Effect of cultivar resistance and rotation crops on clubroot (Plasmodiophora

brassicae) in canola and brassica vegetables

by

Sarah C. Drury

A Thesis

presented to

The University of Guelph

In partial fulfilment of requirements

for the degree of

Master of Science

in

Plant Agriculture

Guelph, Ontario, Canada

© Sarah C. Drury, May, 2021

ABSTRACT

EFFECT OF CULTIVAR RESISTANCE AND ROTATION CROPS ON CLUBROOT

(PLASMODIOPHORA BRASSICAE) IN CANOLA AND BRASSICA VEGETABLES

Sarah C. Drury

University of Guelph, 2021

Advisors:

Dr. Mary Ruth McDonald

Dr. Bruce D. Gossen

Clubroot, caused by Plasmodiophora brassicae Woronin, can dramatically reduce yields of

brassica crops. Once present in a field, eradication is difficult, but resistant cultivars can provide

effective management. The reactions of selected canola and brassica vegetable cultivars to

pathotypes 2 and 6, the prevalent pathotypes in Ontario, were assessed. The canola cultivars

marketed as resistant were resistant to both pathotypes. The vegetable cultivars marketed as

resistant were resistant to both pathotypes except for putative resistant cultivars of cabbage and

broccoli which were resistant to pathotype 6 but susceptible to pathotype 2. The effect of

selected field and cover crops on spore concentrations in soil and the combined effect of planting

a cereal crop and liming and were also assessed. Wheat reduced spores compared to a no-plant

control. Spore concentrations decreased as the lime rate increased and there was no interaction

between wheat and lime. Therefore, growers can use both strategies.

iii

ACKNOWLEDGEMENTS

My M.Sc has at times been a challenging process, but it has been rewarding and

enjoyable as well. I would like to thank my academic advisors, Dr. Mary Ruth McDonald and

Dr. Bruce Gossen for this opportunity, and for helping me to think critically about research

questions. They helped me to grow as a graduate student and I am thankful for their

encouragement to present my research at conferences and to write a manuscript. I am very

grateful for their guidance throughout every step of my project.

I would like to thank Dr. Peter Pauls who was on my advisory committee for his valuable

ideas. Thank you to Drs. Fadi Al-Daoud and Afsaneh Sedaghatkish for sharing their mentorship

and for helping me to troubleshoot any qPCR issue I was having. Thank you to all my lab mates

for their support and encouragement. I would also like to thank Travis Cranmer and Dennis Van

Dyk for sharing their knowledge and expertise when I did an internship with them for a summer.

Thank you to Chris Grainger for his advice and technical support while facing challenges with

qPCR. I would also like to express my gratitude to Kevin Vander Kooi and Laura Riches at the

Muck Crops Research Station for all their assistance with my field trials.

I would like to thank my family and friends for their constant support throughout my

M.Sc. In particular, I am very grateful to my parents for their advice and help whenever I needed

it. They always encouraged me to pursue my goals and have been constant inspirations to me.

iv

TABLE OF CONTENTS

Abstract ................................................................................................................................. ii

Acknowledgements .............................................................................................................. iii

Table of contents .................................................................................................................. iv

List of abbreviations ........................................................................................................... viii

List of figures ....................................................................................................................... ix

List of tables .......................................................................................................................... x

1 Literature review .......................................................................................................... 1

1.1 Brassica crops ........................................................................................................... 1

1.2 Canola (B. napus L., B. rapa L. and B. juncea L.) ................................................... 2

1.2.1 Canola production system ................................................................................. 3

1.2.2 Uses and benefits of canola ............................................................................... 5

1.3 Brassica vegetables ................................................................................................... 5

1.3.1 Brassica vegetable production in Canada .......................................................... 6

1.3.2 Diseases of brassica crops ................................................................................. 7

1.4 Clubroot .................................................................................................................... 8

1.4.1 Disease cycle ..................................................................................................... 9

1.4.2 Pathotyping systems ........................................................................................ 12

1.4.3 Clubroot in Canada .......................................................................................... 14

v

1.4.4 Host-pathogen interaction ................................................................................ 16

1.5 Factors affecting clubroot development .................................................................. 20

1.5.1 Soil pH ............................................................................................................. 20

1.5.2 Temperature ..................................................................................................... 22

1.5.3 Soil moisture .................................................................................................... 23

1.5.4 Soil types ......................................................................................................... 23

1.5.5 Pathogen distribution in soil ............................................................................ 24

1.6 Clubroot management strategies ............................................................................. 24

1.6.1 Preventing pathogen dissemination ................................................................. 24

1.6.2 Resistant cultivars ............................................................................................ 25

1.6.3 Crop rotation .................................................................................................... 28

1.6.4 Bait crops ......................................................................................................... 29

1.6.5 Seeding date ..................................................................................................... 32

1.6.6 Liming ............................................................................................................. 32

1.6.7 Patch management ........................................................................................... 35

1.6.8 Fungicides ........................................................................................................ 35

1.6.9 Biological control ............................................................................................ 37

1.7 Techniques .............................................................................................................. 39

1.7.1 Detecting clubroot in soil ................................................................................ 39

vi

1.7.2 Assessing infection in plants ........................................................................... 39

1.7.3 Quantifying resting spore concentrations ........................................................ 40

1.8 Research objectives ................................................................................................. 41

2 Clubroot resistance in canola and brassica vegetable cultivars .................................. 43

2.1 Introduction ............................................................................................................. 43

2.2 Materials and methods ............................................................................................ 46

2.2.1 Field site .......................................................................................................... 46

2.2.2 Field trials – canola.......................................................................................... 46

2.2.3 Field trials - vegetables .................................................................................... 49

2.2.4 Clubroot inoculum for growth room studies ................................................... 51

2.2.5 Growth room - canola ...................................................................................... 52

2.2.6 Growth room - vegetable cultivars .................................................................. 53

2.2.7 Pathotyping P. brassicae from the field .......................................................... 53

2.2.8 Statistical analysis............................................................................................ 53

2.3 Results ..................................................................................................................... 54

2.3.1 Canola .............................................................................................................. 54

2.3.2 Brassica vegetables .......................................................................................... 57

2.3.3 The pathotype of a field collection .................................................................. 61

2.4 Discussion ............................................................................................................... 62

vii

3 Using field crops and liming to reduce resting spores in soil ..................................... 67

3.1 Introduction ............................................................................................................. 67

3.2 Materials and methods ............................................................................................ 71

3.2.1 Field crop growth room study ......................................................................... 71

3.2.2 Cereal crops × lime study ................................................................................ 75

3.2.3 Propidium monoazide (PMA)-qPCR analysis ................................................. 78

3.2.4 Evans blue stain ............................................................................................... 81

3.2.5 Statistical analysis............................................................................................ 82

3.3 Results ..................................................................................................................... 84

3.3.1 Field crop study - Run 1 .................................................................................. 84

3.3.2 Field crop study - Runs 2 and 3 ....................................................................... 85

3.3.3 Cereal crops × lime study ................................................................................ 87

3.3.4 Evans blue stain ............................................................................................... 92

3.4 Discussion ............................................................................................................... 92

4 General discussion .................................................................................................... 103

References ......................................................................................................................... 109

Appendices ........................................................................................................................ 125

Appendix 1: Supplemental tables and figures, Chapter Two ............................................ 125

Appendix 2: Supplemental tables and figures, Chapter Three .......................................... 146

viii

LIST OF ABBREVIATIONS

Canadian Clubroot Differential – CCD

Clubroot incidence – CI

Clubroot-resistant – CR

Competitive internal positive control – CIPC

Days post inoculation – DPI

Disease severity index – DSI

European Clubroot Differential – ECD

Forward primer – DC1F

Green fluorescent protein – GFP

Jasmonic acid – JA

Organic matter – OM

Propidium monoazide – PMA

Quantification cycle – Cq

Quantitative polymerase chain reaction – qPCR

Quantitative trait loci – QTL

Reverse primer – DC1mR

Salicylic acid – SA

Species – Spp.

ix

LIST OF FIGURES

Figure 1.1 Triangle of U theory of the evolution of Brassica species (Source: U, 1935; Dixon,

2007). .............................................................................................................................................. 2

Figure 2.1 Clubroot disease severity rating scale. (a) 0 = no clubbing on root, (b) 1 = small clubs

on <1/3 of roots, (c) 2 = small to medium clubs on 1/3–2/3 of roots, and (d) 3 = large clubs on

>2/3 of roots. ................................................................................................................................. 49

Figure 3.1 Seedlings of perennial ryegrass, wheat, barley, field pea, soybean, Shanghai pak choi

(susceptible control) and the no-plant control inoculated with Plasmodiophora brassicae under

controlled conditions. .................................................................................................................... 73

Figure 3.2 Root systems of a) perennial ryegrass, b) wheat, c) barley, d) field pea and e) soybean

after 8 weeks of growth and f) Shanghai pak choi after 6 weeks of growth in soil inoculated with

Plasmodiophora brassicae............................................................................................................ 75

Figure 3.3 Seedlings of barley, Shanghai pak choi (susceptible control) and no-plant (negative

control) at three rates of lime incorporated in soil inoculated with Plasmodiophora brassicae. . 76

Figure 3.4 The effect of three rates of lime (calcium hydroxide, Ca(OH)2) on the concentration

of Plasmodiophora brassicae resting spores in soil after growing wheat and a no-plant control

for 8 weeks. The soil was inoculated to attain an initial concentration of 5 × 105 resting spores

g-1. The linear regression line is based on lognormal distribution and presented using natural

logs. ............................................................................................................................................... 89

Figure 3.5 Proportion of viable Plasmodiophora brassicae resting spores, as determined using

Evans blue stain, as a function of the proportion of dead spores killed by heating. Capped lines

represent ± standard error. ............................................................................................................ 92

x

LIST OF TABLES

Table 1.1 Harvested areas (hectares) and farm gate values of brassica vegetables in Canada and

Ontario in 2019 (Statistics Canada, 2020). ..................................................................................... 7

Table 2.1 Expected reaction to pathotypes 2 and 6 (based on seed label), year evaluated in a field

trial, and type of trial used for evaluation (field trial or growth room study) of the canola

cultivars that were screened for resistance. ................................................................................... 48

Table 2.2 Expected reaction to clubroot pathotypes 2 and 6 (based on seed label) of the brassica

vegetable cultivars that were screened for resistance in 2018 and 2019 field trials and in growth

room studies. ................................................................................................................................. 51

Table 2.3 Clubroot incidence (CI, %), disease severity index (DSI), and fresh weight and dry

weight of clubroot susceptible and resistant canola cultivars grown at the Muck Crops Research

Station, ON, in 2018 and 2019...................................................................................................... 56

Table 2.4 Clubroot incidence (CI, %) and disease severity index (DSI) of canola cultivars

inoculated with pathotypes 2 and 6 of Plasmodiophora brassicae in a growth room study (n = 8).

....................................................................................................................................................... 57

Table 2.5 Clubroot incidence (CI, %), disease severity index (DSI), and fresh and dry weight of

clubroot susceptible (S) and resistant (R) brassica vegetable cultivars at the Muck Crops

Research Station, ON in 2018 and 2019. ...................................................................................... 60

Table 2.6 Clubroot incidence (CI, %) and severity (disease severity index, DSI) of clubroot

susceptible (S) and resistant (R) brassica vegetables inoculated with pathotypes 2 (n = 4) and 6 (n

= 8) of Plasmodiophora brassicae in a growth room study. ........................................................ 61

Table 2.7 Clubroot incidence (%) and disease severity index (DSI) of cultivars from Williams’

differential set (1966) inoculated with a field collection of Plasmodiophora brassicae from the

Muck Crops Research Station, 2019. ............................................................................................ 62

Table 3.1 qPCR reaction reagents, concentrations and volumes used to quantify Plasmodiophora

brassicae DNA in inoculated soil. ................................................................................................ 81

Table 3.2 Effect of field and cover crop species on the concentration of resting spores of

Plasmodiophora brassicae in soil and root dry weight in Run 1 after 8 weeks of growth. Resting

spore concentration was based on standard qPCR analysis (n = 6). ............................................. 85

Table 3.3 Effect of field and cover crops on the concentration of resting spores of

Plasmodiophora brassicae in soil and root dry weight after 8 weeks of growth in two runs of the

study (n = 6). ................................................................................................................................. 87

xi

Table 3.4 Correlation between root dry weight of the field/cover crops and resting spore

concentration in soil inoculated with Plasmodiophora brassicae after 8 weeks of growth in two

runs of the experiment (n = 6). ..................................................................................................... 87

Table 3.5 Soil pH in response to application of three rates of lime (calcium hydroxide, Ca(OH)2)

to a soil mix and planted with barley, wheat, Shanghai pak choi or a no-plant control after 6 or 8

weeks of growth (n = 6). ............................................................................................................... 90

Table 3.6 Effect of three rates of lime (calcium hydroxide, Ca(OH)2) on concentration of resting

spores of Plasmodiophora brassicae in soil, clubroot incidence (CI) and severity (disease

severity index, DSI) in Shanghai pak choi at 6 weeks of growth (n = 6). .................................... 91

1

CHAPTER ONE

1 Literature review

1.1 Brassica crops

Many important food crops belong to the family Brassicacea (formerly Cruciferae). There

are six species within the genus Brassica: B. napus (rapeseed), B. juncea (mustard greens),

B. carinata (Ethiopian mustard), Brassica nigra (black mustard), B. rapa (field mustard) and

B. oleracea. Brassica rapa has three subspecies: chinensis (pak choi), pekinensis (Chinese

cabbage), and rapifera (turnip). Also, Brassica oleracea has several subspecies: acephala (kale),

botrytis (cauliflower), capitata (cabbage), gemmifera (Brussels sprouts), gongylodes (Kohlrabi),

italica (broccoli) and sabellica (collards) (Fahey, 2003). Crossing and hybridization of Brassica

spp. has resulted in the diversity of species (Attia and Röbbelen, 1986). The triangle of U

represents a hypothesis the evolution of species in the genus (U, 1935) (Figure 1.1). The

hypothesis is that three diploid species (B. rapa, B. nigra and B. oleracea) were the progenitors

of the three amphidiploid species (B. carinata, B. juncea and B. napus). Genomic analysis

suggests that B. rapa and B. oleracea evolved from a common ancestor while B. nigra evolved

through a separate pathway (Song et al., 1993). It is believed that B. napus is the first of the

amphidiploid species to evolve (Olsson, 1960).

2

Figure 1.1 Triangle of U theory of the evolution of Brassica species (Source: U, 1935; Dixon,

2007).

1.2 Canola (B. napus L., B. rapa L. and B. juncea L.)

Canola is an oilseed quality standard developed in Canada and achieve using traditional

breeding techniques. Three brassica crop species, B. napus L., B. rapa L. and B. juncea L. have

been used to produce cultivars of canola, but by far the dominant species is B. napus. Canola oil

must contain less than 2% erucic acid and have glucosinolate levels below 30 µmol g-1 to qualify

(Canola Council of Canada, 2017c). Breeding to produce rapeseed with low glucosinolate levels

began in the 1960s (Daun, 1986). Dr. Baldur Stephenson from the University of Manitoba

released the first canola cultivar (B. napus) in 1974 and Dr. Keith Downey from the University

of Saskatchewan released the first B. rapa (syn. campestris) cultivar in 1977 (Bell, 1982). The

name ‘Canola’ is abbreviated from ‘Canadian oil’ and was trademarked in 1980 by the Rapeseed

Association of Canada which later became the Canola Council of Canada (Daun, 1986).

Canola production has increased dramatically since it first became available on the market

3

(Canadian Canola Growers Association, n.d.). By 1983, canola accounted for 90% of rapeseed

production in Western Canada (Daun, 1986). In 1986, 3.7 million metric tonnes of canola were

produced and by 2016 this number increased to 18.4 million metric tonnes (Canadian Canola

Growers Association, n.d.). In 2019, 8.5 million hectares of canola were planted in Canada

(Statistics Canada, 2019a), averaging 2.7 tonnes ha-1 (Statistics Canada, 2019b). Around 99% of

canola was planted in the Prairie provinces. Most of the production occurs in Saskatchewan; 4.7

million hectares were planted in 2019 (Statistics Canada, 2019a). The canola industry aims to

produce 3.5 tonnes ha-1 by 2025 (Canadian Canola Growers Association, n.d.).

The canola industry contributes $12.5 billion to worker wages, supports over 250,000 jobs,

and contributes $26.7 billion annually to the Canadian economy (Canadian Canola Growers

Association, n.d.; LMC International, 2016). Canola has produced the highest farm revenue of

any crop in Canada for over 10 years. Currently around 43,000 farms in Canada grow canola

(Canadian Canola Growers Association, n.d.). In 2016, farm cash receipts from canola were

estimated at $9.2 billion (Statistics Canada, 2017) with the Prairie provinces accounting for 91%

of the economic benefits. Ontario is responsible for approximately 4% of the economic impact of

canola in Canada (LMC International, 2016). Canada is the top canola exporter in the world;

90% of canola produced in Canada is exported. Canada exports canola seed that has not been

crushed or processed as well as canola oil and meal. In 2015, canola seed, oil and meal generated

$9 billion in exports (Canadian Canola Growers Association, n.d.).

1.2.1 Canola production system

Canola is seeded in the spring or fall in Canada (Gusta et al., 2004). Most of the canola in

Canada is spring canola. Many factors can influence the success of canola production, including

planting rate. A planting rate of 150 seeds m-2 is recommended as this resulted in higher

4

emergence, stubble density and yield compared to a rate of 75 seeds m-2 (Harker et al., 2012;

Harker et al., 2015b). The average canola seeding rate in Ontario is 5.0–6.2 kg ha-1 and the

optimal plant stand is 75–130 plants m-2 (OMAFRA, 2020). In addition, successful growth of

canola seedlings is dependent on the elimination of weeds, often with herbicides. The first

herbicide-tolerant canola cultivar was released in 1995 (Canadian Canola Growers Association,

n.d.).

Canola can be grown on many types of soil but is most successfully grown on well-drained

clay-loam soils. Canola growth is reduced in waterlogged soils or in drought conditions

(Berglund et al., 2007). The optimal soil temperature for canola seed germination is 22°C

(Nykiforuk and Johnson-Flanagan, 1994). High temperatures during the flowering and pod

development periods can substantially reduce yields (Harker et al., 2012). Low pH levels in soil

can also inhibit canola growth. Soil pH should be above 5.5, although suitable pH levels can vary

with the soil type (Baquy et al., 2017; Penney et al., 1977).

Canola requires a high concentration of many nutrients to produce optimum yields (Grant

and Bailey, 1993). Testing soil for nutrient content is recommended to determine fertilizer

requirements. Applications of nitrogen, phosphorus, and sulphur are often needed as deficiencies

in these nutrients can cause substantial yield losses (Canola Council of Canada, 2020c).

Potassium is also an essential nutrient but is rarely limiting to canola (Grant and Bailey, 1993).

Applications of calcium, magnesium, boron and copper may be needed but these nutrients are

less commonly associated with yield losses (Canola Council of Canada, 2020c).

Generally, canola growers in Ontario choose cultivars that can be straight cut, rather than

swathed prior to combining (M. Moran, OMAFRA Stratford, personal communication). Pod-

shatter-tolerant canola cultivars can be used for straight cutting or delayed swathing (BASF,

5

2019; Canola Council of Canada, 2019). In contrast, swathing is the most common harvest

method in Western Canada as it can accelerate drying and minimize seed losses due to pod

shattering (Canola Council of Canada, 2019; Vera et al., 2007). Growers in Western Canada are,

however, increasingly direct harvesting canola to reduce operational costs (Haile et al., 2014).

1.2.2 Uses and benefits of canola

Oil and meal (livestock feed) are obtained from crushing canola seed. The oil content of

canola seeds is 44%, significantly higher than other oilseed crops (Canadian Canola Growers

Association, n.d.). Canola oil is composed of over 93% monounsaturated and polyunsaturated

fats, making it the healthiest vegetable oil. Health benefits of canola include decreased blood

cholesterol and a lower risk of heart attack and stroke. Canola oil is also high in vitamin E

(Canola Council of Canada, 2017b).

Canola seeds are also used to produce animal meal after the oil has been removed (Canola

Council of Canada, 2017c). Canola meal is high in protein and is therefore the most used protein

source in livestock feed globally (Canola Council of Canada, 2017a). Canola meal is also used

for feed in the aquaculture industry (Casséus, 2009).

Canola oil is also used as an environmentally friendly biodiesel, producing 90% lower

greenhouse gas emissions than fossil fuels. Canola biodiesel is efficient under cold temperature

conditions (Canadian Canola Growers Association, n.d.). Canola has also recently been used as a

component of plastics, adhesives, sealants, and other industrial products (Canola Council of

Canada, 2017c).

1.3 Brassica vegetables

Brassica vegetables are a diverse group of crops obtained through human selection. They

6

are leaf, flower, stem and root vegetables.

Brassica vegetables have many uses including for human consumption, fodder, industrial

lubricants, medicines and biofumigants (Al-Shehbaz et al., 2006; Dixon, 2007; Prakash et al.,

2012). These vegetables contain folic acid, fibre, and antioxidants which provide health benefits

that decrease the risk of cancer, heart disease, and stroke (Agriculture and Agri-Food Canada,

2018a; Dixon, 2014). They are high in vitamins A, C, and K and minerals such as potassium and

manganese (Agriculture and Agri-Food Canada, 2018a).

1.3.1 Brassica vegetable production in Canada

Commercial production of many brassica vegetables occurs across Canada, with a

significant amount of production occurring in Ontario (Table 1.1). While brassica vegetables are

biennial crops, they are predominately grown as annuals in Canada (Agriculture and Agri-Food

Canada, 2018a). Cabbage, broccoli and cauliflower are cold tolerant crops (Atlantic Provinces

Agriculture, n.d.). For instance, cabbage seeds can germinate at 5°C and survive early in the

growing season at a temperature of -10°C (University of Florida, 1994). Cabbage is more

tolerant to high and low temperatures than broccoli and cauliflower (Atlantic Province

Agriculture, n.d.). Depending on the cultivar, well-drained sandy loam, loamy and clay loam

soils with a pH of 6.0–6.8 are optimal for growth (Agriculture and Agri-Food Canada, 2018a).

Cabbage, broccoli and cauliflower are often grown from transplants that are started in a

greenhouse and that can be transplanted into the field when seedlings are 4–6 weeks old

(Agricultural and Agri-Food Canada, 2018a; Atlantic Provinces Agriculture, n.d.). Early-season

crops should be grown as transplants for 5–6 weeks and mid- to late-season crops should be

grown for 4–5 weeks prior to planting. Seedlings are typically grown in greenhouses and should

be hardened off prior to transplanting (OMAFRA, 2016). Harvest occurs 12–13 weeks after

7

seeding. These crops are harvested early, midway, and late in the season (Agriculture and Agri-

Food Canada, 2018a).

The majority of commercially grown rutabaga in Canada is of the cultivar Laurentian.

Rutabaga can be planted in the spring, either by direct seeding or, more rarely, from transplants.

Cool and humid conditions are optimal for rutabaga growth (Agriculture and Agri-Food Canada,

2018b).

Table 1.1 Harvested areas (hectares) and farm gate values of brassica vegetables in Canada and

Ontario in 2019 (Statistics Canada, 2020).

Crop Harvested area (ha) Farm gate value (CAN$) (× 1,000)

Canada Ontario Canada Ontario

Cabbage1 5,285 2,135 88,225 33,058

Broccoli 4,108 1,502 78,124 32,327

Cauliflower 1,756 413 36,670 6,834

Rutabaga and

turnip 1,422 613 30,897 13,443

1The cabbage values include regular cabbage, Chinese cabbage and kale.

1.3.2 Diseases of brassica crops

The most devastating disease of oilseed rape is blackleg, caused by the fungal pathogen,

Leptosphaeria maculans (Desm.) Ces. & de Not. Blackleg is characterized by the formation of

black cankers on stems, causing early senescence, lodging, and plant death (Howlett et al., 2001;

West et al., 2001). Black rot is another serious disease of brassica crops and is caused by a

bacterium, Xanthomonas campestris pv. campestris (Pammel) Dowson (Williams, 1980).

Symptoms of black rot include V-shaped chlorotic lesions, darkened veins, necrotic leaves,

premature defoliation, orange coloration in roots and stunted growth (Meenu et al., 2013;

8

Vicente and Holub, 2013). Sclerotinia sclerotiorum (Lib.) de Bary causes stem rot, another

common disease of brassica crops worldwide (Bardin and Huang, 2001; Sharma et al., 2015).

Sclerotinia rot develops on leaves, stems and pods and can reduce seed yields by up to 80%

(Sharma et al., 2015). Worldwide, brassica crops are affected by dark leaf spot caused by

Alternaria brassicicola (Schw.) Wilts. and Alternaria brassicae (Berk.) Sacc. These fungi infect

the leaves, pods, seeds and stems of plants at various growth stages (Doullah et al., 2006; Köhl et

al., 2010). Rhizoctonia rot, caused by the fungi Rhizoctonia solani Kühn, is characterized by root

rot, damping-off and wirestem in brassica crops (Agriculture and Agri-Food Canada, 2018b).

Swede midge (Contarinia nasturtii Kieffer) (Diptera: Cecidomyiidae) is an insect pest that

forms galls on brassica hosts. This pest is found in Europe and has recently become an invasive

species in North America (Chen and Shelton, 2007). In 2000, Swede midge was first identified in

Ontario and has since spread to Quebec (Chen et al, 2011). Swede midge caused substantial

canola yield losses in many regions in Ontario, including western and northern Ontario where

most canola production in the province occurs. As a result, many Ontario growers have stopped

growing canola (Hallet, 2017). A related species has recently been identified on canola in the

Prairie provinces. Swede midge females lay eggs on tips of plants and the larvae feed on stems,

leaves and flowers (Chen and Shelton, 2007). Symptoms include twisted and misshapen shoots

and leaf stalks, crumpled leaves, swollen growing tips and galls on leaves and flowers (Chen et

al., 2011).

