait in

a certain set of environments but not plastic for other traits in the same environments.

The effects of the two strains on chlorophyll content was not significantly different but all

were significantly less than the uninfested genotypes. The chlorophyll content of the

genotypes Ruzangwaya, Mukadziusaende and Mashava was not affected by the Striga strains

at both sites. These results were similar to observations by Gurney et al., (2002), who

reported that a tolerant maize variety was able to maintain high chlorophyll content levels

despite being infested. Chlorophylls are the light harvesting complexes and tolerant

genotypes should adjust chlorophyll content to be independent to keep photosynthesis at

optimal rate. Aly (2007) reported that the host proteins are exported to the parasite. The

ability of a genotype to maintain chlorophyll content irrespective of infection is key to

tolerance. Chlorophyll content is a key parameter in tolerant genotypes as it depicts the extent

of plant canopies and the subsequent carbon assimilation.

The varieties which lacked tolerance could have been caused by perturbations in host carbon

assimilation that could also limit nitrogen assimilation and in-turn lower chlorophyll

synthesis. This may explain the lower chlorophyll content of the infested Tshwetha,

Isifumbathe, Hlubi and SC Sila genotypes.

Across all genotypes, the root index for Rushinga was 0.388 at Henderson and 0.566 at

BUSE. Chiundura produced 0.349 at Henderson and 0.516 at BUSE against 0.22 and 0.377

for uninfested genotypes at Henderson and BUSE respectively. This indicated that sorghum

genotypes allocated more dry matter to roots in response to Striga infestations. This

behaviour coincides with that established by Poorter and Nagel (2000) and, Shipley and

154

Meziane (2002) who reported a proportional increase in root fraction as soil available

moisture decreases. A study by Acciaressi and Guiamet (2010) on Sorghum halepense found

that the witchweeds incite a host to increase the amount of biomass allocated to roots when

they are stressed. The root parameter is important because the spatial deployment of roots

determines the ability of a plant to secure edaphic resources. According to Campos et al.,

(2004) and Reynolds et al., (2007), there is evidence to suggest that adverse effects of stress

can successfully be avoided by changing the carbon allocation patterns to allow formation of

a deep root system before the onset of a growth limiting stress. In this study, the sorghum

genotypes differed in the allocation of dry matter to the roots. The lowest root indices were

recorded for genotypes Chiredhi, Zambia, Isifumbathe and Mukadziusaende. The highest

performing genotype was Mashava with 0.518 and wild sorghum with 0.493. The varieties

that respond to Striga infestations by allocating more dry matter to roots at the expense of

yield are non tolerant to Striga in terms of grain yield. The genotypes which show plasticity

to Striga infestation and do not alter the allocated carbohydrates to the roots show plasticity

to yield. Therefore, the varieties Chiredhi, Zambia, Mukadziusaende, Isifumbathe and SC

Sila are plastic to Striga infestations in terms of dry matter allocated to roots.

Striga strain did not lower sorghum head weight compared to uninfested sorghum for

genotypes Chiredhi, Hlubi, Tswetha, Mukadziusaende, wild sorghum and Mashava at both

sites. However, Tswetha and wild sorghum had low yields. This is expected for wild sorghum

as it has not undergone any improvement to increase its yield. The genotypes have the

capacity to diminish the consequences of infection. According to Swabrick et al., (2008),

different cultivars differ in their capacity to tolerate the physiological and pathological effects

of Striga parasitism finally resulting in milder or stronger impacts on crop yield. Despite the

fact that several studies (Gurney et al., 2002; Rodenburg et al., 2005), have shown a

reduction in yield after Striga infestation, it may be that these varieties uncouple the process

155

of photosynthesis and dry matter allocation. Similar results were found by Frost et al., (1997)

in sorghum: Striga hermonthica associations. The results confirm the assertion by

Haussmann et al., (2001) that genetic variation for tolerance to Striga under field conditions

exists in cultivated sorghums especially in local African cultivars. This may mean that Striga

does not cause serious changes in the metabolism of some hosts.

Genotypes Isifumbathe, Zambia, Ruzangwaya and SC Sila had their head weight depressed

by Striga. The results showed a depression in the dry matter allocated to the head. The

reduced head weight index may partly result from the parasite acting as a sink of carbon,

inorganic solutes and water and also lower rates of carbon gain by infested cereals (Cechin

and Press, 1993). According to Joel (2000), the parasite develops as a strong metabolic sink,

relative to the host and channels the flow of water and nutrients to itself thereby damaging the

crops’ development. In this study, the stems made up the bulk of the biomass. The same

results were found by Jahn et al., (2010) in rice cultivars.

The Chiundura and Rushinga strains had similar effects on head, root, and stem indices, and

stem weight. This is in agreement with the findings of Dube and Belzile (2010) who found

very low levels of genetic diversity among Striga gesneroides and this was attributed to a

high degree of selfing. The results point to the fact that there are minor genetic variations in

the virulence of S. asiatica strains on the stated sorghum traits. According to Loveless and

Hamrick (1984), S. asiatica is mainly autogamous and this can limit genetic diversity. Studies

done in Kenya by Gethi et al., (2005) showed very low genetic diversity and the reason that

was advanced was that the parasitic weed had recently been introduced in Kenya. In Benin,

Botanga et al., (2002) showed host speciation of Striga asiatica. In our study, the results

indicated that there are particular processes and parameters of sorghum which were affected

more by a particular strain in a particular genotype. These results may indicate that the strain

seriously reduce dry matter accumulation in the affected varieties. When the same varieties

156

are grown in areas in which the Rushinga strain dominates the genotypes may be labelled as

resistant only to lose resistance when grown where the Chiwundura strain dominates. It can

therefore be inferred that the Striga strains each has physiological processes that it affects

more in a particular genotype. In some sorghum genotypes, particular strains affected

chlorophyll content, in some height; in some they caused allocation of dry matter to be more

to the roots than the harvestable part.

5.6 Conclusion

It can therefore be concluded that there was differential virulence of Striga asiatica strains on

plant height, chlorophyll content, tiller production, different sorghum indices and yield. This

study confirms the variable virulence and the existence of physiological strains of Striga

asiatica in Sorghum species in Zimbabwe.

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Annals of Applied biology 121: 362 - 370

Parker C and Reid D.C (1979).Host specificity in striga spp, some preliminary observation.

Supplement to the proceedings of the second International Symposium on Parasitic weeds.

Pages 79 - 90

Rodenburg J, Bastiaans L, Weltzien E and Hess D (2005. How can field selection of for

Striga resistance and tolerance in Sorghum be improved. Field Crops Research 93: 34 – 50

Spallek T, Mutuku J.M and Shirasu K (2013). The genus Striga: a witch profile. Molecular

Plant Pathology.DOI10.1111.mpp.12058.

Swarbrick P.J; Huang K and Liu G (2008). Global patterns of gene expression in rice

cultivars undergoing a susceptible or resistant interaction with the parasitic Striga

hermonthica. New Phytologist 179: 515 – 529.

Taylor A, Martin J, Seel W.E, (1996). Physiology of parasitic associations between maize

and witchweed (Striga hermonthica): Is ABA involved. Journal of Experimental botany 47:

1057 – 1065.

Vincent V and Thomas R.G (1961). An Agricultura survey of southern Rhodesia: agricultural

regions survey. Salisbury, Rhodesia. Ministry of agriculture.

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CHAPTER SIX

Sorghum response to Striga asiatica based on maximum

germination distance, Striga counts and sorghum tillering in

Zimbabwe

6.1 Abstract

Resistance through reduced strigolactones is one of the sustainable ways of managing Striga

asiatica. To verify the existence of reduced strigolactone production in sorghum genotypes,

an agar gel assay was carried out on seven Sorghum bicolor lines and one Sorghum

arundinaceaum sourced in Zimbabwe. The eight sorghum genotypes were also grown in sand

and Striga attachments and sorghum yield were recorded. The results indicated that sorghum

genotypes varied significantly (P<0.05) with respect to maximum germination distance

(MGD) with wild sorghum and SC Sila having the largest MGDs. The genotype

Mukadziusaende had the highest tiller numbers (P<0.05), while SC Sila had the lowest.

Striga counts were highest on Wild Sorghum, Ruzangwaya and Hlubi. There was a negative

correlation coefficient (R2 = 0.2225) between Mgd and tiller number, showing that the

highest strigolactone producers had low tiller numbers. A positive correlation coefficient (P=

0.843) was found between sorghum yield and tiller numbers and it indicates that the more the

tiller numbers the more the yield. It can therefore be concluded that resistance through

reduced strigolactones was found in the sorghum genotype Mukadziusaende. The direct

relationship between MGD and tillering means that tiller number can be used to select for

reduced strigolactone production in the field.

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6.2 Introduction

The average sorghum productivity in the sub-Saharan Africa is low as a result of a myriad of

production constraints of which Striga asiatica is a major obstacle. Striga asiatica is an

obligate hemi-parasite that attaches to the roots of several crop species leading to severe yield

losses (Parker, 1991). Beyond the burden of losing food and water to these parasites, host

plants suffer from a characteristic malady resembling the symptoms of severe drought. Striga

spp parasitise important food crops such as sorghum, maize, millets and rice. They have

functional chloroplasts but their photosynthates provide only part of the energy required for

survival, hence are regarded as hemi-parasites (Xie et al. 2010). This hemi-parasite has long

been recognized as the greatest biological constraint to food production in sub Saharan

Africa, causing annual losses in excess of US$7 billion (Samejina et al., 2016).

