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Volume 3, Number 5, May 2013 (Serial Number 25)

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Journal of Agricultural Science

and Technology A

Volume 3, Number 5, May 2013 (Serial Number 25)

Contents

Review

331 Plant Enzymes, Root Exudates, Cluster Roots and Mycorrhizal Symbiosis are the Drivers of P

Nutrition in Native Legumes Growing in P Deficient Soil of the Cape Fynbos in South Africa

Sipho Thulane Maseko and Felix Dapare Dakora

Research Papers

341 Effect of Ripening Stages on Basic Deep-Fat Frying Qualities of Plantain Chips

Ogan Mba, Jamshid Rahimi and Michael Ngadi

349 Production and Nutritive Value of Shrub Legumes in West Timor, East Nusa Tenggara Province,

Indonesia

Sophia Ratnawaty, Hartutik, Soebarinoto and Siti Chuzaemi

356 Study of Sandy Soil Compaction

Andrea Formato, Gian Pio Pucillo and Antonio Abagnale

368 Potential Impacts of Various Land Use Forms on Land Degradation in Arid Regions (Case Study:

Kuwait)

Raafat Misak and Adeeba Al-Hurban

380 Effects of Using Different Percentages of Fenugreek Flour to Improve the Sensory, Rheological

Properties and Keeping Quality in Maize Dough to Produces Gluten-free Breads

Abdulsalam Abdulrahman Rasool, Dana Azad Abdulkhaleq and Dlir Amin Sabir

385 Applicability of Cytoplasmic Male Sterility (CMS) as a Reliable Biological Confinement Method

for the Cultivation of Genetically Modified Maize in Germany

Heidrun Bückmann, Alexandra Hüsken and Joachim Schiemann

404 Evaluation of Fungicides for Controlling Stem Rust Race Ug99 on Bread Wheat

Joseph Kinyoro Macharia, Ruth Wanyera and Samuel Kilonzo

410 Occurrence and Effects of Pineapple Mealybug Wilt Disease in Central Uganda

Bosco Bua, Jeninah Karungi and Geoffrey Kawube

417 Electronic Identification of Livestock to Improve Turkey’s Animal Production System

Sezen Ocak, Sinan Ogun and Zuhal Gunduz

Journal of Agricultural Science and Technology A 3 (2013) 331-340 Earlier title: Journal of Agricultural Science and Technology, ISSN 1939-1250

Plant Enzymes, Root Exudates, Cluster Roots and

Mycorrhizal Symbiosis are the Drivers of P Nutrition in

Native Legumes Growing in P Deficient Soil of the Cape

Fynbos in South Africa

Sipho Thulane Maseko1 and Felix Dapare Dakora2

1. Department of Crop Sciences, Faculty of Science, Tshwane University of Technology, Pretoria 0001, South Africa

2. Chemistry Department, Faculty of Science, Tshwane University of Technology, Pretoria 0001, South Africa

Received: January 30, 2013 / Published: May 20, 2013. Abstract: The Cape fynbos is characterised by highly leached, sandy, acidic soils with very low nutrient concentrations. Plant-available P levels range from 0.4 μg P g-1 to 3.7 μg P g-1 soil, and 1-2 mg N g-1 soil. Despite these low nutrient concentrations, the fynbos is home to 9,030 vascular plant species with 68.7% endemicity. How native plant species survive such low levels of available P is intriguing, and indeed the subject of this review. In the fynbos soils, P is easily precipitated with cations such as Fe and Al, forming Al-P and Fe-P in acidic soils, or Ca-P in neutral-to-alkaline soils. The mechanisms for promoting P availability and enhancing P nutrition include the development of mycorrhizal symbiosis (with 80%-90% of higher plants, e.g., Cyclopia, Aspalathus, Psoralea and Leucadendron etc.) which exhibits 3-5 times much greater P acquisition than non-mycorrhizal roots. Formation of cluster roots by the Leguminosae (Fabaceae) and their exudation of Kreb cycle intermediates (organic acids) for solubilizing P, secretion of root exudate compounds (organic acids, phenolics, amino acids, etc.) that mobilize P. The synthesis and release of acid and alkaline phosphatase enzyme that catalyze the cleavage of mineral P from organic phosphate esters in acidic and alkaline soils, and the development of deep tap roots as well as massive secondary roots within the uppermost 15 cm of soil for capturing water and nutrients. Some fynbos legumes employ all these adaptive mechanisms for enhancing P nutrition and plant growth. Aspalathus and Cyclopia species typically form mycorrhizal and rhizobial symbiosis for improving P and N nutrition, produce cluster roots and acid phosphatases for increasing P supply, and release root exudates that enhance P solubilisation and uptake.

Key words: Cape fynbos, Cyclopia, Aspalathus, phosphorus, mycorrhiza, phosphatases.

1. Introduction

The Cape fynbos is part of the Cape Floristic

Region, and is characterised by strongly leached,

acidic sandy soils with very low nutrient

concentrations, especially phosphorus (P) [1, 2]. That

not with standing, it has the most diverse flora

comprising about 9,030 vascular plant species with

68.7% endemicity [3, 4]. Although P is an important

nutrient for plant growth, it remains one of the most

Corresponding author: Felix Dapare Dakora, professor,

research fields: agrochemurgy and plant symbioses. E-mail: [email protected].

limiting elements in soils. For example,

plant-available P levels in the Cape fynbos soils in

particular are very low, range between 0.4 μg P g-1

and 3.7 μg P g-1 [5]. How the native plant species

survive on such low levels of available P is intriguing,

and indeed the subject of this review. Although many

soils contain about 20%-80% P in the organic form [6]

and fynbos soils in particular contain about 58%-77%

organic P [7], most of it is unavailable for plant uptake

due to complexion with Ca, Fe and Al [8], and/or

microbial incorporation into organic matter following

decomposition [9].

DAVID PUBLISHING

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Plant enzymes, Root Exudates, Cluster Roots and Mycorrhizal Symbiosis are the Drivers of P Nutrition in Native Legumes Growing in P Deficient Soil of the Cape Fynbos in South Africa

332

Under acidic conditions, phosphate ions easily

precipitate with cations such as Fe and Al, thereby

forming bound-P which is unavailable to plants [10].

As a result, P is generally present in only micromolar

(μΜ), or lesser concentrations in soils, even though

most mineral nutrients occur in millimolar (mM)

levels in the soil solution. Because of its low

micromolar concentrations, P uptake during water

absorption by plants typically accounts for only about

1%-5% of the plant’s P demand [11], an amount too

little to drive the multitude of P-requiring metabolic

processes in cells. Furthermore, P mobility in soils is

very low, and this adds to its limiting status in

ecosystems. Although the application of P-fertilizers

could potentially increase P concentration in soils, the

efficiency of these fertilizers is low in cropping

systems, with only 10%-20% of fertilizer-P being

used by crops in the year of application [12]. This

reduced efficiency of applied P is due to rapid

conversion to bound forms such as Al-P and Fe-P in

acidic soils, or Ca-P in neutral-to-alkaline soils [8,

13].

Where P is low in natural ecosystems, native and

endemic plant species must have mechanisms for

coping with low P stress. Plants that are native to low

P (soils such as those of the fynbos) develop various

strategies that are directed at enhancing P acquisition,

especially sparingly soluble P [14, 15]. The fact that

the Cape fynbos soils are very low in P, and yet this

biome is home to some 9,030 plant species with

68.7% endemicity, suggests the presence of

plant-evolved mechanisms for coping with low P

stress. For example, in addition to deep tap roots,

fynbos plant species develop lots of secondary roots

that are concentrated within the uppermost 15 cm of

soil, and decrease exponentially with depth [16]. A

recent review has described the strategies used by

cultivated crop species to acquire P under low nutrient

conditions [17]. This report addresses the biological

features of plant adaptation to low-P stress in the Cape

fynbos of South Africa. These adaptations include the

role of mycorrhizal symbiosis, cluster root formation,

root exudates, secretion of P-solubilizing enzymes and

root architecture/function.

2. Plant Secretion of Phosphatase Enzymes

Secretion of enzymes such as phosphatases is

another way by which plants and microbes respond to

P deficiency in soils [10, 18]. There are two types of

phosphatases: acid phosphatases (APases), which are

of plant origin and display an optimum activity below

pΗ 7 [19], and alkaline phosphatases, which are

secreted by bacteria, fungi and earthworms and

function catalytically above pΗ 7 [20]. Although a

large proportion of P occurs as organic P in soil [21],

plants can only utilize P in the inorganic form [22]. In

low P soils, phosphatase enzymes serve to catalyze the

cleavage of mineral P from organic phosphate esters

in both acidic and alkaline soils [23], and thus make P

more available in the rhizosphere for root uptake.

Usually, an increase in phosphatase activity in

rhizosphere soil implies increased hydrolysis of soil

phosphate esters, and elevated bioavailability of P for

plant uptake [24]. Thus, acid and alkaline phosphatase

activity is often used as a biological indicator of P

mineralization and P availability in the rhizosphere

[18].

Rhizosphere soil therefore usually has higher

phosphatase activity than bulk soil (Fig. 1A). Three

fynbos legumes, (namely Cyclopia genistoides,

Aspalathus caledonensis, Aspalathus aspalathoides

and the non-legume Leucadendron strictum)

co-occurring at the same fynbos site showed

significant variation in acid phosphatase activity. The

Cyclopia species exhibited significantly higher APase

activity in its rhizosphere, followed by A.

caledonensis, Aspalathus aspalathoides and L.

strictum, which recorded a much lower APase activity

(Fig. 1B). This might suggest that these legumes

exhibit different degrees of tolerance to low P in the

Cape fynbos. No doubt, the synthesis of

macromolecules such as enzymes is very costly to the


333

0

100

200

300

400

500

600

700

Cyclopiagenistoides

Aspalathuscaledonensis

Aspalathusaspalathoides

Leucadendronstrictum

Ac p

hosphata

se

(μg p

-nitro

phenol.g

-1soil Fwt.h

-1)

a

b

c c

B

0

100

200

300

400

500

600

700

Ac

phosp

hat

ase

(μg p

-nitro

phen

ol.g

-1so

il F w

t.h

-1)

Cyclopia genistoides

Rhizosphere soil

Bulk soil

a

b

A

Fig. 1 A) Acid phosphatase activity in rhizosphere and bulk soils of Cyclopia genistoides; B) Acid phosphatase activity in rhizosphere soil of Cyclopia genistoides, Aspalathus caledonensis, Aspalathus aspalathoides and Leucadendron strictum sampled from Koksrivier farm. Data are mean for enzyme activity and error bars show one standard error; columns with different letters are significantly different at P ≤ 0.05.

C economy of plants, hence their formation in large

quantities can only occur when there is a strong

biological demand, such as enhancing P acquisition in

low-P environments [8, 25].

However, the data in Fig. 1B could also be

interpreted to mean that A. aspalathoides and L.

strictum probably have other mechanisms for

increasing P availability in the rhizosphere for plant

uptake. Interestingly, excavation of these plants at

Koksrivier frequently revealed the presence of a large

mass of cluster roots on A. aspalathoides and L.

strictum, and few (or none) on C. genistoides and A.

caledonensis. This could imply that A. aspalathoides

and L. strictum obtain more P from other sources such

as cluster root formation than from secretion of

APases. Whatever the case, the lower APase activity

of A. aspalathoides and L. strictum and the higher

activity in C. genistoides and A. caledonensis (which

all co-occur naturally at the same site in the fynbos)

suggest adaptation to the low P conditions by the

former and sensitivity to low P by the latter [26, 27].

Although one study found no relationship between

organ APase activity and plant adaptation to low-P

soil [28], other studies have suggested that APase

activity in plant organs serve to mobilize and

translocate P from senescing plant parts to P sinks

[29], thus maintaining optimal P metabolism in

species growing in low P soils [30]. A bioassay of

APase activity in organs of the non-legume,

Leucadendron strictum and two Aspalathus species

from different locations in the Cape fynbos revealed

marked variation in enzyme functioning. Aspalathus

cordata sampled from the Silvermine area of the Cape

fynbos exhibited a significantly greater APase activity

in leaves and roots compared to that in stems and

nodules (Fig. 2A). Aspalathus aculeata, however,

showed decreased APase activity from leaves to roots

(Fig. 2B), in a manner similar to Leucadendron

strictum from the Kanetberg Mountains, which also

exhibited a decrease in enzyme activity from leaves

and stems to roots (Fig. 2C). Assuming APase activity

of organs is a measure of P pool size, P metabolism,


334

0

20

40

60

80

100

120

140

160

Leaves Stems Roots Nodules

Ac/

ph

osp

hat

ase

(μg

p-n

itro

ph

eno

l.g-1 F

wt.

h-1)

aa

bb

A. cordata

Silvermine: APase

A

0

100

200

300

400

500

600

Leaves Stems Roots

Ac /p

hosphata

se

(μg p

-nitro

phenol.g

-1 F

wt.h

-1)

a

a

b

A. aculeata

Malmesbury: APase

B

0

2

4

6

8

10

12

14

Leaves Stems Roots

Ac/

ph

osp

hat

ase

(μg

p-n

itro

ph

eno

l.g-1 F

wt.

h-1)

a

ab

c

Kanetberg: APase

L. strictum (non-legume)

C

Fig. 2 Acid phosphatase activity in organs of A) Aspalathus cordata; B) Aspalathus aculeata and C) Leucadendron strictum. Data are mean of five replicates for enzyme activity and error bars show one standard error. Columns with different letters are significantly different at P ≤ 0.05.

and potential P supply to sinks, then the stems of A.

cordata, as well as the roots of A. aculeata and L.

strictum exhibited the lowest P-supplying capacity.

More of these studies are needed to understanding P

acquisition in the low nutrient fynbos.

3. Root Exudates

Plant root exudates consist of simple

polysaccharides, amino acids, fatty acids, organic

acids, phenolic compounds, inorganic ions, enzymes

such as acid phosphatases and gaseous molecules

produced by root hairs [8, 10, 22, 31, 32]. There are

also high-molecular weight components such as

mucilage (polysaccharides), root border cells and

proteins produced by roots of some plants [33]. Root

exudation represents a significant carbon cost to the

plant [34], with the amount of photosynthate secreted

as root exudates varying with plant age and

physiological state, as well as soil type [32, 35, 36].

The concentration of organic acids such as lactate,

acetate, oxalate, succinate, fumarate, malate, citrate,

isocitrate and aconiate is reported to increase in the


335

root exudates of many plant species with P deficiency

[37-39]. Of the organic acids exuded in the

rhizosphere, citric, malic and oxalic acids are the most

efficient in solubilising unavailable soil P due to their

rapid complexation with metals such as Al, Ca, Fe and

trace metals, to form chemically-bound forms like

Al-P, Ca-P and Fe-P [37, 40, 41]. Citric acid is

reported to be the dominant organic acid exuded by

legume species [42] and alfalfa [10], and may well be

the major acid used by fynbos legumes to mobilize P.

Citrate secretion by P-deficient common bean was

found to be effective in mobilizing P from Al-P and

Fe-P compounds [43].

In contrast, graminaceous plant species secrete

phytosiderophores (amino acids) which form much

more stable complexes with Fe, Zn and Cu than Krebs

cycle intermediates [40]. The uptake of these

phytosiderophore-P complexes by plants results in a

desorption of the P ions via a ligand exchange reaction,

and eventually in an increased bioavailability of P in

the rhizosphere [10].

4. Cluster Roots

Cluster roots (also known as proteoid roots)

represent a major adaptation for P acquisition by

terrestrial plants belonging to the families Fabaceae,

Proteaceae, Casuarinaceae and Myricaceae [31, 44].

Cluster root formation is common in the Cape fynbos

of South Africa and in the southwestern part of

Western Australia, and plays an important role in

nutrient acquisition (especially P) in these

nutrient-poor environments [44]. Cluster roots are

hairy rootlets formed during the early rains of the wet

season, and are usually concentrated in the uppermost

10 cm of the soil [16].

Cluster roots formation is reported to be triggered

by P deficiency [9, 31]. However, the fact that

Aspalathus linearis easily forms cluster roots in the

acidic sands of the Cederberg Mountains, but not in

acid-washed sand without P, suggests that there might

be other unknown factors eliciting cluster root

formation in fynbos species. Once formed, cluster

roots can occupy 60%, or more, of the whole root

system [45], in the subsoil containing the highest

concentration of nutrients [46]. Cluster roots enhance

P acquisition, in that, they have over five times the

surface area of an equivalent non-cluster root dry mass

[16].

According to Vorster and Jooste [47], cluster roots

exhibit a more effective P absorption compared to

non-cluster roots. Kreb cycle intermediates released

by cluster roots are probably the most effective in

mobilizing P [11]. These organic acids are able to

release P from strongly bound forms by complexing

with Al or Fe of Al-P and Fe-P in acid soils, or the Ca

of Ca-P in alkaline soils [8, 45]. In so doing, P is

mobilized for uptake by plant roots. Cluster roots also

release phenolics, which may be involved in the

mobilization of P [8]. White lupin (Lupinus albus L.)

is reported to secrete large amounts of organic acids,

H+, isoflavonoids and acid phosphatases [31, 48] for

enhancing P uptake and assimilation.

5. Root Architecture and Function

Plant roots do not only function as organs for water

and nutrient uptake, but also serve to mobilize nutrient

elements in the rhizosphere. The spatial configuration

of plant roots in soil (otherwise called root

architecture) represent a nutritional response to

variations in the supply and distribution of nutrient

elements in a given environment [49, 50]. With

nutrient-poor soils, the fine and long root hairs of

plants are well distributed throughout the soil, thus

covering a large surface area which enables plants to

optimize water and nutrient uptake, especially during

periods of deficit. That way, localized depletion of

minerals, and/or uneven distribution in space and time,

are addressed by root architecture [51, 52]. With

legumes, P availability is greater in surface or

near-surface horizons than in the subsoil due to P

deposition by decaying leaves, roots and nodules, as

well as by biological, chemical and physical processes


336

in the topsoil. The levels of P are therefore generally

greater at the sub-surface and decreases with soil depth

[53]. Ancient soils such as those in the fynbos are

acidic with high concentrations of Al and Fe, which

form unavailable compounds with P (e.g., Al-P and

Fe-P), thus resulting in very low P levels. Plants in

such low-P environments such as the fynbos therefore

tend to have highly branched root architecture in order

to maximize P acquisition. Furthermore, the rate of

diffusion of P in soil is reported to be very low (10-12

to 10-15 m2 s-1) [54]. In low-P soils, this triggers native

plant species to expand their root surface area and thus

provide greater root-soil contact for an effective P

uptake [55].

While little is known about roots in the fynbos, in

general, an increased root length and decreased root

diameter tends to increase the amount of absorptive

surface area of the root relative to the volume of soil

[54, 56]. Whether this mechanism is used by fynbos

legumes (and non-legumes) to enhance P acquisition

remains to be determined. However, root hair density

of the model plant, Arabidospsis thaliana was found

to increase significantly in plants exposed to low-P

compared to high P, being five times greater in low P

than high P [57]. This suggests that in the low-P soils

of the Cape fynbos, native legumes are likely to have

greater root hair density in response to the low P

status of the ecosystem.

6. Mycorrhizal Symbiosis

The formation of fungal symbiosis with native plant

species is one way of enhancing P nutrition in low

nutrient environments [58, 59]. In this mutualistic

association, soil fungi penetrate plant roots and supply

the host plant with nutrients such as P in return for

fixed C. It is therefore not surprising that this fungal

symbiosis is mostly found under nutrient-limiting

conditions such as those of the Cape fynbos. About

80%-90% of higher plants are reportedly infected by

mycorrhizal fungi [60, 61]. In the fynbos, the species

with known mycorrhizal status include those of

Cyclopia [62-64], Aspalathus [63, 65], Leucadendron

[16, 63, 65] and Psoralea [66, 67]. More must be

waiting to be discovered.

There are six types of mycorrhizal symbioses, and

these include arbuscular, arbutoid, ecto, ericoid,

monotropoid, and orchid mycorrhizae [68, 69]. Of

these, arbuscular mycorrhizae and ectomycorrhizae

are the most common in natural ecosystems such as

the fynbos. Colonisation of plant roots by both

arbuscular and ectomycorrhizae are widespread in

nutrient-poor soils [33, 70], with ectomychorrhizae

being more abundant in N-limited ecosystems and

arbuscular mycorrhizae in drier low-P soils [71] of the

Cape fynbos. In these nutrient-poor environments, P

acquisition by mycorrhizal roots can be 3 to 5 times

higher than non-mycorrhizal roots [53, 72]. Over 80%

of terrestrial plant species enhance P uptake from

arbuscular mycorrhizal symbiosis with Zygomycete

fungi of the Order Glomales [73]. Once plant roots are

infected, the fungi proliferate their hyphae to provide

a much greater surface area for water and nutrient

absorption. This increase in surface area together with

the presence of high-affinity P uptake and transporters

in the external hyphae enhance P acquisition and

promote growth of mycorrhizal plants in P-deficient

soils [74, 75].

Both arbuscular mycorrhizae and ectomycorrhizae

produce mycelia that can extend beyond the nutrient

depletion zone of immobile nutrients in the

rhizosphere and form a complex architecture with an

efficient nutrient-collecting network [70]. These

mycelia thus enable mycorrhizal plants to explore a

larger volume of soil, thus decreasing the distance for

diffusion of absorbed phosphate ions. In so doing,

mycorrhizal hyphae can transport P over a distance

exceeding 40 cm to the fungus-root interface, where P

transfer to the host plant is effected [76]. Fungal

mycelia also have smaller diameters (2-4 μm), which

enable the hyphae to penetrate soil pores too small for

plant root hairs to enter [77]. That way, a relatively

larger soil volume is explored for delivering P per unit


337

surface area than uncolonized roots [78]. According to

Ref. [79], arbuscular mycorrhizal fungi belonging to

the genera Acaulospora and Glomus, are the most

dominant in P acquisition in the Cape fynbos. In

addition to mycelial activity, mycorrhizal fungi also

synthesise and release acid and alkaline phosphatase

enzymes that further promote increased P acquisition

by plants in nutrient-poor environments such as the

fynbos [80].

7. Economic Importance of Native Plant Species in the Cape Fynbos

Although no inventory currently exists on the

economic importance of the 9,030 plant species

occurring in the Cape fynbos, it is clear that its

uniqueness and biodiversity of flora is major attraction

for tourists. Additionally, species such as Aspalathus

linearis, which is the source of Rooibos tea, a

beverage with many health benefits, contributes about

R500 million annually to the South African economy.

Cyclopia is also a fynbos legume with 25 species that

are used to make Honeybush tea, another herbal

beverage that contributes about R12 million per year

to the South African economy [81, 82]. Other legume

and non-legume species such as Leucadendron, and

Psoralea are used in the horticultural industry as fresh

or dried cut flowers [83]. Many fynbos species,

including Sutherlandia, are used as medicinal plants

for treating various physiological disorders in rural

communities [84]. Despite the significant contribution

of fynbos flora to the South African economy, so little

is known about their adaptation to the low nutrients

and limiting soil moisture of their environment.

8. Future Research

To overcome constrains to P nutrition, which

decreases crop yields, efforts must be made to

understand how native plants in natural ecosystems

adapt to low-P conditions. Knowing these

mechanisms is likely to provide solutions for breeding

agricultural crops with tolerance of low P.

Furthermore, increasing our knowledge of P

acquisition through the activity of acid and alkaline

phosphatases in naturally low-P-tolerant native plant

species could provide a platform for designing crop

plants with tolerance of P deficiency, which is

prevalent in many agricultural soils of Africa.

Most low-P soils tend to have high Al and Fe or

high Ca. It is therefore important to understand the

biology of P mobilization in soils dominated by Al-P,

Fe-P or Ca-P, as this could provide an opportunity for

identifying crop species for biomes with similar soils.

Finally, improved P nutrition in agricultural crops

in Africa is a necessity for increased food security.

Therefore, any new knowledge added to our current

understanding of P nutrition using native legumes of

the Cape fynbos can only increase agricultural crop

yields.

References

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Effect of Ripening Stages on Basic Deep-Fat Frying

Qualities of Plantain Chips

Ogan Mba, Jamshid Rahimi and Michael Ngadi

Department of Bioresource Engineering, Macdonald Campus of McGill University, Lakeshore Road, Ste-Anne-de-Bellevue, Quebec

H9X 3V9 21111, Canada

Received: December 19, 2012 / Published: May 20, 2013. Abstract: Plantains (Musa paradisiaca L.) are a major food staple in West Africa and are cooked in various forms. The objective of this work was to evaluate the frying characteristics of plantains at different stages of ripening. The plantains used in the study were at the unripe stage through four different ripening stages. The samples were peeled and sliced into 2 mm thickness and blanched in hot water at 70 °C for 3 min. The slices were then deep fried in canola oil at 180 °C. The result showed that ripening stage significantly affected moisture loss and fat absorption profiles of the plantain chips. Fully ripened plantain absorbed up to 34% (db) oil during 4 min frying, much higher than unripe plantain. The oil uptake and moisture loss during frying of the plantain chip samples were modelled using 1st order kinetics. The kinetic parameters including rates of moisture loss and oil uptake varied according to the different stages of ripening. Ripening had a significant effect on the colour lightness (L) of the chips. Similarly, the redness (a), the yellowness (b) and textural characteristics were significantly affected by ripening stage.

Key words: Plantain ripening, plantain chips, deep-frying, oil uptake, moisture loss, kinetics.

1. Introduction

Plantain (Musa paradisiaca L.) is native to

Southeast Asia, Africa and South America. It is one of

the world’s most important food crops. At harvest, the

pulp and peel of plantain make up about 62% and

38%, respectively. The pulp of matured green unripe

fruit is rich in starch, dietary fiber, potassium,

magnesium, iron, phosphorus, calcium, vitamin C and

carotene. The iron content of plantain is 100% usable

for human consumption [1, 2]. Plantain is a

climacteric fruit. Its ripening process continues even

after harvesting from the parent plant due to evolution

of ethylene. Plantain ripening involves irreversible

series of physical, physiochemical, biochemical and

organoleptic changes in the fruit. During ripening, the

peel changes from green to yellow and finally to dark

brown. At the same time, pulp color changes from

Corresponding author: Michael Ngadi, Ph.D., research

fields: food and bioprocess engineering. E-mail: [email protected].

creamy white to yellow or yellow-orange. The change

in the colour of pulp/peel is due to the activity of

polyphenol oxidase which is abundant in plantain [3,

4]. Ripe plantain can be eaten fresh on account of its

content of vitamin C and other essential minerals.

Plantain ripening changes the osmotic balance

between pulp and peel. A significant increase in the

sugar content of the ripe pulp has been reported [5].

There are many different ways of processing and

consuming plantain in West Africa. Deep-frying is a

widespread method of plantain chips production.

Plantain chips are a popular snack food item in Africa

[6]. Plantains are cooked and dried by immersing in

hot edible oil (between 130 °C and 190 °C at

atmospheric pressure) for a few minutes. This results

in simultaneous heat and mass transfer. As heat is

transferred from the oil to the food, moisture is

evaporated and oil is absorbed. The frying process

results in unique flavor, color and texture attributes

which are the main drivers of consumer acceptability

D DAVID PUBLISHING

Effect of Ripening Stages on Basic Deep-Fat Frying Qualities of Plantain Chips

342

of the products [7]. Some models that describe the

characteristics of moisture loss and fat uptake, as well

as the relationship between moisture loss and fat

uptake in deep-fried food products have been

developed [8, 9]. The kinetics of the frying process,

including the oil diffusion and absorption has been

studied for a range of fried products including

potatoes and Musa species [10-12].

The combined effect of high rate of metabolism,

tropical humid conditions, inadequate postharvest

handling systems and poor marketing conditions have

resulted in postharvest losses of plantains. Plantain

becomes very perishable on ripening, resulting in

many fruits being discarded. Hence, the need to

process ripe plantain into other finished products such

as plantain chips. While there are many studies on

fried products and oil deterioration, little attention has

been paid to the effect of the variability of the raw

material on its frying behaviour and the

physicochemical properties of the final product [12].

Therefore, the objective of this work was to evaluate

the frying characteristics of stored plantains at

different stages of ripening. The result will provide

useful information to the millions throughout the

world of whom the plantain fruit is critical to their

nutritional and economic well-being.

2. Materials and Methods

2.1 Preparation of Samples

Mature Columbian Plantain fingers at unripe green

stage and Canola oil, were purchased from a local

grocery store in Montreal, Canada. The plantains were

stored and allowed to ripen slowly under ambient

conditions of 25 °C and 80%-85% RH until they

reached the desired different stages of ripeness. The

guide was the banana ripening chart [13]. The samples

and the stages of ripening used in this work are

described in Table 1. On each frying day, the plantain

sample was washed and manually peeled. The pulp

was sliced to a thickness of 2 ± 0.1 mm using Rival

Precision Slicer model C1105. The diagonal slices

Table 1 Description of plantain ripening stages.

Ripening stage

Storage day

Peel color index number

Peel color

A 1 1 Green

B 3 3 Green-yellow

C 7 6 All yellow

D 8-9 7 Yellow flecked with brown

were blanched at 70 °C for 3 min in a water bath. Paper

towel was used to dry the slices and allowed to

completely dry at room temperature.

2.2 Deep-Frying Process

Four liters of Canola oil was preheated to 180 ±

2 °C in a temperature controlled bench top fryer

(model no: D24527DZ, Délonghi Inc. USA). The

blanched plantain slices was divided into 5 different

portions and fried for 1, 2, 3 and 4 min. The fifth

portion was not fried (0 min) which served as control.

Ten slices per sampling were put into sample holders

that ensured complete immersion in the hot oil. After

each frying time, the chips were well drained of

adhering surface oil by shaking and blotted with paper

towel. The chips were allowed to cool at room

temperature. All the experiments were carried out in

triplicates. Polyethylene self-sealing storage bags were

used to pack the chip samples before the analyses that

followed.