1.4 Clubroot

Clubroot is a soil-borne disease of plants in the Brassicaceae family that results in

excessive growth on plant roots and hypocotyls. The causative agent of clubroot is the obligate

protist Plasmodiophora brassicae (Ingram, 1969; Karling, 1942). The first report identifying the

9

pathogen was in 1878 by M. S. Woronin (Woronin, 1878). Plasmodiophora brassicae is in the

domain Eukarya, kingdom Chromista, infrakingdom Rhizaria, phylum Cercozoa, subphylum

Endomyxa, class Phytomyxea, order Plasmodiophorida, family Plasmodiophoraceae, genus

Plasmodiophora and species brassicae (Bulman et al., 2011; Cavalier-Smith and Chao, 2003;

Cavalier-Smith et al., 2018).

One of the first records of clubroot is thought to be by a Roman named Pallitus in Italy in

the 4th Century A.D. Pallitus recorded descriptions of spongy roots on oilseed rape, turnips and

radishes. An increase in cultivation of brassica crops in the 16th century led to the spread of

clubroot within Europe and from Europe to other continents (Watson and Baker, 1969). The

disease is speculated to have been transported to North America on infected turnip roots

(Sedaghatkish et al., 2019; Watson and Baker, 1969). Clubroot is now found in all parts of the

world where plants in the family Brassicaceae are grown (Dixon, 2009). Potential hosts include

brassica crops, weeds, wild crucifers, and Arabidopsis thaliana (Pedras et al., 2008).

The formation of clubs on roots and disruption of the vascular system by P. brassicae

restricts water and nutrient uptake (Macfarlane and Last, 1959). Above-ground symptoms

include stunted growth, foliar wilting, leaf chlorosis, delayed flowering and premature ripening

(Karling, 1942; Mithen and Magrath, 1992). Some symptoms, such as interveinal mottling, may

be the result of nutrient deficiencies. The number, size and thickness of new leaves can also be

reduced in infected plants (Macfarlane and Last, 1959). Severe cases of clubroot have been

reported to reduce canola yields by 30–100% (Hwang et al., 2012c). Clubroot reduces canola

seed quality and size as well as oil content (Pageau et al., 2006).

1.4.1 Disease cycle

The clubroot disease cycle occurs once every growing season, so P. brassicae is

10

characterized as a monocyclic pathogen. The disease cycle begins with the asynchronous

germination of haploid resting spores in the soil to produce primary zoospores (Ingram and

Tommerup, 1972). As soil temperature rises in the spring, germination is initiated in response to

root exudates (Macfarlane, 1970; Wellman, 1930). Resting spores can germinate at 6–27°, but

germination is lower below 18°C and above 25°C (Wellman, 1930). The serine protease Pro1 in

P. brassicae produces proteolytic compounds that trigger germination. Resting spores can

germinate in the absence of Pro1, but germination rates are lower (Feng et al., 2010).

Primary zoospores are uninucleate, 2.8–5.9 µm in length and oval or pyriform in shape

(Ayers, 1944; Ingram and Tommerup, 1972). Two whiplash flagella, one long and one short,

allow them to move in the soil solution (Ayers, 1944). Zoospores outside the host in the soil

solution are highly vulnerable to soil conditions, such as moisture, antimicrobial organisms and

temperature (Suzuki et al., 1992; Takahashi, 1994a), but the length of time that they survive in

soil is not known. Zoospores encyst on root hairs or epidermal cell walls of host or nonhost

species (Ayers, 1944; Williams, 1971), form adhesoria and penetrate the cell walls. Ovate spore

protoplasts 3.0–5.0 µm in diameter are released from a pore that is 1.4 µm in diameter (Ingram

and Tommerup, 1972).

Uninucleate primary plasmodia develop inside the cytoplasm of root hairs and undergo

synchronous nuclear divisions (Williams et al., 1971). Multinucleate zoosporangia are produced,

containing up to 6 nuclei. The zoosporangia mature and produce 4–16 uninucleate zoospores

(Ingram and Tommercup, 1972). Secondary zoospores are liberated into the soil through breaks

in the cell walls (Ayers, 1944). Root hair infection can occur 2 days after inoculation in canola in

optimal conditions (Sharma et al., 2011b). A pH of 5.0–6.5, temperature of 20–25°C and

sufficient moisture are conducive to root hair infection (Ayers, 1944; Gossen et al., 2013). Root

11

hair infection increases in susceptible cultivars for 6–8 days after inoculation (Hwang et al.,

2011b).

Secondary zoospores are morphologically similar to primary zoospores but invade the root

epidermis and infect the root cortex of the main roots (Ayers, 1944). Some authors report that the

secondary zoospores fuse and form binucleate plasmodia before infecting the root cortex (Ingram

and Tommercup, 1972), but this has never been demonstrated conclusively (Dobson and

Gabrielson, 1983). The plasmodia increase in size and undergo synchronous mitotic divisions to

become multinucleate (Ingram and Tommerup, 1972). Secondary zoospores can also infect root

hairs which facilitates rapid increase of inoculum for root infection (Feng et al., 2012). The

cortical infection stage is optimal at 25°C (Sharma et al., 2011a) and has been observed starting

at 4 days after inoculation (Ingram and Tommerup, 1972).

While P. brassicae nuclei are haploid for the majority of the lifecycle, multinucleate

secondary plasmodia nuclei are thought to fuse to become diploid in the cortical infection stage.

Meiosis of diploid nuclei follows, and the plasmodia cleave into millions of new haploid resting

spores (Ingram and Tommerup, 1972). The continual production of new secondary zoospores

from infection of fresh root hairs can lead to repeated cortical infection. Plasmodia and resting

spores can therefore be found in the same root system (Sharma et al., 2011a). After colonizing

the root cortex, P. brassicae invades the stele, stimulating division of parenchyma cells and de-

differentiation of the xylem (Deora et al., 2013). Hyperplasia and hypertrophy in roots results in

the formation of characteristic clubs (Ingram and Tommerup, 1972). Clubs typically form on

roots 4–6 weeks after the initial infection (Korbas et al., 2009). The resulting disruption of the

xylem inhibits water and nutrient uptake (Karling, 1942).

As the clubs mature, they become brown in color and decompose to disperse the resting

12

spores into the soil (Ayers, 1944). Resting spores start to reach maturity at 5–9 weeks after

infection, and sometimes earlier (Al-Daoud et al., 2020). Resting spores are spherical in shape,

3.0–5.0 µm in size, with spiny ornamentations on the exterior wall, and contain a nucleus 1.5 µm

in diameter (Ingram and Tommerup, 1972). They can be long-lived and remain dormant in the

soil for many years, with a half life estimated as 3–6 years (Wallenhammar, 1996). However,

recent studies have demonstrated that half life is not the best approach to describing the viability

of resting spores. The survival of resting spores follows a Type III survival curve. Many die

within the first two years of production, but the small percentage that survive are very persistent

(Gossen et al., 2019). The cell walls contain 25.1% chitin and 24.4% carbohydrates, which

protect against enzyme degradation in soil (Moxham and Buczacki, 1983). The concentration of

resting spores in the soil is a major determinant of the severity of infection (Korbas et al., 2009).

Generally, consistent clubroot symptoms develop at a minimum concentration of 103 resting

spores g-1 dry soil (Naiki et al., 1978). Infection of cortical cells and overall clubroot severity

increased with increasing concentrations of resting spores in soil with maximum severity

occurring at 106 resting spores g-1 and above (Hwang et al., 2011a; Murakami et al., 2002a; Peng

et al., 2019).

1.4.2 Pathotyping systems

A pathotype is a population of a species in which all members have the same

pathogenicity in a host genotype. Pathotypes can be identified using a set of differential hosts

(Strelkov et al., 2018). In contrast, a race is a population in which all members have the same set

of virulence genes (Parlevliet, 1985). A system for differentiating pathotypes of P. brassicae was

developed by Williams (1966). The hosts in the Williams differential set were two cabbage (B.

oleracea) cultivars, Jersey Queen and Badger Shipper, and two rutabaga (B. napus var.

13

napobrassica) cultivars, Laurentian and Wilhelmsburger. Nine P. brassicae pathotypes were

found with this system from testing 124 isolates from 16 countries.

A European Clubroot Differential (ECD) set was developed using three Brassica spp.

(B. rapa, B. napus and B. oleracea), each represented by five cultivars, for a total of 15

differential hosts. This system uses a binary notation to code pathotypes (Buczacki et al., 1975).

This system has been used internationally to pathotype P. brassicae isolates. However, the ECD

set has limitations. For example, some isolates are resistant to all of the differential hosts or

cause a low clubroot severity, which makes interpretation of assessment difficult, especially

because the host reaction can be highly dependent on environmental conditions (Donald et al.,

2006). Another concern is that the value for determining clubroot incidence required for an

isolate to be considered virulent is arbitrary.

A differential system was developed to characterize P. brassicae populations from

France. The differential hosts from the Williams differential set, five hosts from ECD set and

two new B. napus hosts were included. The three B. napus hosts, Nevin, Wilhelmsburger and

Brutor, and the susceptible B. napus control, Giant Rape could be used to differentiate

pathotypes from 17 single-spore isolates from France (Somé et al., 1996).

The Canadian Clubroot Differential (CCD) set was developed in response to the increase

in new, virulent P. brassicae populations on previously resistant canola cultivars in Canada. The

new virulent pathotypes could not be identified in the differential series of Williams, Somé et al.,

or the ECD. The CCD uses 13 differential hosts, including hosts from Williams, Somé et al., the

ECD and the canola cultivars, Westar and 45H29. This system uses letters (A, B, C, etc.) to

denote pathotypes. Seventeen pathotypes from isolates from 106 fields in Alberta were identified

with the CCD Set. In comparison, the Williams set detected five pathotypes and Somé et al.

14

detected two pathotypes from these isolates (Strelkov et al., 2018). Since the development of this

system, the nomenclature has been modified to include the Williams pathotype number and a

letter to designate differences from the Williams system (Askarian et al., 2020).

A differential set for use with B. oleracea cultivars, including cauliflower, cabbage,

Brussels sprouts and Savoy cabbage, has also been developed (Smilde et al., 2012). This system

uses three B. oleracea cultivars: Lodero (red cabbage), 051632 (white cabbage), and one of

Kilaton (white cabbage), Monclano (broccoli), Clapton (cauliflower) or Crispus (Brussels

sprouts) (International Seed Federation, 2016; Smilde et al., 2012). Kilaton, Monclano, Clapton

and Crispus had the same clubroot reactions against the tested pathotypes (International Seed

Federation, 2016). This system identifies four pathotypes, designated Pb:0, Pb:1, Pb:2 and Pb:3

(International Seed Federation, 2016; Smilde et al., 2012).

A limitation of all of these differential sets is that they include host genotypes that are

open-pollinated, so the seed is not genetically homogenous (Strelkov et al., 2018). Thus, there

can be inconsistent reactions to a specific pathotype. There can also be more than one pathotype

in one club (Sedaghatkish et al., 2019; Strelkov et al., 2018; Xue et al., 2008).

1.4.3 Clubroot in Canada

In Canada, one of the first reports of clubroot on brassica vegetables was in the 1920s

(British Columbia Department of Agriculture, 1920). In 1966, pathotype 6 was reported in

British Colombia and pathotypes 2 and 4 were reported in Quebec (Williams, 1966). In 1972,

pathotypes 1, 2, 3 and 4 were reported in Maritime provinces, pathotype 2 was reported in

Quebec and pathotype 6 was reported in British Colombia and Ontario (Ayers, 1972). Pathotype

2 was found on rutabaga in Ontario in 1974 (Reyes et al., 1974) These early identifications,

together with more recent studies, have recently been summarized (McDonald et al., 2020a).

15

Clubroot was first detected on canola in Alberta in 2003 and was determined to be

pathotype 3. The pathogen spread among fields, primarily in soil carried on farm machinery (Cao

et al., 2009). The importance of this method of spread was shown by the finding that the highest

clubroot incidence was near the entrances of fields and severity decreased further into the fields

(Cao et al., 2009; Strelkov et al., 2007). Inoculum can also move between fields in manure from

livestock fed with fodder infected with the pathogen, on infested seeds, and by wind and water

(Karling, 1942; Rennie et al., 2011). Plasmodiophora brassicae was classified as a controlled

pest under Alberta’s Agriculture Pests Act in 2007, and under Saskatchewan’s Pest Act in 2009

(Cao et al., 2009; Rempel et al., 2014). These acts implemented methods of containing clubroot

spread, such as equipment sanitation and limiting how frequently canola could be planted in

infested fields (Cao et al., 2009).

Clubroot pathotype 2 (Williams’ system) and more recently 2X have recently caused

outbreaks in canola in Ontario (Al-Daoud et al., 2018; McDonald et al., 2020a). The ‘X’

indicates that the pathotype is virulent on the first generation of clubroot resistant canola

cultivars and can not be identified on Williams’ differential set. In 2019, pathotype 3X was also

found in one canola field in Ontario (McDonald et al., 2020a). Pathotype 6, the common

pathotype on vegetables in Ontario, is not very damaging to canola (Al-Daoud et al., 2018).

Pathotype 3 is the most common pathotype found in Alberta and has been found to cause more

severe symptoms on canola than pathotype 6 and other pathotypes (Deora et al., 2013; Gossen et

al., 2016). Between 2014 and 2016, a number of new, virulent pathotypes were identified from

central Alberta (Strelkov et al., 2018). Aggressiveness often varies among pathotypes; however,

this is likely due to pathotype-cultivar specificity rather than characteristics of the pathotypes

themselves (Sharma et al., 2013b).

16

1.4.4 Host-pathogen interaction

All stages of clubroot infection only occur in compatible interactions, where P. brassicae

is virulent and the host is susceptible. In compatible interactions, P. brassicae tends to suppress

any defense reaction initiated by the host (McDonald et al., 2014). For example, P. brassicae

inhibits lignin biosynthesis and production of reactive oxygen species (ROS) that could restrict

plasmodia formation (Deora et al., 2013; Pedras et al., 2008). In addition, P. brassicae alters host

metabolism and the availability of essential molecules and nutrients. Low amyloplast

concentrations have been found in infected plants which may be the result of P. brassicae using

starch as a carbon source (Deora et al., 2013). Clubs are also a major metabolic sink for

photosynthate (Ludwig-Müller and Schuller, 2008).

In compatible interactions, pathogen colonization causes cellular damage and increased

production of growth hormones. This results in rapid cell divisions in cortical tissues and

weakening of the walls of cells neighbouring infected cells (Deora et al., 2013). Cell wall

breakages can occur, and vesicles and inclusion bodies can develop in cell walls (Deora et al.,

2013; Donald et al., 2008). In addition, genes that increase levels of growth hormones, including

auxins, cytokinins and brassinosteroids, are activated (Hwang et al., 2012c; Ludwig-Müller,

2016). High levels of growth hormones cause hyperplasia and hypertrophy in cortical cells.

Auxin concentrates in epidermal cells and is gradually displaced into clubs in later disease

stages, accumulating primarily in the edges of clubs (Ludwig-Müller, 2016). Cytokinins are

produced by both the pathogen and the host and are transported to the secondary plasmodia

(Ludwig-Müller et al., 2009). Brassinosteroids may also cause cellular elongation in host roots

(Ludwig-Müller, 2016). Further, xyloglucan endo-transglucosylase/hydrolase becomes localized

in the epidermal layer of infected roots. Accumulation of indole-3-acetic acid and xyloglucan

17

endo-transglucosylase/hydrolase action is associated with loosening of cell walls and expansion

of epidermal cells and can cause plant growth promotion during the primary infection stage

(Devos et al., 2005). Auxin concentrates in epidermal cells and is gradually displaced into clubs

in later disease stages, accumulating primarily in the edges of clubs (Ludwig-Müller, 2016).

In incompatible interactions, resistant hosts can activate defense responses to restrict

clubroot development. Root hair infection, including the production of secondary zoospores,

occurs in compatible (susceptible host and virulent pathotype), incompatible and intermediate

interactions (Deora et al., 2012). However, the incidence of root hair infection is slightly higher,

and total P. brassicae DNA concentration and rate of disease progression is substantially higher

in susceptible cultivars compared to resistant cultivars (Deora et al., 2013; Hwang et al., 2011b;

Hwang et al., 2012a). It has been suggested that defense genes are generally not expressed

during the root hair infection stage (Hatakeyama et al., 2013), but the work of McDonald et al.

(2014) indicated that host response is initiated during root hair infection/colonization. Resistance

is also initiated during the root hair infection stage of certain nonhost plants, such as perennial

ryegrass (Lolium perenne L.) (Feng et al., 2012). The initiation of resistance in root hairs is

supported by the finding of Mei et al. (2019) that receptor kinases and guanine nucleotide-

binding regulatory proteins (G proteins) were activated in response to P. brassicae during the

root hair infection stage in the resistant B. napus genotype ‘ZHE-226’. G proteins are cell

membrane receptors that transduce extracellular signals to activate effector enzymes. These

effector enzymes in turn activate secondary messengers involved in defense responses (Neer,

1995). Resistance was, however, also initiated in the root cortex during the secondary disease

stage (McDonald et al., 2014).

In incompatible interactions, plasmodia development in the root cortex was limited and did

18

not cause damage to xylem cells (Donald et al., 2008; Hwang et al., 2012c). Generally,

plasmodia did not develop into large, multinucleate plasmodia, but rather, decreased over time.

A hypersensitive response was not a primary resistance reaction in cortical tissues of B. napus, as

ROS accumulation and lignification in these tissues was limited. However, ROS accumulated in

outer areas of the stele, and the secondary xylem cells in the stele became lignified (Deora et al.,

2013).

The timing of initiation of resistance can vary with the host. In the resistant cabbage

‘Kilaherb’, resistance was expressed in the root cortex following cortical infection (Gludovacz et

al., 2014). However, no cortical infection occurred at any inoculum concentration in the resistant

cabbage ‘Tekila’ (Peng et al., 2019), which indicated possible differences in the expression of

resistance among cultivars. In the partially resistant cabbage cultivar ‘B-2819’, cortical infection

was delayed at inoculum concentrations of 1 × 106 resting spores mL-1 at 28 days post inoculation

(DPI) and is intermediate at 1 × 107 spores mL-1 at 28 DPI. This indicated that the mechanism

underlying partially resistance in ‘B-2819’ differed from that in ‘Tekila’ (Peng et al., 2019). ‘B-

2819’ also had a different mechanism than ‘Kilaherb’, as resting spores were produced, and

clubbing developed in ‘B-2819’ but do not in ‘Kilaherb.’ Resistance in ‘Kilaherb’ may be due to

lignin deposition in cell walls and oxidative cross-linking of polymers to inhibit the colonization

of P. brassicae (Gludovacz et al., 2014).

Inoculum concentration has a significant effect on disease development in ‘B-2819’, as

concentrations of 2 × 108 spores mL-1 resulted in higher clubroot severity than concentrations of

1 × 106 spores mL-1 (Peng et al., 2019). This response is consistent with quantitative resistance.

Quantitative resistance is polygenic, resulting from the joined action of multiple genes, and

so does not depend on the race/pathotype of the pathogen. Qualitative resistance is race specific

19

as the mechanisms differ depending on the race/pathotype and the host cultivar. This resistance

is monogenic as it is controlled by major resistance genes in the host (Van der Plank, 1969). The

source of resistance in many brassica hosts is qualitative (Diederichsen et al., 2009). In canola,

resistance in the initial generation of resistant cultivar was due to a minimum of three resistance

genes and a few quantitative trait loci (Hwang et al. 2012c). Resistance to pathotype 2 of P.

brassicae in B. rapa was conferred by the CR loci, Crr1 and Crr2, polygenically. The two loci

did not confer significant resistance alone. The Crr1 and Crr2 loci were located on different

regions of chromosomes or on separate chromosomes (Suwabe et al., 2003). Crr1aG004 allele was

expressed during the cortical infection stage in the stele and cortex of hypocotyls and roots of

susceptible B. rapa and Arabidopsis plants. The Crr1aG004 loci, encoded a Toll-Interleukin-1

receptor/nucleotide-binding site/leucine-rich repeat class of R protein. Expression of Crr1aG004

may be involved in inhibiting the formation of plasmodia in cortical cells (Hatakeyama et al.,

2013). A third CR locus, Crr3, was identified in B. rapa (Hirai et al., 2004). Identifying and

characterizing CR genes is useful in the breeding of CR cultivars (Hirai et al., 2004).

Salicylic acid (SA) is a phytohormone involved in growth and development as well as in

the defense responses in plants. Applied to roots of broccoli, SA was systemically carried to

leaves and up-regulated the pathogenesis related genes PR-1 and PR-2 in leaf tissues (Lovelock

et al., 2013). Clubbing symptoms were lower in plants treated with SA, suggesting that SA could

be used to manage clubroot. Jasmonic acid (JA) also functions in defense responses and when

applied together, SA and JA can increase host resistance. However, SA had toxic effects at

concentrations above 5 mM SA, inhibiting plant growth and photosynthetic reactions and

causing leaf chlorosis and necrosis (Lovelock et al., 2013). Biosynthesis of antimicrobial

compounds, such as phytoalexins and phytoanticipins also occurs in infected roots as a defense

20

response (Pedras et al., 2008).

Resistant hosts can display symptoms, including stunting and delayed flowering (Deora et

al., 2012; Donald et al., 2008) associated with the metabolic costs of resistance, even though

they do not develop clubs. Delayed maturity and reduced growth were most severe in resistant

cultivars grown in heavily infested soil; plants were not as affected at low infestation levels

(Gossen et al., 2017b).

1.5 Factors affecting clubroot development

1.5.1 Soil pH

Soil pH is a measure of the concentration of hydrogen ions in soil and is the negative log

of this concentration. The scale for pH ranges from 0 to 14 where 7 is neutral, 14 is very basic,

and 0 is very acidic. Soil pH is mainly affected by the geological materials of the soil, but is also

affected by other factors, including precipitation, decay of organic material, and fertilizers. In

many soils in Ontario, pH is low or neutral at the soil surface and increases deeper into the soil

profile. The capacity of the soil to withstand changes in pH can be measured by buffer pH.

Buffer pH is affected by the cation exchange capacity of the soil. A greater cation exchange

capacity provides a reserve of absorbed hydrogen ions that can go into solution if pH rises,

allowing soil to resist changes in pH (OMAFRA, 2018).

Many studies have demonstrated the effects of pH on the development of clubroot. For

example, root hair infection and club development were inhibited in broccoli when the soil pH

was increased to over 7.2 (Myers and Campbell, 1985). At these high pH levels, the

zoosporangia aborted, preventing the release of secondary zoospores. Also, acidic soils had

higher concentrations of phenolic compounds, including p-hydroxybenzoic acid, p-

hydroxyphenulpyruvic acid, trans-p-coumaric acid and humic acid, and were conducive to

21

clubroot infections (Young et al., 1991). Generally, pH levels of 5.0–6.5 were more conducive to

clubroot development compared to more alkaline pH levels. The pathogen did not progress

beyond primary plasmodia at a pH of 7.5–8.0 (Gossen et al., 2013). Resting spore germination

also decreased at pH values above 7.0 compared to pH values of 5.0–7.0 (Rashid et al., 2013).

The highest rate of resting spore germination was at pH 6.5. However, there are other factors that

affect the development of clubroot symptoms. While clubroot severity was higher in acidic fields

of canola in Alberta, clubbing still occurred in fields with a soil pH of 4.8–7.6 (Strelkov et al.,

2007).

The effect of pH on clubroot development is influenced by calcium. For example, cabbage

grown in clubroot infested calcium-rich organic waste (farmyard manure or food factory sludge

compost) suppressed clubroot development due to the increase in both soil pH and calcium

concentration (Niwa et al., 2007). A neutral pH, achieved with the application of calcium to soil,

suppressed infection by inhibiting the germination of resting spores in the rhizosphere (Niwa et

al., 2008). In addition, calcium reduced the motility of primary zoospores and restricted the

formation of plasmodia and zoosporangia during the primary infection stage (Dixon and Page,

1998; Myers and Campbell, 1985). Root hair infection in canola was lower at pH values above

7.0 when grown in the presence of a nutrient solution containing calcium. Root hair infection and

disease severity in canola were higher at high pH values (pH 6.5–9.0) when calcium-salt was not

added to the growth medium (Rashid et al., 2013). Calcium suppressed the dehiscence of

zoosporangia under high disease pressure and the formation of zoosporangia at lower pressure

(Webster and Dixon, 1991b). Certain forms of calcium also promote beneficial microorganisms

that are suppressive to P. brassicae by increasing soil pH (Dixon, 2016).

Boron can also reduce clubroot development. Boron inhibited club formation by slowing

22

the rate of infection of root hairs and the cortex. Boron more effectively suppressed clubroot at

pH 7.2 than pH 6.2 (Webster and Dixon,1991a). Boron increased seed yield and shoot weight in

canola even at high levels of clubroot severity. In one study, boron effectively reduced clubroot

infection in organic soils but was less suppressive in mineral soils (Deora et al., 2014). This may

be due to the high capacity of organic soils to retain boron. However, a potential issue with the

application of boron is that residual boron in soil might have a phytotoxic effect on subsequent

crops (Deora et al., 2014).

In addition to boron and calcium, clubroot is also suppressed by potassium hydroxide and

magnesium (Myers and Campbell, 1985; Niwa et al., 2007; Young et al, 1991). Likewise, certain

soil components such as nitrogen, sodium and manganese reduce resting spore germination

(Friberg et al., 2005). Nitrate-nitrogen also suppressed the development of primary plasmodia

into zoospores (Dixon and Page, 1998).