Striga asiatica is geographically the most widespread species with large populations having

been reported throughout sub Saharan Africa, south east China and the Indian subcontinent

while smaller isolated populations have been reported in Arabia, Indonesia, Phillipines, north

and east Carolina (USA) and Australia (Cochrane and Press, 1997). Striga asiatica is the

predominant species towards the east African coast and southern Africa (Parker, 2009).

According to Bouwmeester et al., (2003), these parasites infest about two thirds of the 70

million hectares used for cereal production in Africa. Jamil et al., (2011) asserted that about

20 – 80 % yield losses or even complete crop failure can occur due to Striga parasitism.

The life cycle of the noxious cereal weed has co-evolved with many hosts to comprise a

series of discrete steps that are closely linked to the host’s biochemistry (Hearne, 2009). The

root parasitic weed has developed the ability to germinate only when they are exposed to

germination stimulants released from the host roots, thus syncronising their life cycle to those

of their potential hosts. Thus, they only germinate when a suitable host seed is in proximity to

the Striga seed (Fernandez-Aparacio, et al., 2009). Fernadez-Aparacio et al., (2011) reported

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that the synchrony is vital for parasitic weed survival because they have an absolute

requirement for nutritional support from the host. This complex life cycle also presents

opportunities for disruption (Pierce et al. 2003).

According to Bouwmeester et al., (2003) and Akiyama and Hayashi (2006), the first critical

step in the life cycle of Striga, the germination of its seed, is regulated by strigolactones. The

dependence on strigolactones could be exploited for Striga management through breeding for

low strigolactones producing cultivars. The seeds of these parasitic plants will only germinate

after perceiving a germination stimulant of their host (Yoneyama et al., 2010). After radicle

emergence, the haustoria attaches and penetrates the host roots (Yoder, 2001). Cardoso et al.,

(2011) reported that once germination has been triggered, the radicle protrudes from the testa,

elongates towards the root and develops haustorium, an organ that can attach to and penetrate

roots of the host plant. The parasitic plant grows underground for 4 – 7 weeks prior to

emergence and utilises host water, nutrients and photosynthates (Jamil et al., 2011). Much of

the damage will have occurred by the time the Striga emerges above the ground.

Jamil et al., (2011) found significant variation among NERICA rice cultivars and their

parents for strigolactones production and Striga germination. Production of low germination

stimulants results in low numbers of Striga asiatica attachments thereby producing a resistant

phenotype. Low germination stimulant producing genotypes have enhanced resistance to

Striga because of the reduction in Striga germination (Dun et al., 2009). Striga resistance is

the mechanism that ensures lower field infestation and allows for satisfactorily high yields

than fully susceptible ones (Rodenburg et al., 2005). Studies done in sorghum have also

shown that genotypes with low production of germination stimulants have demonstrated

resistance to Striga in the field (Ramaiah, 1987; Hess et al., 1992; Ejeta, 2007). In the past

decade, several sorghum varieties with Striga resistance based on low germination stimulant

production have been introduced such as SRN 39 and IS9830 in Sudan and Gobiye in

164

Ethiopia (Tefera et al., 2012). However, resistance alone is not sufficient for adoption of a

variety as adaptability to the environment and farmer preference have to be taken into

account (Mohemed et al., 2016). This raises the need to identify resistant genotypes among

those cultivated by farmers locally. Since the root parasites affect the crop from the time they

attach to the root, the development of new control strategies should focus on the initial steps

in host parasite interaction (Lopez-Raez et al., 2008).

Ejeta et al., (2000), Wilson et al., (2000), Gurney et al., (2001), and Gurney et al., (2002)

demonstrated that the near relatives of cereals could provide new sources of tolerance and or

resistance to parasite infection and may provide the way forward for the control of Striga spp.

According to Doggett (1976, 1988) and De Wet (1978), the cultivated sorghums of today

primarily originated in Africa from the wild Sorghum bicolor spp arundinaceaum. Southern

Africa has more sorghum landraces and whilst the quest to find a landrace that produces the

least strigolactones is still on, there is need to look at the wild sorghum and the vast number

of sorghum landraces that are under cultivation in the African savannah. Given the high

genetic diversity of the Sorghum spp, including wild sorghum, there is need to quantify

strigolactones in most of these cultivated lines as they are grown in Striga infested fields.

According to Ejeta et al., (1993), different sorghum genotypes differed by as much as a

billion fold in the amount of germination stimulants they produce. Jamil et al., (2011),

asserted that strigolactones have a triple role which is underground communication between

the plant, AM fungi, parasitic plants and the regulation of tillering. According to Umehara et

al., (2008), and Lopez-Raez et al., (2008), strigolactones inhibit tillering in plants and

therefore the ability to tiller could be used as a selection criteria for reduced strigolactones

production.Therefore, the objectives of this study were to:

i) identify low strigolactone producing sorghum lines using agar gel analysis.

165

ii) establish the relationships between maximum germination distance (MGD), sorghum

tillering, Striga asiatica counts and sorghum yield.

The corresponding alternate hypothese were:

i) the Sorghum genotypes vary in strigolactones production, resulting in variable

resistance to Striga asiatica.

ii) maximum germination distance is inversely related to sorghum tillering, while it is

positively related to Striga asiatica counts.

iii) MGD is inversely related to sorghum yield.

6.3 Materials and methods

6.3.1 Experiment 1: Agar jel assays

6.3.2 Sorghum germplasm and Striga asiatica seed sources

Refer to section 3.2.2

6.3.3 Experimental design

The treatments for this experiment were the sorghum genotypes (Table 3.1). They were

arranged in a completely randomized design replicated four times.

6.3.4 Surface Sterilisation and sorghum seed germination

Sorghum seeds were soaked in 1 % sodium hypohlorite solution for 60 minutes and rinsed in

double deionised water. The seeds were soaked in an aqeous solution of 10 % captan

overnight. Seeds were rinsed with deionised water three times and then incubated in moist

filter paper at 27 oC. After 48 hours, germinating seeds were placed in agar plates as outlined

by Hess et al.(1992).

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6.3.5 Conditioning of Striga seed

Striga asiatica seeds were placed in 30 ml sample bottles and rinsed three times by adding 3-

5 drops of the detergent tween 20 into 10 ml of distilled water. Sonication was done using an

ultra sonic cleaner three minutes during the first rinse (Mutengwa, 2004). The Striga seeds

were incubated at 27 oC for three days prior to transferring them into the fresh sterile flasks

containing 15 ml of 0.001 % acqeous benomyl solution. The sample bottles were re-

incubated at 25 oC for 35 days before they were ready for use in the agar jel assay.

6.3.6 The assay set up

Pre-conditioned Striga seeds were pipetted into petri dishes. Water agar was then poured over

the seed. The roots of the germinating sorghum seeds were placed in the solidifying agar with

the root tip pointing across the plate. The plates were incubated in the dark for five days. The

MGD (distance between the host root and the furthest germinated Striga seed) were used as

indicators of the quantities of strigolactones produced. The MGDs were recorded using a

graduated microscope at 120 hours of incubation time at 30oC. .

6.4 Experiment 2: Pot screening

About 1g of S. asiatica seeds were weighed for every treatment and mixed thoroughly with 2

Kg of washed river sand. The sand was sterilized before the start of the experiment by

heating in an oven at 120 oC for 48 hours to kill any Striga weed seeds that could be in the

sand. The method was adapted from Jamil et al., (2011). Plastic pots of dimensions 18 cm

diameter and 20 cm height were used.

6.4.1 Experimental design, planting and data collection

There were 8 genotypes (Table 3.1) and the experiment was replicated four times and laid

down as a completely randomized design. Five sorghum seeds were planted in pots at a depth

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of 0.5 cm. The seedlings were thinned to one plant per pot at 2 WACE. The sorghum plants

were allowed to grow in pots for 20 weeks and the Striga that emerged were counted. The

number of tillers, maximum germination distance were also recorded. Yield data was also

recorded at the end of the experiment.

6.4.2 Data analysis

The data was analysed according to the model:

Yij = µ + Ti +eij

Yij was the measured parameter e.g tiller number, µ = general mean, Ti effect of the treatment

and eij is the error term. Correlations of the measured parameters were determined using

Satistical Package for Social Sciences and Genstat version 12.

6.5 Results

6.5.1 Maximum germination distance (MGD)

The sorghum genotypes differed strongly (P=0.001) with regard to maximum germination

distance, which is indicative of the strigolactones quantity produced (Figure 6.1). The

minimum germination distance was 1.225 cm and it was for Mukadziusaende whilst the

maximum was 2.775 cm for SC Sila (Figure 6.1).

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Sorghum genotypes

Mukadziusaende

Wild sorghumSC Sila

Chiredhi

Ruzangwaya

Isifumbathe

Hlubi

Zambia

Ger

min

atio

n di

stan

ce (c

m)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Figure 6.1: Maximum germination differences for various sorghum genotypes

6.5.2 Tillering

Sorghum genotypes varied strongly (P <0.01) in tillering, and the average number of tillers varied

from 2 for SC Sila to 5 for Mukadziusaende (Figure 6.2). The genotypes that had the highest number

of tillers were Mukadziusaende and wild sorghum while the lowest were SC Sila and Zambia (Figure

6.2).