2.3 Moisture and Fat Analysis

Fried plantain chips were weighed, and then dried

at 105 °C to constant weight in a forced air convention

oven (Isotemp 700, Fischer Scientific, Pittsburgh,

USA). Moisture content was determined

gravimetrically [14]. AOAC [15] standard procedure

and Soxhlet method were used for fat extraction and

analysis. The dried samples were ground using

Sumeet electric grinder. Approximately 5.0 g of each

ground sample was used for fat extraction. The fat was

extracted using petroleum ether in a Soxhlet extractor

(SER 148, Velp Scientifica, Usmate, Italy). The fat

content was obtained on dry weight bases for each

plantain chip sample as the ratio of mass of oil


343

extracted to mass of dried samples.

2.4 Colour Measurements

The colour parameters (L, a and b) of the plantain

chips samples were measured by reflectance using a

Konica Minolta colorimeter (model no: CR-300,

Konica Minolta Sensing Inc. Osaka, Japan). The

instrument was standardized each time before reading

measurements using a white ceramic plate. Samples

were scanned at 5 different locations to determine the

L, a and b values as the average of the five

measurements.

2.5 Texture Evaluation

Textural properties were evaluated instrumentally at

room temperature by a compression/puncture test

using an Instron Universal Testing Machine (Model

4502, Canton MA, USA). Force vs displacement (F/D)

curves were generated with the puncture test at

different ripening stages and frying times by mounting

the sample on a flat rigid support where the distance

between the support and a cylindrical punch was 15

mm [16]. The punch diameter and the crosshead speed

were 5 mm min-1 and 25 mm min-1, respectively. The

textural parameters Hardness (equals Maximum

Force/Maximum deformation) and Crispiness (equals

slope of the linear section of the curve) [16, 17] were

obtained from the F/D curves. Each measurement was

repeated five times and their mean values were used

as indicators of the parameters.

2.6 Statistical Analysis/Kinetics Model

The SAS system software (Version 9.2, SAS

Institute, Inc., 1999, Cary, NC, USA) was used for

statistical analysis. Duncan’s multiple range test

(DMRT) was used to estimate significant differences

among means at a 5% probability level. All analyses

were conducted in triplicate. Similarly, a first order

kinetics was used to describe oil uptake and moisture

loss during deep-fat frying [8]. Recognizing that there

is a saturation oil content beyond which minimal oil is

absorbed into the product during frying, the following

rate equation was used. d

- ( )ou e

ok O O

dt (1)

where, O is oil uptake in the sample, Oe is the

equilibrium oil content, Kou is the oil uptake rate

constant and t is the frying time. Integrating, the

equation can be adjusted and expressed in the form of

oil uptake as follows:

(1 )ouk tu usO O e (2)

where, Ou is the fat uptake, (i.e., the difference

between the oil content at a given time and the initial

oil content), Ous is saturation oil content (i.e., the

difference between equilibrium oil content and the

initial oil content).

Since frying was done at high temperature (above

boiling point of water), equilibrium moisture content

was assumed to be zero (i.e., moisture was completely

evaporated). Although in reality equilibrium does not

exist in deep fat frying, the system behaves as if there

is equilibrium. This is due to the physical changes in

the product during frying which restrict moisture and

oil transfers. Hence the model described by Debnath

et al. [18] was used to describe the kinetics of

moisture loss ratio: * 1 mlkM e t (3)

where, *M is the moisture ratio (i.e., the ratio of moisture at a given time and initial moisture) and Kml

is the moisture loss rate constant.

The kinetic parameters were obtained using

non-linear regression in MATLAB (Version 7.6.0.324

R2008a, The Mathworks, Inc., Natick, MA, USA).

3. Results and Discussion

3.1 Fat Uptake/Moisture Loss

The overall influence of plantain ripening on the fat

uptake and moisture content of the plantain chips is

presented in Figs. 1 and 2. The initial moisture content

of mature green plantain was 67.126% ± 0.53% which

decreased gradually to a significant 62.274% ± 0.62%

by the yellow-brown stage of ripeness. The initial

moisture content of the green plantain sample is in


344

Fig. 1 Fat uptake trend of unripe and ripe plantain chips during deep-fat frying.

◊ = experimental result plot for unripe green plantain; □ = experimental result plot for plantain at green-yellow stage of ripening; ∆ = experimental result plot for plantain at all yellow stage of ripening; × = experimental result plot for plantain at yellow/fleck of brown stage of ripening; Continuous line = Predicted values.

Fig. 2 Moisture loss trend of unripe and ripe plantain chips during deep-fat frying.

◊ = experimental result plot for unripe green plantain; □ = experimental result plot for plantain at green-yellow stage of ripening; ∆ = experimental result plot for plantain at all yellow stage of ripening; × = experimental result plot for plantain at yellow/fleck of brown stage of ripening; Continuous line = Predicted values.


345

line with the values reported by Agunbiade et al. [19]

and Avallone et al. [20]. The decrease in moisture

content of the un-fried samples could be due to the

reported increase of sugar during ripening from nearly

zero at green stage to around 30% in overripe plantain

[21]. It was observed that the moisture content of the

fried plantain chips continued to decrease as ripening

progressed. There was a significant difference in the

mean moisture content of each of the fried chips at

different ripening stages. As shown in Fig. 1, ripening

increases the fat uptake of the plantain chips. There

was a significant increase in fat absorption from the

initial 0.3% (db) in mature green sample that was not

fried reaching up to 34% (db) oil in fully ripened

plantain chips after 4 min frying. The increased oil

absorption during deep frying of ripe plantains may be

attributed to changes in porosity and molecular size

redistribution as sugar content of plantains increases.

Moreira et al. [22] had shown that porosity and

particle size of masa flour used to produce tortilla

chips had an effect on the oil uptake during the deep

fat frying process.

The average moisture content of the unripe plantain

used in this work was 65.0% and was significantly

higher than the mean moisture content of 8.01% found

in the chips after 4 min of frying. The moisture

changes during frying showed the typical extensive

decrease with increasing frying time [9, 23]. The trend

showed that frying at 1 min led to a rapid moisture

decrease (33.78%). This means that the rate of

moisture loss of the fried chips increased as ripening

progressed and the fruit became softer (Fig. 2). The

moisture loss rate was similar as frying time

progressed. Generally, the results agree with literature

in terms of the moisture content values, oil content

values and the effect of temperature on heat and mass

transfers. The parameters of the first order kinetic

model of fat uptake and moisture loss for different

ripening stages of the fried plantain chips is presented

in Table 2.

It has been reported that there is a rapid linear

Table 2 Parameters of first-order kinetic model of fat uptake and moisture loss for different ripening stages of fried plantain chips.

Ripening stage Ous (% db) Kou (min-1) Kml (min-1)

A 6.611 ± 0.097 0.652 ± 0.493 0.745 ± 0.041

B 10.46 ± 0.388 2.361 ± 0.491 0.773 ± 0.024

C 15.50 ± 0.16 2.015 ± 1.388 0.819 ± 0.028

D 32.93 ± 0.092 1.021 ± 3.357 0.794 ± 0.027

increase in temperature during sensible heating of

chips. The crisp was heated from its initial

temperature to the boiling point of water. As the oil

content plateaus, the moisture content decreased. A

threshold moisture value was achieved when the

moisture evaporation rate became negligible and the

chips were sensibly heated to the frying oil

temperature [24, 25]. Diaz et al. [12] reported that oil

uptake is determined by the variety of plantain used,

irrespective of processing time and temperature. Oil

uptake in the case of plantain does not appear to be

correlated to the raw material water content as it was

previously described for potato chips [26, 27] and

cassava chips [28]. Nevertheless, a positive correlation

was observed in this work between the amount of oil

uptake and the weight of moisture removed. Oil

uptake was influenced by stage of ripening and frying

time. This result might be explained by an indirect

effect associated with the rheological behaviour of

ripe plantain, the firmness of which decreased as

ripening progressed. Previous studies have also shown

that oil uptake was related to the adhesion of oil to the

chip surface after removal from the hot oil [22, 29].

3.2 Colour/Texture Properties

The physical characteristics of the plantain chips,

namely colour is shown in Table 3, while texture

parameters are shown in Figs. 3a and 3b. In Table 3,

the lightness (L), redness (a), yellowness (b), and

metric chroma (C*) values are shown. It was observed

that at all the ripening stages evaluated the chips had

bright colours (L > 50). However, the lightness of the

fried chips significantly decreased as ripening

progressed. The mature “green” samples (A) had a


346

Table 3 Colour characteristics of the plantain chips.

Ripening Stages L a b C*

A 68.01 ± 1.49a 4.57 ± 1.08c 42.13 ± 2.14b 42.74 ± 1.03b

B 65.63 ± 3.46b 6.32 ± 1.73b 42.57 ± 3.08b 43.40 ± 0.90b

C 62.57 ± 4.09c 8.60 ± 1.83a 45.79 ± 3.66a 46.92 ± 0.68a

D 60.99 ± 3.26d 8.78 ± 1.15a 44.78 ± 2.87a 46.09 ± 0.49a

Each value represents the mean ± standard deviation; Means within each column with different letters are significantly different

(P > 0.05). C* = Metric Chroma =2 2a b .

0

2

4

6

8

10

12

14

0 1 2 3 4 5

H*

Frying Time (mins.)

Normalized Hardness

A

B

C

D

0

10

20

30

40

50

60

70

80

0 1 2 3 4 5

CR*

Frying Time (mins)

Normalized Crispiness

A

B

C

D

Fig. 3 Effect of ripening on (A) hardness and (B) crispiness of plantain chips.

H* = Ratio of hardness at any time and hardness at time zero; CR* = Ratio of crispness at any time and crispness at time zero; ◊ = experimental result plot for unripe green plantain; □ = experimental result plot for plantain at green-yellow stage of ripening; ∆ = experimental result plot for plantain at all yellow stage of ripening; × = experimental result plot for plantain at yellow/ fleck of brown stage of ripening.

mean L value of 68.01 ± 1.49 while the “yellow/trace

of brown” samples (D) had a mean score 60.99 ± 3.26.

The redness of the chips samples were significantly

increasing as ripening progressed up to the fully ripe

“yellow” stage (sample C). There was no significant

difference in the redness of chips produced from

ripening stages C and D which had redness mean

score of 8.60 ± 1.83 and 8.78 ± 1.15, respectively. In

general, an increase in redness is negative for colour

of fried products [9]. The redness of the plantain chips

was within the acceptable range (a < 10). The more

desired color of fried chips is the yellowness. The data

also showed that this parameter was significantly

affected by ripening. The result further showed that

yellowness of the chips from samples A and B

(“green” and onset of ripening) were similar but

significantly different from (P > 0.05) samples C and

D (45.79 ± 3.66 and 44.78 ± 2.87). The mean metric

chroma values confirmed this trend in colour change

and indicated a tendency toward browning with

increased frying time. The colour changes also

indicated more Maillard reaction with frying time

which utilized the abundant reducing sugars in ripened

plantain [30]. The increase in colour intensity is in

agreement with the studies that related the colour of

French fries and potato chips [9] and plantains [6] to

their reducing sugar content.

The hardness and crispiness of the plantain chips

were significantly affected by ripening (P > 0.05).

Texture of plantain chips is an important sensory

parameter that determines acceptability and shelf

stability. The data showed a progressive decrease in

the mean values of hardness, 16.99 ± 2.53 N mm-1

(sample A) to 4.90 ± 0.15 N mm-1 (sample D). As

shown in Fig. 3a, hardness increased at all ripening

stages as frying time increased due to crust

A B


347

development [8]. The same trend was observed in the

crispiness values which came down from 20.13 ± 4.28

(sample A) to 2.08 ± 0.09 (sample D). Fig. 3b showed

that mature green plantain chips had a much higher

crispness than the ripe plantains. There was no

significant difference in the crispness of chips

produced from ripening stages C and D. This could be

due to increased oiliness as ripened plantain chip

samples had much higher oil uptake. The observed

textural changes is in agreement with published data

which shows that during fruit ripening, the fruit

changes from hard to pulpy soft due to breakdown of

cell wall structure and polysaccharides and moisture

loss due to respiration [3]. The degradation of pectin

from cell wall and middle lamella seems to be

responsible for tissue softening of plantain. Kajuna et

al. [31] also pointed out a decrease of the modulus of

elasticity over the ripening period of plantains as the

increase in osmotic pressure led to a reduction in

turgor pressure in the pulp tissue. This is attributed to

the hydrolysis of starch to sugar.

4. Conclusions

This work evaluated the influence of ripening on

the fat uptake and water content of stored plantain.

The result showed that ripening had a major effect on

fat uptake. The fat content rose from the initial 0.36%

to 34% after 4 min of frying fully ripened samples.

The moisture loss positively correlated with the fat

uptake. The L, a and b color changes of plantain chips

were affected by ripening especially from the fully

ripe stage. Ripening also significantly affected the

textural parameters evaluated. This work established a

relationship between plantain ripening and behaviour

during frying. This enables utilization of the ripened

plantain for chips production rather than allow ripened

fruits to waste.

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[3] V. Prasanna, T.N. Prabha, R.N. Tharanathan, Fruit ripening phenomena, an overview, Critical Reviews in Food Science and Nutrition 47 (2007) 1-19.

[4] J.O. Offem, O.O. Thomas, Chemical changes in relation to mode and degree of maturation of plantain (Musa paradisiaca) and banana (Musa sapientum) fruits, Food Research Inter. 26 (3) (1993) 187-13.

[5] J. Marriot, M. Robinson, S.K. Karikari, Starch and sugar transformation during the ripening of plantains and bananas, J. Sci. Food Agric. 32 (1981) 1021-1026.

[6] C.A. Onyejegbu, A.O. Olorunda, Effects of raw materials, processing conditions and packaging on the quality of plantain chips, J. Sci. Food Agric. 68 (1995) 279-283.

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[8] P.C. Moyano, F. Pedreschi, Kinetics of oil uptake during frying of potato slices: Effect of pre-treatments, LWT-Food Science and Technology 39 (2006) 285-291.

[9] M.K. Krokida, V. Oreopoulou, Z.B. Maroulis, D. Marinos-Kouris, Effect of pre-drying on quality of french fries, J. Food Engineering 49 (2001) 347-354.

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[11] W. Ammawath, Y.B. Che-Man, S. Yusof, R.A. Rahman, Effect of variety and stage of fruit ripeness on the physicochemical and sensory characteristics of deep-fried banana chips, J. Sci. Food Agric. 81 (2001) 1166-1171.

[12] A. Diaz, G. Trystram, O. Vitrac, D. Dufour, A.L. Raoult-Wack, Kinetics of moisture loss and fat absorption during frying of different varieties of plantain, J. Sci. Food Agric. 79 (1999) 291-299.

[13] J. Conie, M. Young, Banana and Plantain Ripening Manual: A Guide for Small Farmers and Businesses, Publication of the Banana Board of Jamaica, 2003, pp. 15-18.

[14] AACC, Moisture Content, in Approved methods of the American Association of Chemists, St Paul, MN, 1986.

[15] AOAC, Official Methods of Analysis, Association of Official Analytical Chemists, Washington, DC, 1990.

[16] F. Pedreschi, P. Moyano, Oil uptake and texture development in fried potato slices, J. Food Engineering 70 (2005) 557-563.

[17] F. Nourian, H.S. Ramaswamy, Kinetics of quality change during cooking and frying of potatoes: Part 1-Texture, J. Food Process Engineering 26 (2003) 377-394.


348

[18] S. Debnath, K.K. Bhat, N.K. Rastogi, Effect of pre-drying on kinetics of moisture loss and oil uptake during deep fat frying of chickpea flour based snack food, LWT-Food Science and Technology 36 (2003) 91-98.

[19] S.O. Agunbiade, J.O. Olanlokun, O.A. Olaofe, Quality of chips produced from rehydrated dehydrated plantain and banana, Pakistan Journal of Nutrition 5 (5) (2006) 471-473.

[20] S. Avallone, J.A. Rojas-Gonzalez, G. Trystram, P. Bohuon, Thermal Sensitivity of some plantain micronutrients during deep-fat frying, J. of Food Science 74 (5) (2009) 339-347.

[21] D. Mohapatra, S. Mishra, V. Meda, Plantains and their post-harvest uses: An overview, Stewart Postharvest Review 5 (4) (2009) 1-11.

[22] R. Moreira, X. Sun, Y. Chen, Factors effecting oil uptake in tortilla chips in deep-fat frying, J. Food Engineering 31 (1997) 485-498.

[23] L. Kassama, M. Ngadi, Pore development and moisture transfer in chicken meat during deep-fat frying, J. Drying Technology 23 (2005) 907-923.

[24] C.R. Southern, X.D. Chen, M.M. Farid, B. Howard, L. Eyres, Determining internal oil uptake and water content of fried thin potato crisps, Trans. I. Chem. E. 78 (2000) 119-125.

[25] M.M. Farid, X.D. Chen, The analysis of heat and mass transfer during frying of a food using a moving boundary solution procedure, Heat and Mass Transfer 34 (1998) 69-77.

[26] J.H. Makinson, H. Greenfield, M.L. Wong, R.B.H. Wills, Fat uptake during fat frying of coated and uncoated foods, J. Food Composition Anal. 1 (1987) 93-101.

[27] M. Gamble, P. Rice, Effect of initial tuber solids content on final oil content of potato chips, Lebensm-Wiss u-Technol 21 (1988) 62-65.

[28] C.K.V. Nair, C.C. Seow, G.A. Sulebele, Effects of frying Parameters on physical changes of tapioca chips during deep-fat frying, Int., J. Food Sci. Technol. 31 (1996) 249-256.

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[30] G.I. Onwuka, N.D. Onwuka, The effects of ripening on the functional properties of plantain and plantain based cake, International Journal of Food Properties 8 (2) (2005) 1021-1026.

[31] S. Kajuna, W.K. Bilanski, G.S. Mittal, Textural changes in banana and plantain pulp during ripening, Journal of Science Food and Agriculture 75 (1998) 244-250.


Production and Nutritive Value of Shrub Legumes in

West Timor, East Nusa Tenggara Province Indonesia

Sophia Ratnawaty1, 2, Hartutik3, Soebarinoto3 and Siti Chuzaemi3

1. Postgraduate Program, Faculty of Animal Husbandry, University of Brawijaya, Malang, East Java 65145, Indonesia

2. Assesment Institute of Agriculture Technology East Nusa Tenggara, Kupang, East Nusa Tenggara Province 85362, Indonesia

3. Department of Animal Nutrition, Faculty of Animal Husbandry, University of Brawijaya, Malang, East Java 65145, Indonesia

Received: March 4, 2013 / Published: May 20, 2013. Abstract: This study aimed to identify the potential of shrub legumes as protein feed in West Timor. Eight shrub legumes, i.e., Clitoria ternatea Q5455 (CT Q5455), Clitoria ternatea millgara (CT millgara), Centrosema pascuorum bundey (CP bundey), Centrosema pascuorum molle (CP molle), Macroptilium bracteatum juanita (MB Juanita), Macroptilium bracteatum cadaarga (MB cadaarga), Dolichos lablab (DL) and Stylossanthes seabrana (SS) were evaluated for their yield and nutritive value in Randomized Block Design. Each legume was cultivated in four plots of different soil fertility as block (5 × 5 m2 per plot). Phosphorus (P) fertilizer was applied once just before planting at level of 50 kg ha-1. Watering was done three times per week using sprinkler. The legumes were harvested at 120 days after planting (dap) in three sub-plots of 1 × 1 m2 size for their yield measurement. Samples of each legume was taken for Dry Matter (DM), Organic Matter (OM), Crude Protein (CP), cellulose, hemi-cellulose and lignin content and in vitro DM, OM and CP digestibility test. Data were statistically analyzed using Genstat release 12.2. The results showed that the legumes showed significantly different (P < 0.01) in biomass yield. The highest biomass yield was shown by SS (6,739 kg DM ha-1; 6,120 kg OM ha-1 and 1,224 kg CP ha-1) and the lowest was by DL (1,294 kg DM ha-1; 1,157 kg OM ha-1 and 242 kg CP ha-1). In general, there was no significant difference (P > 0.05) of DM digestibility of the eight legumes, except for DL which showed significantly highest (P < 0.01) DM and OM digestibility compared to the other. Key words: Biomass, digestibility, feed, shrub legumes, yield.

1. Introduction

East Nusa Tenggara (NTT) is one of important beef

cattle centre in Indonesia, especially in respect of its

land area for feed resources. Land size of NTT is

2,962,571 ha, 60% of this area is natural savanna,

which is the largest area of savanna in Indonesia.

Population of beef cattle in this area is 720,000 heads

with stocking rate of 4-5 cattle km-2 [1]. Forage

production of the savanna in the rainy season is 1.7

ton Dry Matter (DM) (ha year)-1; which is three times

higher than the production in the dry season (0.54 t

DM (ha year)-1). The carrying capacity of beef cattle is

1.4-2.8 AU (ha year)-1 [2]. The carrying capacity is

still in the range of those reported by McIlroy [3]

Corresponding author: Sophia Ratnawaty, M.Sc., research

field: animal nutrition. E-mail: [email protected].

which is 0.2-7 AU ha-1.

Classical problems of beef cattle production in East

Nusa Tenggara in particular in West Timor district is

lack of feed during the dry season. During this season,

feeds are available in low quantity and quality. These

conditions have caused cattle to loss of weight and

high mortality of calves, especially less than one year

old calves. During dry season, the loss weight reached

up to 20%-25% of the cattle weight [4].

To overcome the problems, it is urgent to improve

the condition of the natural savanna. The improvement

can be done by introduction or planting annual shrub

legumes in the savanna. Legumes have higher

potential advantages in this case compared to natural

grass. Legumes are able to return soil fertility back by

catching natural air nitrogen and deposit it into the soil.

DAVID PUBLISHING

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Production and Nutritive Value of Shrub Legumes in West Timor, East Nusa Tenggara, Province, Indonesia

350

Legumes with their steep roots have higher chance to

get deeper soil water and other nutrients for their

growth and maintain soil humidity. With those

capacities, legumes have higher potential to survive

and produce forage even during the dry season than

grasses. Legumes contain higher crude protein which

can be used as feed supplement during the harsh

season. The characteristic advantage of legumes was

summarized by Gutteridge and Shelton [5]. Bamualim

et al. [4] reported that protein content of natural grass

in June-November declined to below 7%. Rubianty et

al. [6] reported that crude protein content of Clitoria

ternatea and Centrosema pascuorum hay during the

dry season was 21.32% and 19.56%, respectively.

Therefore, in this research, it was to evaluate the

potential of some variety of shrub legumes in East

Nusa Tenggara in terms of their production and

nutritive value.


This study was conducted for 12 months from April

2011 to March 2012 in Field Laboratory of

Assessment Institute of Agriculture Technology

(AIAT) Kupang district East Nusa Tenggara province.

Eight shrub legumes were used and evaluated in

this study, i.e., Clitoria ternatea Q5455 (CT Q5455),

Clitoria ternatea Millgara (CT millgara), Centrosema

pascuorum Bundey (CP bundey), Centrosema

pascuorum Molle (CP molle), Macroptilium

bracteatum Juanita (MB Juanita), Macroptilium

bracteatum Cadaarga (MB cadaarga), Dolichos

lablab (DL) and Stylossanthes seabrana (SS).

The research was done in randomized block design

of eight treatments and four blocks as replication. The

treatments were the eight shrub legumes and the

blocks were based on the soil fertility. The legumes

were planted as monoculture in plots for each legume

and block. Each plot size was 5 × 5 m2.

The legumes were planted using seeds in rows of

holes in each plot, at distance of 50 cm between rows

and 25 cm between holes. Five seeds were planted in

each hole.

Phosphorus fertilizer (P) at level of 50 kg ha-1 was

applied once just before planting and watering using

sprinkler was regularly applied three times per week.

Data collection was done on agronomy parameters,

including seedling percentage, plant height and

biomass yield. Seedling percentage was observed

twice within seven days after planting. Plant height

was measured above the ground until the tip of the

longest leaf on day 14th, 28th, 42nd and 56th after

planting. The measurement was done in 1 × 1 m2

sub-plot of each plot. Biomass yield measurement was

done by harvesting legumes in three 1 × 1 m2

sub-plots on each plot at 120 days after planting.

Sample of biomass from each plot was taken for

analysis of DM, Organic Matter (OM), Crude Protein

(CP), content [7]; Neutral Detergent Fiber (NDF),

Acid Detergent Fiber (ADF), cellulose, hemi-cellulose

and lignin content [8]; and in vitro DM, OM and CP

digestibility test [9]. Data were statistically analyzed

using Genstat release 12.2 [10].


3.1 Growth Parameters and Biomass Yield

Growth parameters and biomass yield of the eight

legumes evaluated in this research are presented in

Table 1.

Data on Table 1 showed that among legumes

showed significantly different of growth parameters

(P < 0.01). All shrub legumes evaluated in this

research showed high seedling percentage, except for

CP bundey. Low seedling percentage of CP bundey

was caused by poor seed quality used in supporting

seedling and also related with type of soil, in which

CP bundey would need medium until high soil fertility.

Previous study done by Ratnawaty and Fernandez at

farmers’ field [11] showed different results from this

study. It was reported that average plant height of

Clitoria ternatea was 12.3 cm; Centrosema

pascuorum (9.93 cm) and Dolichos lablab (4.6 cm) at

the age of 60 days after planting. This was due to

shrub legumes grown in farmers’ fields were not given


351

Table 1 Growth parameters and biomass yield of eight legumes harvested on 120 days after planting (Average ± SD).

Shrub Legumes Seedling percentage (%)

Plant height (cm)Biomass yield on 120 days after planting

(kg DM ha-1) (kg OM ha-1) (kg CP ha-1)

CT Q5455 67.5b ± 8.5 22.9b ± 7.9 5,691d ± 294.0 4,892bc ± 437.1 1,029d ± 68.6

CP bundey 47.5a ± 10.3 13.6ab ± 4.4 3,924bc ± 601.3 3,690b ± 732.8 713bc ± 141.0

DL 90.0c ± 7.1 38.8c ± 13.7 1,294a ± 148.0 1,157a ± 180.1 242a ± 35.8

MB juanita 97.5c ± 2.5 12.7ab ± 4.4 2,528ab ± 286.1 2,277a ± 328.7 451ab ± 65.9

MB cadaarga 100.0c ± 0 16.04ab ± 6.6 1,477a ± 262.2 1,343a ± 309.4 237a ± 62.6

CT millgara 95.0c ± 5 24.3b ± 8.9 5,328cd ± 127.9 4,880bc ± 167.3 972cd ± 30.1

CP molle 82.5bc ± 6.3 10.2a ± 2.9 2,273a ± 308.1 2,116a ± 371.5 408a ± 71.4

SS 70.0c ± 7.1 5.4a ± 2.3 6,739d ± 774.0 6,120c ± 902.6 1,224d ± 181.6 a-dValues in the same column with different superscript are significantly different (P < 0.01).

watering and fertilizer as in this study.

Reksohadiprojo [12] suggested that legumes growth

was highly dependent on seed quality and soil type

where the plants grow. Centrosema was known quite

slow related with resistance and adaptation toward

environmental condition for period of 8-9 months [13].

Centrosema growth would be stunted in environment

temperature of 18-24 °C [14]. Low land is more

appropriate for Centrosema growth [15].

In addition, among legumes species showed

significantly different of biomass yield on 120 days

after planting (P < 0.01). The highest biomass yield

was shown by SS, CT Q5455 and CT Millgara, while

the lowest one was shown by DL. This was as also

reported in several previous research that forage

production varied between shrub legumes species

[14-16]. This was happening due to physiological

difference such as leaf wide index, relationship of

leaf-water, carbohydrates reservation, and water

utilization efficiency [17]. Morphological difference

between shrub legumes species, such as bud residue

after trimming, plant height, roots length and surface

width, bud length and diameter that re-grow [14, 18].

Data on Table 1 showed that there was no likely

consistent relationship between seedling percentage,

plant height or length and biomass yield. Biomass

yield was more likely affected by morphological

differences rather than by plant growth parameters. SS

with moderate seedling percentage but the lowest

plant height showed the highest biomass yield,

however, DL with the highest seedling percentage and

plant height showed the lowest biomass yield.

Biomass yields in this research were higher than the

results of Ratnawaty et al. [19] who reported that

biomass yield of shrub legumes planted as

monoculture in Tobu village, Timor Island was in the

range of 1.1-2.2 t DM ha-1. This might be caused by

better forage management applied in this research

mainly fertilizer and regular watering application.

Budisantoso et al. [20] reported that biomass

production of Centrosema pascuorum was 3.3 t DM

ha-1 and Clitoria ternatea was 1.8 t DM ha-1, and

biomass production of Centrosema pascuorum was

the highest after re-growth with 45 days cutting

interval, followed by Clitoria ternatea, Desmanthus

pernambucanus, Macroptilium bracteatum and

Aeschynomene americana.

Lefi et al. [21] found difference in leaf production

and aging between M. areborea and M. citrina, while

Pang et al. [22] reported difference in phosphorus

utilization efficiency, root surface wide and root

length between perennial legumes species including B.

bituminosa. Cox et al. [23] reported forage production

of Lablab, MB juanita and cadaarga also CT millgara

planted in two seasons was 2.1, 2.0 and 1.0 t ha-1 in

first year, respectively, and the production decreased

as much as 0.2, 1.1 and 0.7 t ha-1 in second year.

Whitbread et al. [24] reported biomass production of

CT millgara increased from 1,277 kg DM ha-1 in the

first year become 4,047 kg DM ha-1 in the third year,


352

while MB juanita was relatively stable with 3,382 kg

DM ha-1 in the first year and 4,940 kg DM ha-1 in the

third year.