1.5.2 Temperature

Temperature during each phase of the disease cycle influences clubroot infection. Root

hair infection developed at a minimum temperature of 12–14°C in swede turnip (Ayers, 1944).

Similarly, severity of root hair infection in Shanghai pak choi was highest at 25°C and

significantly lower below 15°C (Sharma et al., 2011b). Further, the minimum threshold for

clubroot development in canola in field conditions was 14°C (Gossen et al., 2017a). Cortical

infection occurred in Shanghai pak choi at temperatures of 15–30°C and clubs only formed on a

susceptible cultivar at 20–30°C. Temperatures also delayed disease progression; infection of

cortical cells and development of young plasmodia was observed at 10 days after inoculation at

20–30°C and 22 days after inoculation at 15°C. Mature plasmodia were detected in cortical cells

10 days after inoculation at 25°C and 14 days after inoculation at 20°C and 30°C. The production

23

of resting spores occurred 12 days after the formation of mature plasmodia and was not

influenced by temperature (Sharma et al., 2011a). The degree and severity of clubroot infection

and the number of resting spores produced were greatest at 25°C, lower at 20°C and 30°C, and

lowest at 15°C (Sharma et al., 2011b). Soil or air temperature can be used as an indicator for

clubroot development (McDonald and Westerveld, 2008).

The effect of temperature on clubroot infection also varies with pH. Root hair infection

was the most severe at 25°C at a pH of 6.0–6.5 and at 20°C at a pH of 5.5–6.0. The temperature-

pH interaction with the highest disease incidence was a temperature of 25°C and a pH of 6.0.

The infection progressed more slowly at 10°C and 15°C when the pH was between 6.0–8.0 than

at higher temperatures (Gossen et al., 2013). Similarly, the highest activity levels of Pro1

occurred at 25°C and a pH of 6.0–6.4 (Feng et al., 2010).

1.5.3 Soil moisture

High moisture levels in soil are conducive to clubroot development, likely because free

water is required for resting spores to germinate and zoospores to swim and infect root hairs

(Ayers, 1944). Generally, higher clubroot incidence occurs in fields with poorly drained soils.

Low spots in fields often have poor drainage and higher levels of disease (Gossen et al., 2016;

Wellman, 1930). However, waterlogged soils inhibited zoospore respiration and movement in

the soil, which can delay infection (Berglund et al., 2007).

1.5.4 Soil types

Soils low in organic matter or high in clay content have occasionally been identified as

being conducive to clubroot development (Pageau et al., 2006). However, if sufficient moisture

is present, clubroot can develop in many soil types, including sand, mineral soil and soil high in

organic matter (Gossen et al., 2016). For example, susceptible crops can develop 100% clubroot

24

DSI in the high organic matter (50–75% OM) soils of the Holland Marsh. Some authors report

that soil types conducive to infection can also be pathotype dependent; for example, pathotype 2

was typically identified from sandy soils while pathotype 6 was typically from loam and muck

soils (Reyes et al., 1974). However, these differences may be associated to the crops grown on

these soils rather than the soil type itself.

1.5.5 Pathogen distribution in soil

The highest concentration of resting spores of P. brassicae is usually in the top 20 cm of

soil, with the concentration generally decreasing deeper in the soil profile. However, resting

spores move deeper into the soil over time (Cranmer et al., 2017). Therefore, in fields with

recent clubroot outbreaks, resting spores were mostly concentrated on the top layer of soil (10

cm) while in fields infested with P. brassicae for many years, resting spores were also found

deeper in the soil profile. The no-till production of canola in Western Canada would also leave

resting spores in the top layer of the soil. Resting spores at depth in the soil profile will likely

only come in contact with roots late in a growing season and therefore have a low chance of

reducing yield or seed quantity and quality. In addition, resting spores may not germinate at that

low soil depth due to the cooler soil temperature (Cranmer et al., 2017).

1.6 Clubroot management strategies

1.6.1 Preventing pathogen dissemination

The transportation of infested soil on farm equipment is major source of clubroot

dissemination between fields (Karling, 1942). To minimize pathogen dispersal on equipment,

soil and crop residues should be cleaned from equipment with a pressure washer, compressed air,

or scrubbing. A disinfectant should be subsequently applied to the equipment. Footwear,

vehicles, and any other tools should also be cleaned (Howard et al., 2010). However, adoption of

25

disinfection practices has been limited among farmers due to the time required to adequately

sanitize machinery (Rempel et al., 2014).

In addition, farmers should ensure that ponds or creeks used for irrigation have not been

contaminated with runoff from infested fields (Howard et al., 2010). The use of manure of

livestock fed with infected crops should also be avoided (Karling, 1942). Seed can also carry and

disseminate the disease, so cleaning and treating commercial seeds will reduce the risk of seed-

borne infection (Rennie et al., 2011).

Management of cruciferous weeds is important to manage clubroot. Cruciferous weeds,

such as Brassica kaber (wild mustard), Capsella bursa-pastoris (shepherd’s purse), and

Descurainia sophia (flixweed) are hosts of P. brassicae and can significantly increase resting

spore concentrations in soil (Reye et al., 1974). Removing weeds within three weeks of their

emergence is recommended to avoid the release of new resting spores into the soil (Canola

Council of Canada, 2020b). Clubs have fully mature resting spores in canola 5–9 weeks after

sowing in an infested field or inoculation. Resting spores can also continue to mature after hosts

cells have been killed by herbicide or shoots have been removed (Al-Daoud et al., 2020).

1.6.2 Resistant cultivars

The Canola Council of Canada recommends using commercial clubroot-resistant (CR)

cultivars to manage clubroot and to slow its spread in a field. A crop is designated as CR if that

crop does not develop symptoms of clubroot, although this designation has been modified by

seed companies. A crop is tolerant if clubs develop on roots but there is no yield reduction (Crute

et al., 1980). Canola cultivars are classified into categories by seed companies based on their

resistance to clubroot compared to a susceptible check. Cultivars are classified as resistant

(<30% infection compared to the check), moderately susceptible (30–50% infection compared to

26

the check) or susceptible (>50% infection compared to the check) (Canola Council of Canada,

2020b). The use of resistant cultivars is a cost-effective and environmentally friendly method of

managing clubroot (Cao et al., 2009). Resistant cultivars had greater emergence rates, plant

height and overall yields than susceptible cultivars grown in clubroot-infested soil (Hwang et al.,

2011b). However, the effect of CR on canola yield was highest under high disease pressure and

was not observed under low disease pressure (Sharma et al., 2013b).

The introduction of dominant CR genes into cultivars was first conducted in B. napus and

B. rapa (Crute et al., 1980). The development and release of CR cultivars of every brassica

species followed (Piao et al., 2009). Brassica rapa ssp. rapifera (European fodder turnip)

confers resistance to multiple pathotypes and is therefore frequently used as the source of CR

genes (Hirai, 2006).

Multiple CR loci have been identified in B. rapa, including Crr1, Crr2, Crr3, Crr4, CRa,

CRb, CRk, CRc and CRd (Hirai et al., 2004; Matsumoto et al., 1998; Pang et al., 2018; Piao et

al., 2002; Piao et al., 2004; Sakamoto et al., 2008; Suwabe et al., 2003; Suwabe et al., 2006).

Major dominant genes, such as, Pb-Bn1, and quantitative trait loci (QTLs) have been found in B.

napus (Li et al., 2016; Manzanares-Dauleux et al., 2000; Werner et al., 2008). In addition, many

QTLs have been found in B. oleracea, such as CR2a, CR2b, pb-3, pb-4, Pb-Bo1, CRQTL-GN_1

and CRQTL-GN_2 (Figdore et al., 1993; Grandclément and Thomas, 1996; Landry et al., 1992;

Lee et al., 2016; Moriguchi et al., 1999; Rocherieux et al., 2004; Vorrips et al., 1997). There is a

current international initiative to establish consistent nomenclature for CR loci, including

identifying genes that have been given different names by different research groups

(Diederichsen et al., 2019).

Studies of CR resistance have shown that resistance in the hybrid winter B. napus cultivar

27

Mendel was controlled by a major dominant gene from B. rapa ssp. rapifera and two recessive

genes (Diederichsen et al., 2006). Resistance genes from B. rapa have been transferred into

Chinese cabbage, oilseed rape and B. oleracea to create resistant cultivars (Diederichsen et al.,

2009). Also, interspecific hybridization has been used to transfer clubroot resistance from one

brassica species to another (Hirani et al., 2016; Niemann et al., 2018; Zhan et al., 2017).

The first resistant cultivar of canola in Canada, ‘45H29’ (Pioneer), was introduced in 2009.

Initially, most Canadian canola cultivars were resistant to pathotype 6 but are susceptible to

pathotype 3 (Deora et al., 2013). Many resistant canola cultivars have since been released with

over 20 CR canola cultivars registered in 2018 (Strelkov et al., 2018). The source of resistance in

cultivars is not in the public domain (Strelkov et al., 2018), but is known to be based on

resistance genes that are pathotype specific (Diederichsen et al., 2009).

One major drawback of reliance on host resistance has been that resistance based on single

genes is not durable. As a result, rapid selection for virulent pathotypes that were present in the

population in (presumably) low numbers that can overcome resistance can occur (Hollman et al.,

2020; Peng et al., 2014a; Peng et al., 2015; Sedaghatkish et al., 2019; Strelkov et al., 2018).

Around 3–4 years after CR canola cultivars were first released, a few P. brassicae populations

were identified that were able to cause clubroot on the CR cultivars. The number of new virulent

pathotypes continues to increase. The pathotypes that have emerged and overcome clubroot

resistance in Canada were likely already present in P. brassicae populations. Balancing selection

allowed these pathotypes to be retained in the population at low frequencies (Sedaghatkish et al.,

2019).

Similarly, susceptible cultivars of brassica crops, primarily vegetables, were grown at the

University of Guelph Muck Crops Research Station, Holland Marsh, Ontario prior to 2009, while

28

moderately resistant or resistant cultivars of canola and some brassica vegetables were grown

after 2009. The dominant pathotype had been pathotype 6 (Williams’ system) for many years,

but shifted to pathotype 2 between 2011 and 2014 (Al-Daoud et al., 2017a).

Resistance is also less effective if resistant cultivars are grown with susceptible plants such

as weeds and volunteers, that release resting spores back into the soil (Hwang et al., 2012a).

Further, a small percentage of each CR cultivar can become infected, even if they are resistant to

the pathotypes in a field because of off-types in each seed lot (Hwang et al., 2019). Therefore,

cultivating resistant cultivars in infested soil can increase inoculum levels. For example, an

initial concentration of 1.0 × 105 resting spores g-1 of soil was found to increase to 2.6 × 105

spores g-1 soil one year after growing CR canola (Ernst et al., 2019).

Other clubroot management strategies, such as crop rotation and weed management,

should therefore be used in addition to resistant cultivars to delay the breakdown of resistance

and to reduce inoculum in soil (Hwang et al., 2012b).

1.6.3 Crop rotation

Rotation with a nonhost crop or a fallow period decreases soil inoculum, increases yield,

and reduces clubroot severity compared to continuously growing susceptible canola (Hwang et

al., 2019). There is an average yield benefit of 19% in canola when grown in 3-year and 2-year

rotations over 6 years compared to continuously growing canola in the absence of clubroot (Gill,

2018). Many crops are commonly grown in rotation with canola, including wheat (Triticum

aestivum L.), pea (Pisum sativum L.), barley (Hordeum vulgare L.), pulses, and to a lesser extent

flax (Linum usitatissimum L.), buckwheat (Fagopyrum Mill.), oat (Avena sativa L.), rye (Secale

cereal L.), corn (Zea mays L.), and forage legumes (Canola Council of Canada, 2020a; Gill,

2018). The risk of clubroot and other diseases in canola is lower the more species that are

29

included in rotation sequences (Gill, 2018). In Western Canada, cereals and pulses are generally

grown in rotation with canola (Canola Council of Canada, 2020a; Gill, 2018). Wheat, soybean,

and corn are grown in rotation with canola in Ontario (OMAFRA, 2020; Ontario Grain Farmer

Magazine, 2021).

The most important reduction in resting spore concentrations in soil occurs in the first 1–2-

year break from a host, as P. brassicae spores follow a Type III survivorship curve (Gossen et

al., 2019). A 2-year break can reduce resting spore concentrations by 90% in heavily infested

field plots (Peng et al., 2014b). This finding was supported by a study by Peng et al. (2015) that

reported that a 4-year break was not significantly different than a 2-year break in reducing

resting spore concentrations. Therefore, the Canola Council of Canada (2020a) recommends a

minimum 2-year break from growing canola in clubroot-infested fields.

Fully eradicating P. brassicae from a field, however, is difficult as many of the spores that

survive the initial few years break from a host can survive for many years. After a 19-year break

from growing host crops, inoculum was still present in fields (Rastas et al., 2013). Therefore, in

heavily infested soils, high clubroot severity can still occur on susceptible and moderately

susceptible canola cultivars grown after a minimum 2-year break (Gill, 2018).

1.6.4 Bait crops

Bait crops are hosts or nonhosts that produce root exudates that stimulate the germination

of resting spores (Ahmed et al., 2011). Primary zoospores may be unable to infect a host and die,

leading to a reduction in soil inoculum (Friberg et al., 2006; Macfarlane, 1952; Takahashi,

1994a). Leafy daikon (also known as tillage radish, Raphanus sativus L. var. longipinnatus),

perennial ryegrass (Lolium perenne L.), creeping bentgrass (Agrostis stolonifera L.), and

strawberry (Fragaria spp. L.) can be used as bait crops for clubroot (Feng et al., 2012;

30

Murakami et al., 2000). Bait crops are likely to be the most effective in fields with low or

moderate clubroot infestations (Ahmed et al., 2011).

Leafy daikon grown as a cover crop has been effective in clubroot management (Murakami

et al., 2000). Leafy daikon breaks down soil layers to allow for increased water and nutrient

availability and root growth (Sharma et al., 2013b). In addition, leafy daikon decreases clubroot

inoculum in the soil by stimulating resting spore germination without leading to the production

of new resting spores. Disease indices in Chinese cabbage, broccoli, Brussels sprouts and

Shanghai pak choi, when grown after leafy daikon, were found to be significantly lower than

when these crops were grown without leafy daikon as a cover crop (Murakami et al., 2000). Low

levels of clubbing developed on tillage radish in controlled conditions but not under field

conditions (Sharma et al., 2013b).

Potato onion (Allium cepa var. aggregatum Don.) grown in rotation with Chinese cabbage

reduced clubroot incidence in Chinese cabbage (Chen et al., 2018). Root exudates of potato

onion suppressed the expression of Pro1, a gene involved in stimulating resting spore

germination (Chen et al., 2018; Hwang et al., 2012c). Chinese cabbage grown in rotation with

potato onion had a smaller number of secondary plasmodia in cortical cells and had overall lower

clubroot incidence (Chen et al., 2018).

Residues of meadowfoam (Limnanthes alba Hartweg ex. Benth), an oilseed crop, can

reduce clubroot incidence in cauliflower and mustard. Meadowfoam produces allelochemicals,

including glucosinolates and phytoecdysteroids, which can suppress P. brassicae. Glucosinolates

cause fungistasis in resting spores. However, application of high rates of meadowfoam residue

can have phytotoxic effects on cauliflower and mustard seedlings (Deuel and Svenson, 2000).

The proportion of resting spore germination can vary with the plant species. Root exudates

31

from ryegrass triggered the germination of more resting spores than both a host (Brassica rapa

var. perkinensis) and nonhosts, such as leek (Allium porrum L.), rye (Secale cereale L.) and red

clover (Trifolium pretense L.) (Friberg et al, 2005). In addition, root exudates from perennial

ryegrass stimulated resting spore germination at a higher rate than root exudates from canola and

Chinese cabbage (Rashid et al., 2013). In contrast, cruciferous hosts such as canola and Chinese

cabbage were more effective as bait crops compared to cereals and non-cruciferous hosts, such

as bentgrass (Agrotis palustris Huds.), orchardgrass (Dactylis glomerata L.), ryegrass or red

clover (Ahmed et al., 2011).

Smooth bromegrass (Bromus inermis L.), meadow bromegrass (Bromus riparius Rehm.)

and perennial ryegrass reduced resting spore levels in soil under controlled conditions

(Sedaghatkish, 2020). Bioassays to evaluate the effect of bait crops on resting spores and

clubroot severity can, however, be difficult to replicate in field conditions (Friberg et al., 2006).

For example, leek, winter rye, perennial ryegrass and red clover, which stimulated resting spore

germination under controlled conditions, were not effective in reducing P. brassicae in soil in

field studies. Environmental conditions and soil texture, chemistry and composition, and the

initial concentration of resting spores are possible factors that could have influenced this finding

(Friberg et al., 2006).

The root hair infection stage is very similar between a host plant and ryegrass. However,

while the secondary zoospores produced on ryegrass were infectious to both canola and ryegrass,

they caused smaller clubs to form on canola compared to the secondary zoospores produced on

canola. Resistance to the cortical infection stage in ryegrass is likely triggered during the root

hair infection stage (Feng et al., 2012). While clubroot infection is limited to the root hair

infection stage in nonhosts, secondary infection can occur in ryegrass if inoculated with

32

secondary zoospores (Feng et al., 2012; Friberg et al., 2005). However, no vegetative plasmodia

or resting spores developed. Secondary infection can occur in ryegrass inoculated with secondary

zoospores because typical nonhost mechanisms that are initiated during the root hair infection

stage are bypassed (Feng et al., 2012).

1.6.5 Seeding date

Clubroot infection is lower when temperatures are lower early in the season (Hwang et al.,

2012b; Sharma et al., 2011a). Clubroot severity was lower in canola seeded early in spring

compared to canola seeded later in the spring (Hwang et al., 2012b). Similarly, seeding

susceptible Asian brassica vegetables early in the spring or in late in the summer (August or

September) resulted in reduced clubroot severity (McDonald and Westerveld, 2008). Host crops

can become better established when temperatures are low. The optimal temperature for canola

germination and early seedling growth is 22°C and germination is low below 10°C. However,

canola seed can germinate and grow at temperatures as low as 2°C (Nykiforuk and Johnson-

Flanagan, 1994). The pathogen does not develop until temperatures are 14–18°C (Gossen et al.,

2017a). Older plants are less vulnerable to clubroot infection than younger plants in the high

temperatures conditions that are more conducive to infection later in the growing season (Hwang

et al., 2012b). Thus, the highest disease severity and even plant death occurs when plants are

infected at the seedling stage and temperatures are optimum for disease development.

1.6.6 Liming

Farmers have limed fields since the early 19th century to manage clubroot infestations

(Bélec et al., 2004). Early studies have found calcium oxide, stone limes and hydrated limes to

be effective in controlling clubroot (Wellman, 1930). Limes should be applied to attain a soil pH

of 7.2 for optimal for disease suppression (Myers and Campbell, 1985). Calcium cyanamide,

33

dolomite and calcium carbonate are common types of lime to reduce clubroot incidence in

Chinese cabbage and reduce resting spore concentration in soils (Murakami et al., 2002b).

Agricultural limes (calcitic lime) and dolomitic limes (calcium magnesium carbonate) are slow

acting and should be applied in high concentrations in the fall for spring seeding as these limes

take several months to alter soil pH. Other forms of lime include quicklimes (calcium oxide) and

hydrated limes (calcium hydroxide), which is produced by mixing water with calcium oxide,

generating heat. Hydrated limes should be applied in the spring; although they are fast acting,

they have shorter term effects (Hwang et al., 2014b). Organic matter with high calcium content

can also be applied to neutralize soil pH (Niwa et al., 2008). However, large quantities of organic

matter can lead to nitrogen leaching (Niwa et al., 2007).

Calcium cyanamide (trade name Perlka) is a slow-release-nitrogen-source granular

fertilizer that suppressed clubroot in Asian brassica vegetables (Bélec et al., 2004; McDonald et

al., 2004). Calcium cyanamide breaks down into calcium oxide (which neutralizes soil pH) and

urea and should be applied 1–2 weeks prior to seeding to allow for conversion into urea (Bélec et

al., 2004), and reduce the risk of phytotoxicity. Calcium cyanamide has been reported to inhibit

resting spore germination (Ludwig-Müller, 2016).

The effectiveness of a liming product can be dependent on the size of the liming particles.

Smaller particles can react faster in soil as they have a high surface area to volume ratio (Dobson

et al., 1983; Donald et al., 2004). For example, clubroot suppression was greater in powdery

forms of calcium carbonate and dolomite than in granular, fine or coarse forms of these limes

(Dobson et al., 1983; Murakami et al. 2002b). Similarly, a powder formulation of calcium

cyanamide was more effective at reducing clubbing in cabbage and broccoli in field trials than a

standard formulation which was composed of small and large particles, or a formulation that was

34

composed of larger particles (Donald et al., 2004). However, the reduction in clubroot severity in

Chinese cabbage was greater in granular calcium cyanamide than in powdery calcium cyanamide

in a greenhouse study. It was suggested that this finding may be the result of other factors or

modes of actions of cyanamide (Murakami et al., 2002b). Thorough mixing of lime products into

soil was associated with greater clubroot suppression as the lime was uniformly distributed

which prevents microsites with low pH levels (Dobson et al., 1983). Uniform incorporation of

particles in soil can improve calcium cation uptake in plants and was found to control clubroot

even when plants were sown one day after calcium carbonate was applied (Campbell et al.,

1985). Reducing spore levels in soil is also dependent on high concentrations of extractable

calcium cations (Campbell et al., 1985; Murakami et al., 2002b). For example, the pH of soils

with high buffering capacities may be unable to increase sufficiently to provide reduce clubroot

development, even at high rates of lime application (Welch et al., 1976).

Post-harvest application of calcitic lime in the year preceding cauliflower did not

effectively control clubroot (Tremblay et al., 2005). This low efficacy may be due to the large

particle size of the lime. Limestone with finer particles, which could be more uniformly

distributed in soil, suppressed clubroot more effectively than larger, coarser particles. Soil

properties, including texture and water content, that affect the homogenization of the limes in

soil can also influence the levels of control (Dobson et al., 1983). In addition, sufficient moisture

levels may be required to activate certain limes, such as calcium cyanamide (Bélec et al., 2004).

In many cases, more than one application of lime is required to suppress clubroot.

Similarly, a combination of two limes can be effective at managing clubroot, such as an

application of calcitic lime followed by an application of calcium cyanamide (Bélec et al., 2004).

35

While liming can reduce clubroot incidence and inoculum levels, other management

practices would likely also be needed if infestation levels are high and if environmental

conditions other than soil pH are optimal (Gossen et al., 2013).

1.6.7 Patch management

Distribution of clubroot in a field can be patchy (Wallenhammar et al., 2012). Clubroot

patches can occur at field entrances as resting spores can be spread in clumps of soil on farm

machinery and much of the soil will fall off as the equipment enters the field (Gossen et al.,

2018; Karling, 1942). Low spots in a field can also be conducive to clubroot development due to

poor drainage (Gossen et al., 2016; Wellman, 1930). In addition, selection for virulent

pathotypes initially present at low frequencies in the soil can occur in patches (Sedaghatkish et

al., 2019; Strelkov et al., 2018).

Planting grasses in a clubroot infested field as cover crops can be useful for patch

management of clubroot. The extensive root systems of grasses, such as ryegrasses, hold the soil

in place prevent the dissemination of resting spores in a field. Soil solarization can also be used

in highly clubroot-infested spots to reduce resting spore levels (Gossen et al., 2018; McDonald et

al. 2018b).

1.6.8 Fungicides

There are no fungicides currently registered to manage clubroot on canola in Canada.

Fungicides for clubroot management are registered in other countries, but they would not be

economical for Canadian canola production (Canola Council of Canada, 2020b). Hymexazol and

procymidone were found to reduce symptoms of clubroot but did not lead to increased yield. In

contrast, thiophanate-methyl improved yield but did not reduce clubroot development (Peng et

al., 2014b). Fluazinam is registered for clubroot on brassica vegetables but is not recommended.

36

Fluazinam has been reported to kill resting spores (Lahlali et al., 2011). Field trials in southern

Ontario found that fluazinam slightly reduced clubroot severity in susceptible cabbage at one of

three sites (Saude et al., 2012). Similarly, both fluazinam and cyazofamid suppressed clubroot

development on Shanghai pak choi under controlled conditions, but not under field conditions

(Adhikari, 2010). Banded soil incorporation was the most effective method of applying

fluazinam on broccoli and cauliflower (Donald et al., 2001). In contrast, application to plug

seedling trays followed by broadcast soil application with fluazinam reduced clubroot in Chinese

cabbage in heavily infested fields. This study also found that cyazofamid strongly inhibited

clubroot development. Cyazofamid inhibited resting spore germination by 80%, thus restricting

root hair infection and clubbing symptoms in Chinese cabbage. In fields with low clubroot

severity, plug seedling tray application of cyazofamid prior to transplanting is recommended

(Mitani et al., 2003). The fungicides Allegro and Ranman suppressed clubroot development in

Shanghai pak choi under controlled conditions but were not effective under field conditions

(Adhikari, 2010).

Commercial seed cleaning or fungicidal seed treatments also reduced the concentration of

seed-borne resting spores (Rennie et al., 2011). The fungicides azoxystrobin (trade name

Dynasty 100 FS), thiamethoxam + difenoconazole + metataxyl + fludioxonil (trade name Helix

Xtra), flusulfamide (trade name Nebijin 5SC), clothianidin + carbathiin + trifloxystrobin +

metataxyl (trade name Prosper FX) and carbathiin + thiram (Vitavax RS) reduced clubroot

infections on artificially infested canola seeds in greenhouse conditions. Dynasty 100 FS and

Nebijin 5SC were the most effective in reducing clubroot severity (Hwang et al., 2012b).

However, the dissemination of resting spores on seed poses a much lower risk than the transport

of spores on farm equipment as a greater quantity of resting spores can be carried in infested soil

37

on equipment (Rennie et al., 2011).