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Sorghum genotypes

Mukadziusaende

Wild sorghumSC Sila

Chiredhi

Ruzangwaya

Isifumbathe

Hlubi

Zambia

Tille

r num

ber

0

1

2

3

4

5

6

Figure 6.2: Effect of Striga asiatica on tillering of sorghum genotypes

6.5.3 Striga counts

Sorghum genotypes

Mukadziusaende

Wild sorghumSC Sila

Chiredhi

Ruzangwaya

IsifumbatheHlubi

Zambia

Strig

a co

unts

0

2

4

6

8

10

12

14

16

18

Figure 6.3: Effect of Sorghum genotypes on Striga counts

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The sorghum genotypes varied strongly in eliciting Striga germination (P<0.01). The

genotypes that had the highest number of Striga counts were Ruzangwaya and Hlubi, while

the lowest were Mukadziusaende and Chiredhi (Figure 6.3).

6.5.3 Correlations between maximum germination distance and tillering

The results indicate a negative relationship between MGD and tillering (R2 = 0.2225) (Figure

6.4). The relationship indicates that as MGD increases tillering decreases. A positive

relationship between tiller numbers and yield (R2

=0.8436) indicates that as tiller numbers

increase yield also increases (Figure 6.5).

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Figure 6.4: The relationship between germination distance and tiller numbers

Figure 6.5: Relationships between sorghum yield and tiller numbers

6.6 Discussion

The objectives of this study were to identify sorghum genotypes that produced the lowest

strigolactones, and then correlate strigolactones production to tillering, Striga counts and

yield. It is noteworthy that, among all the genotypes evaluated n the present study the

genotype Mukadziusaende was identified as the resistant genotype producing low amount of

strigolactones and sustained lower Striga emergence. The sorghum genotypes with lowest

maximum germination distances were Mukadziusaende, Chiredhi and Isifumbathe, whilst

wild sorghum and SC Sila had the biggest maximum germination distances. However, the

level of susceptibility differed among the genotypes. This is supported by Haussmann et al.,

(2000) who reported that the Striga species negatively affects the growth and yield of crops

they infect but the extent of the negative effects is a function of the environment and genetic

makeup of the host and the parasite.

These results are consistent with previous observations in cereals like rice (Jamil et al., 2011).

The results confirm the existence of large genetic variation among the sorghum cultivars.

172

According to Jamil et al., (2011), up to about 500-fold differences exist in the amounts of

strigolactones exuded by rice Germplasm. Ejeta et al., (1993) confirmed the same results in

sorghum and reported differences as much as a billion fold in the amounts of stimulants

produced by sorghum.

Tillering varied among sorghum genotypes with Mukadziusaende having the highest tiller

number whilst the lowest was SC Sila (Figure 6.2). In sorghum, tillering has been proposed to

be under genetic and environmental control and according to Kim et al., (2010), tillering has

not been comprehensively addressed by the carbohydrate supply and demand framework. In

this study the sorghum genotypes were subjected to the same environmental conditions hence

the environmental influences were eliminated. Therefore, the differences suggested that

sorghum genotypes may also differ in their propensity to tiller which is independent of the

carbon supply demand (Kim et al., 2010). The differences could be due to differences in

hormonal signaling as the plants were in the same environment. According to Umehara et al.,

(2008), the hormone strigolactone reduces tillering in plants, such that plants that produce

less strigolactones have profuse tillering compared to those that produce more. The results of

this study support the propensity to tiller hypothesis as the genotypes were grown in the same

conditions.

Increase in MGD indicates susceptibility of the genotype to Striga infestations. This means

reduced MGD gives a resistant phenotype which inturn gives higher grain yields. The results

corroborates previous findings by Mohemed et al., (2016) on the relationship between

germination stimulant activity and Striga infestation. Smaller MGDs mean low amounts of

active stimulants which confer pre-attachment resistance and accounts for yield mantainance

in the sorghum genotypes. There was a significant correlation between MGD and Striga

counts. To the contrary, Haussmann et al., (2000) compared the results of pot trials and only

weak correlations between germination distance in agar jel assay and the number of emerged

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Striga plants. However, Rodenburg et al., (2005) reported high correlation coefficient

between root exudates and infection levels as illustrated by Striga counts.

6.7 Conclusion

Among the set of eight sorghum genotypes screened under pot conditions in Zimbabwe,

significant differences were found in their levels of resistance. The genotype

Mukadziusaende showed excellent levels of resistance as illustrated by lower MGDs and

Striga counts. The genotypes SC Sila and wild sorghum were the most susceptible. Yield of

sorghum was inversely related to germination distance and tiller number increased as

sorghum yield.

6.8 References

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parasitic weeds in plant roots. Annals of Botany 97: 925 – 931.

Bouwmeester, H.J, Matusova R, Sun Z, Beale M.H (2003). Secondary metabolic signaling in

host-parasite interaction. Current Opinions in Plant Biology 6: 358 – 384.

Cardoso C, Ruyteer-Spira C, Bouwmeester H.J (2011). Strigolactones and root infestation by

plant parasiti Striga, Orobanche and Phillipanche spp. Plant Science 180: 414 - 420

Cochrane V and Press M.C (1997). Geographical distribution and aspects of ecology of the

hemiparasitic angiosperm Striga asiatica (L) Kuntze: a herbarium study. Journal of Tropical

Ecology 13: 371 - 380

De Wet J.M.J (1978). Systematics and evolution of sorghum sect.Sorghum (graminae).

American Journal of Botany 65: 477 – 484

Doggett H (1976). Sorghum. In evolution of Crop Plants (eds Simmonds N.W) 112 – 117.

Longman group, new York. USA.

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Doggett H (1988). Sorghum.2nd

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Dun EA, Brewer PB, Beveridge CA (2009). Strigolactones: discovery of the elusive shoot

branching hormone. Trends in Plant Science 14: 364 - 372

Ejeta G, Mohammed P, Rich A, merlake-berhan T.L, Housely T.L, Hess D.E (2000).

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resistance in cereals. Proceedings of a workshop held at IITA, Ibadan, Nigeria (eds B.I.G

Haussmann, Hess D.E, Koyama L.M, L. Grivet, Rattunde H.F.W and Geiger H.H. 29 – 37.

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biology. Crop Science 47: 216 - 227

Fernandez-Aparicio M, Westwood J.H and Rubiales D (2011). Agronomic, breeding and

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germination stimulant level in agricultural soils. Botany 89: 813 – 826.

Fernandez-aparacio M, Flores F and Rubiales D (2009). Recognition of root exudates by

seeds of boomrape, orobanche and phelipanche spp. Annals of Botany (London) 103: 423 -

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Gurney A.L, Press M.C and Scholes D.J (2002). Can wild relatives of sorghum provide new

sources of resistance or tolerance against Striga spp. Weed Research 42: 317 – 324

Gurney A.L, Grimanelli D, Kanampiu F.K, Hoisinhton, D.A, Scholes J.D, press M.C (2001).

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breeding Striga-resistant sorghum. Field Crops Research 66: 195 – 201.

Hearne S.J. (2009). Control-Striga conundurum. Pest Management Science 65: 603 – 614

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expressing a quantitative biosynthetic trait that confers resistance to Striga. Phytochemistry

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hermonthica resistance of New Rice for Africa (NERICA) cultivars based on low

strigolactones production. New Phytologist 192: 964 – 975.

Jamil M, charnikhova T, Houshyani B, van Ast A, Bouwmeester H.J (2011). Genetic

variation in strigolactones production and tillering in rice and its effect on Striga hermonthica

infection. Planta DOI10.1007/s00425-011-1520-y.

Lopez-Raez J.A, Charnikhova, T, Gome-Rolden V, Matusova R, Kohlen, W, de Vos R

(2008). Tomato strigolactones are derived from the carotenoides and their biosynthesis is

promoted by phosphate starvation. New Phytologist 178: 863 – 874.

Mohemed N, Charnikhova T, Bakker E.J, van Aast A, Babiker AGT, Bouwmeester HJ

(2016). Evaluating of field resistance to Striga hermonthica in Sorghum bicolor: the

relationship with strigolactones. Pest Management Science 72: 2082 – 2090.

Parker C (1991).Protection of crops against parasitic weeds. Crop Protection 10: 6 – 22.

Parker C (2009).Observations on the current status of orobanche and Striga problems

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Pierce S, Mbwaga AM, Press MC and Schles JD (2003). Xenognosin production and

tolerance to Striga asiatica infection of high yielding maize cultivars. Weed Research 43: 139

– 145

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Academic Press.

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resistance and tolerance in sorghum be improved? Field Crops Research 93: 34 – 50.

Rodenburg J, Cissoko M, kayeke J, Dieng I, Khan ZR, Midega C.A.O, Onyuka E.A, Scholes

J.D (2015). Do NERICA rice cultivars express resistance to S. hermontica and S asiatica

under field conditions. Field Crops Research 170: 83 – 94.

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Striga hermonthica. PHD thesis. Wageningen University. The Netherlands.

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germination approach for controlling Strga hermonthica. Pest management Science

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millets and other grains. Instormil collaborative research Support programme.

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strigolactones on the inhibition of tiller bud outgrowth under phosphate deficiency conditions

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accessions of the primary gene pool of Pennisetumglaucum. Phytopathology 90: 1169 –

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Phytopathology 48: 93 - 117

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Plant Biology 4: 359 – 365.

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178

CHAPTER SEVEN: GENERAL DISCUSSION, CONCLUSIONS AND

RECOMMENDATIONS

7.1 Introduction

This chapter is a synopsis of the whole study in relation to the objectives and the major

findings. The main objectives of the study are presented together with major findings and

conclusions. Lastly, a section on recommendations for further research and for farmers who

produce sorghum in Striga asiatica infested fields are presented.