Result of this research was different from research

done by Ayiyi et al. [25] that biomass production of

Lablab purpureus planted in Limpopo, South Africa

was around 1,000-5,000 kg ha-1 on 87 days after

planting. Result of Clem and Cook [26] measured

forage production of several kind of shrub legumes for

three years (2000-2002) obtained that forage

production of Lablab purpureous decreased from

3,863 kg ha-1 in 2000 to 59 kg ha-1 in 2001. Same case

happened on MB juanita where forage production

tended to decrease for the three consecutive years

cuttings from 2.499, 88 to 687 kg ha-1, however,

Stylosanthes scabra showed forage production to

increase from 2.045 kg ha-1 to 5.529 kg ha-1.

3.2 Nutritive Values

Nutrients content of the eight legumes evaluated in

this research is presented in Table 2.

Data in Table 2 showed that crude protein and other

nutrients content of the eight shrub legumes were

relatively similar. Crude protein content ranged from

17.85% to 18.73%. This CP content was relatively

high, therefore the legumes were potential as protein

feed supplement to substitute for concentrate feed.

Energy content of MB cadaarga, MB juanita and CP

molle is lower compared to CT Q5455, CT millgara,

CP bundey and SS. This is consistent with ash content

in this four shrub legumes. NDF is forage component

which is the biggest part of plant’s wall. This

compound consists of cellulose, hemi-cellulose, lignin,

silica and several fibroses protein [27], which is

mainly utilized by rumen microbes to produce energy

and for its life needs.

Ginting and Tarigan [28] reported that Centrosema

pubescens had some advantages compared to Arachis

pintoi based on its chemical composition (crude

protein, NDF and ADF). Other studies which also

reported similar result was done by Khamseekhiew et

al. [29], Nasrullah et al. [30] and Evitayani et al. [31],

although both legumes were planted in different

condition. Protein content of feed was reported had

positive and significant relationship with dry matter

and organic matter consumption [32, 33], but it is

negatively related with NDF content through physical

effect or filling effect [34, 35].

Digestibility reflects the amount of feed consumed,

digested, absorbed and utilized by animals’ body to

supply nutrient requirement. This is an early

indication of nutrient availability for the animal, after

Table 2 Nutrients content of eight legumes harvested on 120 days after planting.

Nutrient (%) Shrub legumes

CT Q5455

CP bundey

DL MB juanita

MB cadaarga

CT millgara

CP molle SS

DM (%) 91.13 91.47 77.88 90.44 91.51 89.27 92.42 93.14

Ash (% DM) 6.16 9.20 7.84 9.38 10.40 6.87 14.74 9.07

CP (% DM) 18.16 18.24 18.73 18.49 17.85 17.95 18.08 18.17

CF (% DM) 38.03 38.34 32.49 41.27 41.06 37.24 34.51 38.23

EE (% DM) 2.43 2.02 2.66 2.83 2.62 2.77 2.05 2.36

NDF (% DM) 59.22 61.23 61.88 61.86 60.29 55.96 56.68 58.56

ADF (% DM) 42.63 41.22 42.08 44.67 45.50 39.87 40.04 43.80

Cell. (% NDF) 31.17 26.94 30.53 30.55 29.97 28.19 23.73 31.97

Hemi-cell. (% NDF) 16.59 20.10 19.80 17.20 14.79 16.09 16.64 14.76

Silica (% NDF) 0.09 0.92 1.10 0.91 1.30 0.38 4.35 0.52

Lignin (% NDF) 11.37 13.36 10.46 13.21 14.23 11.30 11.95 11.32

GE (kkal kg-1) 3,493 3,725 3,548 3,188 3,099 3,895 3,151 3,361

Laboratory Analysis, Laboratory of Animal Feed and Nutrition, Faculty of Animal Husbandry, University of Brawijaya, Malang, Indonesia, 2011.


353

Table 3 In vitro DM, OM and CP digestibility of shrub legumes harvested on 120 days after planting.

Shrub legumes In vitro digestibility (%)

DM OM CP

CT Q5455 61.1a ± 3.1 63.3c ± 2.3 60.5 ± 5.5

CP bundey 64.3a ± 1.3 60.6bc ± 1.2 70.6 ± 2.5

DL 74.2b ± 0.9 74.7d ± 1.4 57.7 ± 5.0

MB juanita 64.6a ± 3.2 62.9c ± 2.7 62.8 ± 1.1

MB cadaarga 67.1a ± 1.7 64.8c ± 1.9 62.9 ± 1.6

CT millgara 59.9a ± 2.3 55.8ab ± 2.9 67.5 ± 3.4

CP molle 64.7a ± 1.9 61.9bc ± 2.2 62.2 ± 4.0

SS 60.9a ± 1.5 53.7a ± 1.1 59.9 ± 0.9 a-dValues in the same column with different superscript are significantly different (P < 0.01).

consumption. The higher the feed digestibility, the

higher the nutrient supply to the animals’ body. In

vitro, DM, OM and CP digestibility of shrub legumes

harvested on 120 days after planting evaluated in this

research are presented in Table 3.

Data in Table 3 showed that in general there was no

significant difference (P > 0.05) of DM digestibility of

eight shrub legumes, except for DL which showed

significantly the highest (P < 0.01) DM and OM

digestibility compared to the other. DL contained the

highest CP but the lowest CF and lignin. It is well

known that high CP content supports high digestibility,

however, high CF and mainly lignin content suppress

digestibility [27, 35]. In respect of Centrosema

pubescen, DM, OM and CP digestibility in this study

were lower than those reported by Ginting et al. [28]

which were 73.3%, 74.2% and 89.9%, respectively.

Digestibility of Clitoria ternatea and Centrosema

pascuorum cv. cavalcade was higher than Rubianty et

al. [6] who reported that DM digestibility of Clitoria

ternatea and Centrosema pascuorum cv. cavalcade in

hay form is about 50.15% and 53.52%, OM

digestibility is 53.47% and 55.67%. Zhou et al. [36]

reported DM digestibility of Flemingia macrophylla

and Casia bicapsularis was at range 58.18%-71.81%

while OM digestibility ranged from 40.70% to

72.70%. Mlay et al. [37] reported OM digestibility of

Macroptilium atropurpureun cv. siratrio is 65.8%,

which was close to the results in this research.

4. Conclusions

It was concluded that Stylosanthes seabrana,

Clitoria ternatea Millgara, Clitoria ternatea Q5455,

and Centrosema pascuorum Bundey produced the

highest digestible protein compared to the other four

legumes. The earlier four legumes are potential as

protein feed supplement to improve crude protein

availability, which is as the most often deficient

nutrient. Therefore, it has potential to be developed in

West Timor.

Acknowledgments

The authors gratefully acknowledge The Board of

Agricultural Research Development and Higher

Education, Ministry of Agriculture, Jakarta for the

financial support. The authors further appreciate the

Field Laboratory of Assessment Institute of

Agriculture Technology (AIAT) Kupang District,

West Timor for growing the legumes.

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Study of Sandy Soil Compaction

Andrea Formato, Gian Pio Pucillo and Antonio Abagnale

Department of Agricultural Science, University of Naples, Naples, Italy

Received: February 11, 2013 / Published: May 20, 2013. Abstract: In this paper, a study of sandy soil compaction with different granulometry and moisture content has been performed, and soil mechanical property variations in moisture and granulometry have been investigated. Investigations were performed to compare hydrostatic compression test (HCT) responses and evaluate the compression index, Cc, which is an indicator of the soil’s susceptibility to compaction-induced damage. The experiments have been performed on 24 soil samples typologies. Each sample has been obtained by combining three types of soil granulometry (types A, B and C) with a relative content varying from 0% to 100% in 20% increments. Soil type A had a granulometry ranging between 0.5 mm and 1 mm, type B between 0.25 mm and 0.5 mm, and type C less than 0.25 mm. These samples were representative of a sandy soil, chemically inactive and had various granulometries and initial moisture contents. A cell for HCT has been set up to allow the initial volume measurement of the test pieces and the subsequent changes during HCT with an estimated error less than 0.1 cm3. All samples were pre-compacted and prepared in agreement with the actual standards. The experimental data are reported in diagrams, the data allowed comparison of the mechanical behaviors between the considered unsaturated soils and underlined how soil moisture and granulometry affect soil response during HCT. Furthermore, because of the methodology used, the equipment was very economical. Key words: Compression test cell, hydrostatic soil compression, soil mechanics, unsaturated soils, sandy soil compaction.

1. Introduction

Soil compaction is a phenomenon causing both the

reduction of agricultural production and an increase in

the energy required to perform soil workmanship [1-7].

Undoubtedly, a better understanding of soil response

to applied loads can improve workmanship systems.

In fact, this knowledge allows the design of more

efficient soil workmanship tools and traction devices

[8-13]. The basic subject concerning soil mechanics in

engineering studies can be summarized as follows:

given an initial state, in terms of strains, stresses and

boundary conditions, the study of the dynamics of a

known type of soil deals with the determination of the

consequent deformation of the masses when external

loads are applied [14-16]. Unlike engineering soils,

unsaturated soil mechanics show greater complexity,

as reported in many important studies [17-19], even in

the simplified hypothesis of both continuity and

Corresponding author: Andrea Formato, professor,

research field: agricultural engineering. E-mail: [email protected].

isotropy. Agricultural soils are unsaturated soils with

few proper exceptions, the main difference from

engineering soil is the organic content. Apart from this

difference, some mechanical phenomena studied in

agriculture (such as the soil spontaneous arrangement

and compacting due to surface loads) point out

problems that are very similar to those experienced by

unsaturated soils in engineering. These problems

come from the prominence of the involved masses,

from the slow evolution of the phenomena and from

the important role of capillary stresses. Therefore, due

to the above-mentioned phenomena, it seems logical

to extend the unsaturated soil mechanics to

agricultural soils through proper engineering.

Nevertheless, some consider such a statement

excessive for agricultural soil break-up workmanship,

so following an approximated and less complicated

approach could be worthwhile [20-22]. Supposing an

initial macroscopic homogeneity of the system before

the tool action, we have to consider a large percentage

of water in its liquid state taking up only a part of the

DAVID PUBLISHING

D


357

voids’ volume. Both meniscus formation (capillary

forces) and stresses can occur due to the presence of

water and air. In these conditions, these forces can be

considered almost negligible in comparison with those

forces related to the physical-chemical bonds that act

on the particles and that require soil break-up by

means of mechanical tools [23, 24]. Therefore, we can

postulate that the contribution to the stress state

provided by the pressure difference between the two

fluid phases for the soil breaking-up workmanship can

be negligible in comparison with that contribution

provided by the forces generated by the working tools.

In these terms, the total main measurable stresses may

be sufficient to define the stress state at every point for

the agricultural soil submitted to breaking-up

workmanship considering the homogeneity, isotropy,

continuity of the soil and neglecting the forces due to

the fluid. In those cases, the soil characteristic

relationship is expressed by a spatial diagram,

reporting the strain variable of the void index, e, for

the stress state parameters, analogous to the actual

approach utilized in the theory of the critical state of

saturated soils [25-28]. Therefore, the soil state can be

represented by assuming the voids index as the strain

variable and expressing it as a function of the applied

load. Generally, this scheme is used to study the

soil-tool interaction. The soil-tool interaction

phenomena have been studied by numerous authors

with mathematical models [29-31]. According to the

mechanical behaviour of the considered soil, the

authors used a particular model, and also with the

simplified hypothesis of homogeneity, isotropy and

continuity of the soil, they were able to validate the

models, obtaining satisfying results. The

above-mentioned hypothesis, utilized to model the soil

for the study of the soil-tool interaction, is therefore

not valid, in general, for engineering soils and for the

soil physics in engineering soils. Furthermore, as we

know, hydrostatic compression tests are also

performed to evaluate the soil mechanical behaviour

when necessary. The soil compression characteristic is

a fundamental mechanical property of the soil that

relates the effect of compressive stress on the soil

volumetric parameter [32]. The modulus of the slope

of the virgin compression curve is commonly called

the compression index, Cc. The Cc parameter is an

indicator of both the susceptibility of a soil to damage

by compaction [33, 34] and of compressibility. The

study of compression curves for widely different soils

aimed to relate, the compression curves to properties

of agricultural soils, and to present methods for

predicting and describing the degree of compaction

from an applied stress has been performed by

numerous authors [35, 36], but since this matter is

ample and complex, they are still necessary further

close examinations and tests. Addressed in this way,

in this paper, we will show how the compacting

curves are obtained by hydrostatic compression tests

on loose sandy soil change with both soil

granulometry and soil moisture content (saturation

value minus the moisture value) and also how to

evaluate the compression index Cc based on

laboratory test data. The tests have been performed on

soil test pieces prepared by starting from a loose soil

with a known granulometry and moisture value and

opportunely pre-compacted to simulate a compacted

agricultural soil in workmanship conditions. The

experiments have been performed using a simplified

equipment set-up that is able to perform compression

hydrostatic tests on initially uncompacted sandy soil

(with known composition and granulometry) and for

different moisture conditions.


To express the strain state, the voids index is

adopted. Denoting the soil sample total volume and

that occupied by the solid with Vc and Vs, respectively,

the void index is:

(1)

we can adopt the normal mean stress, p, and the


358

deviatoric stress, q, as stress state variables. In

particular, denoting as pc the hydrostatic pressure

detected in the test cell and the (measurable)

increase of axial stress acting on the soil test piece

(deviatoric stress), the total stress is:

(2)

On the basis of the above hypotheses, the soil

characteristic can be represented with a spatial

diagram in which the strain state variable, e, depends

on the stress state variables p and q [37-40]. As stated,

the change of the void index according to the

compression pc for a determined soil has been studied

in this research. Therefore, to characterize the soil

response, test equipment has been set up that is able

to detect the hydrostatic compression curves and to

evaluate the changing of the strain variable of the

voids index e for a determined soil.

2.1 Test Equipment

The equipment scheme is shown in Fig. 1. The

equipment includes a cell (6) connected to a

measuring burette (1). The test cell has two flanges (7,

8) that are fixed to a transparent Plexiglas cylinder by

means of brass screws. In addition to the sealing

rings (10), the two flanges have a central conic seat

that avoids air bead formation during cell filling and

emptying operations. The equipment is fully

demountable to allow fast soil test piece preparation.

The upper flange (7) includes a 10 cm3 full scale

burette with 0.1 cm3 resolution that allows accurate

evaluation of soil test piece volume variations. The

burette, however, is able to detect a maximum total

volume variation of only 10 cm3. This problem has

been overcome with an auxiliary reservoir (4), at the

same pressure as the water in the test cell and located

at a higher height. The auxiliary reservoir is connected

by a pipe with an R2 tap to the lower zone of the test

cell. As shown in Fig. 1, the cell and the auxiliary

reservoir are always at the same pressure during the

test. Therefore, opening the tap will send water into

the cell to perform some compensation during the test

when the volume variations are greater than 10 cm3.

During the tests, the cell is submitted to the pressure

imposed by a circuit fed by the reservoir of a

compressor machine. The pressure value is indicated

by a pressure transducer (5) and recorded using a

data acquisition system with a sampling frequency of

1 Hz. The pressure transducer has a 200 kPa full scale

Fig. 1 Equipment scheme.


359

and 5 kPa resolution. The lower flange (8) has a base

(9) where the soil test piece is installed. The base is

connected to the outside through a porous septum.

2.2 Test-cell Setting

Because a Plexiglas cylindrical cell was used, it has

been necessary to evaluate its deformations. Therefore,

after flooding the whole circuit with water, the

equipment was pressurized up to 200 kPa in 5 kPa

increments. The corresponding test cell volume

variations have been recorded.

2.3 Test Piece Preparation

The container for the soil samples is made of 0.5 mm

thick rubber latex that guarantees water-tight sealing for

the soil test piece when it is pressurized. Furthermore,

during the soil filling of the rubber container, because

the working pressure was approximately 1 kPa, the

container elastic reaction on the soil was negligible.

Once the rubber latex container was filled with the

considered soil, the soil test piece was hermetically

sealed by inserting the base, which was shut using a

thread and adhesive tape. Subsequently, the soil test

piece was weighed and then placed in the test cell on

the base (9) to measure the sample volume.

2.4 Soil Volume Measurement

To measure the volume of the soil test piece, it is

necessary to refer to an initial value of the water

volume in the measuring circuit, which is made up of

two branches: one is the test cell with a notched

burette (1) and the other is the burette (2). To

determine the initial value of the water volume, water

was introduced into the system as far as possible (in

both branches), and two lined-up notches were placed

on burettes (1) and (2). The water surfaces of both

branches must coincide with the two lined up notches

when the soil test piece is not in the cell, and in this

condition, the R1 faucet is open and only the

atmospheric pressure works on the water surfaces.

Next, burette (2) is moved downward so that its water

surface is below the flange (8), and the entire volume

of the water circuit moves into burette (2), emptying

the test cell to allow the introduction of the soil test

piece. The R1 faucet is then closed. After installing

the soil test piece, closing and sealing the test cell,

burette (2) of the system (with the R1 faucet closed)

is returned to its initial position where the two

reference notches of the system were lined up.

However, the two water surfaces no longer line up.

By moving all of the circuit water into burette (2), its

water surface is now higher than the reference notches.

Therefore, by opening the R1 faucet, the test cell is

flooded until the water level reaches the preset notch

on burette (1). The R1 faucet is then closed to

interrupt the connection between the two branches.

The level of the water in burette (2) will now be

different from the level in burette (1). The gradient

between the two burettes is equal to the volume of the

soil test piece to be measured. Therefore, the value of

the water volume in burette (2) between the reference

notch and the water surface represents the measure of

the initial volume, Vpi, of the soil test piece. The

volume values of the fitting masses (lower base,

porous septum, rubber membrane) must be deducted

from the initial value of the test piece. Therefore, once

the initial mass of the moisture soil test piece (Mw, its

moisture (w), the density of the solid (s), the initial

volume of the soil test piece (Vpi), and the change in

volume (V) are known, the other characteristic

parameters can be determined as follows: dry mass:

Md = Mw/(1+w); solid phase volume: Vs = Md/s;

soil test piece volume: Vc = Vpi － V; void

volume: Vv = Vc － Vs; void index: e = Vv/Vs.

2.5 Soil Sample Preparation

Starting with three types of soil granulometry,

namely granulometry type A (ranging between 1 mm

and 0.5 mm), B (from 0.5 mm and 0.25 mm) and C (<

0.25 mm), and combining the three types to create a

relative content varying from 0% to 100% in 20%

increments, 24 soil samples were created for the


360

experiments. Each component (types A, B or C) was

present with a content of 0%, 20%, 40%, 60%, 80%

or 100%. The soil sample labels are shown in Table 1.

Additionally, U0, U5 and U10 refer to a moisture

content of 0%, 5% and 10%, respectively. Each

sample was chemically inactive, easily feasible in the

laboratory, and quite representative of a sandy soil.

2.6 Initial Compression of the Test Piece

Because agricultural soils, when subjected to

workmanship, are at a certain level of compaction, all

of the soil test pieces were submitted to 100 kPa

compaction prior to performing the compression tests.

After compaction, the water volume in burette (1) will

decrease to a certain value due to the reduction in

volume of the soil test piece. After the pre-compacting

step, the water level in the burette was re-established

to perform the scheduled tests.

Table 1 Soil granulometry with weight (%) on dry soil.

Soil type

Granulometry type A between 1 mm and 0.5 mm

Granulometry type B between 0.5 mm and 0.25 mm

Granulometrytype C < 0.5 mm

S01 0 0 100

S02 0 20 80

S03 0 40 60

S04 0 60 40

S05 0 80 20

S06 0 100 0

S07 20 0 80

S08 40 0 60

S09 60 0 40

S10 80 0 20

S11 100 0 0

S12 20 80 0

S13 40 60 0

S14 60 40 0

S15 80 20 0

S16 20 60 20

S17 20 40 40

S18 20 20 60

S19 60 20 20

S20 40 20 40

S21 20 20 60

S22 60 20 20

S23 40 40 20

S24 20 60 20

2.7 Test Execution

All of the considered soil test pieces were submitted

to hydrostatic compression following the load cycle

from 0 kPa to 1.5 × 102 kPa in steps of 1 kPa. The

change in volume of the soil test piece was recorded

for every step of pressure increase. During the initial

compression phase, the soil test piece under a constant

pressure continuously changes in volume, resulting in

a time dependence of the volume reached by the soil

test piece during the test. After 5 min, however, the

volume variations of the soil test piece at the same

pressure were almost negligible. Every test has been

repeated three times, and a statistical analysis of the

obtained data has been performed. The results were

processed using Statgraphics Plus Package 4.1

(Statpoint Technologies, INC., Warrenton, Virginia,

USA). A variance and media analysis were performed

to evaluate the percentage error for the obtained

results in the different tests performed.


Figs. 2-4 show the p-e diagrams obtained

experimentally, where p is the pressure value used for

the soil test pieces and e is the corresponding value of

the void index. Each point represents the mean value

of three experimental data, with a maximum error less

than 5% detected during all of the tests. From the p-e

diagrams, a good correspondence to the well-known

behaviour of soil submitted to compression tests can be

seen. The curves obtained by the hydrostatic

compression tests demonstrate that the unsaturated soil

behaviour is quite similar to that of a saturated soil

during the drained compression tests. Starting from an

initial value of the voids ratio, the soil shows a

decreasing volume with increasing pressure. We have

noted that these data results are in agreement with the

results obtained by previous studies available in

literature. [1, 5, 6, 13, 17-19, 25, 27, 35, 38, 41]. In

fact, this soil behaviour is due mainly to two

phenomena: a re-arrangement of the particles, which

probably remain undeformed and tend to fill the initial


361

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 0,2 0,4 0,6 0,8 1 1,2 1,4

Pressure - 10 5 Pa

Vo

id in

dex

- e

-

S01_U0

S02_U0

S03_U0

S04_U0

S05_U0

S06_U0

S07_U0

S08_U0

S09_U0

S10_U0

S11_U0

S12_U0

S13_U0

S14_U0

S15_U0

S16_U0

S17_U0

S18_U0

S19_U0

S20_U0

S21_U0

S22_U0

S23_U0

S24_U0

Fig. 2 p-e diagrams of the considered soil samples with moisture content of 0%.

0,50

0,60

0,70

0,80

0,90

1,00

1,10

0 0,2 0,4 0,6 0,8 1 1,2 1,4

Pressure - 10 5 Pa

Vo

id in

dex -

e -

S01_U5

S02_U5

S03_U5

S04_U5

S05_U5

S06_U5

S07_U5

S08_U5

S09_U5

S10_U5

S11_U5

S12_U5

S13_U5

S14_U5

S15_U5

S16_U5

S17_U5

S18_U5

S19_U5

S20_U5

S21_U5

S22_U5

S23_U5

S24_U5



362

0,50

0,60

0,70

0,80

0,90

1,00

1,10

1,20

0,00 0,20 0,40 0,60 0,80 1,00 1,20 1,40

Pressure - 10 5 Pa

Vo

id in

de

x -

e -

S01_U10

S02_U10

S03_U10

S04_U10

S05_U10

S06_U10

S07_U10

S08_U10

S09_U10

S10_U10

S11_U10

S12_U10

S13_U10

S14_U10

S15_U10

S16_U10

S17_U10

S18_U10

S19_U10

S20_U10

S21_U10

S22_U10

S23_U10

S24_U10


interstitial voids, and an elastic volumetric change of

the whole particles considerably larger than the sum of

the deformations of the single particles. In Figs. 2-4,

the compacting curves obtained from the soil samples

with different moisture values (0%, 5% and 10% in

weight of water) are also compared. Obviously, the

different moisture values cause the initial values of the

voids ratio to be different. In particular, the initial voids

ratio increases with the moisture content, which agrees

well with the compacting curves obtained by other

authors, that have studied this phenomena [1, 6, 17, 27,

28, 40, 42].

Because the moisture content is far from the

saturation point, such behaviour is due to the formation

of new aggregates of particles. In fact, inside a particles

system, the water increase causes the particles

rearranging in agglomerations with greater mean

diameter and so the void index increases, as mentioned

earlier. The compacting curves of the investigated soil

samples demonstrate the regular behaviour of the

samples. Three values of moisture content were

considered, and we have noted that every curve

shows a limit value, and this is in agreement with the

data results obtained by numerous authors. [1, 2, 6, 9,

13, 14, 16, 17, 22, 23]. Table 2 summarizes the Cc

values for the various soil sample compositions, which

have been evaluated considering the first four points in

the p-e diagram. In the same table, the A (big), B

(mean) and C (thin) granulometry values for the soil

samples considered are reported. In the following

section, the experimental data have been compared

considering six groups of soil composition:

Group 1: soil samples S01, S02, S03, S04, S05, S06

In this group, the soil samples with granulometry

types C and B have been compared. Examining the

diagrams with u = 0%, where u is the moisture

content, an exponential law for the compaction

curves can be seen, according to that was found by

numerous authors [1, 2, 6, 9, 13, 14, 16, 17, 22, 23, 42,

43]. The lower limit is attained with the S01 type with


363

Table 2 Cc values for the soil samples considered, obtained considering the first four points in the p-e diagram: Mean ± dxm (data average of three samples considered) dxm = standard deviation of the Mean.

U = 0% Mean ± dxm

U = 5% Mean ± dxm

U = 10% Mean ± dxm

S01 -0.2172 ± 0.068 -0.5319 ± 0.049 -0.6398 ± 0.035

S02 -0.2172 ± 0.041 -0.5319 ± 0.061 -0.6398 ± 0.040

S03 -0.2172 ± 0.032 -0.5319 ± 0.039 -0.6398 ± 0.061

S04 -0.2172 ± 0.055 -0.5319 ± 0.058 -0.6398 ± 0.039

S05 -0.2172 ± 0.022 -0.5319 ± 0.042 -0.6398 ± 0.049

S06 -0.2164 ± 0.041 -0.5319 ± 0.053 -0.6398 ± 0.052

S07 -0.3314 ± 0.037 -0.4720 ± 0.060 -0.4040 ± 0.059

S08 -0.3334 ± 0.051 -0.4720 ± 0.057 -0.3066 ± 0.038

S09 -0.3254 ± 0.045 -0.4720 ± 0.049 -0.3066 ± 0.047

S10 -0.3212 ± 0.062 -0.4720 ± 0.055 -0.3860 ± 0.051

S11 -0.1954 ± 0.055 -0.4720 ± 0.066 -0.4160 ± 0.039

S12 -0.3334 ± 0.061 -0.4720 ± 0.058 -0.3066 ± 0.051

S13 -0.2934 ± 0.043 -0.4720 ± 0.049 -0.3066 ± 0.055

S14 -0.3334 ± 0.058 -0.4720 ± 0.056 -0.3066 ± 0.046

S15 -0.3334 ± 0.039 -0.4720 ± 0.045 -0.3066 ± 0.049

S16 -0.1840 ± 0.047 -0.3090 ± 0.042 -0.5737 ± 0.054

S17 -0.1840 ± 0.051 -0.3090 ± 0.046 -0.5537 ± 0.057

S18 -0.1840 ± 0.060 -0.3090 ± 0.054 -0.5537 ± 0.059

S19 -0.1840 ± 0.048 -0.3090 ± 0.051 -0.5537 ± 0.038

S20 -0.1840 ± 0.039 -0.3090 ± 0.048 -0.5737 ± 0.052

S21 -0.1840 ± 0.053 -0.3090 ± 0.039 -0.5937 ± 0.042

S22 -0.1840 ± 0.039 -0.3090 ± 0.045 -0.5937 ± 0.056

S23 -0.1840 ± 0.048 -0.3090 ± 0.061 -0.5737 ± 0.039

S24 -0.1840 ± 0.051 -0.3090 ± 0.053 -0.5737 ± 0.060

100% of granulometry type C. By increasing the

percentage of B, it increases the total voids index for

the soil sample (B, C) and therefore the curves move

upward and the curves’ slopes increase. Then the

curves show higher values of void index and the gap

between the curves decreases (Figs. 2-4). This is in

agreement with the data available in literature. [1, 6,

13, 16, 17, 27, 34-36, 42]. For the soil samples

considered, changing the content of soil granulometry

B and C, the compression index shows low variations

(between -0.2164 and -0.2172 at u = 0%; -0.5319 at u

= 5%; -0.6398 at u = 10%). As shown in Table 2, by

increasing the moisture content, the compression

index increases, ranging between -0.2164 and -0.6398.

This behavior was also found by numerous authors.

[13, 17, 18, 27, 32, 34, 35, 38, 42, 43].


With soil samples composed of C and A soil types,

the data show that at 0% moisture content, by

increasing the percentage of granulometry type A with

big granulometry in the soil sample considered (A and

C), the total voids index increases, and therefore the

curves tend to shift upward. As in the previous case,

when the moisture content increases, the gap between

the curves decreases and the slope increases (Figs.

2-4). This is in accord with numerous authors [1, 6, 13,

16, 17, 27, 34-36, 42]. For the soil samples

considered, by changing the percentage of A and C,

the compression index changes (between -0.1954 and

-0.3334 at u = 0%; between -0.4720 and -0.5319 at u

= 5%; between -0.3066 and -0.6398 at u = 10%).

Excluding the S01 granulometry combination, the

Cc increases when the moisture content changes from

zero to 5% and decreases when u = 10% (Table 2).


In this group, the soil samples with granulometry


364

type B and A have been compared. With 0% moisture

content, the curves are included between those of S06

and S11. With the increasing percentage of

granulometry type A with big granulometry, in the soil

sample (A and B), the total voids index increases, and

therefore the curves shift upward. By increasing the

moisture content, these differences tend to decrease and

the curves’ slopes increase (Figs. 2-4). By varying the

soil composition, the Cc also changes (between -0.1954

and -0.3334 at u = 0%; between -0.4720 and -0.5319 at

u = 5%; between -0.3066 and -0.6398 at u = 10%).

Excluding the S06 composition, the Cc increases when

the moisture content changes from 0% to 5% and

decreases when u = 10% (Table 2).