The fumigant Vapam (dithiocarbamate; sodium N-methyldithiocarbamate; metam sodium)

reduced root hair and cortical infection and severity of clubbing symptoms in canola (Ludwig-

Müller, 2016). Emergence, biomass, height and yield were higher in canola when Vapam was

applied to clubroot-infested fields (Hwang et al., 2014a). Vapam produces methyl

isothiocyanate, a volatile gas with fungicidal and nematicidal properties, when applied to soil

(Smelt and Leistra 1974). Rates of metam sodium over 75 kg a.i. ha-1 and rates of chloropicrin

over 124 kg ha-1 reduced severity of clubroot. In addition, soil solarization, where field plots

were covered with an impermeable plastic film also reduced clubroot severity (McDonald et al.,

2020b).

1.6.9 Biological control

Biological controls could represent an environmentally safer alternative to fumigants for

managing clubroot. The biofungicide Serenade (Bacillus subtilis) effectively suppressed clubroot

development (Lahlali et al., 2011). The lipopeptides in Serenade produced antibiotics, including

surfactins, iturins, and fengycins, in the rhizosphere that suppress infection by zoospores

(Kinsella et al., 2009; Lahlali et al., 2011; Ongena and Jacques, 2007). Bacillus subtilis also

formed a biofilm on root surfaces with the help of surfactin, and consumed exudates produced at

the root surface that might otherwise stimulate resting spore germination (Kinsella et al., 2009).

Serenade reduced resting spore viability by only 20%. Lipopeptides may also reduce competition

with other microbes, allowing B. subtilis to more effectively establish in the rhizosphere (Lahlali

et al., 2011). For instance, the antibiosis activities of iturins and fengycins suppressed other

microbes. Fengycins and surfactins also induced defense mechanisms in plants (Ongena and

Jacques, 2007). Bacillus subtilis alone suppressed clubroot less effectively than Serenade, which

38

may be due to secondary metabolites that contribute to B. subtilis colonization in the rhizosphere

(Lahlali et al., 2011). However, there were no reductions in clubroot severity in canola treated

with a B. subtilis seed dressing in a field trial (Peng et al., 2013).

Prestop (Clonostachys rosea) can also reduce clubroot infection (Gossen et al., 2016).

Clubroot incidence and severity on canola treated with Prestop was reduced by over 90%

(Lahlali and Peng, 2014b). As in the case of Serenade and B. subtilis, Prestop was more effective

at suppressing clubroot than C. rosea alone. Clonostachys rosea establishes an endophytic

relationship in roots and induces expression of defense genes in the host. In addition, C. rosea

produces antibiotics and lytic enzymes that suppress competing soil microbes, aid in the

establishment of C. rosea in the rhizosphere, and inhibit root hair and cortical infection.

However, as in the case of Serenade, Prestop was not effective in inhibiting resting spore

germination. Clonostachys rosea and B. subtilis may be activating phenylpropanoid, jasmonic

acid and ethylene pathways in host roots in induced systemic resistance responses against P.

brassicae (Lahlali and Peng, 2014). While Serenade was more effective at reducing clubroot on

sand, Prestop was more effective on mineral soil. This may be due to the lower competition with

other microbes for B. subtilis in sand (Gossen et al., 2016). The biofungicides, Mycostop

(Streptomyces griseoviridis) and Actinovate (Streptomyces lydicus), suppressed clubroot on

Shanghai pak choi under controlled conditions (Adhikari, 2010). Biofungicides have not yet,

however, been found to be effective in suppressing clubroot in field trials (Adhikari, 2010;

Gossen et al., 2016; Lahali et al., 2011). Biocontrols are expected to be most effective against

clubroot when disease pressure is low (Adhikari, 2010).

39

1.7 Techniques

1.7.1 Detecting clubroot in soil

To detect clubroot infection in plants or resting spores in soil, fields should be sampled in a

standardized pattern (Faggian and Strelkov, 2009). Many samples should be taken because P.

brassicae distribution can be patchy (Strelkov et al., 2007). Global positioning systems to

identify low spots in fields and entrances to fields where infections often start can be used to

reduce the number of samples taken (Faggian and Strelkov, 2009). Plasmodiophora brassicae

cannot be cultured as it is an obligate parasite (Karling, 1942), so bioassays are often used for

diagnosis. Susceptible plants can be infected with clubroot and clubroot severity can be visually

assessed 5–6 weeks after inoculation (Colhoun, 1957; Toxopeus and Janssen, 1975).

Techniques for more rapid diagnosis of P. brassicae have been developed. Polymerase

chain reaction assays can be used for routine detection of P. brassicae DNA in plant and soil

samples (Cao et al., 2007). Antibody, fatty acid analysis and serology-based tests can also be

used detect and quantify P. brassicae (Faggian and Strelkov, 2009; Hwang et al., 2012c). Highly

specific monoclonal antibodies have been developed for P. brassicae diagnostic tests (Faggian

and Strelkov, 2009). In addition, UV- and G- excitation can detect P. brassicae nuclei under a

fluorescent microscope. Nuclei identification can allow resting spores to be differentiated from

germinated resting spores (Niwa et al., 2008). This method, though effective, requires training in

microscopy and is not ideal for routine P. brassicae diagnosis (Faggian and Strelkov, 2009).

1.7.2 Assessing infection in plants

Clubroot can be visually identified in early stages of infection by assessing root hairs

microscopically (Donald and Porter, 2004). Root hairs in the top 2–3 cm of the tap root below

the hypocotyl should be evaluated as this region has the highest level of infection (Naiki et al.,

40

1978). Plasmodia in root hairs of seedlings can be identified starting at 2 days post-inoculation.

Staining roots with aniline-blue solution can allow plasmodia and zoosporangia structures to be

more easily identified (Sharma et al., 2011b). The percent of root hairs infection can be a strong

indication of the development and severity of clubroot on a plant (Gossen et al., 2013).

A rating system can be used to assess clubroot severity (Crête et al., 1963). Symptoms of

clubroot are routinely assessed on roots using a 0–3 scale. Each root is assigned to a class, where

class 0 = no clubs, 1 = small clubs on less than 1/3 of roots, class 2 = small or intermediate sized

clubs on 1/3 to 2/3 of roots, and class 3 = intermediate sized or large clubs on over 2/3 of roots.

A disease severity index calculates a number between 0 and 100 with the following formula

(Crête et al., 1963):

DSI = Σ[(class no. )(no. plants in each class)]

(total no. plants per sample)(no. classes − 1)× 100

1.7.3 Quantifying resting spore concentrations

Resting spore concentrations can be quantified using a quantitative polymerase chain

reaction (qPCR). However, qPCR quantifies both viable and nonviable resting spores. Spores

can be treated with the chemical, propidium monoazide (PMA) so that only viable spores are

amplified (Al-Daoud et al., 2017b). Propidium monoazide penetrates the cell membrane of

nonviable cells and photoactivation causes it to bind to DNA. Therefore, the DNA of nonviable

cells is not amplified during qPCR (Nocker et al., 2006).

Stains that can differentiate viable from nonviable resting spores when the spores are

viewed with a microscope have also been studied. Evaluation of the Evans blue stain indicated

that this stain did not effectively differentiate mature resting spores from immature resting spores

(Al-Daoud et al., 2017b). However, a subsequent study showed that a longer staining time was

41

required to accurately differentiate viable from nonviable spores (Harding et al., 2019). The

cytoplasm of nonviable cells can take up the stain, resulting in a dark blue colour when assessed

with bright field microscopy. The Evans blue method did not differ from the PMA qPCR method

when the viability of resting spores was assessed in response to 70°C and 90°C heat treatments.

However, the two methods were statistically different in response to the 80°C heat treatment as

the Evans blue stain was found to have a greater accuracy than PMA qPCR (Harding et al.,

2019).

1.8 Research objectives

Clubroot resistance in commercial brassica cultivars is based on major resistance genes

and is pathotype-specific. However, the specific pathotypes against which a cultivar is resistant

are not provided by seed companies. Testing is needed to assess the clubroot reaction of canola

and brassica vegetable cultivars grown in Ontario to pathotypes 2 and 6 of P. brassicae to

provide this information to growers.

Crop rotation is also an important clubroot management method to reduce resting spore

levels in soil. Some crops that are commonly grown in rotation with canola may be more

effective than others at reducing resting spores. For instance, the roots of some crops can

stimulate the germination of resting spores, and the zoospores quickly die if there are no root

hairs that can be infected. Another possibility is that root hairs will be infected, and secondary

zoospores released, but these will not be able to infect the root cortex of the non-host crop. In

either situation, the number of viable resting spores remaining in the soil will be reduced.

Assessing crops commonly grown in rotation with brassica crops in Canada for the ability to

reduce resting spores will provide important information for clubroot management.

Crop rotation and liming to increase calcium content and soil pH are effective for

42

clubroot management but their combined effect on resting spore levels in soil has not been

studied. Certain field crops commonly grown in rotation with canola may induce resting spore

germination, while application of lime can inhibit resting spore germination. The effects of these

two management practices may not be additive due to these different modes of action.

Combining these two strategies may be antagonistic. Studies of the interaction between planting

a field crop and liming soil would provide useful recommendations for growers.

The objectives of the research were:

1. To evaluate the resistance of canola and brassica vegetable (cabbage, cauliflower,

broccoli, napa cabbage and rutabaga) cultivars commonly grown in Ontario to P.

brassicae pathotypes 2 and 6

2. To evaluate rotation and cover crops (spring wheat, barley, soybean, field pea and

perennial ryegrass) to identify those that most effectively reduce resting spores in soil

3. Evaluate the combined effects of planting a cereal crop and liming with calcium

hydroxide on resting spore levels in soil

The following hypotheses were tested:

1. Certain clubroot resistant canola and brassica vegetable cultivars are not resistant to both

P. brassicae pathotypes 2 and 6 as resistance is usually pathotype-specific

2. Growing spring wheat, barley and perennial ryegrass can reduce P. brassicae inoculum

more than legumes (soybeans and field peas) because of their more extensive root

systems

3. Growing a cereal crop in soil treated with lime does not reduce resting spore levels more

than either method alone, due to their different modes of actions

43

CHAPTER TWO

2 Clubroot resistance in canola and brassica vegetable cultivars

Published in a modified format: Drury, S. C., Gossen, B. D., and McDonald, M. R. 2021.

Clubroot resistance in canola and brassica vegetable cultivars in Ontario, Canada. Canadian

Journal of Plant Science doi: 10.1139/CJPS-2020-0273

2.1 Introduction

Cultivars of canola (Brassica napus L.) resistant to clubroot are a cost-effective and

environmentally friendly strategy for clubroot management (Cao et al., 2009; Strelkov et al.,

2011), so genetic resistance is the main strategy for managing clubroot on the Canadian Prairies

(Canola Council of Canada, 2020b). Seedling emergence, above-ground biomass and yield are

greater in resistant cultivars of canola and brassica vegetables compared to susceptible cultivars

when grown in clubroot-infested soil, particularly when disease pressure is high (Hwang et al.,

2011b; Sharma et al., 2013b). Resistant canola and cabbage cultivars suppress or eliminate

cortical infection to prevent symptom development (Deora et al., 2013; Peng et al., 2019). They

can also be effective in slowing the build-up of resting spores of P. brassicae in fields (Hwang et

al., 2019).

Genetic resistance to clubroot is available in all of the major brassica crops, except

B. juncea and B. carinata (Diederichsen et al., 2009; Piao et al., 2009). Both qualitative

resistance, which is pathotype-specific and is often controlled by a single gene, and quantitative

resistance, which is not pathotype-specific and is generally polygenic (Van der Plank, 1969),

have been reported in Brassica species (Crute et al., 1980; Piao et al., 2009). The first clubroot-

resistant (CR) canola cultivar in Canada was released in 2009. More than 20 CR canola cultivars

44

had been registered by 2018, and that number continues to increase (Strelkov et al., 2018).

Single dominant, pathotype-specific resistance genes have generally been used to develop CR

cultivars of canola (Diederichsen et al., 2009). Gene pyramiding, where two or more CR genes

are added to cultivars, is being assessed to determine if this approach might provide a broader

spectrum of clubroot resistance. Pyramided CR genes can have interactive effects, which might

result in higher levels of resistance than using individual CR genes (Matsumoto et al., 2012). For

example, pyramids of CR genes have been developed for B. napus (Shah et al., 2019).

Resistance based on single dominant genes has not provided durable clubroot resistance

(Diederichsen et al., 2009; Piao et al., 2009). Only four years after the first CR canola cultivars

were released in Canada, virulent populations of P. brassicae that could overcome the resistance

in these cultivars were identified, and these virulent populations have increased rapidly (Strelkov

et al., 2018). A recent study of whole-genome sequences of P. brassicae indicated that these

virulent pathotypes were likely present at low frequencies in the initial population in fields and

have became dominant as a result of selection pressure (Sedaghatkish et al., 2019).

Several systems have been developed to characterize the pathotypes of P. brassicae. The

differential set developed by Williams (1966) has been widely adopted in Canada. However, the

emergence of new pathotypes in Canada that could not be identified on Williams’ system led to

the development of a new system, the Canadian Clubroot Differential (CCD) set (Strelkov et al.,

2018). Similarly, differential systems could not accurately describe lines of B. oleracea with

novel sources of resistance, so a differential set was developed to characterize the pathotypes on

B. oleracea (Smilde et al., 2012). This system uses red cabbage (B. oleracea var. capitata) cv.

Lodero, white cabbage cvs. Bejo 51632, and Kilaton, broccoli (B. oleracea var. italica) cv.

Monclano, and cauliflower (B. oleracea var. botrytis) cv. Clapton or Brussels sprouts (B.

45

oleracea var. gemmifera) cv. Crispus (International Seed Federation, 2016). Four pathotypes,

designated Pb:0, Pb:1, Pb:2 and Pb:3, can be identified using this system (Smilde et al., 2012).

The system has not been applied to the brassica vegetables grown in Ontario, and it is not known

which pathotype, based on this newer system, is present in fields in Ontario.

Many brassica vegetables are susceptible to pathotype 6 from Williams’ system (Al-Daoud

et al., 2018), but most canola cultivars are resistant (Deora et al., 2013). Most brassica

vegetables and many canola cultivars are susceptible to pathotype 2 (Al-Daoud et al., 2018).

Pathotype 6 has been predominant on vegetables in Ontario for many years (Al-Daoud et al.,

2017a), but pathotype 2 was recently identified on canola in Ontario (Al-Daoud et al., 2018).

Pathotypes 2 and 6 are currently the predominant pathotypes in Ontario (McDonald et al.,

2020a). Studies on the reaction of canola and brassica vegetable cultivars to pathotypes 2 and 6

have been limited as these pathotypes are not widespread in the Canadian Prairies (Strelkov et

al., 2018) where most of the canola in Canada is grown.

The green cabbage cvs. Kilaherb, Kilaton, Kilaxy and Tekila, and napa cabbage (B. rapa

L. ssp. pekinensis) cvs. Bilko, Yuki, Deneko, Emiko and China Gold are resistant to pathotype 6

(Saude et al., 2012; Sharma et al., 2013b). Some cultivars have resistance to multiple pathotypes.

For instance, cabbage cvs. Kilaherb and Tekila were resistant to pathotypes 2, 3, 5, 6 and 8,

which at the time were the only pathotypes prevalent in Canada (Peng et al., 2014a). In addition,

bok choy cv. Bejo 2834 and napa cabbage cv. Bilko were resistant to pathotypes 2, 3, 4 and 6.

Other cultivars had a differential reaction to the pathotypes. For example, Brussels sprouts cv.

Crispus was resistant to pathotypes 2 and 6 but susceptible to pathotypes 3 and 5 (Sharma et al.,

2013b). Rutabaga (B. napus var. napobrassica Mil.) cv. Laurentian, which is widely grown in

Ontario, is one of the differentials in Williams’ system. It is susceptible to pathotypes 1, 2, 3 and

46

4 and resistant to pathotypes 5 and 6 (Williams, 1966).

Screening germplasm for resistance to specific pathotypes is important for developing

resistant cultivars (Hasan et al., 2012), but information about the source of resistance in

individual cultivars is often not in the public domain (Strelkov et al., 2018).

The objective of this study was to evaluate selected canola and brassica vegetable cultivars

commonly grown in Ontario for resistance to pathotypes 2 and 6, which are the predominant

pathotypes of P. brassicae in the region. The results will help growers to select canola and

brassica vegetable cultivars that are resistant to clubroot for use in fields where clubroot occurs.

2.2 Materials and methods

2.2.1 Field site

Field trials were conducted at the Muck Crops Research Station of the University of

Guelph, Holland Marsh, Ontario in 2018 and 2019 on a muck soil (hemic histosol, pH ≈ 6.5,

organic matter ≈ 66%). Each study was arranged in a randomized complete block design with six

replicates. Each plot consisted of one (canola) or two (vegetables) 5-m-long rows with 40 cm

spacing between rows.

The site has been naturally infested with P. brassicae since 1954 (Anonymous, 1956).

The predominant pathotype at this site was pathotype 6 (Williams’ system) for many years but

has recently shifted to pathotype 2 (Al-Daoud et al., 2017a). The population of clubroot resting

spores in the field plots was 1–6 × 107 spores g-1 of soil in 2019, based on standard qPCR

analyses.

2.2.2 Field trials – canola

InVigor hybrid CR canola cvs. L255PC, L241C and L135C were assessed. Each of the

cultivars is marketed as being resistant to the predominant pathotypes in Canada, and each

47

appears to carry the same source of first-generation CR resistance (Deora et al., 2012; 2013)

(Table 2.1). In addition, the study assessed two InVigor cultivars that are not marketed as

carrying clubroot resistance (InVigor L252 and L233P), together with a number of control

cultivars: the moderately susceptible canola cv. InVigor 5030 (Deora et al., 2012) and two

universally susceptible lines, canola breeding line ACS N39 (Agriculture and Agri-Food Canada,

Saskatoon, SK) and Shanghai pak choi (B. rapa var. chinensis) cv. Mei Qing Choi (Stokes Seeds

Ltd., St. Catharines, ON) (Sharma et al., 2013a). InVigor L234PC was added to the trial in 2019.

This cultivar, released in 2019, was marketed as carrying more than one gene for resistance to

clubroot. Canola cv. 45H29 (Pioneer Hi-Bred, ON, Canada) was also added in 2019; it is

resistant to the original pathotypes 2, 3, 5, 6 and 8 in Canada, but its resistance has been

overcome by several of the new pathotypes that have recently been identified in the region

(Strelkov et al., 2018). This cultivar was added to determine if the pathotype at the site was

virulent on the first generation of CR canola cultivars.

The trials were seeded on 14 June, 2018 and 12 June, 2019 at 50 seeds m-1 of row with an

Earthway Precision Garden Seeder model 1002-105. The InVigor cultivars were sprayed with an

herbicide and all of the plots were also hand weeded. Clubroot symptom severity was assessed

on 50 plants per plot at 6 weeks after seeding on 25 July in 2018 and 2019. Each plant was rated

on a 0–3 scale (Crête et al., 1963), where 0 = no clubs, 1 = small clubs on less than 1/3 of roots,

2 = small or intermediate clubs on 1/3 to 2/3 of roots, and 3 = intermediate or large clubs on over

2/3 of roots (Figure 2.1). At harvest, shoot fresh weight was assessed on 10 plants per plot and

dry weight was determined after 48 hr of oven drying to a constant weight at 60ºC.

Clubroot incidence (CI) was determined as the percentage of plants with clubroot

48

symptoms. A disease severity index (DSI) was calculated using the following formula (Crête et

al., 1963):

DSI = Σ[(class no. )(no. plants in each class)]

(total no. plants per sample)(no. classes − 1)× 100

Table 2.1 Expected reaction to pathotypes 2 and 6 (based on seed label), year evaluated in a field

trial, and type of trial used for evaluation (field trial or growth room study) of the canola

cultivars that were screened for resistance.

Cultivars Seed source Expected

reaction1

Year in field

trial

Type of study

InVigor L255PC BASF Resistant 2018, 2019 Field, growth room

InVigor L135C BASF Resistant 2018, 2019 Field, growth room

InVigor L241C BASF Resistant 2018, 2019 Field, growth room

InVigor L234PC BASF Resistant 2019 Field

45H29 Pioneer Resistant 2019 Field

InVigor 5030 BASF Moderately

susceptible

2018, 2019 Field, growth room

InVigor L252 BASF Susceptible 2018, 2019 Field, growth room

InVigor L233P BASF Susceptible 2018, 2019 Field, growth room

ACS N39 AAFC, SK Susceptible 2018, 2019 Field, growth room

Mei Qing Choi Stokes Seeds Susceptible 2018, 2019 Field, growth room 1The expected clubroot reaction of cultivars was based on breeder descriptions: DSI <30%

compared to a check is resistant, 30–50% is moderately susceptible and >50% is susceptible.

49

Figure 2.1 Clubroot disease severity rating scale. (a) 0 = no clubbing on root, (b) 1 = small clubs

on <1/3 of roots, (c) 2 = small to medium clubs on 1/3–2/3 of roots, and (d) 3 = large clubs on

>2/3 of roots.

2.2.3 Field trials - vegetables

Cabbage, broccoli, cauliflower, napa cabbage and rutabaga cultivars marketed as clubroot

resistant or tolerant were evaluated (Table 2.2). The susceptible control treatments were white

cabbage cv. Bronco (Bejo Seeds Inc., Geneva NY), broccoli cv. Asteroid, cauliflower cv.

Fremont, napa cabbage cv. Blue (Stokes Seeds Ltd., ON), rutabaga cv. Laurentian (sourced from

two suppliers, Stokes Seeds Ltd. and the University of Wisconsin-Madison) and Shanghai pak

choi cv. Mei Qing Choi. The clubroot reactions of the two sources of Laurentian rutabaga, a host

in Williams’ differential set and the CCD Set, were compared to determine if less expensive seed

from Stokes Seeds was equivalent to the University of Wisconsin seed.

Cabbage, cauliflower and broccoli were grown from transplants. These crops were seeded

in Original Grower Potting Soil Mix (ASB Greenworld) in 128-cell plug trays on 08 June, 2018

and 07 June, 2019. They were grown in a greenhouse at the Muck Crops Research Station, where

50

day length was not modified. The crops were transplanted by hand in the field on 11 July in 2018

and 2019. Rutabaga was grown from transplants in 2019 because emergence and growth were

poor when direct seeded in 2018. In 2019, rutabaga was seeded in 288-cell plug trays on 27 June

and transplanted on 18 July. There were 30 cm between each transplant and a mean of 16 plants

per row. Napa cabbage and Shanghai pak choi were direct seeded on 11 July in 2018 and 2019 at

50 seeds m-1. Rutabaga was direct seeded on 11 July, 2018.

Clubroot was assessed on the 0–3 scale as described previously on 30 plants per plot at 6

weeks after seeding/transplanting on 23 August, 2018, and on 22 and 23 August, 2019. Rutabaga

was assessed on 29 August in 2018 and 2019. As with canola, the shoot fresh weight of 10 plants

per plot was assessed at harvest and the shoot dry weight of five plants per plot was determined

after oven drying to constant moisture at 60ºC. Clubroot incidence and DSI were calculated as

described previously.

51

Table 2.2 Expected reaction to clubroot pathotypes 2 and 6 (based on seed label) of the brassica

vegetable cultivars that were screened for resistance in 2018 and 2019 field trials and in growth

room studies.

Cultivars Crop Seed source Expected reaction

Bejo 2962 White cabbage Bejo Seeds Susceptible

Tekila White cabbage Stokes Seeds Tolerant1

Lodero Red cabbage Bejo Seeds Resistant

Bejo 2962 White cabbage Bejo Seeds Resistant to most

clubroot pathotypes

Emerald Jewel Broccoli Stokes Seeds Intermediate tolerance to

some clubroot pathotypes

Asteroid Broccoli Stokes Seeds Susceptible

Clarify Cauliflower Stokes Seeds Resistant

Fremont Cauliflower Stokes Seeds Susceptible

Laurentian Rutabaga Stokes Seeds Resistant to some

pathotypes

Laurentian Rutabaga U. of Wisc. Resistant to some

pathotypes

Yuki Napa cabbage Stokes Seeds Tolerant

Blue Napa cabbage Stokes Seeds Susceptible

Mei Qing Choi Shanghai pak choi Stokes Seeds Susceptible

1Tolerant indicates that clubs can develop on roots but there is no yield reduction.

2.2.4 Clubroot inoculum for growth room studies

Inoculum of pathotype 2 was collected as clubbed canola roots from a commercial field in

Bruce County, ON (mineral soil) in 2017 and from line ACS N39 grown at the Muck Crops

Research Station (muck soil) in 2017. Inoculum of pathotype 6 was collected from an infested

commercial broccoli field near Ottawa, ON (mineral soil) in 2017. The dominant pathotypes in

each of these collections were characterized using Williams’ system (McDonald et al., 2020a).

Pathotype 2 from Bruce County and pathotype 6 populations were increased on Shanghai

52

pak choi cv. Mei Qing Choi grown under controlled conditions in tall narrow 164 mL plastic

pots (conetainers, Steuwe and Sons Inc. Corvallis, OR) filled with L4A Sunshine Mix (Sun Gro

Horticulture, MA) plus a fertilizer solution consisting of a 0.1% solution of nitrogen, phosphate,

potassium (20-20-20, Plant Products Classic, Brampton, ON), and magnesium sulfate. The clubs

were frozen after collection at -20ºC until use.

The inoculum was prepared following the methods of Sharma et al. (2011a). Frozen clubs

were thawed, ground in water with a mortar and pestle, then homogenized for 2 min with water

in a commercial blender on high speed. The resulting spore suspension was passed through eight

layers of cheesecloth and the spore concentration was estimated using a haemocytometer under a

compound microscope.