7.2 Discussion

The ‘niche area’ of the study or the recommendation domain is the small holder sorghum

producers in Zimbabwe and the whole of tropical sub Saharan Africa. Literature review

showed that communal farmers have serious problems in sorghum production as a result of

Striga infestation sometimes resulting in 100 % losses (Berner et al. 1995, Mabasa, 2003,

Rubiales et al. 2009). Management of Striga still remains a major challenge faced by small

holder farmers in Zimbabwe. Results reported elsewhere especially for rice has promising

results through resistance and tolerance (Jamil et al., 2012, Sun et al. 2007, Jamil et al. 2011)

Sorghum genotypes were evaluated on their resistance and tolerance to Striga. This study

investigated the resilience of Striga infested sorghum under drought, mulch and under

various Striga asiatica strains. The study also sought to determine sorghum resistance to S.

asiatica with respect to reduced strigolactone production.

When growing sorghum in Striga infested fields which are prone to drought, the drought

exacerbates the effects of Striga in sorghum. However, there are genotypic differences on

sorghum responses to the two stresses. The sorghum line Mukadziusaende emerged as a

better performer when exposed to both stresses. On growth, water availability and Striga

infestation had the same effect on sorghum. Reduced water availability on Striga infested

sorghum strongly reduced sorghum growth. It is therefore important to subject sorghum

179

varieties to multiple stresses common in the field especially at evaluation stages as

simultaneous occurrence of the stress is common in the subtropical sub Saharan Africa.

Mulching at a rate of 3 tons/ha enables expression of tolerance traits in some sorghum

genotypes and negates the effects of Striga parasitism. Mulching at 3 ton/ha as promoted in

CA has been reported to suppress weeds through physical impedance and allelopathy. When

mulch is aplied, there is increased water penetration into the soil with subsequent prevention

of excessive evapo-transpiration losses (Scopel et al. 1998, Rao et al. 1998, Adekalu et al.

2007). Striga affects the water economy of the sorghum plant hence increased moisture

availability through mulch protects sorghum from the effects of Striga. Tolerance expression

is improved under mulch. Mulching is currently being promoted as a component of

conservation agriculture so adoption can cushion the small scale farmers from the effects of

Striga asiatica parasitism. Mulching increased chlorophyll concentration compared to

unmulched pots which in-turn maintained sorghum productivity. Mulching was advantageous

in the drier season compared to the wetter season. Drier seasons are more common in sub

Saharan Africa due to the effects of climate change. Again, the ability to tiller gave

genotypes higher yield as some genotypes continued to produce tillers after being affected by

Striga.

The problem of the existence of Striga asiatica strains was confirmed in Zimbabwe in this

study. Differential effects were observed when similar genotypes were subjected to the two

strains. This dimension complicates Striga asiatica management in the smallholder sector.

Trials done on supposedly resistant materials should be done all over the country to

determine if they can withstand local Striga asiatica diversity. Sorghum genotypes tended to

vary in their response to the strains.

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No genotype was completely resistant to Striga but were differentially sensitive. The

genotype Mukadziusaende produced the least strigolactones which in turn produces a

resistant phenotype. Wild sorghum and SC Sila (registered variety) were the highest

producers of strigolactones. Sorghum tillering was inversely related to strigolactones and this

confirmed what is found in literature (Jamil et al. 2012). It implies that farmers may use

tillers to predict strigolactone production in the field. The researchers may select for resistant

lines using tiller numbers. Higher tillers are lower producers of strigolactones.

7.3 Conclusions

The following conclusions can be made from the results of this study

1. Reduced water availability caused by droughts increase the effects of Striga asiatica

on sorghum although some genotypes may withstand the pressure.

2. Reduced water availability and Striga asiatica infestation had mutually exclusive

effects on chlorophyll concentration and NDVI.

3. The use of mulch benefits small holder farmers who grow their sorghum in Striga

infested fields since the mulch negates the effects of Striga especially under low

rainfall conditions.

4. There is existence of Striga asiatica physiological strains in Zimbabwe and this calls

for widespread trials on any material to be deemed resistant to the parasite.

5. Mukadziusaende had the least MGD and this means it was the least strigolactones

producer and got fewer Striga attachments and hence it produced the resistant

phenotype.

181

6. Higher tiller producers in sorghum indicates reduced strigolactones producers hence

researchers can use it to select for resistant phenotypes.

7. Sorghum arundinaceaum was found to be susceptible to Striga asiatica and may not

be a source of resistant material in sorghum breeding.

7.4. Recommendations for further research

1. More studies are needed on the link between reduced moisture availability to abscissic

acid need to be done to gain full understanding of the combined effects of drought on Striga

infested sorghum.

2. There is need to quantify the link between mulching, moisture availability and the effects

of parasitism.

3. Striga asiatica strains from the major sorghum producing regions in Zimbabwe to be tested

on any genotypes deemed resistant.

4. More genotypes from the genebank and from farmers’ fields need to be evaluated for

Striga resistance and tolerance.

182

References

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infiltration, surface runoff from two southwestern Nigerian agricultural soils.

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2. Badu-Apraku B, Akinwale RO, Oyenkule M (2014). Efficiency of secondary traits in

selecting for improved grain yield in extra early maize under Striga infested and

Striga free environments. Plant Breeding 133: 373 - 380

3. Berner, DK, Kling JG, Singh BB (1995). Striga research and control- a perspective

from Africa. Plant Disease 79: 652 – 660.

4. Huang K, Whitlock R, Press MC, Scholes JD (2012). Variations of host range within

and among populations of the parasitic plant, Striga hermonthica. Heredity 108: 96 -

104

5. Jamil M, Rodenburg J, Charnikhova T, Bouwmeester H.J (2012) Pre-attachment

Striga hermonthica resistance of new Rice for Africa (NERICA) cultivars based on

strigolactone production. New Phytologist 192: 964 – 975.

6. Jamil M, Charnikhova T, Houshyani B, van AAst A, Bouwmeester HJ (2011).

Genetic variation in strigolactones production and tillering in rice and its effects on

Striga hermonthica infection. Planta DOI 10.1007/s00425-011-1520y.

7. Kountche BA, Hash CT, Dodo H, Laovaly O, Sanogo MD, Timbeli A, Vigouroux Y,

This D, Nokamp D, Hausmann BIG (2013). Development of pearl millet Striga

resistant gene pool, response to five cycles of recurrent selection under Striga infested

field conditions in West Africa. Field Crop Research 154: 82 - 90

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8. Mabasa S (2003). Nitrogen and the control of Striga: timing and dose of organic and

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9. Rao, K, Steenhuis, T, Cogle A, Srinivasan, S, Yule D, Smith G (1998). Rainfall

infiltration and runoff from an alfisol in semi-arid India. 1. No till systems. Soil and

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plant management in sustainable agriculture. Weed Research 49: 1 – 5.

11. Scopel E, Muller, B, Areola Tostado J, Chavez Guera E, Maraux F (1998).

Quantifying and modeling the effects of a light crop residue on the water balance: an

application to rainfed maize in western Mexico. World congress on soil science,

France.