Group 4: soil samples S12, S16, S17, S18, S07

In this group, the soil samples with 20%

granulometry type A and different percentages of

granulometry type B and C have been compared. With

a moisture content of 0%, the curves of the soil

samples S07 (B = 0%) and S12 (C = 0%) are quite

similar, while the others shift upward. These

differences decrease when the moisture content

increases (Figs. 2-4). That is, the percentage increase

of the component B, in the soil sample (A, B and C),

increases the total voids index, and therefore the

curves move upward. For the soil samples, S16, S17

and S18, the granulometry variations do not

appreciably influence the compression index (between

-0.1840 and -0.1840 at u = 0%; -0.3090 at u = 5%;

-0.5537 at u = 10%), but greater values were found for

S12 and S7 at each moisture content (Table 2).



granulometry type B and different percentages of

granulometry type A and C have been compared. With

0% moisture content, the curves of the soil samples

S15 (C = 0%) and S02 (A = 0%) are shifted

downward from the other curves. However, these

differences decrease when the moisture content

increases (Figs. 2-4). In these soil samples with (A, B

and C) components, the influence of the component A,

with big granulometry, is noticed. In fact, when there

is not the component A, the mean granulometry of the

soil sample (A, B and C) is lower than the component

A. For the soil samples S19, S20 and S21, when

changing the soil granulometry, the compression

index Cc shows small variations (-0.1840 at u = 0%;

between -0.3090 and -0.3048 at u = 5%; -0.5737 at u =

10%), but greater values were found for S02 and S15

at each moisture content (Table 2).



granulometry type C and different percentages of

granulometry type A and B have been compared.

With 0% moisture content, the curves of the soil

samples S05 (A = 0%) and S10 (B = 0%) are shifted

downward from the other curves. These differences

decrease when the moisture content increases (Figs.

2-4). The behavior of the soil sample (A, B and C) is

influenced by the presence of the components with

granulometry A and B (big and mean), being fixed to

20% the component C. Therefore their presence

moves upward the obtained diagrams. For the soil

samples considered, by changing the soil

granulometry, the compression index shows a small

variation for S22, S23 and S24 (-0.1840 at u = 0%;

-0.3090 for u = 5% and -0.5737 and -0.5937 for u =

10%), but greater values were found for S05 and S10

at each moisture content. Excluding the S10

granulometry combination, the Cc value increases

with moisture content, ranging between -0.1840 and

-0.5937. The data show that for three typology of soil

granulometry combinations, the slope, for a fixed

value of moisture content, is almost insensitive to the

granulometry composition, in the first group, the A

component is present and the B or C components are

absent; in the second, A is absent and B and C are

present; in the last, all the granulometry types are

present. More specifically, among these typologies,

the greatest slope values are obtained in the second

group. The slope’s absolute value for a fixed

granulometry combination increases with moisture


365

content, with the exception of those combinations in

which neither B nor C is present. Moreover, from all

the obtained Cc data, the minimum value is attained

when the granulometry composition is balanced, that

is, all soil types are present. The maximum value is

obtained with A and C granulometries (A = 40%, C =

60%) and A and B granulometries (A = 20%, B = 80%

and A = 60%, B = 40%). From the diagrams obtained

at the same moisture level but in soils with different

granulometries, we can see that the inclination of the

curves depends on the granulometry value and that the

effects due to the different granulometries tend to zero

as moisture increases, i.e., the effects due to the

different granulometries decrease when the moisture

increases. Comparing the graphs that have been

obtained at the same soil granulometry but with

different moisture values, we can see that the curves’

slopes depend on the moisture value. Therefore,

during these tests, the following results have been

obtained:

(1) All the diagrams obtained by submitting the soil

test pieces to hydrostatics compression tests follow an

exponential curve in the p-e plane, which is the curve

of consolidation;

(2) When the moisture increases under the same

pressure, the soil undergoes greater deformation,

becoming more sensitive to the increasing pressure.

All that was also noted by numerous authors [1, 6,

16, 17, 19, 28, 32, 35, 39, 42], therefore, according to

all the obtained comparisons, it was possible to

confirm the validity of the considered equipment.

4. Conclusions

A study of sandy soil compaction with different

granulometry and moisture content has been

performed. In this way, we can characterize the

considered soil and determine more easily the soil

model that could be utilized in the soil-tool interaction

study. Further, simplified equipment to carry out

hydrostatic compression tests on unsaturated soils has

been set up that makes it possible to examine soil test

pieces with different granulometries and with different

moisture values (those soils were unsaturated and far

from the saturation point). The obtained data agree

with the most reliable theories about soil compression

and confirmed the validity of the equipment.

Furthermore, the considered equipment was very

inexpensive compared to the prices of other

equipment of the same type but maintained the same

margin of error.

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Potential Impacts of Various Land Use Forms on Land

Degradation in Arid Regions (Case Study: Kuwait)

Raafat Misak1 and Adeeba Al-Hurban2

1. Environmental and Urban Development Division, Kuwait Institute for Scientific Research (KISR), Safat 13109, Kuwait

2. Department of Earth and Environmental Sciences, Faculty of Science, Kuwait University, Safat 13060, Kuwait

Received: January 14, 2013 / Published: May 20, 2013. Abstract: During the last 20 years, land use in Kuwait was remarkably changed in various forms. Such changes resulted in positively constructive, as well as, adversely destructive impacts on the local environment and ecology. In 1993-1994, a buffer zone of 15 km wide and more than 200 km long was established between Iraq and Kuwait. This allowed the restoration of biodiversity, enhancement of ecological conditions and stabilization of fragile soils. In 1991, long bund walls were constructed along the Saudi-Kuwaiti borders by Saudi Arabia and in 1993-1994, a ground trench was dug along the Iraqi-Kuwaiti borders by Kuwait. Bund walls are piles of excavated soils, 2-3 m high, 3-5 m wide and several tens of kilometers length. Constructing 1 km length of a bund wall required 2,500-3,000 m3 (1,000 m length × 5 m average width × 0.5 m depth) amount of soil, which disturbed a groundcover strip of an average area of 10,000 m2 (1,000 m length × 10 m average width). Border trenches are ground hollows 2-3 m deep, 3-5 m wide and 220 km long. The amount of excavated soil from digging 1 km long trench ranged from 6,000-8,000 m3. Field work indicated that 1 km long of trench had disturbed a groundcover of an average area of 12,000 m2 (1,000 m length × 12 m average width). Such man-induced land features are closely related to land degradation processes, as they were of adverse environmental impacts on soil, surface hydrologic conditions and natural vegetation. The main objective of this study is to assess the immediate and long term impacts of the introduced land use forms in selected areas in Kuwait, such as Wadi Al Batin (Western part of Kuwait). To achieve such an objective, intensive field program was designed and implemented and the collected data and available information were analyzed and interpreted. Key words: Bund walls, trenches, man-induced land features, surface hydrologic conditions.

1. Introduction

The State of Kuwait occupies a total area of about

118,000 km2. From West and North, it is bordered by

Iraq and from South by Saudi Arabia. The Arabian

Gulf skirts Kuwait from East (Fig. 1). The

Kuwaiti-Iraqi borders are marked by a ground trench

(about 3-5 m wide and 2-3 m deep), established by

Kuwait in 1993-1994 and running along about 212 km.

About 70 km of this trench cut the main course of

Wadi Al Batin, the natural barrier between Iraq and

Kuwait. On the other hand, the border between

Kuwait and Saudi Arabia is marked by a bund wall

Corresponding auther: Raafat Misak, professor, research

fields: desert geomorphology, geomorphological and environmental changes in desert, semi-arid and arid regions. E-mail: [email protected].

(2-3 m high and 3-5 m wide), established by Saudi

Arabia in 1991. Both the trench and bund wall

introduced significant change to the local

environmental, ecological and hydrological systems

existing in the area.

Precipitation in Kuwait is scanty and irregular [1].

Rainy season extends between October and April. The

average annual precipitation is around 110 mm.

Surface runoff is developed few hours after intensive

rainfall of 30-40 mm in one storm [2]. Flood events of

different intensities and impacts were recorded in

February 1993, December 1995, November 1997,

March 2002, January 2007, November 2009 and

January-February 2011.

Kuwait is located on the downwind side of the high

deflation area of the Mesopotamian flood plain in

DAVID PUBLISHING

D

Potential Impacts of Various Land Use Forms on Land Degradation in Arid Regions (Case Study: Kuwait)

369

Fig. 1 Satellite image of Kuwait showing bordering countries and two main strategic landforms (natural wind corridor and Wadi Al Batin). The arrow indicates the prevailing Northwesterly winds.

southern Iraq. This plain is considered as one of the

most significant sources of aeolian sediments to

Kuwait [3-5]. In Kuwait, the prevailing wind

directions are from the Northwesterly quadrant and to

a lesser extent from the southeast. Winds from other

directions occur less frequently and for shorter

durations [3]. The maximum wind speed ranges from

7.5 m s-1 to 20 m s-1 in June, while in July and August

it ranges from 10 m s-1 to 18 m s-1, and from 9 m s-1 to

19 m s-1, respectively. The average wind speed attains

5.8 m s-1, 5.4 m s-1 and 4.7 m s-1 in June, July and

August, respectively. According to the literature

sourced information and field observations, it was

indicated that the prevailing Northwesterly winds,

during summer and spring times, carry huge amounts

of drifted sand from Iraq to Kuwait.

1.1 Land Degradation

In Kuwait, land degradation processes were studied

by several authors including Khalaf [6], Omar, 1991

[7], Misak et al. [8], Zaman [9], Misak et al. [10],

Shahid et al. [11], Al-Dousari et al. [12], Al-Awadhi

and Misak [4], Al-Awadhi et al. [13], Omar et al. [14],

Misak et al. [15] and Misak et al. [5]. A comparison

between the density of the vegetation cover (mainly

perennial desert shrubs) in some parts of Kuwait

during early 1980s of the last century and Feb. 2010

revealed that vegetation cover has been severely

degraded [16].

As stated by Misak [17], land degradation processes


370

prevail in the majority of the terrestrial environment of

Kuwait, which constitutes about 80% of the country.

Land degradation processes include: loss of top soils

(through both wind and water erosion), soil crusting,

sealing and compaction, loss of soil productivity, soil

salinization, vegetation degradation, loss of

biodiversity and hydrological disruption.

Intensive anthropogenic activities (especially during

drought periods), in addition to the military operations

during the Gulf Wars of 1990-1991 and 2003

constitute the main causes of land degradation in the

terrestrial environment of Kuwait. These two main

causes are exacerbated by the inherent fragility of

soils, vegetation cover, micro-landforms and land

misuse. Generally, degradation is obviously

intensified during drought periods, e.g., 1983-1985,

2007/2008 and 2008/2009, whereas rainy periods, e.g.,

1993-1997 and 2003/2004 temporarily restore the

damage caused by land degradation.

The intensity, mechanism and extent of land

degradation exhibit remarkable variations in the

various land use forms [8]. Livestock grazing is the

major land use form in the open desert, which

constitutes about 75% of Kuwait’s surface area. In

these areas, indicators of soil, vegetation and

hydrological degradation, as well as, loss of

biodiversity are prevailing. In the agricultural areas

(about 2.7% of Kuwait), depletion of soil productivity,

water logging and soil salinization are recorded. In the

oil field areas (about 7% of Kuwait) soil

contamination by crude oil and surface deformation

by gatch pits (soil mining sites) are major indicators of

land degradation. The areal extent of oil

contamination in the oil field areas is about 114 km2

and the volume of contaminated soils is close to

4,400,000 m3 [18].

1.2 Interaction between Introduced Land Use Types

and Land Degradation Processes

During the period between 1992 and 2011, Kuwait

experienced remarkable changes in land uses, such as

fencing or protection of wide areas (about 12% of

Kuwait), either due to political demands or to

socioeconomic activities. Under the prevailing

environmental conditions of Kuwait, protection of

desert areas for at least five years resulted in

stabilization of active sandy bodies, enhancement of

physical characteristics of soils, encouragement of

natural recovery of vegetation and wildlife and

rehabilitation of biodiversity. Examples of positively

impacting introduced land use forms are:

establishment of the buffer zone between Iraq

and Kuwait (5 km wide and about 220 km long) in

1994/1995;

fencing of oil fields (about 7% of the country)

during the period 1996-2002;

re-fencing of Sabah Al Ahmad Wildlife Reserve

(about 330 km2) in 2000;

rehabilitation of Liyah degraded terrain (about

200 km2), to the north of Jahra City in 2003-2010;

managing camping and recreational activities in

open desert areas (ongoing);

setting up a plan for establishment of a number of

protected areas in the northwestern and Western parts

of Kuwait (2008);

establishment of Al Quran protected area in the

southeastern part of Kuwait (2011).

Literaturaly, little information is available about

the interaction between land use and land

degradation processes. Based on the intensity of

damage to ground cover (soils and vegetation) [5]

identified three classes of land use: a) extremely

destructive (damage to ground cover extends

between 1.5-5 m from ground surface); b) destructive

(damage to ground cover is restricted to the most

upper 50-75 cm thick of soil); and c) nondestructive

(damage to ground cover is not noticeable, with the

exception of war related damage). Khalaf et al. [16]

stated that bund walls and roads crossing drainage

basins act as dams for surface runoff during heavy

rainfall. The runoff water accumulates at the

upstream sides of the roads and bund walls.


371

2. Methods

To assess the impact of land use on land

degradation, the following activities were conducted:

Delineation of major and secondary drainage basins

(Wadis) using ArcGIS 9.3. For this purpose, Landsat

Thematic Mapper bands 2, 4 and 7 color composite

image of Kuwait (March 1995) was used. In this

image, the near infra-red band four was exposed

through a green filter and therefore significant

vegetation in the main channels and tributaries shows

up in shades of green. This image was recorded during

a good rainy season (about 167 mm of rainfall), so

very dense vegetation is shown in the main courses

and tributaries of drainage basins. Therefore,

digitization of these basins (Wadis) was an easy task.

Zones where drainage basins are dissected by human

induced barriers such as bund walls (2-3 m high and

3-5 m wide), trenches (3-5 m wide and 2-3 m depth)

and highways are delineated. These disrupted zones are

observed in images recorded after 1995. The areal

extent of disrupted zones in km2 was calculated using

Arc GIS 9.3. For this purpose landsat image of Kuwait

(2006) and google image of 2010 were applied.

About eight field trips during different seasons were

arranged to the western, southern and northeaster parts

of Kuwait. Frequent field trips aimed to: 1) roughly

estimate the amounts of soils which were excavated to

establish the border trench and bund wall; 2) assess

and record field observations on the mechanisms of

hydrologic disruption/ hydrologic drought; 3) locate

points of intersection between Wadis and surface

hydrological barriers including trenches, bund walls

and highways in at least 20 stations; and 4) to

document field findings through close up field

photographs.


Under the fragile environment of Kuwait, fluvial

and aeolian land forms and processes are very

sensitive to certain land use changes. At least three

land use types have negative impacts on the

mentioned processes and forms. These are raised

roads, bund walls and trenches. As observed in the

field, a 30-40 km segment of the border trench acts as

a trap for saltating sands coming from Iraq. Moreover,

this trench acts, during heavy rainy seasons, as an

artificial water collector for runoff water. Runoff

water results in considerable soil losses and collapses

of the sides of the trench.

3.1 Inventory and Assessment of Degradation

Processes Connected to Land Use

As indicated from the field survey during the course

of the present study, several mechanisms of land

degradation are observed in wide areas of Kuwait.

Some of these mechanisms are directly related to

current land use types, these include:

soil mining, vegetation degradation and loss of

biodiversity;

surface hydrologic disruption;

interruption of aeolian activities.

3.1.1 Soil Mining, Vegetation Degradation and

Loss of Biodiversity (the case of Iraq-Kuwait border

zone)

The establishment of a trench and a bund wall along

Kuwait-Iraq border resulted in soil mining and

disruption of desert surface. It is estimated that about

12,720,000 m3 and 375,000 m3 of soil were excavated

to establish the trench and the bund wall respectively.

At the same time at least 2,544,000 m2 and 1,500,000

m2 was disturbed by heavy machinery during digging

the trench and establishing the bund wall (Table 1).

The heavy machinery resulted in removal of

vegetation cover (mainly Haloxylon salicornicum and

Stipagro stisplumosa) and degradation of biodiversity.

It is observed that vegetation was completely cleared

from an area of approximately 4 km2 of land adjacent

to the trench and bund wall (Table 1).

3.1.2 Surface Hydrologic Disruption

Before establishment of the border trench between

Kuwait and Iraq in 1993-1994, the runoff water of the

tributaries feeding Wadi Al Batin from Western Iraq


372

Table 1 Approximate amount of excavated soils and disturbed areas along Kuwait-Iraq border.

Land use type (introduced form)

Amount of excavated soils (m3 km-1 length)

Total amount of excavated soils (m3)

Disturbed area (m2 km-1 length)

Total disturbed area (m2)

Remarks

Border trench 6,000 12,720,000 12,000 2,544,000 Total length 212 km

Bund wall 2,500 375,000 10,000 1,500,000

Total - 13,095,000 - 4,044,000

Fig. 2 Drainage basins in Kuwait and adjacent parts in Iraq and Saudi Arabia.

and Eastern Kuwait was flowing towards the main

course of the Wadi. Currently, the runoff water does

not drain in the main course of the Wadi. It is

accumulated in the border trench. Moreover, the

runoff water of Wadi Al Rimma (in Saudi Arabia) was

flowing towards Wadi Al Batin. The bund wall

between Saudi Arabia and Kuwait blocks the runoff

water flowing from Saudi Arabia to Kuwait. In

December 1995, December 2002, November 2009 and

January 2011 huge amounts of runoff water were

drained in the border trench.

To identify changes in surface drainage caused by

land use types, a detailed map for drainage basins was

produced by the first author (Fig. 2). Based on this

map, a detailed field survey was conducted on various

drainage basins.

Field survey indicated that almost all the drainage

basins are subjected to different degrees of surface

disruption. Disruption is represented by the following

forms:

loss of runoff water in the border trench;

blocking the surface runoff with its load of out

washed deposits in front of bund walls and raised roads;

modification of the courses of water channels;

fragmentation of drainage basins into portions of

different sizes;


373

soil losses through water erosion on both sides of

the border trench.

Figs. 3-6 show several forms of surface hydrologic

disruption.

3.1.2.1 Zones of Surface Hydrological Disruption

Based on the results of the present study, four zones

of surface hydrological disruption are described and

mapped (Fig. 7). These are:

Kuwait-Saudi Arabia border (1,961.7 km2);

Wadi Al Batin (552.2 km2);

Al Ritqa-Abdaly (748.1 km2 );

Raudtain-Um Al Eish (714.2 km2).

In the mentioned zones, hydrological disruption is

represented by interruption of the natural flow of

surface runoff during flooding seasons. Consequently

huge amounts of surface runoff are miss-distributed.

Fig. 3 Significant differences in vegetation cover at both sides of a bund wall, east of the main channel of Wadi Al Batin in 2009 (right photo) and 2011 (left photo).

Fig. 4 Blocking of surface runoff with its load of out washed deposits and development of manmade playa in front of a bund wall at the eastern flank of Wadi Al Batin.


374

Fig. 5 Soil losses through surface runoff at Umm Qaser area (Northeastern part of Kuwait). Arrows indicate the direction of runoff which flows towards a trench (February, 2011).

Fig. 6 Accumulation of flood water in the trenches; right photo: border trench at Al Salmi left photo: Umm Qaser trench (Feb. 2011).

The main causes and indicators of surface

hydrological disruption are summarized in Table 2.

3.3 Interruption of Aeolian Activities

The border trench in a stretch of about 35 km length

extending between Al Abraq (South) and Al

Huwaimiliyah (North) acts as a trap for salting sands

coming from Iraq (Figs. 8 and 9). The amount of

sands trapped in the trench between 2005 and 2009

was about 350,000 m3 [19]. After filling the trench

with shifting sands, maintenance operations start to

clear the sands. The removed sands are dumped in

open areas close to the trench. The dumped sands act

as active source of shifting sands and dust.

The supply of sands from Iraq to Al Huwamiliyah

dune fields, at the Northwestern part of Kuwait, is

interrupted by the border trench, which traps salting

sands. As indicated through recent field surveys, the


375

Fig. 7 Zones of surface hydrologic disruption.

Table 2 Causes, indicators and potential impact of surface hydrological disruption.

Zone of disruption Area (km2) Main causes of disruption Indicators of disruption Potential impact

Kuwait-Saudi Arabia border

1,961.7 Border bund wall Blocking of runoff water and outwashed sediments at the upstream portions of Wadis

Development of new sources of dust and sands

Wadi Al Batin 552.2

Border trenches and bund walls Road segments (Salmi and Abraq)

Trapping of surface run off in border trenches. Blocking of runoff water and out washed sediments at the upstream portions of Wadis

Hydrologic drought Development of new sources of dust and sands

Al RitqaAbdaly 748.1

Raudtain-Um El Eish 714.2 Abdaly Road North-south bund walls East-West bund walls

Blocking of runoff water and outwashed sediments along segments of Abdaly Road, Ritqa cut and North-South and East-West bund walls

Disturbance of recharge conditions of fresh groundwater aquifers of Rawdatain-Um Al Eish; Development of new sources of dust and sands

rate of deflation of these dunes exceeds that of

deposition. Deflation of sand dunes is manifested by

exposed plant roots and development of fields of

granule ripples. It is recently observed that several

sand dunes at the extreme upwind side of Al

Huwamiliyah dune fields are in their way to disappear

(blow out). They lost their classic morphology

(Barchan forms) and are transformed into low

featureless deflated sand bodies (Fig. 10). The

common Haloxylon salicornicum plant species, which

was prevailing in this area is replaced with invader

plant species (Cornulacae sp.).

4. Conclusions

During the period 1992-2011, Kuwait experienced

remarkable changes in land uses. Some of these


376

Fig. 8 Right photo: Tongues of shifting sands from Iraq to Kuwait in 2010; left photo: recent sand dunes crossed the border line between Iraq and Kuwait (pipeline) in Al Huwaimiliyah area, Northwestern part of Kuwait in 2009.

Fig. 9 Filling the border trench with shifting sands coming from Iraq (May 2009).

changes have positive environmental and ecological

impacts, while others have destructive effects.

Construction of a trench and a bund wall at the border

between Kuwait and Iraq has negative impacts on

local fluvial and aeolian processes. These two forms

of land use caused hydrologic disruption and

interruption of aeolian processes. It is estimated that

about 12,720,000 m3 and 375,000 m3 of soil were

mined (excavated) to establish the trench and the bund

wall, respectively. At the same time, at least 2,544,000

m2 and 1,500,000 m2 of land was disturbed by heavy

machinery during digging the trench and building the

bund wall. During heavy rainy season, e.g., 2001/2002

and 2009/2010, millions of cubic meters of runoff

water are lost in the border trench. During dust and

sand storms (almost every month), the trench acts as a

trap for salting sands coming from Iraq. Some 350,000

m3 of shifting sands were trapped in the trench during


377

Fig. 10 Deflation and ecological deterioration of sand dunes at Al Huwaimiliyah area (extreme Northwestern part of Kuwait). Note the exposed 30-40 cm of plant roots. Arrow indicates wind direction.

the period from 2005 and 2009. Periodical clearance

of sands outside the trench for maintenance purpose

resulted in sand encroachment problems in parts of

Kuwait. To restore the border zone between Kuwait

and Iraq, it is recommended to design and implement

a watershed management for the Eastern tributaries of

Wadi Al Batin. Currently, huge amounts of runoff are

lost in the border trench. Simple water harvesting

techniques including cisterns and earth dykes are

strongly recommended. To manage the hazards of

shifting sands and in turn to control soil erosion, it is

recommended to protect two highly fragile areas of

total 800 km2 for at least five years.

5. Recommendations

5.1 Proposed Restoration Measures

To restore the border zone between Kuwait and Iraq

(including Wadi Al Batin), the following approaches

are recommended:

watershed management;

managing the hazards of shifting sands.

5.1.1 Watershed Management

To avoid losses of rainwater and runoff and to

protect infrastructures such as the electric security

fence, it is recommended to design and implement a

watershed management for the Eastern tributaries of

Wadi Al Batin. Simple water harvesting techniques

including earth dykes (1-2 m high) are strongly

recommended (Fig. 11). This approach was

successively tested in Kuwait [2]. The harvested water

could be used for irrigation of drought resistance trees

and shrubs as well as other purposes.

5.1.2 Managing the Hazards of Shifting Sands

To manage the hazards of shifting sands, it is

recommended to adopt the following measures:

Establishment of a 25 km green belt of

Ziziphusspinachristi and Tamarixaphlae trees at Al

Huwaimiliyah area (main gate for saltating sands

coming from Iraq). These trees which trap huge

amounts of drift sands, are surviving very well in the

border zone. The number of rows and spacing

between trees and the most appropriate mechanical

measures for mobile sand control can be identified

through wind tunnel experiments.

Controlling human activities, especially grazing and

military maneuvers, for at least five years in areas A

(600 km2) and B (210 km2), which are severely

degraded (Fig. 12). Degradation is represented by soil

losses (mainly through deflation processes), soil

crusting and sealing, surface deformation, vegetation

degradation and loss of biodiversity. Intensive human

pressure during the last two decades including military


378

Fig. 11 A simple model for watershed management, eastern tributaries of Wadi Al Batin; note the dissection of catchment areas by tracks and bund walls at the right side.

Fig. 12 Image of Kuwait showing areas proposed for controlling human activities for at least five years; A: Huwaimiliyah-Al Atraf (600 km2) and B: Umm Qaser-Al Maghasel (210 km2).


379

operations of the Gulf War (August 1990-February

1991) is the main cause of soil and vegetation

degradation. As in the case of areas of similar

environmental conditions, protection of areas A and B

will result in natural recovery represented by soil

stabilization and enhancement of the vegetation cover.

Pre-allowing the public use and utilization of the areas,

a sustainable land use plan should be adopted to

identify and specify land use plan.

Acknowledgments

The authors are grateful to the land border security

staff, Ministry of Interior, Kuwait, specially Mr. A. Al

Bargas and to the Geo-informatics Centre, KISR for

their assistance and support during the course of the

study.

References

[1] S. Omar, R. Misak, P. King, S. Shabbir, H. Abo Rizq, G. Grealish, et al., Mapping the vegetation of Kuwait through reconnaissance soil survey, Journal of Arid Environment 48 (2001) 341-355.

[2] A. Al-Dousari, R. Misak, H. Gamily, N. Neelamani, Integrated System for Flood Management in Shuaiba Area and Its Vicinities. KISR EC055C Final Report, KISR 8910, 2007.

[3] F.I. Khalaf, D. Al-Ajmi, Aeolian processes and sand encroachment problems in Kuwait, Geomorphology 6 (1993) 111-134.

[4] J.M. Al-Awadhi, R.F. Misak, Field assessment of aeolian sand processes and sand control measures in Kuwait, Kuwait Journal of Science & Engineering 27 (1) (2000) 156-176.

[5] R. Misak, F. Khalf, S. Omar, Managing the hazards of drought and shifting sands in dry lands (the case of Kuwait), International Conference on Soil Classification and Reclamation of Degraded Lands in Arid Environments, Abu Dhabi, UAE. May 17-19, 2010.

[6] F.I. Khalaf, Desertification and aeolian processes in the Kuwait desert, Journal of Arid Environments 16 (1989) 125-145.

[7] S.A. Omar, Dynamics of range plants following 10 years of protection in arid rangelands of Kuwait, Journal of Arid Environments 21 (1991) 99-111.

[8] R. Misak, S. Omar, M. Al Sudairawi, Classes of Land

Degradation in the Terrestrial Environment of Kuwait. Application of New Technology for Improvement of Desert Environment, Kuwait-Japan Symposium, State of Kuwait, Jan. 26-28, 2003.

[9] S. Zaman, Effects of rainfall and grazing on vegetation yield and cover of two arid rangelands in Kuwait, Environmental Conservation 24 (1997) 344-350.

[10] R.J.M. Misak, M. Al-Awadhi, M. Al-Sudairawi, Assessment and controlling land degradation in Kuwaiti desert ecosystem, in: Proc. Conf. on the Impact of Environmental Pollution on the Development in the Gulf Region, Kuwait, Mar. 15-17, 1999.

[11] S.A. Shahid, S. Omar, S. Al-Ghawas, Indicators of desertification in Kuwait and their possible management, Desert Control Bull 34 (1999) 61-66.

[12] A.M. Al-Dousari, R. Misak, S. Shahid, Soil compaction and sealing in Al-Salmi area, Western Kuwait, Land Degrad, Development 11 (2000) 401-418.

[13] J.M. Al-Awadhi, S.A. Omar, R.F. Misak, Land degradation indicators in Kuwait, Land Degradation and Development 16 (2) (2005) 163-176.

[14] S. Omar, N.R. Bhat, S. Shahid, A. Assem, Land and vegetation degradation in war-affected areas in the Sabah Al-Ahmad Nature Reserve of Kuwait: A case study of Umm Ar. Rimam, Journal of Arid Environments 62 (2005) 475-490.

[15] R. Misak, A. Kwarteng, M. Al Sudairawi, S. Omar, E. Al Obaid, J. Al Awadhi, et al., Controlling Land Degradation in Several Areas in Kuwait, Final Report, KISR6002, 2000.

[16] F. Khalaf, J. Al Awadhi, R. Misak, Land use planning for controlling land degradation in Kuwait, International Conference on Soil Classification and Reclamation of Degraded Lands in Arid Environments, Abu Dhabi, UAE, May 17-19, 2010.

[17] R. Misak, Degradation of Sandy Soils and its Control in the Terrestrial Environment of Kuwait, in: R. Narayana, A. Al-Nasser, S. Omar (Eds.), Proceeding of Desertification in Arid lands, (KISR), 2009.