The growth room was set to 24/19°C day/night with a 17-hr photoperiod. Two seeds were

planted in each pot and thinned to one plant per pot prior to inoculation. At 6 days after seeding,

5 mL of 2 × 107 resting spores mL-1 of P. brassicae was applied to the stem base of each

seedling. The plants were watered with tap water adjusted to pH 6.0 with 5% acetic acid

(commercial white vinegar) to maintain the slightly acidic conditions conducive for infection

(Gossen et al., 2013). The plants were fertilized weekly with a 0.1% solution of nitrogen,

phosphate, potassium (20-20-20), and magnesium sulfate. Clubs were harvested 6.5 weeks after

inoculation and stored at -20ºC.

2.2.5 Growth room - canola

The canola cultivars evaluated in the field trial, plus a non-inoculated susceptible control,

ACS N39 or Mei Qing Choi, were tested for clubroot reaction under controlled conditions. Each

study was laid out in a randomized compete block design with four replicates and 12 plants per

experimental unit. The growth room conditions and inoculation methods were as described

53

previously. Pathotypes 2 and 6 were assessed in separate studies, and both studies were repeated.

The collection of pathotype 2 from the Muck Crops Research Station was used as the inoculum

source in the initial run and the collection from Bruce County was used in the repetition. The

inoculum concentration used was 5 mL of 1 × 107 resting spores mL-1. Clubroot symptoms were

assessed on all plants at 6 weeks after inoculation on the 0–3 scale, and clubroot incidence and

DSI were determined as described previously.

2.2.6 Growth room - vegetable cultivars

The clubroot reaction of the vegetable cultivars assessed in the field trials, plus a

susceptible control (Shanghai pak choi, inoculated and non-inoculated), to pathotypes 2 and 6

was assessed in separate growth room studies. The same sources of inoculum and methods were

used as in the canola growth room studies described above. The study was conducted once with

pathotype 2 (inoculum from Bruce County) and twice with pathotype 6.

2.2.7 Pathotyping P. brassicae from the field

The pathotype of clubs from the 2019 field trials was determined based on Williams’

system (1966) in a growth room trial. The cabbage cvs., Jersey Queen and Badger Shipper, and

the rutabaga cvs., Laurentian and Wilhelmsburger (source: S.E. Strelkov, University of Alberta)

from Williams’ differential set were evaluated. The CR canola cv. 45H29 was also included to

determine if a virulent pathotype had emerged that could not be identified with Williams’

system. The same experimental design and methods as the canola growth room cultivar

screening studies were used.

2.2.8 Statistical analysis

All statistical analyses were conducted in SAS 9.4 (SAS Institute, Cary, IN). Clubroot

incidence, DSI, shoot fresh weight and shoot dry weight were analyzed in PROC GLIMMIX

54

using Tukey’s test for means separation. A Type 1 error of P = 0.05 was set for all statistical

tests. The Shapiro-Wilk test and scatter plots of the residuals were used to assess the normality of

the data. The clubroot incidence and severity (DSI) data were analyzed based on a binomial

distribution, and shoot fresh and dry weight were analyzed based on a normal distribution.

In the field trials in 2019, canola cv. 45H29 was stunted by herbicide drift, so its shoot

weight was excluded from the analyses. Analyses of fresh and dry shoot weight were conducted

separately for each crop variety or subspecies in the brassica vegetable field trials. Mei Qing

Choi was not included in the shoot analyses of any field trial as there was no resistant cultivar for

comparison.

The data from the two years of fields trials could not be pooled because of significant

treatment × year interactions. There were no interactions among repetitions of growth room

studies of canola cultivars for resistance to pathotype 2 from MCRS and Bruce County, or

among repetitions of the growth room studies of canola or brassica vegetables inoculated with

pathotype 6, so those data were pooled for analysis and presentation.

2.3 Results

2.3.1 Canola

Clubroot severity in the field trials was slightly lower in 2019 than in 2018 (Table 2.3). In

the susceptible cultivars used as controls (including InVigor 5030), clubroot incidence and severity

was high in 2018 (CI = 92–100%, DSI = 83–99) and moderate in 2019 (CI = 67–99%, DSI = 49–

86). The resistant cultivars had low incidence and severity in both 2018 (CI = 2–5%, DSI = 1–2)

and 2019 (CI = 0–21%, DSI = 0–7).

Severe clubroot symptoms in susceptible canola cultivars were consistently associated with

reduced shoot weight (Table 2.3). The mean fresh shoot weight of susceptible canola cultivars

55

was 57% lower compared to the resistant cultivars in 2018. Dry shoot weight showed a similar

trend, but the differences were not always significant. In 2019, fresh and dry shoot weights were

higher in the CR cvs. L234PC and L255PC than the susceptible canola controls, but cvs. L241C

and L135C did not differ from the canola controls.

The clubroot reactions of canola cultivars in the growth room studies inoculated with

pathotype 2 were similar to their reactions in the field trials (Table 2.4). Both incidence and

severity were very low (CI and DSI = 0) in the resistant cultivars, but high in the other canola

cultivars and Mei Qing Choi (CI = 98–100%, DSI = 90–96). Clubroot incidence and severity in

the CR cvs. L255PC, L135C and L241C was very low, which confirmed that they were resistant

to pathotype 2, while cvs. L252, L233P, ACS N39, 5030 and the Shanghai pak choi cv. Mei

Qing Choi were susceptible to pathotype 2.

In the growth room studies, all of the InVigor cultivars and 45H29 were resistant to

pathotype 6 (CI = 0–8%, DSI = 0–4). Even the highly susceptible line ACS N39 had a relatively

low severity (DSI = 29), but Mei Qing Choi was highly susceptible (DSI = 100).

56

Table 2.3 Clubroot incidence (CI, %), disease severity index (DSI), and fresh weight and dry weight of clubroot susceptible and

resistant canola cultivars grown at the Muck Crops Research Station, ON, in 2018 and 2019.

Cultivar1

2018 2019

CI

(%)

DSI

(0–100 )

Fresh wt.

(g plant-1)

Dry wt.

(g plant-1)

CI

(%)

DSI

(0–100)

Fresh wt.

(g plant-1)

Dry wt.

(g plant-1)

Resistant

InVigor L234PC - - - - 0f 0e 109a 12.1a

InVigor L255PC 2c2 1d 130a 8.9a 21e 7d 123a 11.7a

InVigor L135C 2c 1d 108a 7.5abc 1f 0e 96ab 9.2ab

InVigor L241C 5c 2d 109a 8.3ab 1f 0e 83abc 7.7abc

45H29 - - - - 2ef 2de nd3 nd

Mod. susceptible

InVigor 5030 99a 95b 45b 4.8c 79bc 66b 42c 4.2c

Susceptible

Mei Qing Choi 92b 83c 254 1.2 67d 49c 504 1.5

InVigor L252 100a 99a 60b 5.8abc 71cd 66b 59bc 6.4bc

ACS N39 100a 98a 49b 5.6abc 81b 68b 46c 5.5bc

InVigor L233P 100a 98a 47b 5.2bc 99a 86a 52bc 6.0bc

1The expected clubroot reaction of cultivars was based on breeder descriptions: DSI <30% compared to a check is resistant, 30–50% is

moderately susceptible and >50% is susceptible. 2Means followed by the same letter in a column do not differ based on Tukey’s test at P = 0.05. 345H29 was stunted by herbicide, so the shoot weight could not be included. 4Mei Qing Choi was not included in the statistical analysis in both years because there was no resistant cultivar for comparison.

57

Table 2.4 Clubroot incidence (CI, %) and disease severity index (DSI) of canola cultivars

inoculated with pathotypes 2 and 6 of Plasmodiophora brassicae in a growth room study (n = 8).

Cultivar1 Pathotype 2 Pathotype 6

CI (%) DSI (0–100) CI (%) DSI (0–100)

Resistant

InVigor L255PC 0b2 0b 0b 0c

InVigor L135C 0b 0b 0b 0c

InVigor L241C 0b 0b 0b 0c

InVigor L234PC - - 0b 0c

45H29 - - 6b 4c

Mod. susceptible

InVigor 5030 100a 93a 6b 3c

Susceptible

InVigor L252 98a 90a 4b 1c

InVigor L233P 98a 94a 8b 2c

ACS N39 98a 90a 97a 29b

Mei Qing Choi 100a 96a 100a 100a

1The expected clubroot reaction of cultivars was based on breeder descriptions: DSI <30%

compared to a check is resistant, 30–50% is moderately susceptible and >50% is susceptible. 2Means followed by the same letter in a column do not differ based on Tukey’s test at P = 0.05.

2.3.2 Brassica vegetables

As in the canola field trials, overall clubroot incidence and severity in the brassica

vegetable field trials were lower in 2019 compared to 2018. In the 2018 trial, incidence and

severity were low (CI = 0–2%, DSI = 0–1) in cvs. Bejo 2962 (cabbage), Tekila (cabbage),

Clarify (cauliflower), and Yuki (napa cabbage), and high (CI = 94–100%, DSI = 87–100) in

most of the cultivars that were expected to be susceptible, including the susceptible check Mei

Qing Choi (Table 2.5). However, there were two cultivars that did not respond as expected:

cabbage cv. Lodero and broccoli cv. Emerald Jewel. Lodero was marketed as clubroot resistant

58

but developed severe symptoms (CI = 94%, DSI = 87), similar to the susceptible cabbage cv.

Bronco. Similarly, Emerald Jewel was marketed as clubroot resistant but developed severe

symptoms (CI = 97%, DSI = 87), similar to the susceptible broccoli cv. Asteroid. Clubroot

symptoms in rutabaga cv. Laurentian from both Stokes Seeds Ltd. and the University of

Wisconsin were intermediate, but considered susceptible because DSI was over 50% (CI = 64–

70%, DSI = 53–64). Severe clubroot symptoms were associated with reduced fresh shoot weight

(42–65%) in susceptible cultivars relative to resistant cultivars. Dry shoot weight showed a

similar trend, but was lower in broccoli cv. Asteroid than in Emerald Jewel. Also, dry shoot

weight did not differ between napa cabbage cvs. Yuki and Blue.

In 2019, incidence and severity were again low (CI = 0–21%, DSI = 0–9) in all of the

cultivars that were marketed as resistant. The susceptible cultivars had a range of reactions (CI =

12–77%, DSI = 3–55). Incidence and severity on the susceptible check Mei Qing Choi was also

quite low in 2019. Incidence and severity were lower in the cultivars marketed as resistant

compared to the susceptible cultivars. In contrast to 2018, incidence in cabbage cv. Lodero was

lower (CI = 12%) than in Bronco (48%). Clubroot severity in Lodero (DSI = 5) was midway

between the resistant cabbage cultivars (DSI = 0) and Bronco (DSI = 27). Incidence and severity

in broccoli cv. Emerald Jewel were also lower (CI = 21, DSI = 9) than in Asteroid (48%, 31).

Fresh and dry shoot weights were higher in the resistant cabbage cv. Bejo 2962 compared

to Bronco, but fresh and dry shoot weights of the other resistant cultivars were not greater than

the susceptible cultivars of the same crop.

In the growth room studies, the cultivars that were resistant when inoculated with

pathotype 2 were the same cultivars that were resistant in the 2018 field trial (Table 2.5 and

Table 2.6). Incidence and severity were low (CI = 0–4%, DSI = 0–4) in most of the resistant

59

cultivars and high (CI = 100%, DSI = 99–100) in the susceptible cultivars, including Mei Qing

Choi. Cabbage cv. Lodero and broccoli cv. Emerald Jewel were susceptible to pathotype 2,

which was consistent with the 2018 field trial.

There were more differences among the vegetable cultivars in the growth room study

inoculated with pathotype 6. Incidence and severity were low (CI = 0–7%, DSI = 0–5) in all of

the cultivars that were marketed as resistant (Table 2.6). Cabbage cv. Lodero, broccoli cv.

Emerald Jewel and rutabaga cv. Laurentian also had very low clubroot incidence and severity,

but the control cv. Mei Qing Choi was susceptible to both pathotypes.

60

Table 2.5 Clubroot incidence (CI, %), disease severity index (DSI), and fresh and dry weight of clubroot susceptible (S) and resistant (R)

brassica vegetable cultivars at the Muck Crops Research Station, ON in 2018 and 2019.

Crop & Cultivar Expected

(S/R)1

2018 2019

CI

(%)

DSI

(0–100)

Fresh wt.

(g plant-1)

Dry wt.

(g plant-1)

CI

(%)

DSI

(0–100)

Fresh wt.

(g plant-1)

Dry wt.

(g plant-1)

Cabbage

Bejo 2962 R 0d2 0d 875a3 61a 0d 0d 1064a 41a

Tekila R 0d. 0d 626ab 44ab 0d 0d 642b 28b

Lodero R 94a. 87b 271bc 21c 12c 5c 517b 23b

Bronco S 100a. 100a 252c 25bc 48b 27b 703b 27b

Broccoli

Emerald Jewel R 97a. 87b 346ns 33A 21c 9c 654ns 29ns

Asteroid S 100a. 100a 301 15B 48b 31b 656 28

Cauliflower

Clarify R 1d. 1d 479y 54y 1d 1d 707y 32ns

Fremont S 99a. 98a 174z 25z 45b 23b 549z 28

Rutabaga

Laurentian from

Stokes Seed

S 64b. 53c 36ns 4ns 38c 3c 336ns 18ns

Laurentian from

U. of Wisc.

S 70b. 64c 39 5 12c 4c 386 16

Napa cabbage

Yuki R 2c. 1d 302a 15a 0d 0d 198b 5b

Blue S 99a. 99a 173b 12a 77a 55a 484a 13a

Shanghai pak choi

Mei Qing Choi S 94a. 92b 140 6 15c 11c 101 2 1The expected clubroot reaction of cultivars was based on company descriptions. 2Means followed by the same letter in a column do not differ based on Tukey’s test at P = 0.05. 3Statistical analysis for fresh and dry weights was conducted separately by crop. Different case letters and/or letters pairings are used for the

different crops.

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Table 2.6 Clubroot incidence (CI, %) and severity (disease severity index, DSI) of clubroot

susceptible (S) and resistant (R) brassica vegetables inoculated with pathotypes 2 (n = 4) and 6 (n

= 8) of Plasmodiophora brassicae in a growth room study.

Crop & Cultivar Expected

(S/R)1

Pathotype 2 Pathotype 62

CI (%) DSI

(0–100)

CI

(%)

DSI

(0–100)

Cabbage

Bejo 2962 R 0b3 0b 0b 0b

Tekila R 0b 0b 0b 0b

Lodero R 100a 99a 7b 2b

Bronco S 100a 100a 99a 98a

Broccoli

Emerald Jewel R 100a 100a 2b 1b

Asteroid S 100a 100a 100a 100a

Cauliflower

Clarify R 0b 0b 0b 0b

Fremont S 100a 100a 100a 100a

Rutabaga

Laurentian from

Stokes Seed

S 100a 100a 0b 0b

Laurentian from

U. of Wisc.

S 100a 100a 7b 7b

Napa cabbage

Yuki R 4b 4b 5b 5b

Blue S 100a 100a 100a 100a

Shanghai pak choi

Mei Qing Choi S 100a 100a 98a 96a

1The expected clubroot reaction of cultivars was based on company descriptions. 2The data from two repetitions of the experiment with pathotype 6 were pooled for analysis. 3Means followed by the same letter in a column do not differ based on Tukey’s test at P = 0.05.

2.3.3 The pathotype of a field collection

The pathotype of a field collection from the field trials in 2019 at the Muck Crops

Research Station was confirmed to be pathotype 2 based on the disease reaction of the

differential lines of the Williams’ system (1996) (Table 2.7). The canola cv. 45H29 was resistant,

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indicating that the pathotype was not a new virulent pathotype.

Table 2.7 Clubroot incidence (%) and disease severity index (DSI) of cultivars from Williams’

differential set (1966) inoculated with a field collection of Plasmodiophora brassicae from the

Muck Crops Research Station, 2019.

Cultivar Crop Incidence (%) DSI (0–100)

Wilhelmsburger Rutabaga 0 0

Badger Shipper Cabbage 98 90

Jersey Queen Cabbage 100 100

Laurentian Rutabaga 100 100

45H291 Canola 9 9

Mei Qing Choi Shanghai pak choi 100 100

1Added to detect resistance-breaking pathotypes not characterized by the Williams’ differentials.

2.4 Discussion

In the current study, the canola cultivars marketed as clubroot resistant were highly

resistant to both pathotypes 2 and 6. These cultivars likely carry one or more dominant clubroot

resistance genes (Diederichsen et al., 2009). It is interesting to note that the InVigor canola

cultivars were resistant to pathotype 6, including all of the cultivars not marketed as CR. This

supports previous reports that most Canadian canola cultivars are resistant to pathotype 6

(Adhikari et al., 2012; Deora et al., 2012). Canola cv. 45H29 was resistant to pathotype 2,

indicating that the predominant pathotypes at the field site and from the field collections used in

the growth room studies were not new virulent pathotypes.

Canola cv. InVigor 5030 was included as a moderately susceptible control because of

reduced colonization by P. brassicae in the root cortex and intermediate clubroot severity in a

previous study (Deora et al., 2012). Its susceptibility to pathotype 2 may have been associated

with high disease pressure, because clubroot severity in partially resistant cultivars typically

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increases with increasing concentrations of inoculum (Hwang et al., 2017; Peng et al., 2019).

As with the CR canola cultivars, cabbage cvs. Bejo 2962 and Tekila, cauliflower cv.

Clarify and napa cabbage cv. Yuki, which had been marketed as clubroot resistant or tolerant,

were resistant to both pathotypes 2 and 6. In contrast, cabbage cv. Lodero and broccoli cv.

Emerald Jewel, which are also marketed as clubroot resistant or tolerant, were resistant to

pathotype 6 but susceptible to pathotype 2. However, it is important to note that the identification

of pathotype 2 in Ontario is a relatively new development (Al-Daoud et al., 2018), and pathotype

2 has been found almost exclusively on canola (McDonald et al., 2020a). The pathotype-specific

resistance found in the current study corresponds with a previous report that several brassica

vegetable cultivars, such as Brussels sprouts cv. Crispus, had pathotype-specific resistance while

other cultivars, such as bok choy cv. Bejo 2834 and napa cabbage cv. Bilko, were resistant to all

pathotypes assessed (pathotypes 2, 3, 5 and 6) (Sharma et al., 2013b). A study on the resistance

in the cv. Tekila showed that cortical infection was inhibited (Peng et al., 2019) and the clubroot

resistance gene, Rcr7 confers resistance to pathotype 3 in this cultivar (Dakouri et al., 2018).

Additional research to characterize the resistance in cvs. Bejo 2962, Clarify and Yuki might be

warranted.

Rutabaga cv. Laurentian is part of the Williams’ differential set, where it has been

characterized as susceptible to pathotype 2 and resistant to pathotype 6 (Williams, 1966). The

source of seed of Laurentian, from Stokes Seeds Ltd. or the University of Wisconsin, did not

affect the clubroot reactions to pathotypes 2 and 6. In the growth room trials, both seed sources

were susceptible to pathotype 2 and resistant to pathotype 6. In the field trials, both seed sources

had an intermediate reaction in 2018 but were resistant in 2019. The intermediate reaction was

likely due to the delayed emergence in 2018, but may also indicate that pathotype 6 is still an

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important component of the pathogen population in some areas on the Muck Crops Research

Station. We conclude that seed of the Laurentian from commercial sources or from the

University of Wisconsin can be used interchangeably in Williams’ differential set and the CCD

differential set.

Two of the three differential cultivars for the B. oleracea differential system, Lodero and

Kilaton have been assessed at the Muck Crops Research Station. Seed of the third differential,

Bejo 51632, was not available. Lodero was highly to moderately susceptible in the field trials,

and highly susceptible to pathotype 2 in the growth room. Kilaton was highly resistant in other

field trials (Dr. M. R. McDonald, University of Guelph, personal communication). If the overall

reaction of Lodero is considered susceptible, this indicated that the predominant pathotype at the

MCRS could be pathotype Pb:3 in the B. oleracea system (Smilde et al., 2012). A study to

characterize the MCRS site and other vegetable fields in Canada based on the B. oleracea system

is clearly warranted.

Severe clubroot symptoms disrupt the vascular systems of roots, which restricts water

and nutrient uptake (Macfarlane and Last, 1959), and reduces plant height and yield (Hwang et

al., 2011b). In the current study, development of clubroot symptoms was associated with wilting

and reduced shoot weight in susceptible cultivars in the field trials. This difference was most

apparent and consistent in the 2018 field trials, when disease pressure was highest. In 2019,

shoot weights were generally higher in the resistant canola, cabbage and cauliflower cultivars

compared to susceptible cultivars, but the differences were not always statistically significant.

The smaller differences in biomass between resistant and susceptible cultivars in 2019 was likely

associated with lower clubroot severity. Similarly, a previous study on muck soil reported that

yield benefits of CR canola were smaller under low disease pressure relative to high disease

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pressure (Sharma et al., 2013b).

Clubs developed on a small percentage of the plants of CR canola and brassica vegetable

cultivars in the field trials and growth room studies. Low clubroot incidence in resistant canola

cultivars has been reported previously (Hwang et al., 2019). This may be the result of off-types

in the seed lot (Canola Council of Canada, 2020b), or infection by virulent pathotypes present at

low concentrations in the pathogen population (Sedaghatkish et al., 2019). In the growth room

studies, the plants were inoculated with a high concentration of resting spores from field

collections, rather than single-spore isolates, which are not yet readily available for this

biotrophic pathogen. Virulent pathotypes may have been present at a low concentration in the

collection used for inoculum, and the high rate of inoculum used would have increased the

probability that some plants were exposed to virulent pathotypes other than the predominant

pathotype (Sedaghatkish et al., 2019).

The current study confirmed the clubroot resistance in Ontario of canola cultivars that are

marketed as CR on the Canadian Prairies, and also confirmed the resistance to pathotype 2 of

several vegetable cultivars marketed as clubroot resistant in Canada. Growers can use this

information to select cultivars based on the pathotype in a particular field, but need to be aware

that pathotypes can change over time. First-generation CR canola cultivars (e.g. 45H29)

currently provide effective clubroot reduction against the predominant pathotypes in Ontario,

pathotypes 2 and 6. However, growers should be aware that pathotypes that can overcome the

first-generation resistance have been identified in canola fields in Ontario (McDonald et al.,

2020a). Cultivars with more than one major CR gene may provide a more durable and broad-

spectrum resistance to clubroot (Kuginuki et al., 1999; Matsumoto et al., 2012). In addition,

alternating the source of resistance used in a field over time might delay or even prevent the

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emergence of virulent pathotypes (Chu et al., 2013; Hwang et al., 2019), but this option is

currently not available because information about the source of resistance in most commercial

cultivars is not available to producers.

Monitoring for breakdown of resistance in CR cultivars is an important component of

clubroot management (Howard et al., 2010; Strelkov et al., 2018). Growers should also maintain

at least two years between clubroot susceptible crops in infested fields to reduce spore loads in

soil (Hwang et al., 2012a, 2019; Peng et al., 2014b, 2015; Sharma et al., 2013b) and to reduce

the risk of resistance erosion caused by selection for virulent pathotypes (Sedaghatkish et al.,

2019; Strelkov et al., 2018).

In summary, the canola cultivars marketed as resistant to clubroot (InVigor L234PC,

L255PC, L241C and L135C) were all resistant to pathotype 2 of P. brassicae from Ontario in

both the field and growth room trials. Also, all of the canola cultivars were resistant to pathotype

6 in the growth room studies. Cabbage cvs. Bejo 2962 and Tekila, cauliflower cv. Clarify and

napa cabbage cv. Yuki, which were marketed as resistant or tolerant to clubroot, were resistant to

pathotypes 2 and 6. Cabbage cv. Lodero and broccoli cv. Emerald Jewel, also marketed as

resistant or tolerant to clubroot, were resistant to pathotype 6 but susceptible to pathotype 2.

Pathotype 6 is still the predominant pathotype found in fields of brassica vegetables in Ontario,

so susceptibility to pathotype 2 is not an immediate concern. However, vegetable growers should

be aware of the potential of selecting for a more virulent pathotype that will overcome resistance.

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CHAPTER THREE

3 Using field crops and liming to reduce resting spores in soil

3.1 Introduction

In canola cropping systems, a minimum of a one-year break between canola crops is

recommended, although a 2–3-year break provides additional benefits for pest management and

overall production (Canola Council of Canada, 2020a). Cereal and pulse crops are commonly

grown in rotation with canola in western Canada (Canola Council of Canada, 2020a; Gill, 2018).

In Ontario, canola is often grown in rotation with wheat, soybean, and corn (OMAFRA, 2020;

Ontario Grain Farmer Magazine, 2021).

More diversity in the cropping system is associated with higher canola yields (Gill, 2018;

Harker et al., 2015a). For example, the mean yield of canola was 11% higher following spring

wheat or field pea compared to continuous canola on the Canadian Prairies (Harker et al., 2018).

Including other crops in rotation with canola also reduces injury caused by pathogens and insects

(Harker et al., 2015a). For example, growing spring wheat before canola reduced blackleg

incidence compared to continuous canola (Harker et al., 2018). Populations of soil-borne

pathogens such as Fusarium, Pythium and Rhizoctonia also decreased with a greater diversity of

cropping rotation (Hwang et al., 2009).

Crop rotation is also effective in reducing populations of P. brassicae. The survival curve

of populations of resting spores in soil is typically a type III curve, where most resting spores die

in the first few years (Gossen et al., 2019), but the spores that survive can persist for many years

(Moxham and Buczacki, 1983). A minimum 2-year break from canola can reduce the

concentration of spores in the soil and increase canola yield (Gossen et al., 2017b; Hwang et al.,

68

2019; Peng et al., 2014b).