12. Sun, Z, Hans J, Walter M.H, Matusova R, Beekwilder R, Vestapen F.W.A, Ming Z,

van Echtelt E, Strack D, Bisseling T, Boumeester H.J (2008). Cloning and

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184

APPENDIX

APPENDICES

Appendix for Chapter 3: Analysis of variance tables for experiment 1 and 11

Analysis of variance

Variate: Head_DM

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 252.555 63.139 9.07 <.001

Infection 1 83.733 83.733 12.02 0.001

Drought 1 178.124 178.124 25.57 <.001

Variety.Infection 4 5.909 1.477 0.21 0.930

Variety.Drought 4 23.180 5.795 0.83 0.513

Infection.Drought 1 2.481 2.481 0.36 0.554

Variety.Infection.Drought

4 11.714 2.928 0.42 0.793

Residual 40 278.599 6.965

Total 59 836.294

Analysis of variance

Variate: Head_DM_adj

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 328.220 82.055 9.07 <.001

Infection 1 108.819 108.819 12.02 0.001

Drought 1 231.490 231.490 25.57 <.001

Variety.Infection 4 7.679 1.920 0.21 0.930

Variety.Drought 4 30.125 7.531 0.83 0.513

Infection.Drought 1 3.224 3.224 0.36 0.554

Variety.Infection.Drought

4 15.223 3.806 0.42 0.793

Residual 40 362.067 9.052

Total 59 1086.847

Analysis of variance

Variate: Root_dry

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 2850.7 712.7 2.99 0.030

Infection 1 416.0 416.0 1.74 0.194

Drought 1 2163.5 2163.5 9.07 0.004

Variety.Infection 4 408.4 102.1 0.43 0.788

Variety.Drought 4 496.7 124.2 0.52 0.721

Infection.Drought 1 147.7 147.7 0.62 0.436

Variety.Infection.Drought

4 328.4 82.1 0.34 0.847

Residual 40 9544.2 238.6

Total 59 16355.7

185

Analysis of variance

Variate: Rut_index

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.13483 0.03371 2.78 0.040

Infection 1 0.04188 0.04188 3.45 0.071

Drought 1 0.00140 0.00140 0.12 0.735

Variety.Infection 4 0.01746 0.00436 0.36 0.836

Variety.Drought 4 0.03239 0.00810 0.67 0.618

Infection.Drought 1 0.01862 0.01862 1.54 0.223

Variety.Infection.Drought

4 0.02271 0.00568 0.47 0.759

Residual 40 0.48511 0.01213

Total 59 0.75439

186

Analysis of variance for spad in experiment 2 at 10 wace

Variate: Spad_3ex

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 108.45 27.11 0.45 0.768

Infection 1 15.50 15.50 0.26 0.613

Drought 1 41.50 41.50 0.70 0.409

Variety.Infection 4 52.84 13.21 0.22 0.925

Variety.Drought 4 45.59 11.40 0.19 0.942

Infection.Drought 1 28.15 28.15 0.47 0.496

Variety.Infection.Drought

4 151.34 37.83 0.63 0.641

Residual 40 2385.09 59.63

Total 59 2828.47

Analysis of variance

Variate: Total_DM

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 4976.0 1244.0 3.38 0.018

Infection 1 103.4 103.4 0.28 0.599

Drought 1 9986.5 9986.5 27.17 <.001

Variety.Infection 4 2860.0 715.0 1.94 0.122

Variety.Drought 4 231.4 57.9 0.16 0.959

Infection.Drought 1 58.9 58.9 0.16 0.691

Variety.Infection.Drought

4 582.3 145.6 0.40 0.810

Residual 40 14704.8 367.6

Total 59 33503.4

Analysis of variance

Variate: dry_stems

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 283.43 70.86 1.39 0.254

Infection 1 5.94 5.94 0.12 0.734

Drought 1 536.29 536.29 10.53 0.002

Variety.Infection 4 687.27 171.82 3.37 0.018

Variety.Drought 4 101.22 25.31 0.50 0.738

Infection.Drought 1 0.01 0.01 0.00 0.989

Variety.Infection.Drought

4 335.88 83.97 1.65 0.181

Residual 40 2036.62 50.92

Total 59 3986.66

Analysis of variance at 6 wace in experiment 1

Variate: green_1_exp

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.010077 0.002519 0.37 0.829

Infection 1 0.029927 0.029927 4.38 0.043

187

Drought 1 0.390427 0.390427 57.18 <.001

Variety.Infection 4 0.018423 0.004606 0.67 0.614

Variety.Drought 4 0.010123 0.002531 0.37 0.828

Infection.Drought 1 0.023207 0.023207 3.40 0.073

Variety.Infection.Drought

4 0.044577 0.011144 1.63 0.185

Residual 40 0.273133 0.006828

Total 59 0.799893

Analysis of variance

Variate: green_2_exp_2

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.108593 0.027148 4.23 0.006

Infection 1 0.009882 0.009882 1.54 0.222

Drought 1 0.101682 0.101682 15.86 <.001

Variety.Infection 4 0.006060 0.001515 0.24 0.916

Variety.Drought 4 0.031327 0.007832 1.22 0.317

Infection.Drought 1 0.008402 0.008402 1.31 0.259

Variety.Infection.Drought

4 0.027407 0.006852 1.07 0.385

Residual 40 0.256467 0.006412

Total 59 0.549818

Analysis of variance

Variate: head_index

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.119577 0.029894 11.16 <.001

Infection 1 0.019735 0.019735 7.37 0.010

Drought 1 0.016000 0.016000 5.97 0.019

Variety.Infection 4 0.003059 0.000765 0.29 0.886

Variety.Drought 4 0.002850 0.000713 0.27 0.898

Infection.Drought 1 0.000630 0.000630 0.24 0.630

Variety.Infection.Drought

4 0.002811 0.000703 0.26 0.900

Residual 40 0.107182 0.002680

Total 59 0.271845

Analysis of variance

Variate: leaf_index

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.019685 0.004921 1.45 0.235

Infection 1 0.000386 0.000386 0.11 0.738

Drought 1 0.002152 0.002152 0.63 0.430

Variety.Infection 4 0.015046 0.003761 1.11 0.366

Variety.Drought 4 0.007571 0.001893 0.56 0.694

Infection.Drought 1 0.004273 0.004273 1.26 0.268

Variety.Infection.Drought

4 0.000867 0.000217 0.06 0.992

Residual 40 0.135712 0.003393

188

Total 59 0.185692

Analysis of variance

Variate: leaves_DM

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 338.93 84.73 4.98 0.002

Infection 1 6.98 6.98 0.41 0.525

Drought 1 226.40 226.40 13.30 <.001

Variety.Infection 4 160.65 40.16 2.36 0.070

Variety.Drought 4 4.32 1.08 0.06 0.992

Infection.Drought 1 6.66 6.66 0.39 0.535

Variety.Infection.Drought

4 28.12 7.03 0.41 0.798

Residual 40 680.87 17.02

Total 59 1452.93

Analysis of variance for experiment 1 at 6 wace

Variate: spad1_Exp2

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 641.20 160.30 5.03 0.002

Infection 1 141.53 141.53 4.44 0.041

Drought 1 440.38 440.38 13.81 <.001

Variety.Infection 4 74.74 18.68 0.59 0.675

Variety.Drought 4 351.77 87.94 2.76 0.041

Infection.Drought 1 23.60 23.60 0.74 0.395

Variety.Infection.Drought

4 105.80 26.45 0.83 0.514

Residual 40 1275.09 31.88

Total 59 3054.11

Analysis of variance

Variate: stem_index

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.033732 0.008433 1.38 0.257

Infection 1 0.004114 0.004114 0.68 0.416

Drought 1 0.003641 0.003641 0.60 0.444

Variety.Infection 4 0.024635 0.006159 1.01 0.413

Variety.Drought 4 0.029982 0.007496 1.23 0.313

Infection.Drought 1 0.001804 0.001804 0.30 0.589

Variety.Infection.Drought

4 0.020288 0.005072 0.83 0.513

Residual 40 0.243676 0.006092

Total 59 0.361872

189

Analysis of variance

Variate: Height_1

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 5431.7 1357.9 11.83 <.001

Infection 1 268.8 268.8 2.34 0.134

Drought 1 163.4 163.4 1.42 0.240

Variety.Infection 4 97.6 24.4 0.21 0.930

Variety.Drought 4 403.4 100.9 0.88 0.485

Infection.Drought 1 421.3 421.3 3.67 0.063

Variety.Infection.Drought

4 72.4 18.1 0.16 0.958

Residual 40 4590.0 114.8

Total 59 11448.6

Analysis of variance

Variate: Height_2

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 3903.6 975.9 6.60 <.001

Infection 1 777.6 777.6 5.26 0.027

Drought 1 614.4 614.4 4.16 0.048

Variety.Infection 4 116.2 29.1 0.20 0.939

Variety.Drought 4 759.1 189.8 1.28 0.293

Infection.Drought 1 77.1 77.1 0.52 0.474

Variety.Infection.Drought

4 352.4 88.1 0.60 0.668

Residual 40 5913.3 147.8

Total 59 12513.7

Analysis of variance

Variate: Height_3

Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr.

Variety 4 1872.3 468.1 2.15 0.093

Infection 1 908.7 908.7 4.17 0.048

Drought 1 1096.5 1096.5 5.03 0.031

Variety.Infection 4 911.3 227.8 1.05 0.396

Variety.Drought 4 1583.0 395.7 1.82 0.145

Infection.Drought 1 139.5 139.5 0.64 0.428

Variety.Infection.Drought

4 890.6 222.7 1.02 0.408

Residual 39 (1) 8496.5 217.9

Total 58 (1) 15753.5

190

Analysis of variance

Variate: Tillers

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 46.567 11.642 5.87 <.001

Infection 1 5.400 5.400 2.72 0.107

Drought 1 0.067 0.067 0.03 0.855

Variety.Infection 4 11.433 2.858 1.44 0.238

Variety.Drought 4 2.433 0.608 0.31 0.872

Infection.Drought 1 0.267 0.267 0.13 0.716

Variety.Infection.Drought

4 10.900 2.725 1.37 0.260

Residual 40 79.333 1.983

Total 59 156.400

Analysis of variance

Variate: Greeness2

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.090640 0.022660 3.19 0.023

Infection 1 0.003375 0.003375 0.47 0.495

Drought 1 0.001042 0.001042 0.15 0.704

Variety.Infection 4 0.005300 0.001325 0.19 0.944

Variety.Drought 4 0.023133 0.005783 0.81 0.524

Infection.Drought 1 0.004002 0.004002 0.56 0.457

Variety.Infection.Drought

4 0.049140 0.012285 1.73 0.163

Residual 40 0.284333 0.007108

Total 59 0.460965

Analysis of variance

Variate: Spad_1

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 523.73 130.93 4.73 0.003

Infection 1 11.97 11.97 0.43 0.515

Drought 1 17.93 17.93 0.65 0.426

Variety.Infection 4 66.47 16.62 0.60 0.665

Variety.Drought 4 182.16 45.54 1.64 0.182

Infection.Drought 1 10.09 10.09 0.36 0.550

Variety.Infection.Drought

4 36.34 9.08 0.33 0.857

Residual 40 1107.59 27.69

Total 59 1956.27

Analysis of variance

Variate: Spad_2

191

Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr.

Variety 4 734.04 183.51 7.29 <.001

Infection 1 0.23 0.23 0.01 0.924

Drought 1 10.46 10.46 0.42 0.523

Variety.Infection 4 10.32 2.58 0.10 0.981

Variety.Drought 4 133.83 33.46 1.33 0.276

Infection.Drought 1 25.94 25.94 1.03 0.316

Variety.Infection.Drought

4 32.42 8.10 0.32 0.861

Residual 39 (1) 981.38 25.16

Total 58 (1) 1922.27

Analysis of variance for experiment 11 at 6wace

Variate: greeness

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.072640 0.018160 2.07 0.103

Infection 1 0.005042 0.005042 0.57 0.453

Drought 1 0.066002 0.066002 7.51 0.009

Variety.Infection 4 0.042333 0.010583 1.20 0.324

Variety.Drought 4 0.019673 0.004918 0.56 0.693

Infection.Drought 1 0.009882 0.009882 1.12 0.295

Variety.Infection.Drought

4 0.041060 0.010265 1.17 0.339

Residual 40 0.351533 0.008788

Total 59 0.608165

192

Analysis of variance at 10 WACE in experiment 11

Variate: greeness_3

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.03739 0.00935 0.88 0.486

Infection 1 0.09048 0.09048 8.49 0.006

Drought 1 0.06080 0.06080 5.71 0.022

Variety.Infection 4 0.05143 0.01286 1.21 0.323

Variety.Drought 4 0.10554 0.02639 2.48 0.060

Infection.Drought 1 0.00160 0.00160 0.15 0.700

Variety.Infection.Drought

4 0.01591 0.00398 0.37 0.826

Residual 40 0.42627 0.01066

Total 59 0.78942

Analysis of variance

Variate: spad_3

Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr.