[18] Consortium of international Consultants (CIC), Monitoring and Assessment of the Environmental Damages and Rehabilitation in the Terrestrial Environment, Detailed Plan of the Oil Lakes, Oil trenches Monitoring Program, the Public Authority for Assessment of Compensation, 2003.

[19] R. Misak, Proposed Sustainable action plan for maintaining the biodiversity of Wadi Al Batin, Western part of Kuwait, Abstract, International Conference on Impact of Climate Change on Agriculture and Biodiversity in the Arab Region, Nov. 30-Dec. 2, 2010.


Effects of Using Different Percentages of Fenugreek

Flour to Improve the Sensory, Rheological Properties

and Keeping Quality in Maize Dough to Produces

Gluten-free Breads

Abdulsalam Abdulrahman Rasool1, Dana Azad Abdulkhaleq1 and Dlir Amin Sabir2

1. Field Crops Department, Faculty of Agricultural Sciences, University of Sulaimani, Sulaimani, Iraq

2. Food Sciences Department, Faculty of Agricultural Sciences, University of Sulaimani, Sulaimani, Iraq

Received: January 28, 2013 / Published: May 20, 2013. Abstract: Adding different percentages 1%, 3% and 5% of fenugreek flour depending on maize flour base to gluten free bread recipe for making tanoor bread was used to improve the tanoor bread quality, in term of sensory properties like volume, crust, color, symmetry, bake uniformity, texture, grain, aroma and taste. Also some rheological properties like gelatinization temperature and maximum viscosity of dough with bread keeping quality were used. The aim of this work is to produce suitable bread with maintaining the bread quality by selecting the suitable percentage to produce gluten free bread for people who suffering from celiac diseases and its contribution to health benefits. Significant differences were observed by using 5% of fenugreek flour in term of gelatinization temperature, maximum viscosity, breed keeping quality and volume. While using 1% of fenugreek flour significantly improved symmetry value, bread texture, crumb color, aroma and taste. Key words: Maize, Fenugreek, sensory evaluation, rheological properties, keeping quality, gluten-free bread.

1. Introduction

Maize (Zea mays L.) is the most widely grown crop

in the America, with 70-100 million acres grown

annually in the United States alone, accounting for

nearly 40% of the all maize grown in the world. It is a

versatile crop, and can be grown in a number of

different environments; it is grown on every continent

except Antarctica. Maize is also higher yielding than

many other grains (its average yield is 14 t ha-1 but it

can reach over 27 t ha-1), and therefore often less

expensive. Together with wheat and rice, maize is one

of the three most important crops in the world due to

its nutritional qualities and ease of cultivation. Maize

contains high levels of starch and valuable proteins

and oils. Depending on the variety, maize may contain

Corresponding author: Dlir Amin Sabir, Ph.D., research

field: food science. E-mail: [email protected].

a number of important B vitamins, folic acid, Vitamin

C and provitamin A, also rich in minerals and it is a

good source of dietary fiber and protein, while being

very low in fat and sodium [1].

Fenugreek plant (Trigonella foenum graecum L.) is

widely distributed throughout the world and which

belongs to the family Fabacecae. It is a herb recorded

as one of the oldest medicinal herbs, highly esteemed

by both East and West, and has been regarded as a

cure for just about every ailment known to man.

Fenugreek has the most beneficial action on cleansing

the blood. As a diaphoretic, it is able to bring on a

sweat, and help detox the body. Commonly found

growing in the Mediterranean region of the world.

While the seeds and leaves are primarily used as a

culinary spice, it is also used to treat a variety of

health problems in Egypt, Greece, Italy and South

DAVID PUBLISHING

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Effects of Using Different Percentages of Fenugreek Flour to Improve the Sensory, Rheological Properties and Keeping Quality in Maize Dough to Produces Gluten-free Breads

381

Asia. Emphasis is put on studying the practical

feasibility of such bread in a regular bakery

environment, and on understanding the underlying

physicochemical principle [2, 3].

The plant contains active constituents such as

alkaloids, flavonoids, steroids, Saponins, etc.. It is an

old medicinal plant. It has been commonly used as a

traditional food and medicine. Fenugreek is known to

have hypoglycemic, and hypocholesterolaemic, effects,

anti-inflammatory effects. Recent research has

identified fenugreek as a valuable medicinal plant

with potential for curing diseases and also as a source

for preparing raw materials of pharmaceutical industry,

like in steroidal hormones [2].

Gluten-free bread was once regarded as a main

product for people with a rare disorder, celiac disease

[3]. However, it has meanwhile been recognized that

celiac disease is much more widespread than

previously thought, and an average worldwide

prevalence of Gluten-free breads based on isolated

starches, or on flour from gluten-free cereals like maize

have been described in the literature for many decades

has long been known that mixtures of maize, starch

and water can form a dough with properties similar to

wheat dough, provided that they are mixed above room

temperature [4]. Use of fenugreek, a food with

demonstrated efficacy in lowering blood sugar, is

limited by its bitter taste and strong flavor. A bread

incorporating fenugreek using a proprietary process

was tested for its taste acceptability and its effect on

carbohydrate metabolism. We developed a fenugreek

bread formula that was produced in a commercial

bakery by incorporating fenugreek flour into a standard

maize bread formula. Whole wheat bread was prepared

by the same formula in the same bakery using wheat

flour. Fenugreek and maize bread samples were

evaluated for sensory attributes and nutrient

composition. Color, firmness, texture and flavor

intensity between the fenugreek added to maize flour

and control. Tanoor bread is single layered flat. Tanoor

bread is popular in Iraq, Khubz and Naan are different

names used for the same product in various parts of the

Middle East. The name comes from the type of oven

used to bake this product, i.e., tanoor, which means

clay oven. Tanoor bread requires 100% flour, 1%

active dry yeast, 0.75%-1.5% salt and various amounts

of water. The processing steps are mixing, dividing,

proofing, sheeting, docking, baking and packaging.

Crust color is reddish brown. High quality tanoor bread

has a uniform thickness with an even distribution of

small blisters on the top crust [5]. The aim of this work

is to produce suitable bread with maintaining the bread

quality by selecting the suitable percentage to produce

gluten free bread for people whom suffering from

celiac diseases and its contribution to their health and

increase bread shelf life stability.


2.1 Maize Seed

Maize seed cultivar 704 which obtained from

Sulaimani research center was used in this study, then

the seeds were milled by locally miller in city center

then the flour was used alone and mixed with different

percentages 1%, 3% and 5% of fenugreek flour which

is available in the local market.

2.2 Dough Preparation

Measurement of rheological characteristics of

dough bread baking process; the processing steps were

dough mixing to optimum dough development, bulk

fermentation 60 min, dividing and rounding (50 g

pieces), intermediate proofing (10 min), sheeting, final

proofing (30 min), baking (288 °C for 15 min),

cooling. The dough pieces were baked in electric oven.

And then the bread parameters and sensory evaluation

characters like volume crust color, symmetry, bake

uniformity, texture, grain and aroma were evaluated

according to AACC method 10-12.01 baking

guidelines for scoring experimental bread [6].

2.2.1 Rheological Characteristics of Dough

Amylograph procedure was used for rheological


382

characteristics according to AACC methods 61-01.01

Amylograph Method for Milled Rice was performed

using a 60 g of sample [7].

2.2.2 Baking Volume

AACC method 22-10.01 was used for Measurement

of Volume by Rapeseed displacement [8].

2.3 Chemical Composition of Maize and Fenugreek

The following methods were used for flour analysis

as shown in Table 1.

AACC method 08-21.01 Prediction of Ash Content

in Wheat Flour—Near-Infrared Method [9], 39-10.01

Near-Infrared Reflectance Method for Protein

Determination in Small Grains [10], AACC method

Grains 0-10.01 Crude Fat in Flour, Bread, and Baked

Cereal Products [11], AACC method 44-01.01

Calculation of Percent Moisture [12], AACC method

76-13.01 Total Starch Assay Procedure Megazyme

Amyloglucosidase/Alpha-Amylase Method [13].

2.4 Method of Statistical Analysis

For the statistical tests of variance analysis, least

significant difference (LSD) test and SPSS software,

version 18, were used.


Table 2 and Appendix 1 show highly significant

differences regarding bread volume, the biggest

volume was obtained by using 5% fenugreek. This

may be due to the physiochemical properties of the

fenugreek protein which present in the seeds. The

highest symmetry, bread texture, crumb color aroma

Table 1 Chemical composition of maize and fenugreek.

Chemical composition (%)

Maize Fenugreek

Starch 71.5 51

Protein 10.3 26.0

Fat 3.8 8.0

Ash 1.3 3.0

Moisture 13.1 12

and taste were obtained by using 1% Fenugreek, this

may be due to the effect of the emulsion agent which

present in fenugreek seeds which lead to produce a

desirable and uniform air bubbles in the dough and

final product similar results observed by those whom

reported by Maleki et al. [14]. The desirable aroma of

fenugreek seeds came from polysaccharides

(galactomannan), volatile oils and alkaloids, such as

choline and trigonelline, that is why the addition of

1% of fenugreek seeds was more desirable to add in

such cases. Regarding crust color, bake uniformity

and grain, there were no significant differences among

all of the treatments, this results are in agreement with

researchers [15].

As shown in Table 3 and Appendix 2, highly

significant differences were noticed among the

treatments. The addition of 5% Fenugreeks increased

gelatinization temperature and maximum viscosity.

This could be due to the effect of emulation agent that

found in this kind of improver that has been used in

our local area at house levels similar results are

reported by authors [16].

Data in Table 4 and Appendix 3 indicate that there

were significant differences between treatments in

term of adding different percentages of fenugreek

Table 2 Effect of the addition of fenugreek flour on the sensory evaluation characters.

Treatments Volume (15)

Crust color (15)

Symmetry (5)

Bake uniformity (5)

Texture (15)

Crumb color (10)

Grain (10)

Aroma (15)

Taste (20)

Control 8.333 2.333 1.333 2.667 9.333 6.667 5.000 8.667 9.000

1% Fenugreek 13.667 3.333 4.000 3.333 13.333 9.333 8.667 12.667 16.333

3% Fenugreek 13.000 1.667 2.000 2.667 6.667 5.667 7.333 10.000 5.000

5% Fenugreek 14.333 1.667 3.667 2.333 6.333 4.667 5.333 7.333 3.667

L.S.D (P ≤ 0.05) 2.306 n.s 1.803 n.s 2.369 1.960 1.883 2.306 3.216


383

Appendix 1 Mean squares of variance analysis for the sensory evaluation characters.

S.O.V d.f MS

Volume (15)

Crust color (15)

Symmetry (5)

Bake uniformity (5)

Texture (15)

Crumb color (10)

Grain (10)

Aroma (15)

Taste (20)

Treatments 3 22.222** 1.444n.s 4.972* 0.528n.s 31.417** 12.083** 8.972** 15.556** 97.222**

Exp. error 8 1.500 0.333 0.917 0.833 1.583 1.083 1.000 1.500 2.917

Table 3 Effect of the addition of fenugreek flour on the rheological properties.

Treatments Gelatinization temp. (°C) Maximum viscosity (Bu)

Control 72.000 620.000

1% Fenugreek 81.000 340.000

3% Fenugreek 82.667 510.000

5% Fenugreek 89.667 713.333

L.S.D (P ≤ 0.05) 3.075 44.490

Appendix 2 Mean squares of variance analysis for the rheological properties.

S.O.V d.f MS

Gelatinization temp. (°C) Maximum viscosity (Bu)

Treatments 3 158.444** 77208.333**

Exp. error 8 2.667 558.333

Table 4 Effect of fenugreek addition on breed keeping quality.

Treatments 24 h 48 h 72 h

Control 5.667 4.667 3.333

1% Fenugreek 6.667 5.333 4.667

3% Fenugreek 7.000 6.333 5.333

5% Fenugreek 8.000 7.000 6.333

L.S.D (P ≤ 0.05) n.s 1.631 1.438

Keeping quality score = 10 degrees.

Appendix 3 Mean squares of variance analysis for breed keeping quality.

S.O.V d.f MS

24 h 48 h 72 h

Treatments 3 2.778n.s 3.222* 4.750**

Exp. error 8 1.167 0.750 0.583

after 48 h and 72 h of shelf life at laboratory

temperature. In this study, the ability to roll and fold

characteristic used for evaluating shelf life stability of

tanoor bread. Breads made with the three levels (1%,

3% and 5%) of fenugreek flour had higher scores for

tearing quality compared with the control, this may be

due to the effect of preservation agent choline and

trigonellin which found in high amount in fenugreek,

this results are in agreement with researchers [15] or

may belong to the emulation properties of fenugreek

protein content and its role in improving bread

keeping quality similar results are observed by

researchers [17].

4. Conclusions

It was concluded that there were significant

differences between treatments in term of adding 1%)

of fenugreek regarding bread volume, bread texture,

crumb color, symmetry and aroma. While using (5%)

of fenugreek increase shelf life stability for 48 h and

72 h which was significantly differed from the other

additions of 1% and 3 % respectively.


384

Acknowledgments

Appreciation and highly grateful are also expressed

to Food Science Department, Faculty of Agricultural

Sciences-University of Sulaimani for making this

research possible. Special thanks and appreciations are

due to Mr. Nehad the Chairman of the Quality Control

Department in Sulaimani. The authors’ best gratitude

and thanks are also expressed to Mrs. Jutyar the Head

of Field Crops Department at Bakrajo Research

Station for his help during this research.

References

[1] T.M. Fulton, C.S. Buckler, R.A. Kissel, The Teacher-Friendly Guide to the Evolution of Maize, Paleontological Research Institution, Ithaca, NY, 2011.

[2] H.S. Snehlata, D.R. Payal, Fenugreek (Trigonella foenum-graecum L.): An overview, International Journal of Current Pharmaceutical Review and Research 2 (2012) 169-187.

[3] A. Fasano, C. Catassi, Current approaches to diagnosis and treatment of celiac disease: An evolving spectrum, Gastroenterology 120 (2001) 636-651.

[4] T.J. Schober, S.R. Bean, D.L. Boyle, Gluten-free sorghum bread improved by sourdough fermentation: Biochemical, rheological, and microstructural background, Journal of Agricultural and Food Chemistry 55 (2007) 5137-5146.

[5] H.A. Faridi, Flat breads, in: Y. Pomeranz (Ed.), Wheat Chemistry and Tech-Srinology, St. Paul, 1988, pp. 457-506.

[6] AACC Methods 10-12.01 Baking Guidelines for Scoring Experimental Bread Methods of the American Association of Cereal Chemistry, Am. Assoc. Cereal Chem. Inc., St. Paul, Minnesota, 2000.

[7] AACC Methods 61-01.01 Amylograph Method for Milled Rice Measurement of Alpha-Amylase Activity with the Amylograph Approved Methods of the

American Association of Cereal Chemistry, Am. Assoc. Cereal Chem. Inc., St. Paul, Minnesota, 2000.

[8] AACC Methods 22-10.01 Measurement of Volume by

Rapeseed Displacement Approved Methods of the

American Association of Cereal Chemistry, Am. Assoc.

Cereal Chem. Inc., St. Paul, Minnesota, 2000.

[9] AACC Method 08-21.01 Prediction of Ash Content in

Wheat Flour—Near-Infrared Method, Approved Methods

of the American Association of Cereal Chemistry, Am.

Assoc. Cereal Chem. Inc., St. Paul, Minnesota, 2000.

[10] AACC, 39-10.01 Near-Infrared Reflectance Method for

Protein Determination in Small Grains American

Association of Cereal Chemistry, Am. Assoc. Cereal

Chem. Inc., St. Paul, Minnesota, 2000.

[11] AACC Method Grains 0-10.01 Crude Fat in Flour, Bread,

and Baked Cereal Products. American Association of

Cereal Chemistry, Am. Assoc. Cereal Chem. Inc., St.

Paul, Minnesota, 2000.

[12] AACC Method 44-01.01 Calculation of Percent Moisture.

American Association of Cereal Chemistry, Am. Assoc.

Cereal Chem. Inc., St. Paul, Minnesota, 2000.

[13] AACC Methods 76-13.01 Total Starch Assay Procedure

(Megazyme Amyloglucosidase/Alpha-Amylase Method

the American Association of Cereal Chemistry, Am.

Assoc. Cereal Chem. Inc., St. Paul, Minnesota, 2000.

[14] M. Maleki, J.L. Vetter, W.J. Hoover, The effect of

fenugreek seeds, sugar, shortening and soya flour on the

staling of barbari flat bread, Journal of the Science of

Food and Agriculture 32 (1981) 1209-1212.

[15] N.A. El Nasri, A.H. El Tinay, Functional properties of

fenugreek (Trigonella foenum graecum) protein

concentrate, Food Chemistry 103 (2007) 582-589.

[16] J.F. Qarooni, Governing the quality of bread in the

Middle East, Ph.D. Dissertation, School of Biological

Technologies, University of New South Wales, 1988, pp.

1-215.

[17] M. Maleki, R.C. Hoseney, P.J. Mattern, Effects of loaf volume, moisture content and protein quality on the softness and staling rate of bread, Cereal Chemistry 57 (1980) 138-140.


Applicability of Cytoplasmic Male Sterility (CMS) as a

Reliable Biological Confinement Method for the

Cultivation of Genetically Modified Maize in Germany

Heidrun Bückmann1, Alexandra Hüsken2 and Joachim Schiemann1

1. Institute for Biosafety in Plant Biotechnology, Julius Kühn-Institut-Federal Research Centre for Cultivated Plants, Quedlinburg

06484, Germany

2. Department of Safety and Quality of Cereals, Max Rubner-Institut, Detmold 32756, Germany

Received: February 7, 2013 / Published: May 20, 2013. Abstract: The cultivation of genetically modified (GM) plants requires the reduction of an unwanted spread of genes (biological confinement). Cytoplasmic male sterility (CMS) inhibits the development of functional pollen, but nuclear restorer (Rf) genes and environmental impacts can restore the fertility. The aim of this study was to verify whether CMS in maize hybrids is a reliable confinement method for the prospective cultivation of GM maize in Germany. Two-year field experiments in three different environments were conducted with three CMS maize hybrids which vary in the CMS stability, one conventional maize variety (all yellow kernels) and white maize as pollen recipient. Tassel characteristics, pollen vitality and cross-pollination rates were investigated. The CMS stability was dependent on the genotype and the specific weather conditions per year and location. In all maize hybrids CMS was unstable. One CMS maize hybrid showed a high level of CMS stability and very low cross-pollination rates in any case (< 1%). The two other CMS maize hybrids developed more fluctuant and fertile tassels with few or many pollen, respectively. Compared with a conventional and fully fertile maize variety, cross-pollination of all CMS maize hybrids was strongly reduced (84%-99%). In conclusion, the CMS trait can be proposed as a useful biological confinement method to reduce pollen-mediated gene flow from GM maize. Key words: CMS, pollen release, biological confinement, cross-pollination reduction, GM maize (Zea mays L.).

1. Introduction

The cultivation of genetically modified (GM) crops

might result in unwanted intermingling with other

agricultural products based on the so-called gene flow.

Gene flow can occur seed-mediated,

vegetative-propagule-mediated or pollen-mediated [1].

The extent of each type of gene flow depends on the

cultivated plant species. Several biological

confinement methods have been developed to prevent

or reduce pollen-mediated gene flow [2-5]. These

methods are based on either naturally occurring or

engineered phenomena, like cleistogamy, plastid

Corresponding author: Heidrun Bückmann, Ph.D.,

research field: biosafety research with genetically modified plants. E-mail: [email protected].

transformation, cytoplasmic male sterility (CMS),

transgene excisions or incompatible genomes [1]. An

effective biological confinement method requires a

high level of gene stability and the knowledge of its

reliability. It should meet the requirements of gene

flow reduction for the specific GM crop.

For the cultivation of maize in the Middle-European

climate, gene flow occurs mainly by pollen dispersal.

It is based on the huge amount of pollen, the flowering

time and synchronisation of pollen donor and pollen

recipient plants and the pollen competition between

both. External conditions like wind direction and

speed, temperature and air humidity as well as

distances between different maize fields can influence

the pollen-mediated gene flow significantly [6, 7].

DAVID PUBLISHING

D

Applicability of Cytoplasmic Male Sterility (CMS) as a Reliable Biological Confinement Method for the Cultivation of Genetically Modified Maize in Germany

386

Biological confinement methods like CMS are not

applied in GM maize cultivation yet but should be

considered and tested for gene flow reduction in

specific applications.

CMS occurs naturally in many plant species [8, 9].

It is a maternally inherited trait that prevents the

development of functional pollen [10, 11]. CMS

results from a loss-of-function mutation in the

mitochondrial genome [12] which causes a

dysfunction of the respiratory metabolism and an

abnormal production of male gametes [13, 14]. Hence,

plants develop no vital pollen while the female

fertility is not affected. Three main CMS-types are

known for maize [15]: CMS-T or Texas cytoplasm

[16, 17], CMS-S or USDA-cytoplasm [18] and

CMS-C or Charrua-cytoplasm [19]. Although the

primary determination of CMS occurs extranuclearly,

certain nuclear genes-restorer of fertility genes

(Rf)-can compensate the CMS effect of the cytoplasm

[11] and can result in fluctuated or fertile tassels with

more or less vital pollen in the first-generation

progeny (F1).

Apart from the internal interactions between

mitochondrial and nuclear genes, fertility of many

CMS plant species can also be restored by

environmental impacts like heavy rain or extreme heat

[7, 20-23]. Sterility decreases with decreasing

temperatures and day length [21, 24, 25]. Correlations

between climatic factors during the 10 days before

anthesis of maize with partial reversion to male

fertility were ascertained by Weider et al. [7] for

several CMS hybrids in different environments. In

most instances, the involved mechanisms are still

unclear.

The aim of this study was to verify whether CMS in

maize might be a reliable method to reduce the

pollen-mediated gene flow. It should be clarified

whether selected CMS maize hybrids are stably sterile

or restored to fertility within different environments in

Germany. In case that (partial) restoration of fertility

occurs, knowledge about out-crossing rates from CMS

maize hybrids into pollen recipient maize is important.

Therefore, field trials were performed to study the

stability of CMS and the extent of gene flow from

unstable maize hybrids as a function of the distance to

recipient maize plants under practical agricultural

conditions.


2.1 Site Descriptions

In 2009 and 2010, field trials were conducted in

three different environments in Germany. Groß

Lüsewitz is located in Western Pomerania,

North-Eastern Germany, and characterised by an

average annual precipitation of 610 mm with summer

drought and soils of sandy loam. The average

temperature is 6.9 °C (Table 1). Braunschweig in

Lower Saxony (Northern Germany) belongs to a

typical agricultural area with deep-grounded loamy

clay soils and average rain fall rates of 628 mm per

year and temperatures of 9.2 °C. Freising, Bavaria

(Southern Germany), is characterised by a mild

climate with an average annual temperature of 7.5 °C,

an average precipitation of 788 mm and a sandy loam

soil.

2.2 Field Trial Design

The field trials included plots of three different

Table 1 Characteristics of the field trial locations in Germany.

Groß Lüsewitz Braunschweig Freising

Soil type Sandy loam Loamy clay Sandy loam

Altitude 15 m 82 m 480 m

Ø annual temperature 6.9 °C 9.6 °C 7.5 °C

Ø annual precipitation 610 mm 580 mm 793 mm


387

CMS maize hybrids and one conventional fully fertile

maize hybrid variety. At the adverse side of each of

these plots, one plot with a white maize variety used

as pollen recipient was located. The distance between

these plots was 3.5 m. Each plot measured 48 m width

to 69 m length (Fig. 1). The trials were designed

downwind with the CMS maize hybrid plots

westwards of the white maize plots at all locations. To

prevent cross-pollination between the test units (CMS

maize hybrid and pollen recipient maize) hemp was

grown as a natural pollen barrier. The trials were

conducted under local agricultural conditions.

2.3 Maize Genotypes

The appropriate CMS hybrids for the field trials

were selected according to the results of a previous

experiment in 2008 when 10 CMS maize hybrids of

the three CMS types [7] were tested in a randomised

block trial with four repetitions at each location. The

plants were tested for the flowering behaviour (tassel

characteristics, pollen shedding, flowering time and

duration), the vitality of pollen is produced, the

flowering synchronism with pollen recipient plants

and the plant height. The hybrids with the highest

out-crossing potential caused by pollen production

and pollen vitality and the lowest out-crossing

potential were selected as well as a CMS hybrid with

a medium out-crossing tendency. The following

hybrids were selected: “DSP2”, a CMS T-type maize

hybrid (Delley Seeds and Plants Company, DSP,

Switzerland) and “Torres” and “Zidane”, both CMS

S-type maize hybrids (Kleinwanzlebener Saatzucht

AG, Germany). These hybrids were grown in

comparison with the conventional fully fertile maize

hybrid “Delitop”. All plants develop yellow kernels.

A white grain maize test hybrid, DSP 17007(Delley

Seeds and Plants Company, Switzerland), was

cultivated as pollen recipient [26].

Fig. 1 Field trial design with assessment and sampling points.


388

2.4 Tassel Characteristics and Pollen Vitality

At 12 assessment points (Fig. 1) within one CMS

maize plot always 20 plants were tested on their tassel

characteristics during the male flowering period.

According to the stability of the CMS trait, they were

classified into sterile, restored or fertile tassels as

described by Weider et al. [7]. Sterile tassels do not

develop any anthers and therefore pollen, while partly

restored tassels produce anthers, generally only on the

lateral branches. They can produce different amounts

of pollen that can be vital or sterile. A fertile tassel

produces many anthers on all branches and sheds lots

of vital pollen.

If anthers were developed, 12 self-pollinations per

plot were carried out to investigate the vitality of the

pollen. Within one plot, a minimum number of 12 ears

were isolated with a paper bag before silking. The day

before self-pollination, the tassels were isolated and

the pollen was collected in a paper bag. When

self-pollinated, the ears were carefully fertilised with

the collected pollen and were further isolated until the

end of the pollen shedding period to prevent allogamy.

At harvest, the self-pollinated ears were picked and

the mean kernel set (MKS) was calculated by counting

the kernels developed and compared with a fully

germinated ear of the same CMS maize hybrid. This

hybrid was hand-pollinated with vital pollen of the

white maize. The MKS is an indicator of the vitality

of pollen developed and is expressed in percentage.

2.5 Cross-Pollination

At defined distances (Fig. 1) within the white maize

plots, 20 cobs were harvested and yellow and white

kernels, respectively, were counted to determine the

level of cross-pollination.

The cross-pollination from CMS maize into

conventional maize was tested by a simple colour

detection system. All CMS maize hybrids develop

yellow kernels. If white maize is pollinated by yellow

maize pollen, it produces yellow kernels due to

hereditary dominance. To calculate the

cross-pollination rate of the pollen donor plots, it is

necessary to determine the average grain number per

ear/cob. On this number, the percentage of the

cross-pollination rate can be based and the results are

expressed as percentages from the total number of

kernels per cob. The data of all 20 plants per

assessment point were averaged.

2.6 Weather Data

At all field trial locations, weather data were

collected during the whole flowering period. In

Braunschweig and Freising mobile weather stations

were kindly provided by the Deutsche Wetterdienst

(DWD Braunschweig and DWD Freising). In Groß

Lüsewitz, the data were provided by biovativ GbmH.

Wind speed and direction were measured at 2 m above

soil surface. Air temperature and precipitation as well

as air humidity were recorded.

2.7 Data Analysis

The average results of 20 plants per assessment and

harvest point within each plot in two years were

visualised by using the software Origin 8.1.

3. Results

3.1 Experimental Years

The two experimental years differed tremendously.

2009 was characterised by a higher mean temperature

in Braunschweig (10.0 °C), Freising (8.7 °C) and

Groß Lüsewitz (8.8 °C) compared to the local

long-standing mean temperature (9.3 °C, 7.5 °C,

8.3 °C; Figs. 2a-2c). Temperature peaks appeared in

July and August at each location. The annual

precipitation was similar to the mean values in

Braunschweig (619 mm vs. 628 mm). The rainfall

measured in Freising was about 30 mm above average

(820 vs. 788 mm), whereas in Groß Lüsewitz


389

Fig. 2a Long-standing annual precipitations and average temperatures compared with 2009 and 2010 data from Braunschweig (prec.: precipitation; temp.: temperature).

Fig. 2b Long-standing annual precipitations and average temperatures compared with 2009 and 2010 data from Groß Lüsewitz (prec.: precipitation; temp.: temperature).

Fig. 2c Long-standing annual precipitations and average temperatures compared with 2009 and 2010 data from Freising (prec.: precipitation; temp.: temperature).


390

rainfall rates were 40 mm below the long-standing

mean.

For the outcome of the field trials, the period

between April and August between sowing and the

end of the flowering period is important. In April

2009, weather conditions were satisfactory in

Braunschweig and Groß Lüsewitz. Temperatures and

precipitations were comparable to the long-standing

means. In Freising, it was about 4 °C warmer and

more humid. The following months were similar to

the long-standing weather conditions. Hence, seed

emergence succeeded and the crop developed equally

at any location.

2010 was generally colder and wetter than in the

long-standing mean which was clearly shown in

Braunschweig with a 1 °C lower mean temperature

and a precipitation increase of 122 mm. Especially in

May, when the maize started to grow, 3 °C lower

temperatures and heavy rainfall rates occurred. Just

before onset of flowering, temperatures raised up to

3.5 °C above the long-standing mean in July. A

similar situation was measured in Groß Lüsewitz with

temperatures of 0.8 °C below, and rainfall of 53 mm

above the long-standing mean. Therefore, vegetation

began late and crops did not develop equally. The

flowering period started about five days later than in

2009, and flowering was generally inhomogeneous.

As in Braunschweig, mean temperatures were 3.5 °C

above the long-standing mean in July.

In Freising, temperatures were comparable to the

mean, and a 62 mm higher precipitation was measured.

The plants developed more equally than in

Braunschweig and Groß Lüsewitz without important

delays. In July, at the onset of flowering, mean

temperatures measured 3 °C above the long-standing

mean.