Inoculum levels of many pathogens can also be suppressed with the use of bait crops,

which stimulate the germination of soil-borne inoculum but do not allow the pathogen to

complete its life cycle. For example, host plants can be used as bait crops for P. brassicae if

removed from a field before P. brassicae can complete its life cycle. Removing a host after 4–5

weeks of growth was reported to reduce clubroot incidence and increase yield in a subsequent

host crop (Harling and Kennedy, 1991). However, mature resting spores were reported to be

present in clubs starting at 5 weeks following sowing in an infested site or inoculation. Also,

maturation of resting spores can continue after a host plant has been killed, so removal of

infected material from a field is important (Al-Daoud et al., 2020). If clubs form on even a small

number of bait plants, inoculum levels will increase because each club can contain millions or

billions of spores (Al-Daoud et al., 2020; Ingram and Tommerup, 1972; Hwang et al., 2015).

Bait crops for P. brassicae can also be nonhost crops that stimulate the germination of

resting spores (Ahmed et al., 2011; Friberg et al., 2005; Heath, 2000). Infection of nonhost crops

is generally restricted to the root hair infection stage, where primary plasmodia and zoosporangia

develop within root hairs, and secondary zoospores are released starting just 2 days after

infection (Liu et al., 2020; Murakami et al., 2000; Sharma et al., 2011b). These crops display

nonhost resistance, which can include both constitutive and induced defence responses (Heath,

2000; Niks and Marcel, 2009; Thordal-Christensen, 2003). Nonhost bait crops, such as perennial

ryegrass, leafy daikon, potato onion and creeping bentgrass, produce root exudates that stimulate

resting spore germination (Chen et al., 2018; Feng et al., 2012; Murakami et al., 2000). Root

exudates of perennial ryegrass stimulated the germination of a higher percentage of resting

spores than Chinese cabbage, which is a susceptible host (Friberg et al., 2005). Secondary

69

zoospores produced in root hairs cannot persist in soil for long periods because they do not have

cell walls that protect them against degradation (Moxham and Buczacki, 1983). They are

considered to be highly vulnerable to microbial organisms, temperature, pH, low moisture levels

and other soil factors and quickly disappear without a host to infect (Ayers, 1944; Suzuki et al.,

1992; Takahashi, 1994a), although the length of time that they survive is not known.

Grass cover crop species, including smooth bromegrass, meadow bromegrass and

perennial ryegrass, reduce the concentration of resting spores in soil under controlled conditions,

likely by stimulating resting spore germination (Sedaghatkish, 2020). The extensive root systems

of grass cover crops can also be useful in holding soil in place to prevent dispersal of resting

spores in a field. Therefore, grass species, especially perennial cover crops, are recommended for

patch management of clubroot and may have the added benefit of reducing resting spore

concentrations (Gossen et al., 2018).

Field studies assessing the effects of bait crops have faced limitations, including high

initial inoculum levels. It is difficult to detect small reductions in resting spore concentrations in

heavily infested fields (Ahmed et al., 2011; Friberg et al., 2006). In addition, the duration of

current studies may not be long enough for substantial reductions in spore levels (Ahmed et al.,

2011). Environmental conditions in the field can also interfere with the effect of bait crops, so

can make the extrapolation of controlled environment studies difficult (Friberg et al., 2006).

Applying large volumes of lime to raise soil pH is also an effective clubroot management

strategy. Soil pH levels between 5.0–6.5 are conducive to clubroot development (Gossen et al.,

2013). In early studies, calcium oxide, limestone and calcium hydroxide (Ca(OH)2) were shown

to suppress clubroot (Wellman, 1930). Calcium carbonate (CaCO3), dolomite (composed of

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CaCO3 and MgCO3) and calcium cyanamide (CaCN2) also reduced resting spore levels in soil

(Murakami et al. 2002b; Naiki and Dixon, 1987). Commonly used forms of calcium carbonate,

which is a slow acting lime, include ground limestone, calcitic lime and dolomitic lime

(Campbell et al., 1985; McDonald et al., 2004; Wellman, 1930). Quicklime (calcium oxide,

CaO) is a highly unstable chemical that produces calcium hydroxide if sufficient moisture is

present in soil (Wellman, 1930). Calcium cyanamide, a granular fertilizer, is converted to

calcium oxide and urea in soil. It has also been reported to be effective in reducing clubroot

(Bélec et al., 2004; McDonald et al., 2004). Hydrated limes are composed of calcium hydroxide,

and are fast acting and highly effective against P. brassicae (Wellman, 1930). However,

hydrated limes are caustic, explosive and costly, which limits their use by growers (Anderson et

al., 2013). Applying calcium-rich organic waste to soil to increase soil pH also suppressed

clubroot development (Niwa et al., 2007).

Soil pH levels above 7.2 are generally suppressive to clubroot (Myers and Campbell,

1985; Gossen et al., 2013). Liming can inhibit the germination of resting spores in the

rhizosphere and reduce the concentration of resting spores (Murakami et al., 2002b; Niwa et al.,

2008). Calcium has some effects on clubroot that are separate from changes in soil pH (Hamilton

and Crête, 1978), such as inducing host resistance, which suppresses clubroot development

(Webster and Dixon, 1991b). High levels of calcium also reduce the motility of zoospores, the

development of plasmodia, and the formation and dehiscence of zoosporangia (Myers and

Campbell, 1985; Webster and Dixon, 1991b). The interaction of bait crops and liming on the

concentration of resting spores of P. brassicae is currently unknown. The interaction may be

antagonistic, because many nonhosts stimulate the germination of resting spores, but calcium in

the form of lime applied to raise soil pH inhibits resting spore germination (Friberg et al., 2005;

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Rashid et al., 2013).

The main objective of this study was to determine if selected field crops reduce the

quantity of resting spores of P. brassicae in short-duration studies under controlled conditions. A

second objective was to assess the combined effect of a cereal crop and lime on resting spores in

soil to determine if the combination was more effective than each treatment alone.

3.2 Materials and methods

3.2.1 Field crop growth room study

Controlled environment studies were conducted at the University of Guelph to evaluate

the potential of selected field and cover crops to reduce resting spores of P. brassicae in soil. The

crops examined were: perennial ryegrass (Lolium perenne L.) cv. Norlea (provided by the Forage

breeding program at the University of Saskatchewan, Saskatoon, SK), spring wheat (Triticum

aestivum L.) cv. AAC Connery (Canterra Seeds, Balcarres, SK), barley (Hordeum vulgare L.)

cv. Trochu (SeCan, Ottawa, ON), soybean (Glycine max L.) cv. PRO 26X662N (ProSeeds-Sevita

International, Inkerman, Ontario), field pea (Pisum sativum L.) cv. CDC Meadow (Saskatchewan

Pulse Growers, Saskatoon, SK), and the clubroot-susceptible Shanghai pak choi (B. rapa var.

chinensis) cv. Mei Qing Choi (Stokes Seeds Ltd., St. Catharines, ON), which was included as a

positive control. A no-plant (bare soil) control was also included in the study. These crops are

common rotation crops in Ontario (soybean and barley) or the Prairie provinces (spring wheat,

field pea) (Canola Council of Canada, 2020a; Ontario Grain Farmer Magazine, 2021).

The growth medium was 2:1:1 by volume of mineral field soil (pH 6.4) from Elora,

Ontario, noncalcareous coarse sand (Hutcheson Sand & Mixes, Huntsville, ON) and soil-less

mix (L4A Sunshine Mix, Sun Gro Horticulture, MA). Sand and soil-less mix were added to

maintain soil texture. The soil for each replicate was prepared separately, with 1.4 kg of field

72

soil, 1.4 kg of sand and 0.2 kg of soil-less mix by weight for a total of 3.0 kg per replicate. This

growing medium (pH 6.4) was inoculated with resting spores of P. brassicae pathotype 2

obtained from clubbed roots of canola cv. ACS N39 grown for 9 weeks at the University of

Guelph Muck Crops Research Station, Holland Marsh, Ontario in 2017. The clubs were

maintained at -20°C after collection until use.

The inoculum was prepared following the methods of Sharma et al. (2011a). Briefly,

clubs were homogenized for 2 min with water in a commercial blender. The resulting spore

suspension was passed through eight layers of cheesecloth and the concentration of spores was

determined using a haemocytometer under a compound microscope. Each replicate was

inoculated separately, with a target of 5 × 105 spores g-1 of soil which was chosen as it represents

moderate clubroot infestation (Wallenhammar et al., 2012). To inoculate, 7.5 mL of 2.0 × 108

spores mL-1 was diluted with deionized water for a final spore suspension volume of 100 mL.

The inoculum was divided into two 50 mL falcon tubes and an EZ plant spray bottle was used to

apply the inoculum to the soil. The soil was spread out in a 74 cm × 46 cm × 15 cm bin to a

thickness of about 4 cm. The spray was applied at a 10 cm distance from the soil to moisten the

soil surface evenly. Then soil was mixed by hand for 30 sec. This process (inoculum sprayed,

soil mixed) was repeated 10 times, until all of the inoculum had been applied and incorporated,

to ensure that the inoculum was evenly distributed within the soil sample. The inoculated soil

was divided into sterilize 16 oz. plastic cups, where drainage holes had been punched into the

bottom of each cup. The study was arranged as a randomized complete block design, with six

replicates and one pot per experimental unit.

In the first run of the experiment, the cups were filled with 410 g of soil, and 15 seeds

were planted in each cup and thinned to 10 seedlings per cup at 6 days after planting (Figure

73

3.1). All crops were seeded at a 2.5 cm depth, except for perennial ryegrass, which was seeded

just below the soil surface. The soybean seed used in Run 1 did not germinate, so soybean was

not included in that initial assessment. Not all crops produced 10 plants in each replicate of Run

1, so 20 seeds were planted in each cup in Runs 2 and 3. The cups were filled with 385 g of soil

in Run 2 and 410 g in Run 3.

Figure 3.1 Seedlings of perennial ryegrass, wheat, barley, field pea, soybean, Shanghai

pak choi (susceptible control) and the no-plant control inoculated with Plasmodiophora

brassicae under controlled conditions.

The cups were each placed in a 20 cm × 16 cm × 10 cm plastic container and plants were

watered from the bottom with tap water adjusted to pH 6.0 with commercial white vinegar. In

Runs 2 and 3, the plants were watered based on field capacity, which was determined based on

soil bulk density and soil porosity (Reynolds et al., 2002). Soil bulk density was determined with

the following equation:

Bulk density (g cm−3) = Dry soil mass (g)

Soil volume (cm−3)

Porosity was determined with the following equation, with the assumption that particle

density was 2.65 g cm-3:

74

Porosity (%) = 1 − Bulk density (g cm−3)

2.65 g cm−3

Field capacity was considered as 50% of the porosity of the soil. The permanent wilting

point was considered as 50% of field capacity. Available water content was calculated as follows

(Reynolds et al., 2002):

Available water content (mL) = Field capacity (mL) − Permanent wilting point (mL)

The pots were initially weighed and watered to bring the soil to field capacity. Each pot

was weighed daily; when water content dropped below 50% of available water capacity, the pot

was watered to bring the soil back to field capacity. Adjustments were made to account for plants

weights after ~3 weeks of growth.

In each run, a fertilizer solution consisting of a 0.1% solution of nitrogen, phosphate,

potassium (20-20-20, Plant Products Classic, Brampton, ON), and magnesium sulfate was

applied weekly (from the bottom). The growth room was set at 24/19°C day/night, with 17-hr

photoperiod.

Pak choi was harvested at 6 weeks after seeding to avoid decay of clubs and loss of resting

spores back into the soil. The roots were assessed for clubroot severity on a 0–3 scale (Crête et

al., 1963), DSI was calculated as described previously. At 8 weeks after seeding, plants of the

other treatments were removed from their pots (Figure 3.2). Roots were extracted from the soil,

washed to remove excess soil, oven dried at 80ºC for 24 hr and root dry weight per pot was

measured. In addition, 20 g of soil from each replicate was air dried and then oven dried to

determine soil moisture content. The soil had a moisture content of 1% based on the difference

between air-dried and oven-dried soil.

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Figure 3.2 Root systems of a) perennial ryegrass, b) wheat, c) barley, d) field pea and e)

soybean after 8 weeks of growth and f) Shanghai pak choi after 6 weeks of growth in soil

inoculated with Plasmodiophora brassicae.

3.2.2 Cereal crops × lime study

A study was conducted to evaluate the interaction of growing barley or spring wheat

with/without added lime (calcium hydroxide) on the concentration of resting spores in soil, using

similar methods and growth conditions as in the rotation crop study. It was factorial experiment,

with two factors: the cereal crop (presence/absence) and rates of lime, in a randomized block

with six replicates and one pot per experimental unit. A no-plant control and a susceptible check,

Shanghai pak choi cv. Mei Qing Choi, were also included.

Barley cv. Trochu was selected for the initial run of this study because barley had the

lowest final concentration of resting spores in Run 1 of the rotation crop study (Figure 3.3). A

powder form of calcium hydroxide was used because the small particle size would allow faster

reaction in the soil and would achieve a uniform homogenization in the soil (Dobson et al., 1983;

Donald et al., 2004). The lime was thoroughly mixed into the soil to prevent microsites with low

pH (Dobson et al., 1983). Three rates of lime were selected: 0 mg, 0.077 mg g-1 of soil and 0.3

76

mg g-1 of soil to target a pH of 6.4, 6.8, and 7.2, respectively. The rates of lime required to

achieve the targeted pH values were determined using a range of rates in a preliminary study.

The test rates of lime were mixed into 100 g of soil. The soil pH was measured prior to planting

to ensure that the target pH levels were attained. To test the soil pH, 5 g of air-dried soil was

placed in a 15 mL conical tube and 5 mL of deionized water and a drop of 0.01 M CaCl2 were

added. The soil solution was vortexed for 1 min and left to stand for 30 min. The pH meter

electrode was inserted and swirled to measure pH (Eckert and Sims, 1995; Miller and Kissel,

2010).

Figure 3.3 Seedlings of barley, Shanghai pak choi (susceptible control) and no-plant

(negative control) at three rates of lime incorporated in soil inoculated with

Plasmodiophora brassicae.

Spring wheat cv. AAC Connery was used instead of barley in the second run of this

experiment because it reduced the concentration of resting spores in soil in Runs 2 and 3 of the

rotation crop study. Higher rates of lime were applied in Runs 2 and 3 because the pH levels in

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soil dropped throughout the 8-week growth period in the barley run. The rates of lime were: 0

mg, 0.24 mg g-1 of soil and 0.52 mg g-1 of soil to attain a target pH of 6.4, 7.0 and 7.6,

respectively.

The soil medium used was the same as in the field crops study. For each replicate, 4.7 kg

of soil was prepared: a mixture of 2.4 kg of field soil, 2.1 kg of sand and 0.2 kg of soil-less mix.

The inoculum source, preparation of inoculum, and soil inoculation process were the same as the

rotation crop study. In this study, 10 mL of 2.3 × 108 spores mL-1 was diluted in 50 mL of

deionized water and applied to the soil of each replicate to provide 5 ×105 spores g-1 of soil.

Following inoculation, the soil from each replicate was divided to apply the rates of lime.

In the initial run with barley, 77 mg and 465 mg of lime were applied to attain a pH of 6.8 and

7.2, respectively. In the wheat run, 155 mg and 651 mg of lime were applied to attain a pH of 7.0

and 7.6, respectively. The lime was thoroughly mixed by hand for ~30 sec into 1.5 kg of soil for

each replicate. In both runs, no lime was applied to the negative control, which had a pH of 6.4.

As in the rotation crop study, the soil was potted into clean plastic 16 oz. cups with

drainage holes. In each cup, 0.5 kg of soil was added and 20 seeds of pak choi, barley or wheat

were planted. The plants were watered from the bottom with tap water adjusted with commercial

white vinegar to target soil pH 6.4 and 6.8 or sodium hydroxide (NaOH) to target pH 7.0, 7.2 and

7.6. The water used for watering was adjusted to pH 7.2, 6.8 and 6.4 in the barley run and to pH

7.6, 7.0 and 6.4 in the wheat run. Fertilizer was also adjusted with NaOH to the target soil pH

and applied from the bottom, weekly. The volume of fertilizer applied increased throughout the

study for barley, wheat and pak choi to support increased plant size. Soil pH was tested weekly

in the no-plant control in the barley run and in one test pot per rate every 5 days in the wheat run.

78

Clubroot disease severity on pak choi was evaluated at 6 weeks after seeding using the

standard 0–3 scale described above. The soil from the barley/wheat and no-plant control

treatments was removed from the cups after 8 weeks. Barley or wheat roots were extracted, and

root dry weight per pot was measured after oven drying at 60ºC for 4 days.

3.2.3 Propidium monoazide (PMA)-qPCR analysis

The quantity of P. brassicae DNA in soil was determined in Runs 1 and 2 of the rotation

crop study and in the barley run of the cereal crop × lime study using standard quantitative

Polymerase Chain Reaction (qPCR) methods, and the quantity of total spores and viable spores

was determined using PMA-qPCR (Al-Daoud et al., 2017b). Pre-plant soil samples were taken

from each replicate to quantify the initial concentration of spores and post-plant samples were

taken from each experimental unit to quantify the final concentration of spores. Air-dried soil

samples of 1 g were ground to a fine powder with a mortar and pestle. The samples were

vortexed with 5 mL of deionized water in 50 mL falcon tubes for 2 min. The samples were left to

stand overnight.

The next day, propidium monoazide (PMA) was applied following the methods of Al-

Daoud et al. (2017b) to allow only the viable resting spores to be amplified with qPCR. The

spore suspensions were vortexed for 2 min and for each sample, 94 µL was dispensed into four

1.5 mL microcentrifuge tubes. In each tube, 6 µL of PMA- (equivalent to 120 uM PMA) or

DEPC-treated water (Invitrogen) were added. The water control was included to allow both

viable and nonviable resting spores to be amplified during qPCR. For each sample, two

subsamples were taken for each treatment (PMA and water). During this procedure, lights were

dimmed, and the PMA stock solution and the samples treated with PMA were covered with

aluminium foil to prevent PMA from reacting prematurely.

79

The samples were vortexed, spun in a mini-centrifuge and placed in a shaker at 300 rmp

for 30 min. The samples were placed on ice and exposed to 500-W halogen light (Globe Electric

Company) at a 20 cm distance from the samples for 15 min. The samples were flash frozen with

liquid nitrogen and stored at -80°C until DNA extraction was performed.

PMA was not utilized in Run 3 of the rotation crop study or in the wheat run of the crop

× lime study because there were no differences between the concentration of spores in the PMA-

and water-treated samples in Runs 1 and 2 of the rotation crop study or the barley run of the crop

× lime study. Instead, three subsamples were assessed for each experimental unit.

A DNeasy® PowerSoil® Kit (Qiagen) was used for extraction of P. brassicae DNA from

samples following the manufacturer’s instructions. A DNeasy® PowerSoil® Pro Kit (Qiagen)

was used for the post-plant samples in the wheat run of the crop × lime study because production

of the DNeasy® PowerSoil® Kit had been discontinued. For Runs 2 (post-plant) and 3 (pre-plant

and post-plant) of the rotation crop study and for the crop × lime study (pre-plant and post-plant),

a few small improvements were made based on methods by Wen et al. (2020). Specifically, the

soil samples and PowerBead Solution were homogenized three times for 1 min each with a

MiniG automated tissue homogenizer and cell lyser (SPEX SamplePrep) to maximize cell lysis.

In addition, the samples were eluted in 200 µL instead of 100 µL of elution buffer. All samples

were stored at -20°C until used for qPCR analysis.

The samples were quantified with qPCR using a TaqMan multiplex system. A forward

primer (DC1F) and a reverse primer (DC1mR) for P. brassicae were used (Table 3.1). The

P. brassicae probe had a FAM reporter dye at the 5’ end and an NFQ-MGB quencher at the 3’

end. A competitive internal positive control (CIPC) from a plasmid with a variant of the gene

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coding for GFP (Deora et al., 2015) was used to assess amplification inhibition in each run. A

GFP probe with a VIC reporter dye at the 5’ end and an NFQ-MGB quencher at the 3’ end was

used to quantify the CIPC amplification. Serial dilutions of P. brassicae resting spore

suspensions from 103 to 107 spores were used to create a standard curve. Technical triplicates for

each subsample were analyzed.

The qPCR assays were conducted in a 96-well plate StepOnePlus real-time PCR system

(Applied Biosystems) using StepOne v2.1 software. The qPCR assays were run on a machine in

the Crop Sciences building at the University of Guelph, except for the wheat run of the crop ×

lime study, which was run at the Advanced Analysis Centre at the University of Guelph. The run

conditions were 50°C for 2 min, 95°C for 10 min, 40 cycles of 95°C for 15 sec and 62°C for 1

min. Results were analyzed if the assay efficiency was 90–110% and the R2 ≥ 0.93, based on the

standard curve. Due to technical challenges with the thermal cycler during the barley run of the

crop × lime study, assays were analyzed when R2 ≥ 0.87. The concentration of spores was

calculated as spores per gram of oven-dried soil based on the 1% moisture content of the air-

dried soil. The quantification cycle (Cq) of the CIPC in the no-template control was 28 to 35.

Samples were adjusted for inhibition based on the Cq in the no-template control. If inhibition

was high (∆Cq ≥ 3), the samples were repeated or diluted. In Run 1 of the rotation crop study, a

maximum Cq variation of 2 was set between technical replicates as there was more variability in

the estimates due to inexperience with qPCR. In Runs 2 and 3 of the rotation crop study and in

the wheat run of the crop × lime study, a smaller maximum Cq variation of 1.3 was used. Due to

challenges with the qPCR machine in Crop Science that reduced the efficiency of the assays, a

wider maximum Cq variation of 1.5 was set between technical replicates for the barley run of the

crop × lime study. Technical replicates were removed from the calculation for the mean for the

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subsample if the maximum Cq variation threshold was exceeded. If two of the technical

replicates for an experimental unit exceeded the maximum Cq variation threshold, all three

technical replicates were repeated.

Table 3.1 qPCR reaction reagents, concentrations and volumes used to quantify

Plasmodiophora brassicae DNA in inoculated soil.

Reagents Concentration Quantity per reaction (µL)

Water 1.4

Taqman Universal PCR Master Mix 10.0

Forward primer (DC1F) 10 µmol 1.8

Reverse primer (DC1mR) 10 µmol 1.8

Plasmodiophora brassicae probe 10 µmol 0.5

GFP probe 10 µmol 0.5

Internal control 10-7 ng µL-1 2.0

Sample DNA 2.0

Total volume 20.0

3.2.4 Evans blue stain

Evans blue staining and light microscopy were evaluated to assess the concentration of

viable and nonviable resting spores as an alternative to PMA-qPCR. For this procedure, 50 µL of

resting spore suspension in 1.5 mL microcentrifuge tubes were treated with 50 µL of 20 mg mL-1

Evans blue stain solution. The Evans blue stain was prepared using deionized water. The spore

suspensions were incubated at room temperature for over 8 hrs (Harding et al., 2019). Resting

spores with dark blue-stained cytoplasm were considered to be nonviable. One hundred resting

spores were counted for each experimental unit using bright field microscopy and the percentage

of viable spores was determined.

To verify the efficacy of the Evans blue stain procedure, Evans blue-treated spore

suspensions were heat treated at 80°C for 72 hr to kill the spores. Spores stained with Evans blue

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prior to the heat treatment were compared to spores stained with Evans blue after the heat

treatment using ×125 magnification on a bright field compound microscope. There was no

difference between the two approaches. The heat-treated spore suspensions were mixed with

non-heat-treated spore suspensions (also treated with Evans blue) at six ratios of non-heated to

heat-treated spores: 1:0, 4:1, 3:2, 3:2, 1:4, and 0:1. Six replicates were prepared, with one 100 µL

spore suspension mixture for each treatment ratio as the experimental unit. For each mixture, 10

µL of each spore suspension was dispensed onto a slide and the viability of 100 spores was

assessed using ×125 magnification on a bright field compound microscope.

3.2.5 Statistical analysis

All statistical analyses were conducted in SAS 9.4 (SAS Institute, Cary, IN).

Concentrations of resting spores in soil and dry root weight per pot were analyzed in PROC

GLIMMIX, and Tukey’s test was used for means separation. A type 1 error rate of P = 0.05 was

set for all statistical tests. The Shapiro-Wilk test and scatter plots of the residuals were used to

evaluate the normality of the data. Spore concentration was analyzed based on a lognormal

distribution. The spore concentration of the pak choi control was excluded from statistical

analyses of crop treatments because it was expected to increase over time rather than decrease. A

factorial analysis was used to evaluate Runs 1 and 2 of the rotation crop study. The two factors

were the evaluation method (PMA- or water-treated) and crop. There was no difference in spore

numbers between the PMA- and water-treated spores and no interaction between these factors in

either run. Therefore, the PMA- and water-treated samples were treated as subsamples. Variance

analyses of the rotation crop study showed that the three runs could not be pooled, so each run

was assessed separately. Dry root weight per pot among crop species was analyzed based on a

normal distribution. Pearson correlations were used to examine the relationship between the

83

concentration of resting spores and root weight among all crops and within each crop species

using PROC CORR.

The crop × lime study was also analyzed as a factorial design with two factors: crop

(cereal and no-plant control) and the lime rate. PMA application (PMA- or water-treated) was

initially included as a factor in the barley run, but was dropped from the subsequent analyses

because PMA did not affect spore concentration, based on data from the rotation crop studies.

Therefore, the PMA- and water-treated samples were treated as subsamples.

A mixed model analysis of variance (ANOVA) was conducted using PROC GLIMMIX

for the crop treatment (cereal and no-plant control) and pak choi, where the fixed effects were

the crop treatment and lime rate, and the random effects were block and subsample within block.

Orthogonal contrasts were used to determine if rate of lime had a linear or quadratic effect on

spore concentration. If significant linear or quadratic relationships were present, regression

analysis, estimation of regression coefficients and comparison of regression responses were

conducted. Efron’s pseudo R2 values were used to describe the fit of the regression equations

using PROC CORR.