Variety 4 346.18 86.54 1.05 0.395

Infection 1 12.97 12.97 0.16 0.694

Drought 1 843.00 843.00 10.22 0.003

Variety.Infection 4 121.81 30.45 0.37 0.829

Variety.Drought 4 203.81 50.95 0.62 0.653

Infection.Drought 1 36.97 36.97 0.45 0.507

Variety.Infection.Drought

4 246.88 61.72 0.75 0.565

Residual 39 (1) 3217.59 82.50

Total 58 (1) 4845.74

Analysis of variance

Variate: Head_index

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.177163 0.044291 10.37 <.001

Infection 1 0.035755 0.035755 8.37 0.006

Drought 1 0.009396 0.009396 2.20 0.146

Variety.Infection 4 0.014336 0.003584 0.84 0.509

Variety.Drought 4 0.018068 0.004517 1.06 0.390

Infection.Drought 1 0.000334 0.000334 0.08 0.781

Variety.Infection.Drought

4 0.008320 0.002080 0.49 0.745

Residual 40 0.170891 0.004272

Total 59 0.434264

Analysis of variance

Variate: Head_wei

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 404.89 101.22 9.92 <.001

193

Infection 1 90.28 90.28 8.85 0.005

Drought 1 116.82 116.82 11.45 0.002

Variety.Infection 4 32.75 8.19 0.80 0.531

Variety.Drought 4 111.80 27.95 2.74 0.042

Infection.Drought 1 4.98 4.98 0.49 0.489

Variety.Infection.Drought

4 15.97 3.99 0.39 0.814

Residual 40 408.14 10.20

Total 59 1185.64

Analysis of variance

Variate: Internode

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 64.077 16.019 1.66 0.178

Infection 1 75.264 75.264 7.80 0.008

Drought 1 14.017 14.017 1.45 0.235

Variety.Infection 4 37.273 9.318 0.97 0.437

Variety.Drought 4 33.353 8.338 0.86 0.494

Infection.Drought 1 97.283 97.283 10.09 0.003

Variety.Infection.Drought

4 14.067 3.517 0.36 0.832

Residual 40 385.813 9.645

Total 59 721.147

Analysis of variance

Variate: Leaf_index

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.007335 0.001834 0.39 0.812

Infection 1 0.000971 0.000971 0.21 0.650

Drought 1 0.002985 0.002985 0.64 0.428

Variety.Infection 4 0.003511 0.000878 0.19 0.943

Variety.Drought 4 0.003462 0.000866 0.19 0.944

Infection.Drought 1 0.026219 0.026219 5.64 0.022

Variety.Infection.Drought

4 0.004498 0.001124 0.24 0.913

Residual 40 0.186057 0.004651

Total 59 0.235038

Analysis of variance

Variate: LeavesDM

Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr.

Variety 4 421.57 105.39 5.71 0.001

Infection 1 9.91 9.91 0.54 0.468

Drought 1 151.02 151.02 8.18 0.007

Variety.Infection 4 180.02 45.00 2.44 0.063

Variety.Drought 4 13.98 3.50 0.19 0.943

Infection.Drought 1 8.19 8.19 0.44 0.509

Variety.Infection.Drought

4 68.25 17.06 0.92 0.460

194

Residual 39 (1) 719.91 18.46

Total 58 (1) 1566.35

Analysis of variance

Variate: Root_dry

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 5019.6 1254.9 4.08 0.007

Infection 1 1567.0 1567.0 5.10 0.029

Drought 1 2840.2 2840.2 9.25 0.004

Variety.Infection 4 535.5 133.9 0.44 0.782

Variety.Drought 4 615.4 153.9 0.50 0.735

Infection.Drought 1 890.5 890.5 2.90 0.096

Variety.Infection.Drought

4 265.4 66.3 0.22 0.928

Residual 40 12288.3 307.2

Total 59 24022.0

Analysis of variance

Variate: Root_index

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.29315 0.07329 5.75 <.001

Infection 1 0.05435 0.05435 4.26 0.045

Drought 1 0.00155 0.00155 0.12 0.729

Variety.Infection 4 0.01544 0.00386 0.30 0.874

Variety.Drought 4 0.01643 0.00411 0.32 0.861

Infection.Drought 1 0.04829 0.04829 3.79 0.059

Variety.Infection.Drought

4 0.02045 0.00511 0.40 0.807

Residual 40 0.50983 0.01275

Total 59 0.95949

Analysis of variance

Variate: Stem_index

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 0.039043 0.009761 1.60 0.193

Infection 1 0.005657 0.005657 0.93 0.341

Drought 1 0.006670 0.006670 1.09 0.302

Variety.Infection 4 0.039305 0.009826 1.61 0.190

Variety.Drought 4 0.029976 0.007494 1.23 0.314

Infection.Drought 1 0.005795 0.005795 0.95 0.335

Variety.Infection.Drought

4 0.012942 0.003235 0.53 0.714

Residual 40 0.243833 0.006096

Total 59 0.383221

Analysis of variance

Variate: Total_DM

195

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 7122.8 1780.7 3.50 0.015

Infection 1 1287.7 1287.7 2.53 0.119

Drought 1 9983.1 9983.1 19.62 <.001

Variety.Infection 4 3449.9 862.5 1.70 0.170

Variety.Drought 4 412.6 103.2 0.20 0.935

Infection.Drought 1 942.5 942.5 1.85 0.181

Variety.Infection.Drought

4 1254.5 313.6 0.62 0.653

Residual 40 20350.3 508.8

Total 59 44803.3

Analysis of variance

Variate: dry_stems

Source of variation d.f. s.s. m.s. v.r. F pr.

Variety 4 357.61 89.40 1.45 0.234

Infection 1 0.24 0.24 0.00 0.951

Drought 1 456.34 456.34 7.42 0.010

Variety.Infection 4 850.16 212.54 3.46 0.016

Variety.Drought 4 76.22 19.05 0.31 0.870

Infection.Drought 1 13.34 13.34 0.22 0.644

Variety.Infection.Drought

4 427.87 106.97 1.74 0.160

Residual 40 2460.59 61.51

Total 59 4642.37

APPENDIX 2: Analysis of variance tables for Chapter 4

Analysis of variance

Variate: Chlorophy_I_3 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 1862.54 206.95 5.30 <.001 Mulch 1 0.16 0.16 0.00 0.949 infestati 1 22.06 22.06 0.57 0.454 Variety.Mulch 9 461.28 51.25 1.31 0.244 Variety.infestati 9 440.13 48.90 1.25 0.276 Mulch.infestati 1 109.92 109.92 2.82 0.097 Variety.Mulch.infestati 9 417.35 46.37 1.19 0.315 Residual 79 (1) 3084.37 39.04

196

Total 118 (1) 6314.94

Analysis of variance for chlorophyll content at 6 WACE in 2013-14 season

Variate: Chlorophyl1 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 343.60 38.18 1.81 0.080 Mulch 1 6.42 6.42 0.30 0.583 infestati 1 46.94 46.94 2.23 0.140 Variety.Mulch 9 201.91 22.43 1.06 0.399 Variety.infestati 9 375.21 41.69 1.98 0.053 Mulch.infestati 1 1.11 1.11 0.05 0.819 Variety.Mulch.infestati 9 172.52 19.17 0.91 0.522 Residual 77 (3) 1623.73 21.09 Total 116 (3) 2740.53

Analysis of variance for chlorophyll content at 8 WACE in the 2013 – 14 season

Variate: Chlorophyl_2 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 488.52 54.28 3.60 <.001 Mulch 1 42.96 42.96 2.85 0.096 infestati 1 3.47 3.47 0.23 0.633 Variety.Mulch 9 108.70 12.08 0.80 0.617 Variety.infestati 9 166.80 18.53 1.23 0.290 Mulch.infestati 1 16.88 16.88 1.12 0.294 Variety.Mulch.infestati 9 130.23 14.47 0.96 0.481 Residual 79 (1) 1192.75 15.10 Total 118 (1) 2145.72

Analysis of variance

Variate: Chlorophyl_4 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 856.97 95.22 1.32 0.242 Mulch 1 51.16 51.16 0.71 0.403 infestati 1 0.16 0.16 0.00 0.963 Variety.Mulch 9 1560.43 173.38 2.40 0.019 Variety.infestati 9 734.54 81.62 1.13 0.353 Mulch.infestati 1 36.14 36.14 0.50 0.482 Variety.Mulch.infestati 9 1033.34 114.82 1.59 0.134 Residual 73 (7) 5270.21 72.19 Total 112 (7) 8981.34

Analysis of variance

Variate: Chlorophyl_5

197

Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 842.61 93.62 1.04 0.420 Mulch 1 375.77 375.77 4.16 0.045 infestati 1 81.43 81.43 0.90 0.346 Variety.Mulch 9 660.95 73.44 0.81 0.606 Variety.infestati 9 881.51 97.95 1.08 0.385 Mulch.infestati 1 145.31 145.31 1.61 0.209 Variety.Mulch.infestati 9 984.42 109.38 1.21 0.302 Residual 72 (8) 6505.40 90.35 Total 111 (8) 10367.63