3.2 Flowering Period

Depending on the mild 2009 climate in Freising,

flowering occurred efficiently. Male flowering of CMS

hybrids and “Delitop” started about 90 days after

sowing and was finished after 97 days (Fig. 3). In the

same year, the tassels of the CMS maize hybrids in

Braunschweig bloomed between 92 and 111 days after

sowing. BBCH 65 (main pollen shedding) laid about

100 days after sowing except for “Zidane” where main

pollen shedding developed faster (95-97 days after

sowing). In Groß Lüsewitz vegetation started later and

tassel development varied according to the genotype.

The CMS hybrids bloomed between 96 and 117 days

after sowing. BBCH 65 was reached after 105 days on

average. Flowering synchronisation between pollen

shedding of the hybrids and silking of the white maize

was generally ascertained. Male flowering of pollen

donor and pollen acceptor plots, respectively,

developed within the same period.

Depending on the weather conditions, plant

development in 2010 was delayed and unbalanced in

Braunschweig and Groß Lüsewitz. Therefore, the

flowering time was long and the development stages of

maize plants differed within one plot. In Braunschweig

tassels of the CMS hybrids as well as the control hybrid

began blooming after 91 days, and flowering lasted up

to 115 days after sowing. The growth stage BBCH 65

was reached after about 101 to 108 days after sowing.

Silking of the white maize began 5 to 7 days later and

ended up to 130 days after sowing. The latest crop

development was observed in Groß Lüsewitz and took

between 97 and 124 days after sowing; the main pollen

shedding occurred between 105 and 115 days after

sowing. The crop was generally badly developed and

extremely irregular grown. Silking of the white maize

was delayed up to 10 days. Therefore, synchronisation

between pollen shedding of donor plants and silking of

receptor plants was weak.

In Freising, flowering conditions were comparable

with 2009. The plants developed more equally than at

the two other locations. Based on the average

temperature and slightly higher precipitation, the male

flowering of the CMS maize hybrids and “Delitop”


391

Fig. 3 Main flowering periods of tassels of the CMS maize hybrids (DSP2, Torres and Zidane) and the fully fertile control variety (Delitop) as well as ears of white maize at Braunschweig, Groß Lüsewitz and Freising in 2009 and 2010 (mB: male flower; wB: female flower; FR: Freising; BS: Braunschweig; GL: Groß Lüsewitz).


392

took place between 84 and 101 days after sowing. The

main pollen shedding period of the CMS maize

hybrids was between 90 and 93 days, while main

pollen shedding of “Delitop” lasted up to 98 days after

sowing. In general, tassels of the pollen donor and

ears of the recipient occurred synchronously.

3.3 CMS Stability

In both growing seasons, no CMS hybrid was 100%

sterile at any location but differences between the

levels of sterility were identified. In 2009, the highest

level of CMS stability was detected for “Torres”,

CMS S-cytoplasm, within all environments. “Torres”

developed partly restored tassels (99%) with a small

amount of pollen in Braunschweig (Table 2). In Groß

Lüsewitz, 80% partly restored and 20% fertile tassels

were observed but pollen developed very scarce.

Self-pollination of “Torres” resulted in a mean kernel

set (MKS) of less than 1% kernel per cob without

differences between the locations. No environmental

impact on tassels depending on the location was found

for “Zidane” either (CMS S-cytoplasm). Partly

restored and fertile tassels were found in

Braunschweig and Groß Lüsewitz. The pollen

developed was vital, and a relatively large proportion

of kernels developed after self-pollination (MKS Table 2 Tassel characteristics and pollen development and vitality of CMS maize hybrids (DSP2, Torres and Zidane) at Braunschweig, Groß Lüsewitz and Freising in 2009 and 2010.

CMS hybrid Location Tassel (%) Pollen (%)

MKS (%) pollen vitality

2009 2010 2009 2010 2009 2010

DSP2

Braunschweig

Sterile 96 98 No 96 99

8.6 Partly restored 3 1 Few 3 1 0.2

Fertile 1 1 Many 1 0

Groß Lüsewitz

Sterile 5 76 No 10 76

0.0 Partly restored 87 22 Few 78 24 40


Freising

Sterile n.s. 96 No n.s. 96

1.7 Partly restored n.s. 4 Few n.s. 4 81

Fertile n.s. 0 Many n.s. 0

Sterile 1 7 No 13 39 0.0

Torres

Braunschweig Partly restored 99 92 Few 87 61* 0.7


Groß Lüsewitz

Sterile 0 1 No 12 3

3.1 Partly restored 80 98 Few 87 96 0.0


Freising


0.4 Partly restored n.s. 97 Few n.s. 0 0.2


Sterile 0 0 No 0 0 1.6

Zidane

Braunschweig Partly restored 58 59 Few 33 87 20


Groß Lüsewitz

Sterile 0 0 No 0 0

6.9 Part rest 51 87 Few 57 87 44


Freising


4.1 Partly restored n.s. 98 Few n.s. 95 44


n.s. = not specified; * = very few.


393

20%-40%). Contrary to the results of the previous

experiments, the CMS maize hybrid “DSP2” (CMS

T-cytoplasm) developed different tassels at different

locations. In Braunschweig, the majority of plants

were sterile (96% at the assessment points), except

single plants with fully fertile tassels and a lot of

pollen, equally spread within the plot. These plants

did not occur at the assessment points and were,

therefore, not measured. Nearly no kernel was

produced after self-pollination. Mainly partly

restored tassels (87%) with a small amount of pollen

(78%) but a MKS of 40% was measured in Groß

Lüsewitz. In Freising, the majority of plants

developed fertile tassels containing a lot of vital

pollen (observed but not measured), and a MKS of

80% was measured. To prove whether environmental

impacts of seed impurity caused partly restored or

fertile DSP2 tassels, DNA extractions of leaf

material and qualitative PCRs [27] were carried out.

100 seeds were germinated in the greenhouse, and

leaves were used for analysis. All 100 plants

possessed the CMS T-type of the DSP2 plants and

seed purity could be proven (data not shown).

In 2010, all CMS maize hybrids developed their

tassels similarly at the different locations. “Torres”

developed mainly partly restored tassels (92%-98%).

No pollen was developed at all in Freising while in

Groß Lüsewitz a small amount of pollen was found

(96%). Compared with results from 2009 there was a

difference within the ranking of “few” (Table 2) in

Braunschweig. In 2010, a much smaller amount of

pollen was developed than in 2009. “Zidane”

developed comparably at all locations. The majority of

the tassels expressed fluctuated tassels (59%-98%)

with a small amount of pollen (87%-95%). At all

locations, “DSP2” developed mainly sterile tassels.

Partly restored and sometimes fertile tassels were

observed, equally distributed over the whole plots.

The tassels developed no or only a little pollen. The

pollen vitality of all three CMS maize hybrids resulted

only low rates of MKS compared to 2009.

Summarising the tassel developments in both

experimental years, the highest stability of sterility

was estimated for “Torres”, and the highest variability

could be detected for “DSP2”. The pollen vitality of

“DSP2” and “Zidane” was mainly influenced by the

experimental year.

3.4 Cross-Pollination

In both experimental years, the cross-pollination

of the CMS maize hybrids and the control variety

“Delitop” differed considerably at all locations. In

2009, higher cross-pollination rates were measured

than in 2010, resulting from the weather conditions

in both years. Influenced by the flowering period and

delayed crop development as well as the locally

reduced synchronisation in flowering, combined with

lower wind speeds in 2010 (Braunschweig: 2.5 m s-1,

2009: 2.9 m s-1; Groß Lüsewitz: 2.2 m s-1, 2009: 2.3

m s-1; Freising: 1.5 m s-1; 2009: 1.8 m s-1),

cross-pollination was relatively low (see data for

“Delitop”; Figs. 4a and 4b, Tables 3a and 3b).

The geographical position of the trial sites should

be taken into account when cross-pollination rates are

compared. According to the higher wind speeds in

both years, the highest cross-pollination rates of

“Delitop” (on average of the whole plot: 12.8% in

2009, 7.2% in 2010) were measured in Braunschweig

compared to Freising (mean 2009: 4.8%; 2010: 5.1%)

and Groß Lüsewitz (mean 2009: 4.8%; 2010: 2.6%).

As expected, cross-pollination decreased with higher

distances to the pollen donor field. In Braunschweig,

in 2009, an out-crossing rate from “Delitop” of 62.2%

was measured in the first row and after 3.5 m distance

to the donor plot, respectively, and was already

reduced to 13.6% after further 3 m. At 35.25 m and

68.25 m distance to “Delitop”, cross-pollination rates

of 4.4% and 1.1%, respectively, were found. Lower

cross-pollination rates of “Delitop” were detected in

Freising with 21.6% and Groß Lüsewitz with 27.3%

in the first row of the recipient plot. At 52 m, only

0.5% out-crossing of “Delitop” was found in Freising,


394

Fig. 4a Distribution and cross-pollination rates of CMS-maize hybrids (DSP2, Torres and Zidane) and the fully fertile control variety Delitop as well as wind regimes during flowering in Braunschweig, Groß Lüsewitz and Freising in 2009 (WH = wind hours).


395

Fig. 4b Distribution and cross-pollination rates of CMS-maize hybrids (DSP2, Torres and Zidane) and the fully fertile control variety Delitop as well as wind regimes during flowering in Braunschweig, Groß Lüsewitz and Freising in 2010 (WH = wind hours).


396

Table 3a Mean values and standard deviations of the cross-pollination data in 2009.

Distance to pollen donor (m) 3.50 6.50 11.00 14.75 19.25 30.25 35.75 52.25 68.75

Braunschweig

Delitop

MV 62.20 14.20 14.30 6.65 8.50 4.41 4.60 1.86 1.13

SD 2.07 1.57 3.91 2.84 2.33 2.18 2.59 1.00 0.18

DSP2

MV 12.50 1.46 0.65 0.26 0.24 0.24 0.26 0.35 0.15

SD 2.42 0.56 0.26 0.09 0.03 0.15 0.15 0.09 0.06

Torres

MV 0.89 0.16 0.12 0.21 0.21 0.11 0.11 0.12 0.12

SD 0.17 0.04 0.02 0.10 0.14 0.05 0.02 0.03 0.05

Zidane

MV 6.63 1.02 0.89 0.96 1.68 0.61 0.66 0.59 0.64

SD 1.63 0.34 0.18 0.16 0.62 0.05 0.39 0.27 0.24

Groß Lüsewitz

Delitop

MV 27.30 2.34 7.47 3.01 1.57 0.70 0.57 0.14 0.20

SD 10.10 1.63 2.10 1.03 1.01 0.54 0.25 0.07 0.19

DSP2

MV 6.74 1.16 0.42 0.14 0.18 0.04 0.13 0.07 0.05

SD 1.50 0.81 0.13 0.02 0.13 0.03 0.09 0.05 0.04

Torres

MV 0.49 0.07 0.03 0.08 0.06 0.06 0.04 0.06 0.03

SD 0.08 0.04 0.02 0.03 0.04 0.04 0.03 0.05 0.02

Zidane

MV 2.47 0.32 0.22 0.24 0.14 0.12 0.08 0.09 0.11

SD 0.50 0.21 0.11 0.13 0.13 0.21 0.08 0.08 0.06

Freising

Delitop

MV 21.60 6.95 3.71 3.31 3.10 1.79 1.41 0.50 1.10

SD 5.62 0.49 0.69 0.70 1.07 0.55 0.33 0.12 0.33

DSP2

MV 11.20 1.19 0.72 0.44 0.54 0.25 0.20 0.12 1.10

SD 3.25 0.30 0.08 0.16 0.24 0.03 0.05 0.04 0.03

Torres

MV 0.60 0.18 0.18 0.14 0.20 0.18 0.17 0.16 0.14

SD 0.16 0.09 0.08 0.05 0.03 0.03 0.05 0.06 0.03

Zidane

MV 11.70 1.38 0.99 0.67 0.51 0.34 0.33 0.30 0.23

SD 2.13 0.19 0.20 0.21 0.19 0.04 0.13 0.11 0.08

MV, mean value; SD, standard deviation.


397

Table 3b Mean values and standard deviations of the cross-pollination data in 2010.

Distance to pollen donor [m] 3.50 6.50 11.00 14.75 19.25 30.25 35.75 52.25 68.75

Braunschweig

Delitop

MV 45.33 7.49 3.95 2.70 2.55 1.19 0.60 0.42 0.32

SD 3.46 1.75 1.61 0.87 0.46 0.34 0.24 0.11 0.13

DSP2

MV 3.19 0.26 0.21 0.17 0.13 0.15 0.36 0.06 0.15

SD 1.79 0.13 0.08 0.05 0.03 0.11 0.43 0.02 0.06

Torres

MV 0.27 0.11 0.09 0.09 0.10 0.08 0.09 0.05 0.08

SD 0.14 0.09 0.02 0.02 0.06 0.09 0.04 0.04 0.04

Zidane

MV 0.98 0.23 0.31 0.28 0.39 0.28 0.14 0.19 0.20

SD 0.18 0.80 0.11 0.09 0.14 0.09 0.11 0.07 0.17

Groß Lüsewitz

Delitop

MV 16.40 4.34 1.13 0.48 0.18 0.17 0.14 0.05 0.04

SD 4.02 1.14 0.37 0.16 0.02 0.08 0.05 0.02 0.03

DSP2

MV 1.37 0.33 0.15 0.09 0.06 0.08 0.06 0.02 0.05

SD 0.65 0.08 0.05 0.02 0.02 0.04 0.03 0.01 0.04

Torres

MV 0.37 0.32 0.31 0.29 0.16 0.25 0.22 0.09 0.06

SD 0.06 0.16 0.13 0.23 0.06 0.10 0.04 0.11 0.02

Zidane

MV 1.15 0.44 0.28 0.31 0.16 0.89 0.36 0.14 0.08

SD 0.47 0.12 0.14 0.18 0.17 0.89 0.12 0.07 0.04

Freising

Delitop

MV 25.80 7.77 3.51 3.41 3.25 2.26 1.38 1.25 1.01

SD 6.92 2.30 1.12 1.06 0.56 1.09 1.03 0.95 0.78

DSP2

MV 2.07 0.13 0.35 0.40 0.25 0.05 0.14 0.04 0.03

SD 1.11 0. 03 0.42 0.57 0.25 0.05 0.18 0.03 0.03

Torres

MV 0.53 0.15 0.08 0.15 0.15 0.30 0.20 0.22 0.11

SD 0.18 0.15 0.06 0.15 0.09 0.33 0.24 0.33 0.12

Zidane

MV 1.75 0.50 0.30 0.35 0.31 0.25 0.25 0.25 0.24

SD 0.78 0.36 0.30 0.16 0.24 0.14 0.18 0.23 0.18

MV, mean value; SD, standard deviation.

and already after 30.25 m 0.7% cross-pollination was

detected in Groß Lüsewitz. A similar situation but

lower out-crossing rates were measured in 2010. At 35

m distance to the “Delitop” plot the cross-pollination

rate was below 1.0% in Braunschweig and Freising.

This rate was already reached at a distance of 14.75 m

in Groß Lüsewitz.

Comparing the 2009 CMS maize hybrids, the

highest cross-pollination rate was detected for “DSP2”

(on average 1.0%-1.8% of the whole plot), and the

lowest for “Torres” (< 0.2%) at all locations (Fig. 4a

and Table 3a). The highest values were measured in


398

the first pollen recipient plot of “DSP2” in

Braunschweig (12.6%) with a strong decrease (1.4%

at 6.5 m and < 1% at 11 m). This decrease was also

found in Freising and Groß Lüsewitz and for “Zidane”

at all locations on a lower level. In 2010, the lowest

cross-pollination rates were measured for “Torres”

again (0.1%-0.2%). Differences between “DSP2” and

“Zidane” were small. The values varied between 0.3%

and 0.5%. In Freising and Groß Lüsewitz,

out-crossing from “Zidane” was even slightly higher

than “DSP2” (Fig. 4b and Table 3b). At a distance of

6.5 m to the pollen donor plot, all cross-pollination

rates were below 1% for all CMS maize hybrids.

3.5 Reduction of Cross-Pollination

In relation to the conventional fully fertile maize

hybrid “Delitop” cross-pollination of the CMS maize

hybrids was strongly reduced. Within the first 30 m of

the white maize plots, the area of the highest

out-crossing potential, the cultivation of “Torres”

reduced cross-pollination by 96.5% in 2009 and

88.9% in 2010, respectively, on average of all three

locations (Table 4). With “Zidane”, a reduction of

83.7% (2009) and 84.4% (2010) on average and

“DSP2” of 84.2% (2009) and 89.9% (2010) on

average was realised. Except for “Zidane”, the highest

reductions of out-crossing were found for

Braunschweig in both trial years which can be clearly

seen in the first row at 3.5 m distance to the pollen

donor plot.

Depending on the generally low cross-pollination

rates of Torres, the cross-pollination reduction was

consistently high from 3.5 m to 30.25 m distances and

was mainly above 95% at the different distances

within one plot. The two other CMS maize hybrids

showed an increasing reduction of cross-pollination

from 6.5 m onwards based on the higher

cross-pollination rates at 3.5 m distance to the pollen

donor plots in 2009. These effects were more balanced

in 2010, depending on the lower out-crossing rates.

Although these values are very satisfactory at the

first instant, no CMS maize hybrid could realise a

cross-pollination reduction of 100%.

4. Discussion

The objective of this study was to verify whether

CMS is a reliable confinement tool for the cultivation

of GM maize. The reliability of the CMS trait was

tested in three different environments in Germany and

data on the stability and reliability of the CMS trait for

confinement purposes were collected.

The relatively good growing conditions at all

locations in 2009, closely linked to the long-standing

mean temperatures and precipitations, allowed for

satisfactory crop development in an appropriate and

expected time scale. Contrary, the weather conditions

in 2010 were poor and crop development delayed

resulting in longer flowering periods and an

unsatisfactory synchronisation of male and female

flowers in donor and recipient plots, particularly in

Groß Lüsewitz and Braunschweig. Especially, the

temperature during germination and juvenile

development of the plants is vital. Delays in crop

development are highly expectable if temperatures

decrease below 10 °C for several days [28]. In May

2010, this situation occurred in Braunschweig and

Groß Lüsewitz. Temperatures in Freising were similar

to the long-standing mean temperature. Water

availability was not a critical point even if it was dry

at sowing and wet during the juvenile development in

May at all locations.

In both experimental years, no CMS maize hybrid

developed 100% sterile tassels, but differences in the

restoration of fertility were assessed. Generally, the

CMS effect, which is caused by a mitochondrial

dysfunction, can be compensated by restorer of

fertility genes (Rf genes) [11]. This compensation can

result in partly restored or fertile tassels with more or

less vital pollen. This fact is described in a number of

publications and explained as nucleo-mitochondrial

conflict which leads to gynodioecy, a co-occurrence

of female and hermaphroditic individuals within one


399

Table 4 Reduction of cross-pollination by using CMS maize hybrids (DSP2, Torres and Zidane) in comparison to a conventional and fully fertile maize hybrid (Delitop = 100%) in (a) 2009 and (b) 2010 at Braunschweig, Groß Lüsewitz and Freising.

(a) 2009 Distance to pollen donor (m)

3.50 6.50 11.00 14.75 19.25 30.25

DSP2 MW

Braunschweig -79.82 -89.90 -95.42 -93.48 -97.15 -94.65 -91.73

Groß Lüsewitz -74.16 -55.58 -95.18 -94.52 -86.50 -91.69 -82.94

Freising -48.29 -82.92 -80.48 -86.85 -82.72 -85.98 -77.87

MW -67.42 -76.13 -90.36 -91.62 -88.79 -90.77 -84.18

Torres

Braunschweig -98.57 -98.85 -98.90 -96.84 -97.51 -97.51 -98.03

Groß Lüsewitz -98.24 -96.41 -99.60 -97.48 -96.44 -91.74 -96.65

Freising -97.20 -97.41 -95.05 -95.92 -93.58 -89.84 -94.83

MW -98.00 -97.56 -97.85 -96.74 -95.84 -93.03 -96.50

Zidane

Braunschweig -89.33 -92.18 -92.39 -85.48 -80.25 -86.22 -87.64

Groß Lüsewitz -88.73 -81.52 -97.46 -93.63 -96.70 -78.92 -89.49

Freising -45.87 -80.17 -73.30 -79.84 -83.57 -81.22 -74.00

MW -74.64 -84.62 -87.71 -86.32 -86.84 -82.12 -83.71

(b) 2010 Distance to pollen donor [m]

3.50 6.50 11.00 14.75 19.25 30.25

DSP2 MW

Braunschweig -92.96 -96.48 -94.32 -93.22 -94.84 -87.81 -93.27

Groß Lüsewitz -91.66 -92.44 -86.72 -80.46 -67.98 -83.85

Freising -91.64 -98.31 -88.33 -86.96 -92.00 -97.40 -92.44

MW -92.09 -95.74 -89.79 -86.88 -84.94 -92.60 -89.85

Torres

Braunschweig -99.25 -98.52 -97.74 -96.55 -95.87 -91.55 -96.58

Groß Lüsewitz -97.76 -92.60 -72.48 -39.36 -75.55

Freising -97.88 -98.05 -97.38 -94.91 -95.16 -83.21 -94.43

MW -98.29 -96.39 -89.20 -76.94 -95.52 -87.38 -88.85

Zidane

Braunschweig -97.84 -96.95 -92.20 -88.89 -84.54 -76.62 -89.51

Groß Lüsewitz -92.98 -89.75 -75.36 -35.88 -73.49

Freising -93.66 -93.46 -89.90 -88.49 -89.93 -85.65 -90.18

MW -94.82 -93.39 -85.82 -71.09 -87.24 -81.14 -84.39

MV = mean value.

population [14]. Apart from that, environmental

conditions can affect maize with respect to partial

restoration of male fertility [7, 8, 20-23, 29-31]. The

data presented revealed differences in the

development of tassels and the release of pollen

according to the location and the year, which were

dependent on the genotype.

The CMS-T-maize hybrid “DSP2” developed all

forms of tassels, depending on the location and

weather conditions of the years. CMS-T-cytoplasm is

considered to provide the most reliable male sterility

[7] but exceptions are known. Generally, two

dominant and jointly acting Rf genes are essential for

the restoration of fertility, Rf1 and Rf2. Especially, the

Rf1 allel affects the transcription of the responsible

mitochondrial gene (T-urf13) and leads to pollen

fertility [32]. This process can only happen in the

presence of Rf2. Dominant alleles of other Rf genes


400

like Rf8 and Rf* which were detected by Dill et al. [33]

can compensate the Rf1 gene in the presence of Rf2.

These genes are rare in T-cytoplasms of maize, and

their expression is affected by the environment and

results in a few fertile or partly fertile plants in one

population [7]. The fact that in Braunschweig only a

few individuals of “DSP2” restored to fertility can

lead to the conclusion that the minor Rf8 gene was

involved in this process as described by Dill et al. [33].

Weider et al. [7] who tested “DSP2” as well but on a

smaller scale, described a slightly unstable behaviour

of sterility, but reversion to fertility occurred also only

a few times across all environments. Different to this,

a stronger response of “DSP2” to weather conditions

was found in Freising and Groß Lüsewitz, where

partly restored and fertile tassels appeared in 2009 but

mainly sterile tassels were found in 2010. The related

MKS data of “DSP2” underlined this weather impact

slightly because much higher rates were measured in

2009 than in 2010. The existing pollen is, therefore,

viable depending on the sporophytic T-cytoplasm as

described by Dill et al. [33]. Weider et al. [7] revealed

that the MKS values of “DSP2” decrease when

temperatures increase and, therefore, correspond with

the results from Groß Lüsewitz and Freising, where

MKS values were low and the temperatures increased

a short time before the onset of anthesis.

In both years, the CMS-S-types “Torres” and

“Zidane” developed partly restored and fertile tassels

at all three locations. “Torres” developed the smallest

amount of pollen which was mainly sterile, while

“Zidane” developed fluctuated and fertile tassels and

released explicitly more vital pollen. Hence, the

sterility of this cytoplasmic type is classified as being

unstable [34, 35]. Compared to the T-cytoplasm, the

restoration in S-cytoplasms is generally more complex

which is likely depending on the dominant Rf3

restorer gene and a large number of further

spontaneously occurring Rf genes and more than 60

restoring allele mutations [34, 36, 37]. The Rf3 gene is

not environmentally sensitive [38] compared to the

recently identified Rf9 gene [38]. Especially moderate

temperatures were positively affecting the expression

of Rf9 compared to higher temperatures. Therefore, a

higher level of Rf9 gene expression in “Zidane” could

be expected, especially in 2009 when this hybrid

developed large amounts of pollen per tassel. “Torres”

stayed more sterile, even when partly restored tassels

were detected. Possibly more Rf3 genes were involved

in the restoration process.

At all locations and for all CMS maize hybrids, the

development of vital pollen was depending on the year.

Higher MKS values were detected in 2009 than in

2010. This phenomenon might be explained by the

sensitivity of rf gene activation or inactivation to

environmental impacts and temperatures just before

anthesis [7]. In the first half of July 2010, the air

temperatures raised by 3 °C and 3.5 °C, respectively,

above the long-standing average temperature at all

trial locations. In general, low quantities of pollen

were produced by all CMS maize hybrids and,

consequently, MKS values were very low as well.

This indicates an influence of air temperature just

before anthesis on the restoration of fertility on both

T- and S-cytoplasm. Weider et al. [7] studied the

period of 10 days before anthesis to clarify whether

different climatic factors affect the MKS of several

CMS hybrids. They found positive as well as negative

correlations between the MKS and different climatic

factors, but a rule for interactions could not be

detected. Duvick [29] and Tracy et al. [30] already

assumed that humid and cool conditions cooperate in

restoration of fertility, whereas dry and hot conditions

maintain sterility. The influence of high temperatures

was described for other crops as well. Increasing rates

of sterility of CMS cotton plants were found with

increasing temperatures and day length [21]. This

might not only be caused by Rf expression but also by

toxin production [39] which affects the CMS trait. In

experiments with sorghum, Elkonin et al. [40]

revealed that variations of precipitation up to three

weeks before the beginning of anthesis correlate


401

positively in the expression of fertility restoring genes

with water availability. Elkonin et al. [40] described

that following a wet season, the percentage of fertile

and partially fertile plants was significantly higher

than in drought seasons. This suggests that water

limiting conditions prevent the expression of restorer

genes resulting in a stable sterility.

In our study, the stability of the CMS trait of maize

hybrids was tested under large-scale and practical

agricultural conditions for the first time. Thus, no

comparable data of cross-pollination rates are

available in the scientific literature.

Very low cross-pollination rates of the CMS-maize

hybrids were found in both experimental years and at

all locations. The maximum pollen spread was

measured for “DSP2” at Braunschweig in 2009, where

12.6% cross-pollination was found in the first row of

the recipient plot. The values decreased rapidly and

were already below 1% at 11 m distance to the pollen

donor plot. All other cross-pollination rates ranged

below these, particularly for “Torres” based on very

low pollen releases. The data presented are based on a

visual detection system where yellow kernels in white

maize cobs were counted.

In relation to the fully fertile variety “Delitop”, all

CMS maize hybrids provided a strong reduction of

cross-pollination which varied slightly between 2009

and 2010, due to the weather conditions and crop

development. Generally, the reduction was on average

highest for “Torres” (up to 99%) and the lowest for

“Zidane” (84%). The reduction decreased with further

distances to the pollen donor plot. According to these

results, CMS maize hybrids provide efficient

confinement for pollen-mediated gene flow.

The choice of an appropriate CMS maize hybrid

should depend on the trait and the purpose of its

release to the environment. The T-cytoplasm is no

longer used for breeding due to its sensitivity to the

fungal pathogen Bipolaris maydis [7]. Apart from the

CMS-C-type which is the most widely applied form of

CMS today [41], it is also possible to cultivate

CMS-S-types successfully. A number of interesting

S-cytoplasms existed that produce only a very small

amount of viable pollen [7] and could be used for

confinement purposes. Thus, it may be concluded that

CMS can be a useful confinement tool when used in

carefully selected genotypes and accurately tested for

stability. Wang et al. [42] recently developed a system

for producing plant-made pharmaceuticals (PMP) in

CMS maize by using CMS-T-cytoplasm lines. It is not

developed with CMS maize hybrids yet. A successful

cultivation of GM CMS-maize hybrids requires a

sufficient pollination of the plants by admixing a

male-fertile and non-GM pollen donor [43]. If the

CMS maize hybrid and the pollinator plant provide a

different genetic background, yield can be

significantly increased [26, 44, 45]. The so-called

Plus-Hybrid-Effect [43, 46] combines the potential

benefits of CMS and a Xenia effect. Hence, pollen

confinement combined with yield increase offers the

potential for a successful cultivation of GM maize.

Currently, it is recommended to grow 80:20 mixtures

of GM:CMS hybrids and male fertile non-GM hybrids

for obtaining sufficient yields [44]. Studies being

performed in the frame of an EU-funded project

(www.price-coexistence.com) will provide further

data to precise the current recommendations.

Summarising the data presented, it becomes

obvious that efficient confinement strategies can be

developed by exploring the CMS trait. For example,

depending on the CMS maize hybrids explored,

isolation distances between neighbouring GM and

non-GM maize fields could be strongly reduced to a

maximum 10 m to be in line with the European

coexistence requirements based on a labelling

threshold of 0.9%.

5. Conclusions

Cultivation of the CMS maize hybrids tested in our

study can be proposed as a useful tool for

cross-pollination reduction. The out-crossing potential

of traits into neighbouring maize crops can be


402

drastically reduced.