Spore concentration from the pak choi treatment was analyzed among lime rates based on

a lognormal distribution and are presented in tables and text as back transformed least square

means. The effect of lime rate on CI and DSI in pak choi was analyzed based on a binomial

distribution in PROC GLIMMIX. Dry root weight per pot in barley and wheat among lime rates

were analyzed based on a normal distribution. The effect of the crop treatment (barley/wheat, no-

plant control and pak choi) on soil pH at the end of the experiment at each individual lime rate

was analyzed based on a normal distribution using PROC GLIMMIX.

84

Studentized residuals were evaluated to identify outliers in the data. One outlier was

removed from Run 2 of the rotation crop study (a water-treated subsample from the field pea

treatment in replicate 1). Three outliers were removed from the wheat study (all subsamples from

the no-plant control at pH 7.6 in replicate 6). One outlier was removed from the pak choi

samples in the wheat study (a subsample at pH 7.6 in replicate 6).

3.3 Results

3.3.1 Field crop study - Run 1

In Run 1 of the field crop study, clubroot development was severe in Shanghai pak choi

cv. Mei Qing Choi (CI = 100%, DSI = 100) after 6 weeks of growth. Some decay was observed

in the clubs. Perennial ryegrass, barley and field pea did not have 10 plants in each pot, and the

soybean treatment had to be dropped entirely because of low seedling emergence. Growth was

stunted and leaf yellowing occurred in all the crops except for perennial ryegrass, and was

particular severe in field pea. There were 46 of 122 samples that were not analyzed because they

did not amplify, or they exceeded the maximum Cq variation of 2. These samples were not

specific to any treatment or replicate. No clubs developed in any of the field crops or perennial

ryegrass.

There were no differences between the PMA- and water-treated samples in pre- or post-

plant concentration of spores. This indicated that most or all of the spores were viable or that

compounds in the soil interfered with the activity of the PMA, so these samples were treated as

subsamples. The soil was inoculated with resting spores to target 5 × 105 spores g-1 and the mean

pre-plant concentration of resting spores tested with qPCR was 2.3 × 105 spores g-1. The

concentration of spores increased to 2.5 × 107 spores g-1 in the pak choi susceptible control and

decreased to 5.2 × 104 spores g-1 in the no-plant control. There were no differences in the post-

85

plant concentration of spores among the crop treatments (Table 3.2). Resting spore counts ranged

from 3.8 × 104 to 8.7 × 105 spores g-1. There was a significant effect of block in the analysis of

spore concentrations (P = 0.02).

Dry root weight per pot was higher in perennial ryegrass than barley or field pea. Also,

the dry weight of roots of field pea was lower than wheat roots. There was no correlation

between root weight and concentration of spores when analyzed across crops or within

individual crop species (Table 3.2).

Table 3.2 Effect of field and cover crop species on the concentration of resting spores of

Plasmodiophora brassicae in soil and root dry weight in Run 1 after 8 weeks of growth. Resting

spore concentration was based on standard qPCR analysis (n = 6).

Crop Cultivar Resting spore concentration1

(spores g-1)

Root dry weight

(g pot-1)

Pre-plant mean 2.3 × 105 nd

Perennial ryegrass Norlea 8.7 × 105 ns2 5.3 a3

Field pea Meadow 7.6 × 104 0.6 c

Wheat AAC Connery 5.5 × 104 3.5 ab

No-plant (control) 5.2 × 104 nd

Barley Trochu 3.8 × 104 2.6 bc 1Resting spore concentration data were analyzed based on a lognormal distribution and presented

as back transformed least square means. nd = not done. 2ns = not significant. 3Means followed by the same letter in a column do not differ based on Tukey’s test at P = 0.05.

3.3.2 Field crop study - Runs 2 and 3

In Runs 2 and 3 of the field crop study, plant growth was improved, and yellowing was

reduced compared to Run 1, likely in response to the change to watering based on field capacity.

Each crop treatment had 10 plants per pot. No clubs developed in any crop, except Shanghai pak

choi, where clubroot was severe (CI = 100%, DSI = 100). The clubs in pak choi had started to

decay when harvested at 6 weeks after planting.

As in Run 1, there were no differences between the PMA- and water-treated samples for

86

the pre- or post-plant concentration of spores in Run 2, so they were treated as subsamples and

samples were not treated with PMA in Run 3. The target pre-plant concentration of resting

spores was 5 × 105 spores g-1, but the mean concentration immediately after inoculation was 7.2

× 106 spores g-1 in Run 2 and 6.1 × 104 spores g-1 in Run 3. The concentration of resting spores in

the no-plant control decreased by 90% in Run 2 and increased by 11% in Run 3 compared to the

pre-plant levels. The concentration of spores for the susceptible control pak choi increased to 1.9

× 107 spores g-1 in Run 2 and 2.1 × 107 spores g-1 in Run 3.

In Run 2, the resting spore concentration was reduced by 37% in perennial ryegrass and

36% in wheat relative to the no-plant control (Table 3.3). The other crops did not reduce spore

concentrations compared to the no-plant control. In Run 3, wheat reduced the concentration of

resting spores by 57% compared to the no-plant control, but the other crop species had no effect

on spore concentration (Table 3.3).

Perennial ryegrass had a higher root dry weight per pot than the other crops in Runs 2 and

3, field pea had the lowest weight, and the other crop species were intermediate (Table 3.3).

There was a positive correlation between root weight and concentration of spores for perennial

ryegrass in both Runs (

Table 3.4). There was no correlation between root weight and concentration of spores

within any of the other crop species, or when all crops were assessed together.

87

Table 3.3 Effect of field and cover crops on the concentration of resting spores of

Plasmodiophora brassicae in soil and root dry weight after 8 weeks of growth in two runs of the

study (n = 6).

Crop Cultivar

Resting spore concentration1

(spores g-1)

Root dry weight

(g pot-1)

Run 2 Run 3 Run 2 Run 3

Pre-plant mean 7.2 × 106 6.1 × 104 nd nd

No-plant control 6.8 × 105 ab2 2.1 × 105 a nd nd

Soybean PRO 26X662N 8.7 × 105 a 2.1 × 105 a 4.8 b 4.2 b

Barley Trochu 3.8 × 105 bc 1.2 × 105 ab 2.9 bc 4.2 b

Field pea Meadow 3.4 × 105 bc 1.4 × 105 a 1.9 c 1.9 c

Wheat AAC Connery 3.3 × 105 c 6.6 × 104 b 3.0 bc 4.8 b

Perennial ryegrass Norlea 3.1 × 105 c 1.2 × 105 ab 8.5 a 9.5 a 1Resting spore concentration data were analyzed based on a lognormal distribution and presented

as back transformed least square means. nd = not done. 2Means followed by the same letter in a column do not differ based on Tukey’s test at P = 0.05.

Table 3.4 Correlation between root dry weight of the field/cover crops and resting spore

concentration in soil inoculated with Plasmodiophora brassicae after 8 weeks of growth in two

runs of the experiment (n = 6).

Field crop

Resting spore concentration (spores g-1)

Run 2 Run 3

r P1 r P

Perennial ryegrass 0.87 0.03 0.90 0.01

Barley 0.48 ns 0.54 ns

Wheat -0.29 ns -0.42 ns

Field pea -0.29 ns 0.52 ns

Soybean -0.33 ns -0.20 ns

Total 0.14 ns 0.23 ns 1ns = not significant.

3.3.3 Cereal crops × lime study

In the crop × lime study, the mean pre-plant concentration of spores was 1.5 × 106 spores

g-1 in the barley run and 2.3 × 105 spores g-1 in the wheat run. The target concentration was 5 ×

105 spores g-1. There were no differences between the PMA- and water-treated samples for both

88

the pre- or post-plant concentration of spores in the barley run, so these were treated as

subsamples, and PMA was not assessed in the wheat run. Compared to the pre-plant levels, the

concentration of spores increased in the no-plant control by 41% in the barley run and by 20% in

the wheat run.

In the barley run, there was a main effect of crop; the concentration of resting spores was

higher (P = 0.02) after barley (2.6 × 106 spores g-1) compared to the no-plant control (1.4 × 106

spores g-1). There was no main effect of lime and no crop × lime interaction. The range of resting

spore concentrations was 1.2–3.0 × 106 spores g-1. As expected, given that there was no effect of

lime, single df contrasts for the effect of rate of lime on the concentration of resting spores were

not significant.

In the wheat run, there was a main effect for crop (P = 0.004), and a main effect of lime

(P= 0.001), but no interaction. Following wheat, spore concentration was reduced by 27%

relative to the no-plant control (2.7 × 106 spores g-1 vs. 3.7 × 106 spores g-1). There were 4.0 ×

106 spores g-1 in the soil limed to pH 7.6 and 2.4 × 106 spores g-1 in the soil limed to pH 6.4.

The linear relationship for the effect of soil pH on the natural log of concentration of

resting spores was significant for the crop treatments in the wheat run (P = 0.0002) (Figure 3.4).

The least square regression equation for the concentration of spores in soil was ln(spores) =

18.01 – 0.44(pH), Pseudo R2 = 0.26. The range of resting spore concentrations was 2.1–4.7 × 106

spores g-1. There was a significant (P < 0.0001) effect of block in the wheat run. There was no

effect of the lime rate on the dry root weight per pot of barley (mean = 5.1 g) or wheat (4.2 g).

89

Figure 3.4 The effect of three rates of lime (calcium hydroxide, Ca(OH)2) on the

concentration of Plasmodiophora brassicae resting spores in soil after growing wheat and

a no-plant control for 8 weeks. The soil was inoculated to attain an initial concentration of

5 × 105 resting spores g-1. The linear regression line is based on lognormal distribution and

presented using natural logs.

The pH of the non-limed soil in the no-plant control increased after ~3 weeks to pH 6.8

(barley run) and pH 6.6 (wheat run), and stayed at those pH levels until the end of the study. Soil

limed to target pH 6.8, 7.0 and 7.2 stayed at around those pH levels over the course of the study

in the no-plant control. Soil limed to target pH 7.6 dropped to ~pH 7.3 in the first 2 weeks of the

study and was ~pH 7.1 by the end of the study (Table 3.5).

a a b0

1000000

2000000

3000000

4000000

5000000

6000000

6.4 7.0 7.6

Res

ting s

pore

s g

-1so

il

Target soil pH

ln(spores) = 18.01 – 0.44(pH), Pseudo R2 = 0.26

90

Table 3.5 Soil pH in response to application of three rates of lime (calcium hydroxide, Ca(OH)2)

to a soil mix and planted with barley, wheat, Shanghai pak choi or a no-plant control after 6 or 8

weeks of growth (n = 6).

Rate of Ca(OH)2 (mg g-1)1 Crop2 Initial pH Final pH

Barley run

0 mg No-plant 6.4 6.8 a3

Barley 6.4 6.9 a

Pak choi 6.4 6.8 a

0.077 mg No-plant 6.8 6.8 b

Barley 6.8 7.0 a

Pak choi 6.8 7.0 ab

0.30 mg No-plant 7.2 7.0 b

Barley 7.2 7.1 a

Pak choi 7.2 7.0 b

Wheat run

0 mg No-plant 6.4 6.6 z

Wheat 6.4 7.0 x

Pak choi 6.4 6.9 y

0.24 mg No-plant 7.0 6.7 z

Wheat 7.0 7.1 y

Pak choi 7.0 7.0 y

0.52 mg No-plant 7.6 6.9 z

Wheat 7.6 7.2 y

Pak choi 7.6 7.1 yz 1Statistical analysis was conducted for each lime rate separately. 2The soil pH of the no-plant control and barley/wheat treatments were measured at 8 weeks after

seeding and for Shanghai pak choi after 6 weeks. 3Means followed by the same letter in a column do not differ based on Tukey’s test at P = 0.05.

Different letter pairings are used for the different runs.

Clubroot developed in Shanghai pak choi cv. Mei Qing Choi at all three rates of lime in

both runs (barley and wheat), with incidence and severity over 90% in the non-limed soil.

Application of lime reduced severity, especially at pH > 7.0 (Table 3.6). Clubroot severity was

lower in the treatments that received the highest rate of lime in both studies, which targeted a pH

of 7.2 and 7.6 and the DSI was 50 and 57, respectively.

The concentration of spores after growing pak choi increased at all three rates of lime, but

spore numbers were lower at the high rate lime relative to no added lime in both studies. The

91

linear relationship for the effect of pH on the natural log of spore concentrations was significant

for pak choi in the barley run (P = 0.0002) and the least square regression equation for the

concentration of spores in soil was ln(spores) = 39.78 -3.34(pH), Pseudo R2 = 0.15 (Figure

A2.1). There was a significant effect of block (P < 0.0001) and block by subsample (P = 0.01)

for pak choi in the barley run.

For pak choi, the linear and quadratic relationships for the effect of soil pH on the

concentration of resting spores were both significant in the wheat run (P = 0.0005 and P =

0.0006, respectively) and the quadratic relationship best fit the data (Figure A2.2). The least

square regression equation for the concentration of spores in soil was ln(spores) = -171.24 –

55.90(pH) – 4.09(pH)2, Pseudo R2 = 0.005. There was a significant effect (P < 0.0001) of block

and of subsample within block for pak choi in the wheat run.

Table 3.6 Effect of three rates of lime (calcium hydroxide, Ca(OH)2) on concentration of resting

spores of Plasmodiophora brassicae in soil, clubroot incidence (CI) and severity (disease

severity index, DSI) in Shanghai pak choi at 6 weeks of growth (n = 6).

Rate of

Ca(OH)2 (g-1)

Initial/target

soil pH

Final

soil pH

Resting spore concentration1

(spores g-1)

CI (%) DSI

(0–100)

Barley run

Pre-plant 1.5 × 106

0 mg 6.4 6.8 1.0 × 108 a 95 a 90 a

0.077 mg 6.8 7.0 2.2 × 107 b 93 a 86 a

0.30 mg 7.2 7.0 7.4 × 106 b 70 b 50 b

Wheat run

Pre-plant 2.3 × 105

0 mg 6.4 6.9 1.5 × 108 a 100 a 99 a

0.24 mg 7.0 7.0 3.1 × 108 a 100 a 99 a

0.52 mg 7.6 7.1 3.0 × 107 b 83 b 57 b 1Resting spore concentrations were analyzed based on a lognormal distribution and are presented

as back transformed least square means. 2Means followed by the same letter in a column and run do not differ based on Tukey’s test at P =

0.05.

92

3.3.4 Evans blue stain

To evaluate the Evans blue staining method for differentiating viable from nonviable

spores, selected ratios of heat-treated to non-heat-treated spores were evaluated and the

effectiveness of Evans blue stain in determining resting spore viability was confirmed (Figure

3.5). There was not, however, enough spores that could be extracted from the post-plant soil

samples in any of the studies to count 100 spores per experimental unit so this method could not

be used.

Figure 3.5 Proportion of viable Plasmodiophora brassicae resting spores, as determined

using Evans blue stain, as a function of the proportion of dead spores killed by heating.

Capped lines represent ± standard error.

3.4 Discussion

Only a few studies have examined the effects of crops suitable for rotation with canola and

how they affect the concentration of P. brassicae spores in soil. This is the first study to examine

the effects of wheat, barley, field pea and soybean on spore levels. This is also the first study to

examine the interaction of crop × lime on spore levels. This study demonstrated that a wheat

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

Via

ble

re

sti

ng

sp

ore

s (

%)

Proportion of heated spores (%)

93

crop reduced spore concentrations of P. brassicae in soil, and provided some support for a

previous study (Sedaghatkish, 2020) that reported that perennial ryegrass reduced spore numbers

relative to the no-plant control. In the study to investigate the interaction of crop × lime, applying

lime and growing wheat reduced spore numbers and there was no negative interaction between

these strategies, demonstrating that both can be used for clubroot management. The absence of

an interaction demonstrated that the two approaches do not counteract each other.

In the field crop study, Run 1 was used as a preliminary study and portions of the sample

analysis were never completed. There were issues with low seed emergence in perennial

ryegrass, barley and field pea, and soybean. In addition, wheat, barley and field pea plants were

stunted, possibly from overwatering and from nutrient deficiency resulting from dense planting

in small pots. In Runs 2 and 3, plant density was uniform, and growth was improved by watering

based on field capacity.

Wheat reduced resting spore concentrations in soil relative to the no-plant control in Runs

2 and 3, and perennial ryegrass reduced spore concentrations in one of the two runs. Barley, field

pea and soybean did not have an effect on resting spore levels in either run. Wheat may produce

root exudates similar to other bait crops that can stimulate the germination of resting spores of

P. brassicae, but the pathogen is unable to complete its life cycle because wheat is not a

susceptible host (Friberg et al., 2005). Primary plasmodia developed at a low frequency in root

hairs and epidermal cells of wheat and barley, but infection did not progress beyond the primary

infection phase, so no zoosporangia or secondary zoospores were produced (Liu et al., 2020).

Therefore, P. brassicae may have died in the root hairs of wheat, leading to a reduction in spore

concentrations. In contrast, a previous study based on resting spore counts reported that wheat

94

and barley did not consistently reduce resting spore loads when used as bait crops at field sites

where initial inoculum levels were high (Ahmed et al., 2011).

Root exudates of nonhosts crops are known to trigger the germination of resting spores

(Friberg et al., 2006; Murakami et al., 2000). A concurrent assessment of root hair infection

showed that a moderate level of root hair infection occurred in perennial ryegrass cv. Norlea, low

levels of root hair infection occurred in wheat and barley, but there was no root hair infection in

field pea and soybean (Dr. J. Feng, Alberta Agriculture and Food, personal communication).

Previous studies have also reported that perennial ryegrass stimulated resting spore germination

(Ahmed et al., 2011; Feng et al., 2012; Friberg et al., 2005; Friberg et al., 2006; Rashid et al.,

2013). In the current study, perennial ryegrass cv. Norlea reduced spore levels compared to the

no-plant control in one of two runs of the field crop study.

In a recent controlled environment study, not all grasses evaluated reduced spore levels in

soil (Sedaghatkish, 2020). Perennial ryegrass was also not effective in suppressing clubroot

infection in a susceptible host in a field trial in Stockholm, Sweden (Friberg et al., 2006). Grass

species are likely to reduce inoculum levels only by small amounts and the effect can be difficult

to quantify due to variability in the assessment methods. Populations of resting spores in soil are

often high since a club can contain millions of resting spores (Ingram and Tommerup, 1972), and

grasses will likely stimulate the germination of only a portion of these spores. These small

reductions may not reduce clubroot severity in subsequently grown susceptible hosts.

A hypothesis for this study was that bait crops with more extensive root systems would

produce greater quantities of root exudates and consequently induce higher levels of spore

germination and concomitantly greater reduction in spore numbers. This hypothesis was not

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supported in this study. There was no correlation between root weight and final concentration of

spores when crops were analyzed together, or within most crop species. The only exception was

perennial ryegrass, which had the largest roots of all the crops assessed; there was a positive

correlation between root weight of perennial ryegrass and spore con in both runs of the study.

This correlation may indicate that the DNA of zoospores in the root hairs of this grass was

amplified because perennial ryegrass has a much higher rate of root hair infection than the field

crops (Dr. J. Feng, Alberta Agriculture and Food, personal communication). The correlation may

also be spurious because cereal crops that likely also stimulated resting spore germination did not

show the same response. The lack of correlation between root weight and concentration of spores

indicated that the extent of soil colonization by the roots was either not related to resting spore

germination, or the effect was too small to measure in the limited time frame of the study.

However, grass crops with extensive root systems can still be useful for managing clubroot

because they hold soil in place and so prevent the dispersal of resting spores in the field (Gossen

et al., 2019b). Multi-year field trials that are currently in progress in the Prairie provinces may

provide this information (Dr. B.D. Gossen, AAFC Saskatoon, personal communication).

Differences among crops in stimulation of resting spore germination may be due to

differences in the composition of root exudates, including the presence and quantity of the

proteolytic products of a serine protease (Pro1) that can stimulate germination (Feng et al., 2010;

Sukuzi et al., 1992), rather than due solely to the quantity of root exudates. Also, the highest

concentration of resting spores is typically in the top 20 cm of soil, but spores appear to be

carried deeper into the soil over time (Cranmer et al., 2017). Growth of the bait crop over time

would let the roots explore more widely and deeper into the soil, which might stimulate

germination of spores throughout the soil profile (Sedaghatkish, 2020).

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The conditions in the studies were designed to be conducive for resting spore

germination. The soil in the field crop study was kept moist at pH ~6.4, and temperature was

near optimal for clubroot development (Sharma et al., 2011b). Resting spores can germinate

starting at one day after exposure to root exudates (Rashid et al., 2013). Previous studies have

shown that resting spore germination rates were higher when spores were mature, moisture

content was high (Ayers, 1944; Macfarlane, 1970; Takahashi, 1994b), and pH was 6.5, which is

also optimal (25°C, pH 6.0–6.4) for Pro1 activity (Feng et al., 2010; Macfarlane, 1970; Rashid et

al., 2013).

Emerged zoospores only survive for a short period of time because they are highly

vulnerable to adverse soil conditions and to other microbes (Suzuki et al., 1992; Takahashi,

1994a). Primary zoospores can infect the root hairs of many nonhost species (Feng et al., 2012;

Friberg et al., 2005; Liu et al., 2020) and root hair infection generally increases in the first 6–8

days after infection (Hwang et al., 2011b). Infection of wheat, barley and many other nonhosts

does not progress beyond primary plasmodia, but for others, such as perennial ryegrass,

development and release of secondary zoospores can occur (Feng et al., 2012; Friberg et al.,

2005; Liu et al., 2020). A dramatic increase in secondary zoospores can occur during the root

hair infection stage, as each zoosporangium contains 4–16 zoospores (Ingram and Tommercup,

1972). However, secondary zoospores rarely, if ever, infect the root cortex of a nonhost (Feng et

al., 2012; Friberg et al., 2005).

Quantitative PCR is a commonly used method to quantify P. brassicae spores (e.g. Al-

Daoud et al., 2017; Deora et al., 2015; Ernst et al., 2019; Wallenhammer et al., 2012) and was

used in this study to assess spore concentration in soil. A high number of nonviable resting

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spores detected using the PMA treatment (PMA-qPCR) would have indicated that DNA from

primary or secondary zoospores remained in the soil to confound spore estimates after their death

in the absence of a susceptible host. However, the PMA treatment did not show any consistent

differences between the concentration estimates of total resting spores and viable resting spores

from qPCR in the current study or in a similar study evaluating selected grass species under

controlled conditions (Sedaghatkish, 2020). Therefore, low levels of root hair infection in wheat

that did not result in secondary zoospore production, as noted in a recent report (Liu et al., 2020),

may have resulted in an overall reduction in spores. An alternative interpretation is that PMA

was not effective because compounds in the soil solution interfered with PMA activity or the rate

of PMA or incubation time may not have also not been sufficient for the high amount of DNA in

the samples (Harding et al., 2019).

In the study to investigate the interaction of crop × lime, both factors reduced resting

spore levels in soil. The wheat crop reduced resting spores in comparison to the no-plant control

and resting spore concentrations declined as the rate of lime increased. The results from the field

crop study indicate that root exudates from wheat can stimulate the germination of resting spores

while application of calcium to increase soil pH inhibited spore germination (Niwa et al., 2008).

The current study demonstrated that the effects of these two modes of action on resting spores

did not cancel each other out.

The regression response of lime rate on the log concentration of spores for wheat and the

no-plant control was linear. If liming only inhibited resting spore germination, the spore levels

would not be expected to decrease compared to the control. The reduction in spore levels with

increasing pH levels for wheat may have been possible because liming did not inhibit the

germination of all resting spores. Some primary infection can still occur, and the zoosporangia

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that develop are misshapen and abort (Myers and Campbell, 1985). Therefore, the reduction in

spore levels may be because P. brassicae died in root hairs. Resting spore concentrations

decreased with increasing lime even in the no-plant control. This finding has been previously

reported with calcium cyanamide, dolomite and calcium carbonate under controlled conditions,

based on assessments with microscopy (Murakami et al., 2002b). This report and the finding of

the current study indicate that in addition to inhibiting resting spore germination, calcium limes

may kill resting spores, so that spores in alkaline soil are removed from soil at a faster rate than

would be expected in an acidic soil. The current study should be repeated to confirm that liming

reduces spores in bare soil.

There was no effect of barley on resting spore levels in soil, and no effect of applied lime

in the barley run of the crop × lime study. Barley was selected as the crop species for the first run

of this study based on results of Run 1 of the field crop study, which indicated that barley

reduced the concentration of spores. Primary infection has also been reported in barley, which

indicated that it might stimulate resting spore germination (Liu et al., 2020). However, barley did

not reduce the concentration of spores in soil relative to the no-plant control in Runs 2 and 3 of

the field crop study.

The absence of response to application of lime in the barley run may have been due to the

gradual decrease in pH over the course of the experiment. Optimal clubroot suppression occurs

at pH levels over 7.2 (Gossen et al., 2013; Myers and Campbell, 1985) and the soil pH in the

highest lime treatment dropped to pH 7.0–7.1. In addition, technical issues with the Step-one

real-time PCR thermal cycler at the Crop Science facility used for this study introduced more

variability in qPCR estimates, so may have also been a confounding factor.

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Pak choi was included as a susceptible check in the crop × lime study. Liming reduced

clubroot severity in pak choi, which led to fewer spores being released from clubs into the soil.