Analysis of variance for stomatal conductance in the 2013 – 14 season

Variate: Conductance_1 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 6839.8 760.0 3.73 <.001 Mulch 1 0.3 0.3 0.00 0.969 infestati 1 793.9 793.9 3.89 0.052 Variety.Mulch 9 1525.5 169.5 0.83 0.590 Variety.infestati 9 2044.1 227.1 1.11 0.364 Mulch.infestati 1 57.8 57.8 0.28 0.596 Variety.Mulch.infestati 9 2063.8 229.3 1.12 0.357 Residual 74 (6) 15095.3 204.0 Total 113 (6) 26690.3

Analysis of variance

Variate: Height_1 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 2586.89 287.43 5.17 <.001 Mulch 1 12.50 12.50 0.22 0.637 infestati 1 191.83 191.83 3.45 0.067 Variety.Mulch 9 770.53 85.61 1.54 0.150 Variety.infestati 9 951.86 105.76 1.90 0.065 Mulch.infestati 1 39.99 39.99 0.72 0.399 Variety.Mulch.infestati 9 540.70 60.08 1.08 0.388 Residual 73 (7) 4059.35 55.61 Total 112 (7) 8943.01

Analysis of variance

Variate: Height_2 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 4060.7 451.2 3.78 <.001 Mulch 1 0.5 0.5 0.00 0.948

198

infestati 1 1658.9 1658.9 13.89 <.001 Variety.Mulch 9 1780.5 197.8 1.66 0.116 Variety.infestati 9 1270.9 141.2 1.18 0.320 Mulch.infestati 1 69.3 69.3 0.58 0.449 Variety.Mulch.infestati 9 605.0 67.2 0.56 0.823 Residual 70 (10) 8360.9 119.4 Total 109 (10) 15730.4

Analysis of variance

Variate: Height_4 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 69831. 7759. 5.92 <.001 Mulch 1 241. 241. 0.18 0.670 infestati 1 23801. 23801. 18.15 <.001 Variety.Mulch 9 7446. 827. 0.63 0.767 Variety.infestati 9 16268. 1808. 1.38 0.214 Mulch.infestati 1 1665. 1665. 1.27 0.264 Variety.Mulch.infestati 9 4834. 537. 0.41 0.926 Residual 71 (9) 93108. 1311. Total 110 (9) 200388.

Analysis of variance

Variate: Leaf_length Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 14022.9 1558.1 15.37 <.001 Mulch 1 7.8 7.8 0.08 0.783 infestati 1 55.4 55.4 0.55 0.462 Variety.Mulch 9 1109.3 123.3 1.22 0.299 Variety.infestati 9 734.0 81.6 0.80 0.614 Mulch.infestati 1 0.1 0.1 0.00 0.975 Variety.Mulch.infestati 9 407.5 45.3 0.45 0.905 Residual 71 (9) 7198.8 101.4 Total 110 (9) 23007.7

Analysis of variance for effect of sorghum genotypes on tiller number in the 2013 – 14 season

Variate: Tiller_1 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 106.135 11.793 6.33 <.001 Mulch 1 5.852 5.852 3.14 0.080 infestati 1 13.002 13.002 6.98 0.010 Variety.Mulch 9 20.335 2.259 1.21 0.299 Variety.infestati 9 29.185 3.243 1.74 0.093 Mulch.infestati 1 1.302 1.302 0.70 0.406

199

Variety.Mulch.infestati 9 31.052 3.450 1.85 0.072 Residual 79 (1) 147.167 1.863 Total 118 (1) 353.933

Analysis of variance

Variate: height_3 Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 17558.5 1950.9 3.38 0.002 Mulch 1 218.7 218.7 0.38 0.540 infestati 1 6453.3 6453.3 11.17 0.001 Variety.Mulch 9 4393.1 488.1 0.84 0.578 Variety.infestati 9 2637.4 293.0 0.51 0.865 Mulch.infestati 1 224.1 224.1 0.39 0.535 Variety.Mulch.infestati 9 1299.2 144.4 0.25 0.985 Residual 72 (8) 41597.0 577.7 Total 111 (8) 70805.4

Analysis of variance

Variate: leaves_1 Source of variation d.f. s.s. m.s. v.r. F pr. Variety 9 34.000 3.778 1.76 0.090 Mulch 1 1.200 1.200 0.56 0.457 infestati 1 8.533 8.533 3.97 0.050 Variety.Mulch 9 28.967 3.219 1.50 0.163 Variety.infestati 9 37.300 4.144 1.93 0.060 Mulch.infestati 1 0.833 0.833 0.39 0.535 Variety.Mulch.infestati 9 18.333 2.037 0.95 0.489 Residual 80 172.000 2.150 Total 119 301.167

Analysis of variance for head weight in the 2014 – 15 season

Variate: Headweight_15 Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 8424.1 936.0 7.95 <.001 Infestation 1 1780.9 1780.9 15.13 <.001 Mulch 1 4179.7 4179.7 35.50 <.001 variety.Infestation 9 1503.0 167.0 1.42 0.194 variety.Mulch 9 834.7 92.7 0.79 0.628 Infestation.Mulch 1 36.4 36.4 0.31 0.580 variety.Infestation.Mulch 9 554.2 61.6 0.52 0.854 Residual 80 9419.6 117.7 Total 119 26732.5

200

Appendix 3: Analysis of variance table for Chapter 5 experiment 1 and 11

Analysis of variance for head weight at Henderson research station

Variate: HEAD_WEI_g Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 6378.43 708.71 14.86 <.001 Strain 2 1098.93 549.46 11.52 <.001 variety.Strain 18 1541.34 85.63 1.79 0.047 Residual 60 2862.33 47.71 Total 89 11881.03

Analysis of variance

Variate: Head_weight_g Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 7776.93 864.10 16.87 <.001 Strain 2 596.40 298.20 5.82 0.005 variety.Strain 18 2058.11 114.34 2.23 0.011 Residual 60 3074.01 51.23 Total 89 13505.45

Analysis of variance

Variate: LEAF_WEI_g Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 527.380 58.598 7.64 <.001 Strain 2 1.550 0.775 0.10 0.904 variety.Strain 18 216.699 12.039 1.57 0.098 Residual 60 460.220 7.670 Total 89 1205.849

Analysis of variance

Variate: L_LENGTH Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 418.23 46.47 1.36 0.226 Strain 2 16.07 8.03 0.24 0.791 variety.Strain 18 965.93 53.66 1.57 0.097 Residual 60 2046.67 34.11 Total 89 3446.90

Analysis of variance

Variate: Leaf_weight_g

201

Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 1425.37 158.37 9.02 <.001 Strain 2 4.31 2.15 0.12 0.885 variety.Strain 18 456.57 25.36 1.44 0.145 Residual 60 1053.60 17.56 Total 89 2939.85

Analysis of variance for sorghum height at Buse at 12 WACE

Variate: P_HEIGHT Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 53351. 5928. 4.30 <.001 Strain 2 10432. 5216. 3.79 0.028 variety.Strain 18 35048. 1947. 1.41 0.159 Residual 60 82631. 1377. Total 89 181463.

Analysis of variance for root weight at BUSE

Variate: Root_weight Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 36290.6 4032.3 5.56 <.001 Strain 2 16331.9 8165.9 11.26 <.001 variety.Strain 18 17350.5 963.9 1.33 0.204 Residual 60 43531.7 725.5 Total 89 113504.6

Analysis of variance for root index at BUSE

Variate: Rutindex Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 1.29520 0.14391 13.68 <.001 Strain 2 0.57482 0.28741 27.32 <.001 variety.Strain 18 0.25376 0.01410 1.34 0.197 Residual 60 0.63115 0.01052 Total 89 2.75493

Analysis of variance

Variate: STEM_WEI_g Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 3080.2 342.2 3.20 0.003 Strain 2 1268.5 634.3 5.93 0.004 variety.Strain 18 3796.0 210.9 1.97 0.026 Residual 60 6413.5 106.9 Total 89 14558.2

Analysis of variance

202

Variate: S_COUNT Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 474.27 52.70 1.19 0.319 Strain 2 424.09 212.04 4.78 0.012 variety.Strain 18 1021.47 56.75 1.28 0.234 Residual 60 2660.00 44.33 Total 89 4579.82

Analysis of variance for stem index at Buse

Variate: Stem_Inde Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 0.188103 0.020900 3.46 0.002 Strain 2 0.133236 0.066618 11.03 <.001 variety.Strain 18 0.171405 0.009522 1.58 0.096 Residual 60 0.362323 0.006039 Total 89 0.855066

Analysis of variance

Variate: Stem_weight_g Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 48728. 5414. 5.35 <.001 Strain 2 8141. 4070. 4.03 0.023 variety.Strain 18 28045. 1558. 1.54 0.108 Residual 60 60675. 1011. Total 89 145589.