The behavior and development under several

environmental conditions should be known before

selecting the appropriate CMS maize hybrid for

combinations with GM traits. More knowledge is

required on terms and conditions of the expression of

Rf genes and their sensitivity towards environmental

factors. Depending on the GM trait and the purpose of

the environmental release, CMS as a reliable

biological confinement method for GM maize might

be combined with other confinement methods, e.g.,

small isolation distances, buffer zones or border zones

of non-GM maize [6, 47-50] or variations in flowering

behavior which could be influenced by growing

varieties of different ripening groups and/or choosing

different sowing dates [51, 52]. The co-cultivation

with a sufficient quantity of a non-related, non-GM

male fertile maize is necessary for gaining sufficient

yield.

Acknowledgments

The project was kindly funded by the Federal

Ministry of Education and Research, BMBF (Project

No.: 0315 210 D).

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Evaluation of Fungicides for Controlling Stem Rust Race

Ug99 on Bread Wheat

Joseph Kinyoro Macharia1, Ruth Wanyera2 and Samuel Kilonzo2

1. Department of Crops, Horticulture and Soils, University of Egerton, Njoro 536-20115, Kenya

2. Kenya Agricultural Research Institute (KARI)-Njoro, Njoro 20107, Kenya

Received: February 9, 2013 / Published: May 20, 2013. Abstract: Stem rust race Ug99, also designated TTKSK (Puccinia graminis f. sp. tritici) cause stem or black rust, which is a serious disease of wheat worldwide. Field experiments were conducted at two sites during 2008 and 2009 growing seasons to evaluate the effectiveness of two new foliar fungicides: viz. Nativo 300 SC (trifloxystrobin 100 g L-1 + tebuconazole 200 g L-1) and Prosaro 250 EC (prothioconazole 125 g L-1 + tebuconazole 125 g L-1), in controlling stem rust on susceptible wheat cultivar Duma. AmistarXtra 280 SC (azoxystrobin 200 g L-1 + cyproconazole 80 g L-1) and Folicur 250 EC (tebuconazole) were used as checks. The treatment at each site and year included non-treated control and two spray applications of the fungicides at growth stages (GS) 55 (heading) and 65 (flowering). Stem rust severities were scored using the modified Cobb scale at 14-day intervals after application. The data were used to calculate mean rust severity (MRS). Stem rust epidemics were severe at KARI-Njoro in 2008 and the treatment effects on stem rust severities, grain yield and 1,000 kernel weights were significant at both KARI-Njoro and Mau-Narok sites. The fungicide treatments, significantly (P ≤ 0.05) reduced stem rust severity, increased grain yield and 1,000 kernel weight of the susceptible wheat cultivar Duma compared to the non-treated control. Both fungicides: Nativo 300 SC and Prosaro 250 EC applied at the rate of 1.0 L ha-1 were recommended for commercial use.

Key words: Stem rust, wheat (Triticum aestivum L.), fungicide.

1. Introduction

Stem or black rust, caused by Puccinia graminis

Pers. f. sp. tritici Eriks. and E. Henn., is a periodically

devastating disease of wheat (Triticum aestivum L.)

worldwide [1, 2]. The disease had been controlled

effectively through widespread growing of resistant

cultivars [3]. Following the re-emergence of an

aggressive and highly virulent race Ug99 detected in

Uganda in 1999 [4], also designated as TTKSK based

on the North American nomenclature [2, 5] and the

subsequent isolation of other variants within the Ug99

lineage in Kenya, poses a serious threat to the existing

wheat cultivars worldwide. Kenya is designated as a

“hotspot” for stem rust because disease outbreaks

occur regularly due to favorable environmental

Corresponding author: Joseph Kinyoro Macharia, Ph.D.,

research fields: crop pathology and cereal rusts. E-mail: [email protected].

conditions [6]. For over 30 years genetic resistance

has provided adequate protection against stem rust

disease [7, 8]. However, the susceptibility of the most

wheat cultivars and heavy yield losses exceeding 80%

[9] incurred by farmers has entailed the adoption of an

integrated mitigation strategy. Therefore, the

evaluation of the available fungicides for efficacy

against the stem rust pathogen is necessary.

Fungicide application has become an integral part

of wheat production in Kenya since the mutation of

stem rust race Ug99. However, the number of

fungicides recommended for the control of stem rust

are few. This is because the effects of fungicides on

yield loss prevention are poorly understood and data

limited [10]. This paper reports field experiments

conducted under natural infection to determine the

efficacy of two new foliar fungicides, viz. Nativo 300

SC (trifloxystrobin 100 g L-1 + tebuconazole 200 g L-1)

DAVID PUBLISHING

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Evaluation of Fungicides for Controlling Stem Rust Race Ug99 on Bread Wheat

405

and Prosaro 250 EC (prothioconazole 125 g L-1 +

tebuconazole 125 g L-1) on stem rust severity, grain

yield and 1,000-kernel weight.


2.1 Materials

Field trials were conducted in 2008 and 2009 at

Kenya Agricultural Research Institute (KARI)-Njoro

and Mau-Narok (Purko Ranch), Kenya. The test

cultivar was Duma, which is popular and

recommended for low and medium elevation

growing-areas. The cultivar is highly susceptible to

stem rust, but is fairly resistant to other rusts. Stem

rust epidemics occurred naturally at both sites. A

randomized complete block design with four

replications was used. The cultivar Duma was planted

in 9 m2 plots (Table 1) using an experimental

seed-drill at a seeding rate of 100 g plot-1. A uniform

application of Di-ammonium phosphate fertilizer

(18% N: 46%; P: 0% K) was applied at planting at the

recommended rate of 150 kg ha-1. The plots were

sprayed with Stomp 500 E (pendimethalin), a

pre-emergent herbicide at the rate of 3 L ha-1, to

control grass weeds and Buctril MC (bromoxynil +

MCPA) at the rate of 1.25 L ha-1 at growth stage (GS)

24 (tillering) [11] to control broad leaf weeds.

Metasystox 250 EC (oxy-demeton-s-methyl)

insecticide was applied at the rate of 0.5 L ha-1 to

control cereal aphids. The fungicide treatments

included two new products: Nativo 300 SC

(trifloxystrobin 100 g L-1 + tebuconazole 200 g L-1)

and Prosaro 250 EC (prothioconazole 125 g L-1 +

tebuconazole 125 g L-1), each applied at three rates:

0.6, 0.75 and 1.0 L ha-1. Two standard fungicides:

AmistarXtra 280 SC (azoxystrobin 200 g L-1 +

cyproconazole 80 g L-1) and Folicur 250 EC

(tebuconazole), each applied at the rate of 1.0 L ha-1,

and non-treated control were used for comparison.

2.2 Methods

The fungicides were applied twice at GS 55 and 65

(Table 1) using a 15 L capacity knapsack sprayer and

recommended water volumes of 200 L ha-1. The

applications were on the stems and the flag leaf

canopy. The plots were monitored for the appearance

of stem rust and disease severities were scored on

whole plots using the modified Cobb scale [12] before

fungicide application, and at two 14-day intervals

following the application (Table 1). In 2008, the first

reading prior to fungicide treatment was done at GS

65 (flowering) and the second reading was 14-16 days

after the first treatment at GS 71 (seed water ripe).

The third reading was done at GS 77 (late milk). At

maturity, the plots were harvested using a Hans-Ulrich

Hege plot combine harvester (Type: Hege 125C.

Maschinenbau D 7112 Waldenburg/Wurtt-Hohebuch,

Table 1 Management activities for each of the four trials evaluating fungicides for efficacy against stem rust.

Management activity, GS* Trial

2008-2009 2009-2010

KARI-Njoro Mau-Narok KARI-Njoro Mau-Narok

Planting date: May 30 Sept. 19 May 16 Sept. 29

Fungicide application:

1st date at GS 55 Aug. 4 Nov. 15 Aug. 9 Dec. 15

2nd date at GS 65 Aug. 18 Nov. 30 Aug. 23 Jan. 2

Rust evaluation:

1st date at GS 65 Aug. 9 Oct. 4 July 24 Nov. 28

2nd date at GS 71 Aug. 23 Nov. 8 Aug. 7 Dec. 12

3rd date at GS 77 Sept. 8 Nov. 22 Aug. 21 Feb. 19

Harvesting: Nov. 6 Apr. 4, 2010 Oct. 31 Apr. 1, 2011

GS* = Growth Stage; GS 55 = heading, GS 65 = flowering, GS 71 = seed water ripe and GS 77 = late milk [11].


406

West Germany). Grain weight measurements were

taken after harvest and drying to 13% moisture

content. A sample of grain was taken from each plot

for determination of kernel weight based on the weight

of 1,000 grains.

2.3 Data Analysis

Data on disease severity, grain yield and 1,000

kernel weight were analyzed according to the analysis

of variance procedure using the SAS statistical

package (PROC-ANOVA), and differences in

treatment effects were compared at P ≤ 0.05 using the

least significant difference test [13, 14].


In 2008, stem rust at both KARI-Njoro and

Mau-Narok trials developed early in the growing

season; as a result, the mean rust severity (MRS) in

non-treated plots was 52.5% and 40.8%, respectively

(Table 2). In 2009, the MRS was moderate and the

MRS in non-treated control plots was 23.8% and

16.9%, respectively (Table 3). All the fungicide

treatments reduced stem rust on susceptible cultivar

Duma. Fungicide applications significantly (P ≤ 0.05)

reduced MRS compared to the non-treated control,

with Prosaro at 1.0 L ha-1, Nativo at 0.75 and 1.0 L

ha-1 and the standards (Folicur 250 EC and

AmistarXtra 280 SC), performing better than Prosaro

at 0.6 L ha-1, 0.75 L ha-1 and Nativo 300 SC at the

rate of 0.6 L ha-1 (Tables 2 and 3). The highest

disease severity reduction in 2008 was generally

observed in plots that were sprayed with Prosaro 250

EC at 1.0 L ha-1 (59.4%), Nativo 300 SC and

AmistaXtra 280 SC at 1.0 L ha-1 (55.6% each) at

KARI-Njoro and Prosaro 250 EC at 0.6 L ha-1

(75.7%), Prosaro 250 EC at 1.0 L ha-1 (75.5%) and

Nativo 300 SC at 1.0 L ha-1 (73.5%) at Mau-Narok.

In 2009, the highest disease severity reduction was in

plots sprayed with Folicur 250 EC at 1.0 L ha-1

(85.3%), followed by Prosaro 250 EC at 0.75 L ha-1

(82.6%) and 1.0 L ha-1 (77.8%) at KARI-Njoro and

Prosaro 250 EC at 0.6 L ha-1 (76.5%), Prosaro 250

EC at 1.0 L ha-1 (75.5%) and Nativo 300 SC at 1.0 L

ha-1 (73.47%) at Mau-Narok.

Table 2 Effect of fungicide treatments on stem rust severity, grain yield and 1,000 kernel weight on wheat cultivar Duma KARI-Njoro and Mau-Narok 2008.

KARI-Njoro Mau-Narok

Treatmente Stem rust severity Grain yield 1,000 kernel weight Stem rust severity Grain yield 1,000 kernel weight

Rate (L ha-1)

MRSa Reductionb

(%) (t ha-1)

Increasec

(%) (g)

Increasec

(%) MRSA Reductionb

(%) (t ha-1)

Increasec

(%) (g)

Increasec

(%)

Non-treated - 52.5 a - 0.5 b - 27.9 c - 40.8 a - 1.4 c - 29.4 c - Nativo 300 SC

0.6 31.3 b 40.4 1.1 a 54.5 33.4 b 19.7 14.7 bc 63.9 2.8 ab 50.0 39.3 ab 33.7

Nativo 300 SC

0.75 24.6 bc 53.1 1.2 a 58.3 35.9 a 28.7 11.3 bc 72.3 2.6 b 46.2 41.1 a 39.8

Nativo 300 SC

1.0 23.3 c 55.6 1.3 a 61.5 33.8 b 21.1 10.8 bc 73.5 2.6 b 46.2 38.2 ab 29.9

Prosaro 250 EC

0.6 25.4 bc 51.6 1.2 a 58.3 34.9 ab 25.1 9.9 c 75.7 3.3 b 75.6 41.0 a 39.5

Prosaro 250 EC

0.75 24.2 bc 53.9 1.1 a 54.5 34.7 ab 24.4 14.2 bc 65.2 2.5 b 44.0 37.4 b 27.2

Prosaro 250 EC

1.0 21.3 c 59.4 1.2 a 58.3 35.6 a 27.6 10.0 bc 75.5 2.4 b 41.2 38.4 ab 30.6

AmistaXtra 280SC

1.0 23.3c 55.6 1.1 a 54.5 33.6 b 20.4 15.4 bc 62.3 2.6 b 46.2 37.4 b 27.2

Folicur 250EC 1.0 25.4 bc 51.6 1.2 a 58.3 35.9 28.7 16.7 b 59.1 2.7 b 48.1 38.4 ab 30.6

Meand - 24.9 52.7 1.2 57.3 28.5 24.5 12.9 68.4 2.7 49.7 38.9 25.1

Lsd (0.05) - 7.2 - 0.2 - 1.7 - 6.7 - 0.5 - 3.0 - aMRS = mean rust severity (modified Cobb scale); breduction (%) = (non-treated MRS－fungicide-treated MRS) × 100 non-treated-1; cincrease (%) = (treated – non-treated) × 100 treated-1; dmean = mean of fungicide-treatments; etreatment means within columns followed by the same letter are not significantly different at P ≤ 0.05 according to least significant difference (LSD) test.


407

Table 3 Effect of fungicide treatments on stem rust severity, grain yield and 1,000 kernel weight on wheat cultivar Duma KARI-Njoro and Mau-Narok 2009.

KARI-Njoro Mau-Narok

Treatmente

Stem rust severity Grain yield 1,000kernel weight Stem rust severity Grain yield 1,000 kernel weight

Rate (L ha-1)

MRSa Reductionb

(%) (t ha-1)

Increasec

(%) (g)

Increasec

(%) MRSA Reductionb

(%) (t ha-1)

Increasec

(%) (g)

Increasec

(%)

Non-treated - 23.8 a - 1.0 c - 38.7 b - 16.9 ab - 2.2 d - 34.8 b - Nativo 300 SC

0.6 7.8 bc 67.4 1.8 b 44.4 43.0 a 10.0 12.5 abc 26.0 4.3 ab 48.8 46.4 a 25.0

Nativo 300 SC

0.75 6.5 bc 72.6 1.9 b 47.4 42.6 a 9.2 6.7 c 59.2 3.2 c 31.3 44.2a 21.3

Nativo 300 SC

1.0 6.9 bc 71.0 2.3 a 56.5 43.7 a 11.4 8.3 c 50.9 4.4 a 50.0 47.2 a 26.3

Prosaro 250 EC

0.6 8.9 b 62.6 2.1 ab 52.4 43.9 a 11.8 15.6 ab 7.7 3.6 bc 38.9 43.6 a 20.2

Prosaro 250 EC

0.75 4.1 bc 82.6 1.9 ab 47.4 43.2 a 10.4 18.1 a 7.1 4.3 ab 48.8 43.7 a 20.4

Prosaro 250 EC

1.0 5.3 bc 77.8 2.1 ab 52.4 42.9 a 9.8 11.9 bc 29.6 3.9 abc 43.6 46.9 a 25.8

AmistaXtra 280 SC

1.0 8.9 b 62.6 2.3 a 56.5 43.7 a 11.4 11.3 bc 33.1 4.2 ab 47.6 45.2 a 23.0

Folicur 250 EC

1.0 3.5 c 85.3 2.2 ab 54.5 42.7 a 9.2 9.4 c 44.4 4.3 ab 48.8 46.1 a 24.5

Meand - 6.5 72.7 2.1 54.1 43.2 10.4 11.8 32.3 4.0 44.7 45.4 23.3

Lsd (0.05) - 5.2 - 0.4 - 2.5 - 5.9 - 0.7 - 5.3 - aMRS = mean rust severity (modified Cobb scale); breduction (%) = (Non-treated MRS - fungicide-treated MRS) × 100/Non-treated;

cincrease (%) = (treated – Non-treated) × 100 Non-treated-1; dmean = mean of fungicide-treatments; etreatment means within columns followed by the same letter are not significantly different at P ≤ 0.05 according to least significant difference (LSD) test.

The fungicide treatment effect on grain yield and

1,000 kernel weight was significant (P ≤ 0.05) at the

two sites and years. In 2008, the highest grain yield of

1.3 t ha-1 was recorded in plots treated with Nativo

300 SC at 1.0 L ha-1, which was 61.5% higher than the

non-treated control at KARI-Njoro. This was followed

by Nativo 300 SC at 0.75 L ha-1 Prosaro 250 EC at 0.6

L ha-1 and 1.0 L ha-1, and Folicur 250 EC at 1.0 L ha-1,

which were 58.3% higher than the non-treated control.

Plots treated with Nativo 300 SC at 0.75 L ha-1 and

Prosaro 250 EC at 1.0 L ha-1 had the highest

1,000-kernel weights with 28.7% and 27.6% increases,

respectively, over the control. In Mau-Narok in the

same year, Prosaro 250 EC and Nativo 300 SC at the

rate of 0.6 L ha-1 and Folicur 250 EC at 1.0 L ha-1 had

the highest grain yields of 3.3 t ha-1, 2.8 t ha-1 and 2.7 t

ha-1, increases of 75.6%, 50% and 48.1%, over the

untreated control (Table 1). In 2009, treatments of

Nativo 300 SC, AmistarXtra 280 SC and Folicur 250

EC, all at 1.0 L ha-1, had the highest grain yields of

2.3 t ha-1 and 2.2 t ha-1. Plots treated with Prosaro 250

EC at 0.6 L, Nativo 300 SC and AmistarXtra 280 SC

at 1.0 L ha-1 had increased 1,000 kernel of 11.8% and

11.4% over the non-treated control at KARI-Njoro. In

Mau-Narok, treatments of Nativo 300 SC at 1.0 L ha-1,

Prosaro 250 EC at 0.75 L ha-1 and Folicur 250 EC at

1.0 L ha-1 had the highest grain yields of 4.4 t ha-1 and

4.3 t ha-1. The 1,000 kernel weight was the highest

with Nativo at 0.75 L ha-1, 1.0 L ha-1 and Prosaro 250

EC at 1.0 L ha-1.

The average grain yields and 1,000 kernel weights

across the sites varied from one treatment to another,

ranging from 1.2-4.0 t ha-1 and 28.5-45.4 g,

respectively. Significant (P ≤ 0.05) grain yield

increases of 57.3% and 49.7% were obtained at

KARI-Njoro and Mau-Narok in 2008, while 54.1%

and 44.7% increases occurred in 2009, respectively.

Similar increases in 1,000 kernel weight occurred at

both sites, KARI-Njoro (24.5% and 25.1%) in 2008,

and 10.4% and 23.3% in 2009 (Tables 2 and 3).

In Kenya, wheat is grown in many agro-ecological

zones that have different planting dates [15]. These


408

staggered plantings provide green crops for most of

the year allowing urediniospores to move from one

area to another. The favorable environmental

conditions, and the presence of host plants year-round,

favor the survival of high levels of inoculum. It is

therefore difficult to prevent or reduce infection of

susceptible cultivars. There is very little published

information on fungicide-use to control wheat stem

rust specifically related to the stem rust race Ug99 and

its variants. The occurrence of stem rust infections and

the onset of epidemics differed from year to year and

site to site. Stem rust levels were high in 2008 at

KARI-Njoro and Mau-Narok (despite early moisture

stress at KARI-Njoro; rain showers at GS 65 initiated

the spread of the disease). In 2009, the epidemics were

moderate to low at both sites. The low disease

pressure could have been due to the heavy rains at the

vegetative growth stage (May-September at

KARI-Njoro and October-November at Mau-Narok)

and later on, drought in Mau-Narok during December,

2009 and January-February, 2010.

In environments, such as those at KARI-Njoro and

Mau-Narok in 2008, where stem rust epidemics began

early, followed by conditions favorable for pathogen

growth and spread, stem rust can greatly reduce grain

yield and 1,000 kernel weight in susceptible varieties.

In that year, the average grain yield and 1,000 kernel

weight loss at KARI-Njoro and Mau-Narok in 2008

were 50.0% and 48.0%, 2.1% and 24.4%, respectively.

In 2009, the losses were 52.4%, 45.0%, 10.4% and

23.3%, respectively, in untreated control plots versus

fungicide-treated plots. These results are consistent

with losses reported in other studies [8, 16, 17].

Pretorius [18] reported that yield losses caused by

stem rust ranged from 7% to 35% depending on

variety. Dill-Macky and Roelfs [17] observed yield

losses of 50% to 58% after inducing severe stem rust

epidemics in barley and wheat, respectively. Mayfield

[19] found a clear relationship between grain yield and

disease severity by demonstrating that prevention of a

1% increase in stem rust severity saved a 2% loss in

grain yield. In the present study, all fungicide

applications resulted in lower disease severities and

higher yields than non-treated control plots.

Loughman et al. [8] reported that Folicur

(tebuconazole) provided more consistent results in

terms of both disease control and yield increases than

Triad (triadimefon) or Impact (flutriafol). In the

current study, the new fungicide treatments: Nativo

300 SC (trifloxystrobin 100 g L-1 + tebuconazole 200

g L-1) and Prosaro 250 EC (prothioconazole 125 g L-1

+ tebuconazole 125 g L-1) and the standards, applied

at 1.0 L ha-1 were generally effective in reducing the

disease and increasing grain yield and 1,000 kernel

weight. The lower rates resulted in more variable

disease control, grain yields and 1,000 kernel weight

responses.

Rust severity was relatively low in 2009 in the trials

at KARI-Njoro and Mau-Narok compared to 2008, yet

grain yields increased in response to fungicide

applications. This yield increase under relatively low

disease pressures may have been due to greening

effects of the fungicides [6]. Such stimulatory effect

of fungicide treatments on growth may enhance grain

yields even in the absence of disease [20, 21] and as

demonstrated in this study, fungicides treatments may,

if applied under high and moderate disease pressure at

critical crop growth stages, increase yields by

suppressing or eliminating the negative effects of stem

rust disease.

4. Conclusions

The impact of fungicide-use in the management of

stem rust was well illustrated at both trial sites. The

fungicide treatments had the ability to suppress

disease development and protect the crop canopy,

which is vital for dry matter accumulation and yield.

The study also displayed that stem rust could severely

reduce wheat grain yield of susceptible cultivars,

therefore, the adoption of foliar fungicides to combat

stem rust disease as a short term control strategy until

resistant cultivars are developed is encouraged in


409

Kenya. Consequently, both fungicides: Nativo 300 SC

and Prosaro 250 EC applied at the rate of 1.0 L ha-1

were recommended for commercial use.

Acknowledgments

The authors acknowledge the funding from Bayer

Crop Science, East Africa, and the support of D.

Onyango and P. Kinyanjui during implementation of

the trials.

References

[1] R.P. Singh, D.P. Hodson, Y. Jin, J. Huerta-Espino, M.G. Kinyua, R. Wanyera, et al., Current status, likely migration and strategies to mitigate the threat to wheat production from race Ug99 (TTKS) of stem rust pathogen, CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 2006, 1, No. 054.

[2] R. P. Singh, D.P. Hodon, J. Huerta-Espino, Y. Jin, P. Njau, R. Wanyera, et al., Will stem rust destroy the world’s wheat crops?, in: D.L. Sparks (Ed.), Advances in Agronomy, Academic Press, London, UK, 2008, pp. 271-309.

[3] Y. Jin, L.J. Szabo, M.N. Rouse, T. Fetch, Jr., Z.A. Pretorius, R. Wanyera, et al., Detection of virulence to resistance gene Sr36 within the TTKS race lineage of Puccinia graminis f. sp. Tritici, Plant Disease 93 (2008) 367-370.

[4] Z.A. Pretorius, R.P. Singh, W.W. Wagoire, T.S. Payne, Detection of virulence to wheat stem rust gene Sr31 in Puccinia graminis f. sp. tritici in Uganda, Phytopathology 84 (2000) 203.

[5] P.N. Njau, Y. Jin, J. Huerta-Espino, B. Keller, R.P. Singh, Identification and evaluation of sources of resistance to stem rust race Ug99 in wheat, Plant Disease 94 (2010) 413-419.

[6] R. Wanyera, J.K. Macharia, S.M. Kilonzo, J.W. Kamundia, Foliar fungicides to control wheat stem rust, Race TTKS (Ug99), in Kenya, Plant Disease 93 (2009) 929-932.

[7] Expert Panel on the Stem Rust Outbreak in East Africa, Sounding the alarm on global stem rust: An assessment of race Ug99 in Kenya and Ethiopia and potential for impact in neighboring regions and beyond, CIMMYT, Mexico, 2005, pp. 1-25.

[8] R. Loughman, K. Jayasena, J. Majewski, Yield loss and

fungicide control of stem rust of wheat, Australian Journal of Agricultural Research 56 (2005) 91-96.

[9] J.K. Macharia, R. Wanyera, Effect of stem rust race Ug99 on grain yield and yield components of wheat cultivars in Kenya, Journal of Agricultural Science and Technology A 2 (2012) 423-431.

[10] R. Wanyera, J.K. Macharia, S.M. Kilonzo, Challenges of fungicide control on wheat rusts in Kenya, in: O. Carisse (Ed.), Fungicides, ISBN: 978-953-307-266-1, Publisher: in Tech., 2010, pp. 123-138.

[11] J.C. Zadoks, T.T. Chang, C.F. Konazak, A decimal code for growth stages of cereals, Weed Research 14 (1974) 415-421.

[12] R.F. Peterson, A.B. Campbell, A.E. Hannah, A diagrammatic scale for estimating rust intensity of leaves and stems of cereals, Canadian Journal of Research 26 (1948) 415-421.

[13] SAS Institute, Inc. SAS/STAT User’s Guide, Version 8, SAS Inc., Cary, NC., 1999.

[14] A.G. Clewer, D.H. Scarisbrick, Practical Statistics and Experimental Design for Plant and Crop Science, John Wiley & Sons Ltd, West Sussex, England, 2001, pp. 114-115.

[15] R. Jaetzold, H. Schmidt, Farm management handbook of agriculture Vol. II/B Central Kenya, Ministry of Agriculture, Kenya in cooperation with German Agency of Technical Cooperation: Nairobi, Kenya, 1993.

[16] R. Dill-Mackey, G. Rees, G.J. Platz, Stem rust epidemics and their effects on grain yield and quality in Australian barley cultivars, Australian Journal of Agricultural Research 41 (1990) 1057-1063.

[17] R. Dill-Macky, A.P. Roelfs, The effect of stand density on the development of Puccinia graminis f. sp. tritici in barley, Plant Disease 84 (2000) 29-34.

[18] Z.A. Pretorius, Disease Progress and yield response in spring wheat cultivars and lines infected with Puccinia graminis f. sp. Tritici, Phytophylactica 15 (1983) 35-45.

[19] A.H. Mayfield, Efficacies of fungicides for the control of stem rust of wheat, Australian Journal of Experimental Agriculture 25 (1985) 440-443.

[20] S.L.H. Viljanen-Rollinson, M.V. Marroni, R.C. Butler, Wheat stripe rust control using fungicides in New Zealand, New Zealand J. Plant Protec. 59 (2006) 155-159.

[21] S.N. Wegulo, J.M. Rivera, C.A. Martison, F.W. Nutter, Jr., Efficacy of fungicide treatments for common rust and northern leaf sport in hybrid corn seed production, Plant Dis. 82 (1998) 547-554.


Occurrence and Effects of Pineapple Mealybug Wilt

Disease in Central Uganda

Bosco Bua1, Jeninah Karungi2 and Geoffrey Kawube2

1. Department of Agriculture, Kyambogo University, Kampala, Uganda

2. Department of Agricultural Production, College of Agricultural and Environmental Sciences, Makerere University, Kampala,

Uganda

Received: October 12, 2012 / Published: May 20, 2013. Abstract: Pineapple mealybug wilt disease (PMWD) is one of the latest outbreaks of diseases attacking pineapple in Uganda. However, its occurrence and effects have not been documented and quantified, yet the disease poses a serious threat to the pineapple industry. Therefore, the objective of this study was to assess the occurrence and effects of PMWD on pineapple in central Uganda. Semi-structured questionnaire was used to solicit information from 82 respondents consisting of farmers, opinion leaders, key informants, political and technical leadership during May 2011. PMWD was observed in all the fields surveyed but with varying incidences and severities. In addition, PMWD was more common during the dry seasons than the rainy seasons where higher incidences were associated with high mealybug populations. PMWD manifested as a syndrome characterized by yellowing of leaves, stunting, wilting and rotting of roots. The effects of PMWD were variable but yield reductions and low plant populations were widely reported. Although, the occurrence of PMWD was reported to the different level of authority in the districts, very little was done to curb its spread.

Key words: Control, effects, perceptions, pineapple mealybug wilt disease, occurrence.

1. Introduction

Pineapple (Ananas comosus (L.) Merr) is an

important horticultural crop in many tropical and

sub-tropical countries including Uganda [1]. In

Uganda, pineapple is widely grown in the central

region in the districts of Mukono, Kayunga, Luwero

and Masaka. The other pineapple growing districts are

Ntungamo and Kabale in South-Western Uganda.

Although, the local and export demand for Pineapple

has steadily increased with the estimated production

and export earnings of 2,426,000 MT and

US$181,000 in 2008, respectively, pineapple

production is still below optimum because of a

diversity of constraints [2]. Pests and diseases, lack of

improved pineapple production technologies and

Corresponding author: Bosco Bua, Ph.D., research fields:

crop science, plant diseases diagnosis, management and epidemiology, pathogens genetic diversity, horticulture. E-mail: [email protected], [email protected].

declining soil fertility are among the notable

constraints [3, 4]. Pineapple mealy bug wilt disease

(PMWD) also called pineapple wilt or quick wilt, the

latest outbreak of diseases attacking pineapple in

Uganda has been reported and confirmed in two major

pineapple growing districts of Mukono and Kayunga

[5]. Since its first reported outbreak in the two

districts in 2009, PMWD has continued to spread in

many parts of the country and is a serious threat to the

pineapple industry.

Pineapple mealy bug wilt disease manifests itself as

wilting of the central leaves due to loss of turgidity in

the leaves and inability of the roots to grow, collapse

and rotting. According to Gary et al. [6], PMWD is a

widespread and devastating disease in many pineapple

growing areas of the world. However, PMWD is only

reported from areas of the world where members of

the Dysmicoccus mealybugs species complex occur.

In fact, higher incidences of PMWD were associated

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Occurrence and Effects of Pineapple Mealybug Wilt Disease in Central Uganda

411

with high mealybugs populations. However, PMWD

only develops in plants infected with a closterovirus,

designated pineapple mealybug associated virus

(PMaV-1 & PMaV-2) that are also exposed to

mealybugs feeding [7-9]. In fact, a strong association

was found between PMWaV and PMWD [10, 11],

where both grey and pink pineapple mealybugs

(Dysmicoccus neobrevipes and D. brevipes) were

identified as vectors of the virus [10]. PMWaV-1 is

correlated with growth reductions of plant crop [10]

and yield reductions in the ratoon crops [12].

However, PMWaV-2 infection and mealybugs feeding

are necessary for the development of PMWD [13, 14].

Although, the yield effects of PMWD is variable

losses amounting to 35% has been reported [13].

Unless managed, the disease is very destructive and

devastating making commercial growing of pineapple

impossible [6]. Although, PMWD has been reported

in Uganda, the occurrence and effects have not been

documented. Therefore, the objectives of this study

were to 1) assess the occurrence and distribution of

pineapple mealybugs wilt disease in the districts of

Kayunga and Mukono and 2) assess the effects of

pineapple mealybugs wilt disease on pineapple.


The study was conducted in central Uganda in 2011.

Both Mukono and Kayunga districts located within

the Lake Victoria basin crescent are among the

leading pineapple producers in the country.

Multi-stage random sampling technique was used to

identify the sub counties, parishes, villages and the

respondents in the study sites. The two leading

pineapple growing sub counties identified in each

district were Ntunda and Goma, and Kangulumira and

Kayunga for Mukono and Kayunga, respectively.

From each sub county, two major pineapple growing

parishes were selected depending on the size and

intensity of pineapple production. In general, 2-3

villages were surveyed per parish depending on the

population in the area giving a total of 20 farmers per

sub-county and 40 farmers per district including one

technical staff per sub-county. Semi-structured

questionnaires were used to gather information from

82 respondents in the two districts. For each of the

farmer interviewed, a pineapple field was visited to

assess the incidence and severity of the PMWD using

visual symptoms. Disease incidence was assessed as

the number of plants diseased expressed as a percent

of the total number of plants assessed per field.

Disease severity was visually assessed as the

percentage leaf area affected (PLAA) using a scale of

1-5, where, 1 = no symptoms and 5 = over 75% of the

leaf wilted and dead [15]. Diseased pineapple plant

samples were also collected for laboratory

identification of mealybug species associated with

PMWD and viral characterisation. Detailed

descriptions of the locations of the fields surveyed

were captured by geographical positioning systems

(GPS). All the data collected was edited, coded and

entered into an excel spreadsheet (version 2007). The

data was analyzed using descriptive statistics of the

SPSS computer package (version 14.0).

3. Results

The socio-economic characteristics of the

respondents are presented in Table 1. Over 60% of the

respondents were males compared to the females.

Similarly, over 60% of the respondents were married

as opposed to the unmarried. Additionally, 40% of the

respondents had secondary school education whereas

12% had no formal education. Overall, over 90% of

the respondents grew pineapple as a major of source

of cash income. Besides, pineapple was reportedly

used for a variety of other purposes including home

consumption and processing into juices as well as

solar drying for exports. The other crops grown for

income generation included coffee, maize, cooking

banana and tomatoes, although maize and cooking

banana were also the major staple crops in the areas.

However, beans and cassava were also ranked very

highly as the major staple crops in the area (Table 2).


412

Table 1 Social characteristics of the respondents in Mukono and Kayunga districts, Uganda, 2011.

Characteristics Frequency (%)

Sex

Male 66

Female 34

Marital status

Single 18

Married 65

Others (divorce, widowed) 17

Educational level

Not educated 12

Primary 37

Secondary 40

Tertiary 11

Occupation

Farming 92

Business 4

Others 4

Total 100

The scale of area under pineapple production varied

greatly from a minimum of 0.25 to a maximum of 20

acres, respectively (data not shown). Similarly, the

length of involvement in pineapple growing ranged

from 1 to 33 years, respectively (Table 3). However,

the planting of pineapple was done throughout the

year, although over 50% of the pineapple was planted

during the dry seasons compared to the rainy seasons.

Interestingly, a sizeable proportion of the pineapple

was also planted in both seasons (Table 4). Although,

the source of pineapple planting materials was diverse,

close to 60% of the respondents obtained planting

materials from the plural compared to other sources

(Table 5). In fact, 70% of the respondents prefer

growing smooth cayenne to other varieties (Table 5).

Farmers’ perceptions of the constraints to pineapple

production are presented in Table 6. The major

constraints were diseases, drought and pests as

opposed to lack of planting materials. Of the diseases,

the major challenge is the outbreak of PMWD which

has devastated a large expanse of pineapple

plantations in the two districts. Seventy five percent of

the respondents reported PMWD as a widespread and

devastating disease of pineapple (Table 7). However,

the respondents had varied views on the number of

years that PMWD has been observed in pineapple

fields.

PMWD was observed in all the fields surveyed but

with varying incidences and severities on individual

farms. The lowest and highest PMWD incidence was

Table 2 Food and cash crops grown in Mukono and

Kayunga districts, 2011.

Crops Frequency (%)

Food

Maize 80

Banana 73

Beans 67 Potato Cassava

66 59

Cash

Pineapple 96 Coffee Banana Maize Tomato

37 11 7 7

Total 100

Table 3 Years of involvement in Pineapple cultivation in

Mukono and Kayunga districts, 2011.

Involvement Time (years)

Minimum 1

Maximum 33

Table 4 Planting seasons of Pineapple in Mukono and


Seasons Frequency (%)

Rainy seasons 15

Dry seasons 52

All seasons 33

Total 100

Table 5 Source of Pineapple planting materials and

varieties grown in Mukono and Kayunga districts, 2011.


Source of planting material

Own field 28

Neighbours 57

Markets 11

Donations 4

Varieties/cultivars

Smooth cayenne 70

Others 30

Total 100


413

Table 6 Constraints to Pineapple growing in Mukono and


Constraints Frequency (%)

Diseases 78

Drought 71

Pests 67

Shortage of land 55

Low price 47

Lack of transport 38 Soil infertility Lack of planting materials

45 17

Table 7 Knowledge of Pineapple mealybugs wilt disease in

Mukono and Kayunga districts, 2011.

Knowledge Frequency (%)

Yes 75

No 25

Total 100

15% and 100%, respectively. Correspondingly, fields

with higher PMWD incidences also recorded higher

severities and vice versa. However, the frequency of

occurrences ranged from 7% to 27% for the 15-30 and

95 and above incidence, respectively (Fig. 1). In

addition, PMWD was more common during the dry

seasons than the rainy seasons (Table 8). Pineapple

mealybugs wilt disease manifested as yellowing of

leaves, wilting, stunting and rotting of the roots (Table

9). Although, various views were advanced on the

causes of PMWD, the agents mentioned included

insects, sunshine and other unknown factors (Table

10). The major effects of PMWD reported were low

yield and low plant populations, respectively (Table

10). Because of the perceived effects of PMWD, the

respondents reported the occurrences of the disease to

the different level of authority in the districts (Table

11). However, the same respondents affirmed that no

actions were being taken to minimize the spread of the

disease (Table 11).

The various methods used to control PMWD by the

respondents are presented in Table 12. Although, over

50% of the respondents rogued off the infected

pineapple plants, 34% did nothing to control PMWD.

Admittedly, the effectiveness and efficacy of the

control measures were not very obvious to the

respondents. To facilitate control and management of

PMWD, the respondents reported that they were

trained on disease recognition, spread and control by a

number of institutions including the district

agricultural extension officials, the national

agricultural research organization (NARO) and

national agricultural advisory services (NAADS)

among others. However, due to the difficulty in

differentiating among the latent infections, other

diseases and selection of clean planting materials, a

number of respondents just used whatever plant

Fig. 1 Incidence and frequency occurrence of PMWD in Mukono and kayunga distrits, 2011.

Incidence

Fre

quen

cy (

%)


414

Table 8 Season of occurrences of Pineapple mealybug wilt disease in Mukono and Kayunga districts, 2011.

Season Frequency (%)

Rainy seasons 71

Dry seasons 3

Both seasons 24

Do not know 2

Total 100

Table 9 Symptoms of Pineapple mealybug wilt diseases in Mukono and Kayunga, 2011.

Symptoms Frequency (%)

Wilting 8

Purpling and yellowing of leaves 11

Stunting 1

Yellowing and wilting 57

Rotting 3

Don’t know 20

Total 100

Table 10 Causes and effects of Pineapple mealybug wilt disease in Mukono and Kayunga districts, 2011.


Causes

Pests 10

Sunlight 2

Do not know 88

Effects

Low yield 48

Low plant population 27

Do not know 25

Total 100

Table 11 Reporting and action on the presence of Pineapple mealybug wilt disease in Mukono and Kayunga districts, 2011.


Report

Yes 28

No 72

Action

No action 82

Action 18

Total 100

materials were available. Overall, the majority of the

respondents obtained information on the control of

PMWD through friends, progressive farmers and mass

media (data not shown).

Table 12 Control of Pineapple mealybug wilt disease in Mukono and Kayunga districts, 2011.

Method Frequency (%)

Roguing 52

Spraying 3

Roguing and spraying 9

Use of resistant varieties 1

Do nothing 35

Total 100

4. Discussion

Pineapple mealybug wilt disease (PMWD) was

observed in all fields surveyed but the incidences and

severities varied within the individual farms in central

Uganda. However, the frequency of occurrences was

more during the dry seasons than the rainy seasons.

According to National agricultural research

organisation [3], PMWD is a widespread and

devastating disease in many pineapple growing areas

of the world. In fact, the high frequency of occurrence

of PMWD is expected because the mealybugs which

vector PMWD are normally abundant in the dry

seasons [3, 11]. In addition, the high frequency of

occurrences of PMWD may be attributed to the

unknown status of the planting materials. This is

expected because most of the planting materials used

by the respondents were reportedly sourced from own

fields’ and neigbhours within the locality. Yet,

common knowledge indicates that recycling of

planting materials especially vegetatively propagated

crops is risky because the status of the disease is not

easily verifiable [16].

Although, PMWD was observed in all the fields

surveyed, only 20% of the fields had 100% incidence

indicating probably that PMWD is not a fast spreading

disease or low transmission efficiency of the

mealybugs vectors. This could be true because the

mealybugs which vector PMWD are immobile and

therefore requires to be moved from one plant to

another or from field to field. In fact, the strong

association reported between the mealybugs and

PMWD may support these assertions [11]. Similarly,


415

studies on the epidemiology of banana streak virus

disease by Kubiriba [17] showed that mealybugs are

important vector of banana streak virus in banana

plantations. However, the causes of PMWD were

unknown to the majority of the respondents though it

was indirectly related to factors such as sunshine,

insects, soil infertility and witchcraft. Although, the

majority of the respondents were not able to pinpoint

the actual causes of PMWD but related it indirectly to

factors such as sunshine, insects, soil infertility and

witchcraft shows that the respondents are aware of the

constraints inflicting their crops. Therefore, there is

need to empower the respondents to be able to

understand the relationships between the host plant,

pathogens or disease causing organisms and the

environment or the disease triangle. Earlier, Awuah

and Adzim [18] also admitted that the causes of red

leaf disease (RLD) assumed to be PMWD is not

known with accuracy. Yet, it has been demonstrated

by many authors that the identification of the causal

organisms, their biology, means of spread and host

range is imperative towards the development of

appropriate control measures against many diseases

[16]. Unless managed, the PMWD is very destructive

and devastating making commercial growing of

pineapple impossible. Accordingly, in this study,

various attempts were reported towards the control

and management of PMWD including roguing of the

infected plants, use of host plant resistance, spraying

or a combination of the above methods. Although, the

majority of the respondents relied on roguing as the

main way of controlling pineapple mealybugs wilt

disease, Gibson et al [19] and Thresh [20] asserted

that the use of phytosanitary practices such as roguing

is only effective for viral infections and diseases

which do not spread very fast. In fact, the consistent

association between mealybugs and PMWD as well as

the strong association between ants and mealybugs

may confirm this assertion [3]. Although, the use of

host plant resistance has been recommended as the

most economical and sustainable way of managing

many plant diseases [20], the use of host plant

resistance in this study was minimal. This is also true

for other countries. According to Sether and Hu [14],

smooth cayenne, the most commonly grown pineapple

variety is very susceptible to PMWD. In fact, no

sources of resistance to PMWD have so far been

reported in Uganda. Besides, the polyploidy and

vegetatively propagated nature makes the

identification of sources of resistance in pineapple

very complicated. The study has also shown that

majority of the respondents had adequate knowledge

of PMWD. Although, roguing is recommended for the

control of PMWD, the use of insecticidal sprays to

control the attendant ants is considered the best option.

In fact, limited varietal resistance was reported for the

control of PMWD. Although, it was reported that

training on disease recognition, means of spread and

control of PMWD was conducted by different

technical groups, the majority of the respondents

continue to seek for more information about PMWD

through friends, mass media and progressive farmers.

This therefore calls for more awareness creation and

sensitisation if PMWD is to be properly managed.

5. Conclusions

Although, production and export statistics show that

pineapple is an important source of livelihoods to the

farming communities in Central Uganda, especially

the districts of Mukono and Kayunga, the outbreak of

PMWD among other constraints is threatening to the

pineapple industry. Unless managed, the disease is

very destructive and devastating making commercial

growing of pineapple impossible. However, the study

has shown that the causes of PMWD were unknown to

the majority of the respondents though indirectly

related to factors such as sunshine, insects and soil

infertility making it very difficult to institute an

appropriate control and management strategy.

Therefore, there is need to empower the respondents

to be able to understand the relationships between the

host plants, pathogens or disease causing organisms


416

and the environment so as to take appropriate control

measures. In fact, it has been recommended that the

identification of the causal organisms, their biology,

means of spread and host range is imperative towards

the development of appropriate control measures

against any disease. Therefore, it is imperative that the

search for sources of resistance to PMWD be

undertaken so as promote the sustainable pineapple

production by growing resistant varieties.

Acknowledgments

Fund for this study was a grant awarded to the first

author by the Ministry of Education and Sports

through National Council for Higher Education. The

facilities and permission provided by the collaborating

institutions as well as the information by the

respondents are very gratefully acknowledged.

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[21] J.E. Vanderplank, Plant Diseases: Epidemics and Control, Academic Press, New York and London, 1963.


Electronic Identification of Livestock to Improve

Turkey’s Animal Production System

Sezen Ocak, Sinan Ogun and Zuhal Gunduz

Middle East Sustainable Livestock, Biotechnology and Agro-Ecology Research and Development Centre, University of Zirve,

Gaziantep 27260, Turkey

Received: January 22, 2013 / Published: May 20, 2013. Abstract: Major disease outbreaks, increasing demand for animal food products, intensification of animal production systems, increased consumer awareness about food quality and safety, as well as heightened consciousness about animal welfare issues has seen the need for more reliable animal identification in Turkey’s animal production system. Animal identification and traceability systems have seen rapid development in the world’s main livestock producing nations and have been recognised by the main food, health and livestock trading authorities. The benefit of this system affects all the participants in the food chain (farm to fork) by limiting the spread of animal disease, assuring food safety and quality, minimizing the potential trade loss and minimizing government control. Electronic identification (EID) is one of the main technologies adopted, whereby each individual animal is identified and traced through a unique identification number saved on an electronic transponder (eartag or bolus). The present animal identification and registration system in Turkey does not use an electronic identification tool and is administered manually which often causes unreliable and incorrect results. Concerns for animal and human health, as well as food safety assurance, have motivated efforts in Turkey to intensify animal identification system. This paper has provided the basis for how animals can be accurately traced and monitored from their birth until their slaughter, tracking every single parameter that could be of interest: animal health history, disease control, milk/meat/wool production and nutrition. This study summarizes information on EID available from around the world, discusses the advantages and challenges in its application in Turkey and provides recommendations as to the systems suitability to upgrade the present status of the Turkish National Livestock Identification System. Key words: EID, radio-frequency identification (RFID), livestock identification, food safety and traceability, Turkish national livestock identification system.

1. Introduction

The ability to identify and trace livestock from

property of birth to sale or final slaughter is crucial to

the national livestock registration scheme. The

adoption of such a system benefits the nation livestock

sector by limiting the spread of animal disease,

assuring food safety and quality, reducing potential

trade loss and minimising government control.

Livestock registration system in Turkey is carried out

manually and is administered by the Ministry of Food,

Agriculture and Livestock. A government appointed

veterinary officer records the visual eartag number at

Corresponding author: Sezen Ocak, Ph.D., research fields: reproductive biotechnology, small ruminant breeding and animal management systems. E-mail: [email protected].

each farm manually and then transfers the information

onto the electronic database known as Turk-Vet. A

number of mistakes are often experienced during this

information transfer process due to the manual entry

of each identification number. Human error is a major

factor the more times a piece of data is handled.

To minimize these issues, in many of the world’s

main livestock producing nations including Europe

and Australia, electronic identification systems (EID)

are utilized. EID reduces reading time, errors and

administrative burden via automatic digital reading of

the unique identification number assigned to each

transponder chip. As a result, the system provides

major advantages in disease control, monitoring any

illegal movement or sourcing of livestock within or

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Electronic Identification of Livestock to Improve Turkey’s Animal Production System

418

entering the country. In addition, one can easily trace

the animal or the animal product, as well as evaluate

the performance of the animal at the production stage

far more easily than if were recorded manually. The

use of a radio frequency regulated ear tag (EID)

allows the automatic reading of individual animal

identification number, to which one can assign

numerous traits or information about the animal whilst

transferring it into a database. It is quick, safe and

reliable. Electronic identification system can also be a

very useful tool for on-farm management. By the use

of electronic tag reading equipment, scales, automatic

drafting systems and computer management software

farmers can correlate the identifying number with all

relevant information to that animal and its

performance. Depending on the farmers management

objectives, records could include: genetics/bloodlines,

breeding history, weight gain, vaccine and disease

control history and relevant withholding periods for

certain pharmaceuticals, AI and pregnancy scanning

data, wool fibre or milk value measurements and the

list goes on [1].

As a result of their research and past experience in

various other livestock producing nations, the authors

strongly feel that EID is an inevitable must for Turkey

livestock industry. It will not only be of great benefit

to the producers in re-establishing their herd but will

be a much needed tool for maintaining the health of

that herd by the government keeping reliable records

for disease control. In most other nations noted for

their livestock industry, the use of EID has allowed

them to eradicate serious diseases such as Brucellosis

and TB. In conclusion, EID system in Turkey, if

adopted, will provide effective disease control, fast

access to accurate information, precise record keeping

for breeding, monitor and minimizing animal health

risks, providing full traceability of produce for

consumers, tracing and recalling unsafe foods rapidly

and finally averting illegal animal imports.

History of EID or RFID and its application to

livestock.

In 1948, a paper entitled “Communication by

Means of Reflected Power” written by Stockman [2]

was published. In 1964, Harrington examined the

electromagnetic theory related to RFID in his paper

“Theory of Loaded Scatterers” [3]. In the late 1960s,

two companies named Sensormatic and Checkpoint

were founded. These companies together with another

company called Knogo developed Electronic Article

Surveillance (EAS) equipment to deter the theft of

merchandise [4]. Large companies, such as Raytheon

and RCA, developed electronic identification systems

in 1973 and in 1975, respectively. During the 1970s,

research laboratories and universities, such as the Los

Alamos Scientific Laboratory and Northwestern

University, were involved in RFID research. The

adoption of the system for vehicle surveillance was

considered. The Los Alamos Scientific Laboratory,

the International Bridge Turnpike and Tunnel

Association (IBTTA) and the United States Federal

Highway Administration organized in 1973 a

conference on RFID which concluded that there was

no national interest in the development of a standard

for vehicle identification. This decision to the

development of a range of RFID systems.

In 1987, the first commercial application of RFID

was developed in Norway and followed by the Dallas

North Turnpike in the United States in 1989. In the

1990s European companies, such as Alcatel, Bosch

and Phillips spin-off companies, such as Combitech,

Tagmaster and Baumer were involved in the

development of a pan-European standard for vehicle

tolling applications. These companies helped develop

a common standard for electronic tolling [4]. In 1996,

Australia’s Department of Agriculture on the

recommendation of a government-industry working

party agreed to utilize the RFID concept and develop

an electronic identification system which has become

known as the National Livestock Identification

System (NLIS) in Australia. The objective was to

improve the existing visually read identification

arrangements in place at the time by identifying cattle


419

more permanently on their property of birth with an

electronic ear tag or rumen bolus that could be read

quickly and accurately. A key driver for the NLIS in

Australia was concern about the identification and

tracing of cattle in the event of a major exotic disease

outbreak such as Foot and Mouth Disease (FMD). A

government study estimated that in Australia the

overall economic loss as a result of such an outbreak

would be between 2 to 13 billion dollars. Though an

NLIS would not prevent a disease outbreak, it would

be able to reduce the financial and social impact of a

disease epidemic due to its accurate identification and

rapid traceability capabilities. This concept also

applies directly to Turkey.

Since then, there has been extensive development

and introduction of “whole of life” identification and

tracking systems in major cattle producing and/or beef

consuming countries such as Canada, United States,

Japan, South Korea, New Zealand, Brazil, Uruguay

and Botswana in addition to European Union (EU)

countries, Turkey will need to be following such

examples in order to maintain access to, and remain

competitive in, key overseas and regional markets.

Regulation (EC) No. 1760/2000 of the European

Parliament and of the Council of July 17, 2000

establishes rules for the identification and registration

of bovine animals and labeling of beef and beef

products [5]. Whether Turkey joins the EU or just

remains a trading partner, it needs to adhere to these

regulations by establishing similar standards in it

livestock identification standards.

2. Principles of EID/RFID

Electronic ID is synonymous with RFID. RFID is

accomplished through the use of two main

components: a transponder and a reader. A

transponder (integrated circuit and antenna) or

“microchip” is attached to an animal using a tag, bolus,

subcutaneous implant or electronic mark on the

pastern (leg band). A reader emits energy in the form

of radio waves. The transponder absorbs energy from

waves and transmits a signal containing the unique

number. The reader receives the transponder signal

and displays a unique identifier in the form of a

number [6]. This can be linked to a computer database

(either on a PC or on a handheld computer) which

links the electronic number to a recognized animal

identifier, e.g., the ear tag number for cattle.

In practice this means that when the animal is

“read” by the electronic reader, the animal ID is

displayed or recorded. This means that the animal

does not need to be physically identified, making the

process less stressful for the animal and easier for the

person keeping record. The two most common types

of electronic identifiers are electronic eartags and

ruminal boluses. Electronic eartags can be applied

early in the life of an animal. Eartags are easily visible

to the naked eye where as the bolus is swallowed by

the animal and is finally deposited in the reticulum.

Albeit fairly minimal, there is a certain loss rate with

eartags and the problem with the bolus id that it is

sometimes difficult to get a reading. If the right type

of bolus is applied to the right type of animal, loss

rates are extremely low. There are also other types of

identifiers (injectable transponder, electronic mark on

the pastern = leg band), but they can only be used with

certain limitations due to trade. RFID tags can be

either passive, active or battery assisted passive. An

active tag has an on-board battery and periodically

transmits its ID signal. A battery-assisted passive

(BAP) has a small battery on board and is activated

when in the presence of a RFID reader. A passive tag

is cheaper and smaller because it has no battery.

Instead, the tag uses the radio energy transmitted by

the reader as its energy source. The interrogator must

be close for RF field to be strong enough to transfer

sufficient power to the tag. Since tags have individual

serial numbers, the RFID system design can

discriminate several tags that might be within the

range of the RFID reader and read them

simultaneously [7].

Tags may either be read-only, having a


420

factory-assigned serial number that is used as a key

into a database, or may be read/written, where

object-specific data can be written into the tag by the

system user. Field programmable tags may be

written-once, read-multiple; “blank” tags may be

written with an electronic product code by the user.

RFID tags contain at least two parts: an integrated

circuit for storing and processing information,

modulating and demodulating a radio-frequency (RF)

signal, collecting DC power from the incident reader

signal, and other specialized functions; and an antenna

for receiving and transmitting the signal. Fixed readers

are set up to create a specific interrogation zone which

can be tightly controlled. This allows a highly defined

reading area for when tags go in and out of the

interrogation zone. The commonly used frequency

bands can be seen in Table 1. Mobile readers may be

hand-held or mounted on carts or vehicles.

Signaling between the reader and the tag is done in

several different incompatible ways, depending on the

frequency band used by the tag. Tags operating on LF

and HF frequencies are, in terms of radio wavelength,

very close to the reader antenna, less than one

wavelength away. In this near field region, the tag is

closely coupled electronically with the transmitter in

the reader. The tag can modulate the field produced by

the reader by changing the electrical loading the tag

represents. By switching between lower and higher

relative loads, the tag produces a change that the

reader can detect. At UHF and higher frequencies, the

tag is more than one radio wavelength from the reader.

The tag can backscatter a signal. Active tags may

contain functionally separated transmitters and

receivers, and the tag need not respond on a frequency

related to the reader’s interrogation signal [10].

An electronic product code (EPC) is one common

type of data stored in a tag. When written into the tag

by an RFID printer, the tag contains a 96-bit string of

data. The first eight bits are a header which identifies

the version of the protocol. The next 28 bits identify the

organization that manages the data for this tag; the

organization number is assigned by the EPCG lobal

consortium. The next 24 bits are an object class,

identifying the kind of product; the last 36 bits are a

unique serial number for a particular tag. These last two

fields are set by the organization that issued the tag.

Rather like a URL, the total electronic product code

number can be used as a key into a global database to

uniquely identify a particular product or an animal [11].

3. Advantages and Challenges of EID

Electronic identification system is an important tool

for traceability of products (animal and public health,

products, brands etc.), traceability of animals for

disease control (e.g., foot and mouth disease),

management on farm (lambing, milk recording,

feeding etc.), health certificates (national and

international livestock trade), animal welfare (e.g.

transport), herd book (e.g., pedigree, performance),

application of certain medications (hormones, vaccines

etc.), eradication programs (brucellosis, tuberculosis

scrapie) [12]. It provides to make less error and much

Table 1 RFID frequency bands [8, 9].

Band Regulations Range Data speed Remarks

120-150 kHz (LF) Unregulated 10 cm Low Animal identification, factory data collection

13.56 MHz (HF) ISM band worldwide 1 m Low to moderate Smart cards

433 MHz (UHF) Short range devices

1-100 m Moderate Defense applications, with active tags

868-870 MHz (Europe) 902-928 MHz (North America) UHF

ISM band 1-2 m Moderate to high

EAN, various standards

2,450-5,800 MHz (microwave)

ISM band 1-2 m High 802.11 WLAN, bluetooth standards

3.1-10 GHz (microwave) Ultra wide band to 200 m High Requires semi-active or active tags


421

faster than data recording manually. Electronic

tagging is therefore an essential tool for automatic

reading of individual identities and recording of

movements. This system can be a very useful tool for

on-farm management. Farmers have the possibility to

record individually management data like weights or

lambing results and could recall data of their animals

from the slaughterhouse. Equipment failure, the

average failure rate of tags (i.e., tags not

communicating with the reader) is very low.

Environment and facility challenges—The working

environment for livestock involves dust, water,

manure and many elements that are unfriendly to

electronic equipment [13], however, most EID

equipment in these days are built to meet the harsh

challenges of the environments, they are required to

perform in. Electromagnetic interference is another

problem source. Several forms of electronic animal ID

use radio signals to send information between the tag

and the reader antenna. In many livestock processing

facilities, there are multiple sources of

electromagnetic interference including: metal, motors,

and other radio frequency signals [6]. As long as the

used is mindful of these issues, they are not overly

burdensome to overcome as locations can be

manipulated. A common concern for producers is the

impact electronic animal ID will have on the

efficiency of working livestock whether sheep, goats

or cattle. Equipment breakdowns can be particularly

frustrating when labor costs increase due to down time.

Issues with how livestock flow past the panel reader to

make sure each ID is captured will require advice

from the technology provider. In these types of

installations, if alleys and gates do not force animals

to walk single file, the system may experience

problems with tag collision. Tag collision occurs

when more than one electronic identification tag

passes by the reader simultaneously [14]. This is a

design issue and can be averted if proper yards or

handling facilities are built with EID readers in mind.

4. Conclusions

Electronic animal identification system is a

developing field in the world. Concerns for animal

and human health, as well as food safety assurance,

have motivated efforts to intensify animal

identification system. This paper has provided the

basis for how animals can be accurately traced and

monitored from their birth until their slaughter,

tracking every single parameter that could be of

interest: animal health history, disease control,

milk/meat/wool production and nutrition. EID systems

used in many countries around the world have had a

high success rate. There is no reason that the same

success rate could not be achieved in Turkey’s

livestock industry.

Acknowledgments

This paper has been presented in the 23rd

International Scientific Expert Congress on

Agriculture and Food Industry, on September 27-29,

2012 in Izmir, Turkey.

References

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[3] K. Domdouzis, B. Kumar, C. Anumba, Radio-frequency identification (RFID) applications: A brief introduction, Advanced Engineering Informatics 21 (2007) 350-355.

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422

[8] S. Dipankar, S. Prosenjit, M.D. Anand, RFID for energy and utility industries: PennWell, Oklahoma, 2009, pp. 1-48.

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