Analysis of variance

Variate: Striga_Counts Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 792.90 88.10 1.69 0.111 Strain 2 687.09 343.54 6.59 0.003 variety.Strain 18 809.80 44.99 0.86 0.622 Residual 60 3126.67 52.11 Total 89 5416.46

203

Analysis of variance

Variate: TILLER_No Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 440.267 48.919 5.35 <.001 Strain 2 43.889 21.944 2.40 0.099 variety.Strain 18 103.667 5.759 0.63 0.862 Residual 60 548.667 9.144 Total 89 1136.489

Analysis of variance

Variate: Total Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 28960.4 3217.8 3.32 0.002 Strain 2 8709.5 4354.8 4.49 0.015 variety.Strain 18 27440.5 1524.5 1.57 0.097 Residual 60 58132.2 968.9 Total 89 123242.6

Analysis of variance

Variate: chloro_1 Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 1112.223 123.580 12.41 <.001 Strain 2 532.241 266.120 26.71 <.001 variety.Strain 18 712.641 39.591 3.97 <.001 Residual 60 597.693 9.962 Total 89 2954.798

Analysis of variance for chlorophyll content at 8 wace at BUSE

Variate: chloro_2 Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 602.738 66.971 7.26 <.001 Strain 2 186.027 93.013 10.08 <.001 variety.Strain 18 454.389 25.244 2.74 0.002 Residual 60 553.773 9.230 Total 89 1796.927

Analysis of variance for chlorophyll content at 12 wace at BUSE

Variate: chloro_3 Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 917.362 101.929 12.11 <.001 Strain 2 171.811 85.905 10.21 <.001 variety.Strain 18 412.843 22.936 2.73 0.002 Residual 60 504.973 8.416

204

Total 89 2006.989

Analysis of variance

Source d.f. s.s. m.s. v.r. F pr. variety ignoring Strain 9 359.48 39.94 1.17 0.333 variety eliminating Strain 9 369.94 41.10 1.20 0.312 Strain ignoring variety 2 194.15 97.07 2.84 0.067 Strain eliminating variety 2 204.60 102.30 2.99 0.058 variety.Strain 18 609.21 33.84 0.99 0.485 Residual 58 1984.81 34.22 Total 87 3158.10 36.30

Analysis of variance for head index at BUSE

Variate: headindex Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 0.812826 0.090314 14.78 <.001 Strain 2 0.135071 0.067535 11.05 <.001 variety.Strain 18 0.141500 0.007861 1.29 0.229 Residual 60 0.366666 0.006111 Total 89 1.456063

Analysis of variance for plant height at 6 wace at Buse

Source d.f. s.s. m.s. v.r. F pr. variety ignoring Strain 9 1874.00 208.22 6.99 < 0.001 variety eliminating Strain 9 1907.52 211.95 7.11 < 0.001 Strain ignoring variety 2 112.02 56.01 1.88 0.162 Strain eliminating variety 2 145.54 72.77 2.44 0.096 variety.Strain 18 512.05 28.45 0.95 0.522 Residual 56 1669.17 29.81 Total 85 4200.76 49.42

Analysis of variance for leaf index at BUSE

Variate: lifindex Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 0.0361770 0.0040197 8.15 <.001 Strain 2 0.0026811 0.0013405 2.72 0.074 variety.Strain 18 0.0109778 0.0006099 1.24 0.264 Residual 60 0.0296068 0.0004934 Total 89 0.0794427

205

Analysis of variance

Variate: tiller_num Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 71.833 7.981 6.41 <.001 Strain 2 10.422 5.211 4.19 0.020 variety.Strain 18 15.800 0.878 0.71 0.792 Residual 60 74.667 1.244 Total 89 172.722

Analysis of variance

Variate: HEAD_WEI_g Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. VARIETY 9 8979.0 997.7 9.65 <.001 STRI_STR 2 1055.4 527.7 5.10 0.009 VARIETY.STRI_STR 18 2633.8 146.3 1.41 0.161 Residual 56 (4) 5791.6 103.4 Total 85 (4) 18103.9

Analysis of variance

Variate: LEAF_WEI_g Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. VARIETY 9 523.919 58.213 7.09 <.001 STRI_STR 2 1.806 0.903 0.11 0.896 VARIETY.STRI_STR 18 218.240 12.124 1.48 0.134 Residual 56 (4) 459.493 8.205 Total 85 (4) 1184.259

Analysis of variance

Variate: STEM_WEI_g Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. VARIETY 9 3432.8 381.4 2.78 0.009 STRI_STR 2 411.5 205.7 1.50 0.231 VARIETY.STRI_STR 18 3839.5 213.3 1.56 0.103 Residual 59 (1) 8086.3 137.1 Total 88 (1) 15765.2

Analysis of variance

Variate: Head_index Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 0.404695 0.044966 18.37 <.001 STRI_STR 2 0.036723 0.018362 7.50 0.001

206

VARIETY.STRI_STR 18 0.062302 0.003461 1.41 0.159 Residual 60 0.146895 0.002448 Total 89 0.650616

Analysis of variance

Variate: Head_weight_g Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 6677.58 741.95 16.79 <.001 STRI_STR 2 1329.86 664.93 15.05 <.001 VARIETY.STRI_STR 18 1631.83 90.66 2.05 0.020 Residual 60 2651.25 44.19 Total 89 12290.51

Analysis of variance for leaf index for the Henderson experiment

Variate: Leaf_index Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 0.0332699 0.0036967 10.10 <.001 STRI_STR 2 0.0092419 0.0046209 12.63 <.001 VARIETY.STRI_STR 18 0.0128970 0.0007165 1.96 0.027 Residual 60 0.0219552 0.0003659 Total 89 0.0773640

Analysis of variance

Variate: Leaf_weight_g Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 1444.88 160.54 12.59 <.001 STRI_STR 2 23.77 11.89 0.93 0.399 VARIETY.STRI_STR 18 530.42 29.47 2.31 0.008 Residual 60 764.80 12.75 Total 89 2763.87

Analysis of variance for Root index at henderson

Variate: Root_Index Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 0.92416 0.10268 9.22 <.001 STRI_STR 2 0.40930 0.20465 18.37 <.001 VARIETY.STRI_STR 18 0.24271 0.01348 1.21 0.283 Residual 60 0.66855 0.01114 Total 89 2.24472

Analysis of variance

Variate: Root_weight

207

Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 36290.6 4032.3 5.56 <.001 STRI_STR 2 16331.9 8165.9 11.26 <.001 VARIETY.STRI_STR 18 17350.5 963.9 1.33 0.204 Residual 60 43531.7 725.5 Total 89 113504.6

Analysis of variance for stem index for the Henderson experiment.

Variate: Stem_index Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 0.63802 0.07089 5.52 <.001 STRI_STR 2 0.23920 0.11960 9.32 <.001 VARIETY.STRI_STR 18 0.30578 0.01699 1.32 0.206 Residual 60 0.77000 0.01283 Total 89 1.95300

Analysis of variance

Variate: Stem_weight_g Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 48626. 5403. 5.34 <.001 STRI_STR 2 8114. 4057. 4.01 0.023 VARIETY.STRI_STR 18 28040. 1558. 1.54 0.108 Residual 60 60677. 1011. Total 89 145458.

Analysis of variance for total dry weight at henderson

Variate: Total_Dry Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 86549. 9617. 4.70 <.001 STRI_STR 2 10423. 5211. 2.54 0.087 VARIETY.STRI_STR 18 68784. 3821. 1.87 0.037 Residual 60 122889. 2048. Total 89 288645.

Analysis of variance for chlorophyll content at 8 WACE at Henderson

Variate: chloro_1 Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 1112.223 123.580 12.41 <.001 Strain 2 532.241 266.120 26.71 <.001 variety.Strain 18 712.641 39.591 3.97 <.001 Residual 60 597.693 9.962

208

Total 89 2954.798

Analysis of variance FOR CHLOROPHYLL CONTENT AT buse AT 10 WACE

Variate: chloro_2 Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 602.738 66.971 7.26 <.001 Strain 2 186.027 93.013 10.08 <.001 variety.Strain 18 454.389 25.244 2.74 0.002 Residual 60 553.773 9.230 Total 89 1796.927

Analysis of variance

Variate: chloro_3 Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 917.362 101.929 12.11 <.001 Strain 2 171.811 85.905 10.21 <.001 variety.Strain 18 412.843 22.936 2.73 0.002 Residual 60 504.973 8.416 Total 89 2006.989

209

Appendix 6: ANOVA tables for Chapter 6

Analysis of variance for tiller number for quantification trial Variate: Tiller Source of variation d.f. s.s. m.s. v.r. F pr. treatment 7 24.0000 3.4286 4.70 0.002 Residual 24 17.5000 0.7292 Total 31 41.5000

Analysis of variance for maximum germination distance

Variate: germ_dist Source of variation d.f. s.s. m.s. v.r. F pr. treatment 7 7.40219 1.05746 14.16 <.001 Residual 24 1.79250 0.07469 Total 31 9.19469

Analysis of variance for Striga counts in the quantification experiments

Variate: stri_counts Source of variation d.f. s.s. m.s. v.r. F pr. treatment 7 492.969 70.424 19.26 <.001 Residual 24 87.750 3.656 Total 31 580.719

Correlations

210

germ distance tiller striga counts

Kendall's tau_b

germ distance

Correlation Coefficient 1.000 -.191 .564**

Sig. (2-tailed) . .172 .000

N 32 32 32

tiller

Correlation Coefficient -.191 1.000 .090

Sig. (2-tailed) .172 . .518

N 32 32 32

striga counts

Correlation Coefficient .564** .090 1.000

Sig. (2-tailed) .000 .518 .

N 32 32 32

Spearman's rho

germ distance

Correlation Coefficient 1.000 -.258 .741**

Sig. (2-tailed) . .154 .000

N 32 32 32

tiller

Correlation Coefficient -.258 1.000 .062

Sig. (2-tailed) .154 . .735

N 32 32 32

striga counts

Correlation Coefficient .741** .062 1.000

Sig. (2-tailed) .000 .735 .

N 32 32 32

**. Correlation is significant at the 0.01 level (2-tailed).

211