The regression response of lime rate on the log concentration of spores for pak choi was linear in

the barley run but quadratic in the wheat run, which demonstrated that the rate of lime applied

had a strong impact on clubroot development on pak choi. This is consistent with other reports

that raising soil pH with calcium-rich compost or calcium carbonate inhibited resting spore

germination (Niwa et al., 2008). While clubroot incidence and severity were lower at pH 7.2

than at pH 6.4 and 6.8 in the barley run and at pH 7.6 than at pH 6.4 and 7.0 in the wheat run,

moderate clubbing occurred even at these higher pH levels (pH 7.2 and 7.6). Club development

was also reported in field conditions at pH levels up to 7.6 (Strelkov et al., 2007). Similarly,

moderately severe clubs developed in canola at pH 8.0 under optimal temperature and moisture

conditions (Gossen et al., 2013). The drop in pH over the course of the 8-week studies may have

also contributed to the moderate clubroot infection, especially at the intermediate levels of target

pH. However, root hair infection occurs rapidly after inoculation (Hwang et al., 2011b; Sharma

et al., 2011b), so some suppression likely occurred before the soil pH dropped. The pak choi

plants were harvested after 6 weeks of growth to reduce the decay of clubs in all the studies.

There was, however, some decay of clubs by the time of harvest, which likely contributed to the

release of resting spores that resulted in an increased concentration of spores in soil.

Soil pH in the liming treatments was not maintained throughout the barley and wheat

runs of the crop × lime study. A high concentration of extractable calcium cations in soil is

required for effective clubroot suppression (Campbell et al., 1985; Murakami et al., 2002b).

Some soils are more effective in maintaining pH than others (Welch et al., 1976), so the

buffering capacity of the soil from Elora used in these studies may have affected the pH levels

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over time. Also, calcium hydroxide has a short-term effect on soil pH, particularly compared to

agricultural and dolomitic limes, which can take several months to increase the pH (Hwang et

al., 2014b). Therefore, to maintain soil pH, several applications of calcium hydroxide may be

required, or an agricultural or dolomitic lime could be used instead.

The effects of increased pH may be separate from the direct effects of calcium (Hamilton

and Crête, 1978; Webster and Dixon, 1991b), although liming affects both. Calcium has been

reported to increase activation of host resistance mechanisms to limit infection by primary and

secondary zoospores, development of plasmodia in the root cortex, mitotic divisions of

plasmodia and cellular hypertrophy (Webster and Dixon, 1991b). Calcium may also reduce

zoospore motility, independent of changes in soil pH (Sleigh and Barlow, 1981), which could

account for the reduction in clubroot severity in pak choi at increasing rates of lime despite the

pH not being maintained throughout the study.

There were differences in soil pH among the crop treatments, as the soil pH after

growing wheat, barley and pak choi was generally higher (more alkaline) than the no-plant

control. These differences may be associated with slightly different water and fertilizer

applications among the treatments. Barley and wheat had the highest water requirement,

followed by pak choi. The water requirement for the no-plant control was substantially lower. A

similar volume of fertilizer was applied to barley, wheat and pak choi, but a lower volume was

applied to the no-plant control. Further, the pH and chemical composition of root exudates

differs among crops. For example, the pH of root exudates was 6.3 in Chinese cabbage and 7.1 in

perennial ryegrass (Rashid et al., 2013). Also, some plant roots, such as oilseed rape plants,

released H+ due to an imbalance in the uptake of ions, which increases soil acidity (Hedley et al.,

101

1982). The root exudates of barley and wheat are composed of amino acids, organic acids,

sugars, and phenolic compounds (Vančura, 1964), which can affect soil pH. Therefore, the root

exudates produced by the crops may have affected soil pH, which in turn could have affected the

impact of the lime rate treatments.

All of the studies were inoculated with spore suspensions targeted to produce 5 × 105

spores g-1 of soil, but there was an unexpectedly high variation in the pre-plant concentration of

spores tested with qPCR. In particular, the pre-plant spore levels for Run 2 of the field crop study

and for the barley run were over 106 spores g-1. Previous studies have shown that the

quantification of resting spores with qPCR is subject to high variability on account of the low

quantities of soil that are assessed (Bilodeau, 2011, Deora et al., 2015; Wen et al., 2020). Resting

spores may aggregate and lack a uniform distribution in soil, even with careful mixing, which

may have contributed to the high levels of spore estimates with qPCR. Variability within the

qPCR assays may have also contributed to differences in the spore levels tested. The pre-plant

concentration of spores was lower than the post-plant levels in the wheat run, which likely

indicates that the pre-plant estimate was substantially lower than the actual value. The DNeasy®

PowerSoil® Pro Kit used for the post-plant samples is more effective at extracting DNA than the

DNeasy® PowerSoil® Kit used for the pre-plant samples, and this improved efficiency may

have contributed to the difference in spore levels.

Also, there was a significant block and/or subsample by block effect in several of the

studies. Each block was inoculated separately, which could have contributed to some variation

between initial concentrations of spores. Variability in the qPCR estimates may have been a

factor in the variability among blocks and subsamples. Not all blocks and subsamples were run

102

in the same assay because of repeating subsamples that failed to amplify or that had high

inhibition, and this may have contributed to the significant subsample by block effect.

Further studies are needed to determine the mechanism by which wheat reduces resting

spore levels in soil and the combined effect of bait crops and lime and/or calcium on resting

spores are needed. Determining the mechanism will help to confirm that there is no negative

interaction between bait crops and liming and could provide useful information about how these

strategies can be used together. In addition, studies should be conducted to evaluate the effect of

bait crops and the interaction with lime under field conditions. Evaluating the effects of bait

crops in soil with different initial resting spore loads could provide valuable insights, as other

studies have concluded that the use of bait crops in a clubroot management program will not

likely reduce resting concentrations of spores in soil to a useful level if infestation levels are high

(Ahmed et al., 2011; Friberg et al., 2006). Even a moderate reduction in resting spore levels in

heavily infested field would likely result in clubroot infection, as clubs can develop at

concentrations of resting spores as low as 103 spores g-1 of soil (Naiki et al., 1987). Many

commercial field sites with clubroot infestations have concentrations of resting spores above 105

spores g-1 of soil (Ahmed et al., 2011; Ernst et al., 2019). Bait crops would likely be most

effective in fields with low clubroot infestations (Ahmed et al., 2011).

In summary, planting spring wheat as a rotation crop in clubroot infested soil may reduce

the number of P. brassicae spores in soil, but the changes are likely to be too small to have an

effect on grower operations or clubroot management. No negative interaction on spore reduction

was identified between applying lime and growing spring wheat, so growers can use both

clubroot management practices without concern about negative synergies.

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CHAPTER FOUR

4 General discussion

Two important components of clubroot management were examined in the current study:

pathotype-specific genetic resistance and the reduction of the concentration of resting spores in

soil resulting from non-host crops. Growth room studies and field trials were conducted to

evaluate clubroot resistance in canola and brassica vegetables against clubroot pathotypes 2 and

6 (Williams’ system), which are prevalent in Ontario. In addition, growth room studies were

conducted to evaluate the effect of field and cover crops on the concentration of resting spores of

P. brassicae in soil, including studies to evaluate the interaction of lime application and growth

of a cereal crop.

Genetic resistance has been the primary method used to manage clubroot in canola crops

in Canada, and is becoming more common for clubroot management in brassica vegetables.

Therefore, screening cultivars for resistance to the pathotypes present in a region is an important

component of clubroot management. However, only limited information is available on the

reaction of many cultivars to specific pathotypes, especially in brassica vegetables. Most studies

on cultivar resistance have focused on the Prairie region, where 99% of canola is planted in

Canada. Initially, pathotypes 3 and 5 were prevalent on canola in Alberta (Hollman et al., 2020;

Statistics Canada, 2019a; Strelkov et al., 2018). Almost all of the canola cultivars in Canada are

partially resistant to pathotype 6 (Deora et al., 2013), but most were initially susceptible to

pathotype 3. The predominant pathotype on canola in Ontario is pathotype 2, and pathotype 6 is

predominant on vegetables (McDonald et al., 2020a).

The clubroot reaction of a sample of CR canola cultivars, InVigor L234PC, L255PC,

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L241C and L135C, were resistant to both pathotypes 2 and 6 in a controlled environment study

and to pathotype 2 in the field. The sample of InVigor canola cultivars that were not marketed as

CR were resistant to pathotype 6 but not pathotype 2, which is consistent previous reports

(Adhikari et al., 2012; Deora et al., 2012). In the field trials, shoot weight was higher in resistant

cultivars relative to susceptible ones, as expected.

Pathotype 6 has been the predominant pathotype on brassica vegetables in Ontario for

decades (Al-Daoud et al., 2017), and pathotype 2 was recently identified in Ontario canola fields

(Al-Daoud et al., 2018). Some vegetable cultivars carry resistance to multiple pathotypes, while

the resistance in others is known to be effective against only one pathotype (Peng et al., 2014a;

Sharma et al., 2013b). Most of the resistant cultivars were resistant to pathotypes 2 and 6, except

for cabbage cv. Lodero and broccoli cv. Emerald Jewel, which were marketed as

resistant/tolerant and were resistant to pathotype 6 but susceptible to pathotype 2. As in the

canola trials, severe clubroot developed and reduced shoot weight in the susceptible cultivars, as

expected. In addition, Laurentian rutabaga seed from Stokes Seed had the same reaction to

pathotypes 2 and 6 as seed from the University of Wisconsin. Therefore, the Laurentian rutabaga

host in the Williams’ system and the CCD set can be sourced from Stokes Seed, which is a less

expensive source.

In the current study, the predominant pathotype at the MCRS was characterized to

determine if the pathotype had changed over time. The pathotype was confirmed to be pathotype

2. It might also be useful to characterize pathotypes affecting vegetables in Canada using the

clubroot differential set that was recently developed specifically for B. oleracea. Two of the

three differentials for the B. oleracea system have been assessed at the MCRS, cabbage cvs.

Lodero and Kilaton. Lodero was susceptible and Kilaton was resistant, which indicated that the

105

predominant pathotype at the MCRS could be classified as Pb:3 (Smilde et al., 2012).

The second objective of the current study was to determine if selected field crops and

perennial ryegrass reduced resting spore concentrations in soil in short duration studies under

controlled conditions. This is the first study to evaluate the effect of spring wheat, field pea and

soybean on resting spore concentrations in soil and the first to investigate the interaction of a

cereal crop and lime on spore concentrations. Resting spore quantities were estimated using

qPCR. Root hair infection has been previously reported in a wide range of nonhosts, including

perennial ryegrass, wheat, and barley (Liu et al., 2020; Macfarlane, 1952). Root exudates from

these crops may stimulate the germination of resting spores, but the pathogen is unable to

complete its lifecycle in a nonhost crop. In the current study, spring wheat slightly reduced the

spore concentration in soil compared to a no-plant control. Growers can therefore select spring

wheat as a rotation crop to reduce levels of clubroot inoculum, even though the effect was small.

Perennial ryegrass also reduced spore levels compared to the no-plant control, but only in one of

two repetitions of the study. Several previous studies have found that perennial ryegrass

stimulated resting spore germination (Ahmed et al., 2011; Feng et al., 2012; Friberg et al., 2005;

Friberg et al., 2006; Rashid et al., 2013), but the effect of perennial ryegrass on spore

concentration could not be detected under field conditions (Friberg et al., 2006). It is difficult to

evaluate bait crops in field conditions as their effect on reducing spore levels is likely small

(Ahmed et al., 2011).

The initial hypothesis was that crops with greater root biomasses would produce greater

quantities of root exudates, which would in turn result in more spore germination and greater

reductions in spore levels. However, there was no relationship between root weight and

reduction of resting spores. This may indicate that plants with a more extensive root system are

106

not more effective at stimulating spore germination. Some crops may produce more root

exudates, or more effective root exudates, regardless of the extent of the root system. However, a

longer-term study may be needed to quantify the effects of root systems on spore reduction.

Liming to raise soil pH above 7.2 has been used for many years to suppress clubroot

symptom development (Myers and Campbell, 1985), and many types of lime are effective

(Murakami et al., 2002b; Naiki and Dixon, 1987; Wellman, 1930). In addition, calcium inhibits

resting spore germination, zoospore motility, and the development of plasmodia and

zoosporangia (Murakami et al., 2002b; Myers and Campbell, 1985; Niwa et al., 2008; Webster

and Dixon, 1991b). Therefore, it seems likely that bait crops, which stimulate the germination of

resting spores, could have a negative effect when combined with liming to inhibit spore

germination. A study was conducted to investigate if the effects of liming with calcium

hydroxide interacted with those of a spring wheat for reduction of spores in soil. Spore

concentration was reduced with increasing rate of lime and there was no statistical interaction

with the effect of the wheat crop. Therefore, growers can employ both management strategies

and expect a reduction in resting spores.

There was considerable variability in the spore concentrations estimates from qPCR, even

though a competitive internal control was used to account for the effects of inhibition (Deora et

al, 2015). In several of the studies, estimates of pre-plant concentrations of resting spores were

much higher than the targeted levels, but one study was much lower than the target. Extracting

DNA from soil samples may have contributed to the variability, because only a very small

amount of soil is actually assessed for each extraction. Even with careful mixing of soil, resting

spores of P. brassicae may be clumped and unevenly distributed. A recent study found that

droplet digital PCR (ddPCR) had a higher accuracy and was more effective in diverse soil types

107

at quantifying P. brassicae spores compared to qPCR (Wen et al., 2020). Further, estimates on

ddPCR was less severely affected relative to qPCR when there were inhibitors in the soil.

Droplet digital PCR is recommended to be used at spore concentrations from 102 to 107 spores g-1

(Wen et al., 2020). Future studies should therefore consider using ddPCR because of its potential

for more accurate P. brassicae quantification.

Additional research is needed to investigate the effect of field crops and the interaction

between crop and liming on concentrations of clubroot resting spores under field conditions.

Longer duration field trials could investigate the effect of root growth on reduction of resting

spores in soil. The crops would be able to develop extensive root systems which produce root

exudates to stimulate the germination of resting spores. In addition, a bioassay to grow a

susceptible host after growing field crops or growing a field crop and liming could determine the

ability of these management strategies to suppress resting spores to sufficiently low levels to

reduce the development of clubroot symptoms. Evaluating different initial spore concentrations

to determine a threshold at which these strategies would be effective in reducing clubroot

severity would also be useful. Studies to investigate the mechanism by which wheat reduces

resting spore levels are also warranted. In addition, studies to evaluate the development of

primary plasmodia in root hairs of bait crops grown in limed soil would help to gain insight into

the effect of both management strategies on root hair infection. Determining the mode of action

of these strategies on the root hair infection stage would confirm the absence of a negative

interaction and would provide useful information on optimal timing of using these strategies.

This research has contributed information that is directly relevant to growers in Ontario.

Several CR canola cultivars were resistant to the prevalent clubroot pathotypes in Ontario,

108

pathotypes 2 and 6. This resistance can be used against the predominant pathotypes in Ontario.

Most brassica vegetable cultivars marketed as resistant were resistant to pathotypes 2 and 6, with

the exception of cabbage cv. Lodero and broccoli cv. Emerald Jewel, which were resistant to

pathotype 6 but susceptible to pathotype 2. Also, spring wheat reduced concentrations of resting

spores in soil compared to fallow (no-plant) soil with no negative interaction with liming to

increase the pH. This result indicated that these two strategies can be used together to manage

clubroot, but field studies to validate the result are still required.

109

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APPENDICES

Appendix 1: Supplemental tables and figures, Chapter Two

Table A1.1 Clubroot incidence (CI, %), disease severity index (DSI), and fresh dry weight of

clubroot susceptible and resistant canola cultivars grown at the Muck Crops Research Station,

ON, in 2018 (n = 6).

Cultivar Block Incidence

(%)

DSI (0–100) Fresh weight

(g)

Dry weight

(g)

L241C 1 0 0 106.4 14.52

L241C 2 6 2 112.4 15.37

L241C 3 0 0 90.4 13.22

L241C 4 22 7.333333 93.4 15.43

L241C 5 0 0 110.4 13.73

L241C 6 0 0 138.4 17.32

L255PC 1 0 0 133.4 15.77

L255PC 2 0 0 118.4 16.13

L255PC 3 2 0.666667 96.4 14.5

L255PC 4 8 2.666667 168.4 16.84

L255PC 5 0 0 114.4 14.12

L255PC 6 2 0.666667 149.4 15.38

L135C 1 0 0 118.4 13.69

L135C 2 0 0 127.4 15.43

L135C 3 0 0 82.4 12.72

L135C 4 12 4 107.4 12.93

L135C 5 0 0 171.4 19.23

L135C 6 0 0 40.4 10.6

L233P 1 100 100 50.4 12.74

L233P 2 100 100 54.4 11.44

L233P 3 100 99.33333 53.4 13.53

L233P 4 98 92.66667 48.4 11.75

L233P 5 100 99.33333 42.4 10.94

L233P 6 100 97.33333 30.4 10.36

L252 1 100 98.66667 73.4 14.27

L252 2 100 100 72.4 12.8

L252 3 100 100 70.4 15.44

L252 4 97.87234 97.16312 68.4 12.33

L252 5 100 100 43.4 10.33

L252 6 100 97.16312 34.4 8.99

ACS N39 1 100 98.66667 41.4 12.24

ACS N39 2 100 99.33333 48.4 12.21

ACS N39 3 100 100 58.4 12.49

126

ACS N39 4 100 96.66667 61.4 14.22

ACS N39 5 98 96.66667 45.4 11.52

ACS N39 6 100 98 36.4 10.72

InVigor 5030 1 100 100 61.4 14.02

InVigor 5030 2 100 100 50.4 12.23

InVigor 5030 3 100 98.66667 48.4 12.44

InVigor 5030 4 95.91837 78.23129 57.4 11.39

InVigor 5030 5 100 99.33333 30.4 10.05

InVigor 5030 6 100 91.47287 20.4 8.39

Mei Qing Choi 1 94 92 46.4 5.77

Mei Qing Choi 2 98 94.66667 28.4 7.04

Mei Qing Choi 3 90 78 22.4 7.63

Mei Qing Choi 4 96 81.33333 10.4 7.7

Mei Qing Choi 5 90 79.33333 24.4 7.35

Mei Qing Choi 6 83.78378 69.36937 19.4 8.28

Table A1.2 Clubroot incidence (CI, %), disease severity index (DSI), and fresh dry weight of

clubroot susceptible and resistant canola cultivars grown at the Muck Crops Research Station,

ON, in 2019 (n = 6).

Cultivar Block Incidence (%) DSI (0–100) Fresh weight

(g)

Dry weight

(g)

L2421C 1 0 0 134 10.92

L2421C 2 2 0.666667 130 10.81

L2421C 3 2 0.666667 44 5.61

L2421C 4 0 0 61 4.98

L2421C 5 0 0 100 9.97

L2421C 6 0 0 31 3.93

L255PC 1 62 20.66667 132 12.44

L255PC 2 2 0.666667 164 12.64

L255PC 3 4 1.333333 92 10.26

L255PC 4 38 12.66667 123 11.83

L255PC 5 14 4.666667 118 11.65

L255PC 6 4 1.333333 107 11.52

L135C 1 6 2 119 9.73

L135C 2 0 0 136 11.26

L135C 3 0 0 49 6.98

L135C 4 0 0 84 8.28

L135C 5 2 0.666667 112 11.05

L135C 6 0 0 75 7.96

L233P 1 100 100 26 3.12

L233P 2 98 60.66667 94 9.8

L233P 3 94 79.33333 63 5.84

127

L233P 4 100 98.66667 17 2.16

L233P 5 100 98 51 5.93

L233P 6 100 76.87075 60 8.88

L252 1 100 99.33333 32 3.65

L252 2 94 88 63 5.69

L252 3 30 13.33333 59 8.2

L252 4 2 0.666667 35 4.44

L252 5 100 98 143 13.68

L252 6 100 96.66667 22 3.02

L234PC 1 0 0 145 15.79

L234PC 2 0 0 133 14.02

L234PC 3 0 0 98 10.95

L234PC 4 0 0 92 11.26

L234PC 5 0 0 126 12.6

L234PC 6 0 0 58 7.81

ACS N39 1 100 99.04762 37 3.55

ACS N39 2 90.90909 83.83838 40 3.67

ACS N39 3 94 75.33333 62 8.37

ACS N39 4 17.5 7.5 23 3.07

ACS N39 5 91.66667 68.75 66 7.96

ACS N39 6 94 71.33333 45 6.57

InVigor 5030 1 100 98.66667 9 1.11

InVigor 5030 2 98 82 57 5.3

InVigor 5030 3 40 14 41 5.31

InVigor 5030 4 100 99.33333 9 1.19

InVigor 5030 5 98 76.66667 89 8.47

InVigor 5030 6 38 27.33333 45 3.9

Table A1.3 Clubroot incidence (CI, %), disease severity index (DSI), and fresh dry weight of

clubroot susceptible and resistant brassica vegetable cultivars grown at the Muck Crops Research

Station, ON, in 2018 (n = 6).

Cultivar Crop Block Incidence

(%)

DSI (0–100) Fresh

weight (g)

Dry weight

(g)

Bronco Cabbage 1 100 100 187 17.94

Bronco Cabbage 2 100 100 231 34.72

Bronco Cabbage 3 100 97.77778 436 41.06

Bronco Cabbage 4 100 100 196 21.12

Bronco Cabbage 5 100 100 113 10.14

Bronco Cabbage 6 100 100 348 22.94

Bejo Cabbage 1 0 0 970 58.4

Bejo Cabbage 2 0 0 1041 70.52

Bejo Cabbage 3 0 0 858 63.14

128

Bejo Cabbage 4 0 0 1080 74.24

Bejo Cabbage 5 0 0 1203 58.44

Bejo Cabbage 6 0 0 96 43.2

Lodero Cabbage 1 100 100 139 13.62

Lodero Cabbage 2 73.33333 65.55556 475 27.58

Lodero Cabbage 3 100 100 224 21.7

Lodero Cabbage 4 90 61.11111 450 26

Lodero Cabbage 5 100 94.44444 230 16.96

Lodero Cabbage 6 100 100 107 17.9

Emerald

Jewel Broccoli 1 100 100 268 25.2

Emerald

Jewel Broccoli 2 96.66667 96.66667 288 38.32

Emerald

Jewel Broccoli 3 100 100 263 26.82

Emerald

Jewel Broccoli 4 86.66667 33.33333 681 61

Emerald

Jewel Broccoli 5 100 90.32258 323 34.62

Emerald

Jewel Broccoli 6 100 98.85057 253 14.94

Asteroid Broccoli 1 100 100 106 13.44

Asteroid Broccoli 2 100 100 163 9.58

Asteroid Broccoli 3 100 100 148 15.66

Asteroid Broccoli 4 100 100 214 22.82

Asteroid Broccoli 5 100 100 213 14.26

Asteroid Broccoli 6 100 100 964 13.26

Tekila Cabbage 1 0 0 734 63.22

Tekila Cabbage 2 0 0 631 37.18

Tekila Cabbage 3 0 0 508 34.16

Tekila Cabbage 4 0 0 628 34.14

Tekila Cabbage 5 0 0 752 27.4

Tekila Cabbage 6 0 0 503 68.06

Clarify Cauliflower 1 0 0 453 43.56

Clarify Cauliflower 2 0 0 641 46.04

Clarify Cauliflower 3 0 0 756 71.06

Clarify Cauliflower 4 3.333333 3.333333 655 65.78

Clarify Cauliflower 5 0 0 268 51.24

Clarify Cauliflower 6 0 0 98 49.3

Fremont Cauliflower 1 93.33333 93.33333 20 4.4

Fremont Cauliflower 2 100 97.77778 239 27.74

Fremont Cauliflower 3 100 100 208 24.4

Fremont Cauliflower 4 100 100 366 40.64

129

Fremont Cauliflower 5 100 100 52 12.04

Fremont Cauliflower 6 100 97.33333 158 39.52

Stokes Rutabaga 1 90 84.44444 12 1.78

Stokes Rutabaga 2 93.33333 84.44444 60 5.58

Stokes Rutabaga 3 66.66667 42.22222 30 4.88

Stokes Rutabaga 4 0 0 55 5.06

Stokes Rutabaga 5 56.66667 43.33333 42 3.98

Stokes Rutabaga 6 78.26087 63.76812 16 2.06

Wisconsin Rutabaga 1 100 88 36 5.24

Wisconsin Rutabaga 2

Wisconsin Rutabaga 3 100 100 38 6.16

Wisconsin Rutabaga 4 0 0 78 8.3

Wisconsin Rutabaga 5 50 33.33333 15 2.32

Wisconsin Rutabaga 6 100 100 26.66667 3.433333

Yuki

Napa

cabbage 1 0 0 372 14.56

Yuki

Napa

cabbage 2 0 0 291 22.725

Yuki

Napa

cabbage 3 3.333333 3.333333 252 12.46

Yuki

Napa

cabbage 4 3.333333 1.111111 335 13.44

Yuki

Napa

cabbage 5 6.666667 2.222222 344 19

Yuki

Napa

cabbage 6 0 0 215 9.92

Blue

Napa

cabbage 1 96.66667 96.66667 54 7.08

Blue

Napa

cabbage 2 100 100 139 9.18

Blue

Napa

cabbage 3 100 100 144 11.16

Blue

Napa

cabbage 4 100 98.76543 191 16.12

Blue

Napa

cabbage 5 100 100 258 8.88

Blue

Napa

cabbage 6 96.66667 95.55556 253 20.7

Mei Qing

Choi

Shanghai

pak choi 1 96.66667 96.66667 63 3.96

Mei Qing

Choi

Shanghai

pak choi 2 100 95.55556 130 4.8

Mei Qing

Choi

Shanghai

pak choi 3 96.2963 93.82716 128 9.7

130

Mei Qing

Choi

Shanghai

pak choi 4 100 100 156 7.8

Mei Qing

Choi

Shanghai

pak choi 5 96.66667 94.44444 40 2.92

Mei Qing

Choi

Shanghai

pak choi 6 74.19355 69.89247 324 6.1

Table A1.3 Clubroot incidence (CI, %), disease severity index (DSI), and fresh dry weight of

clubroot susceptible and resistant brassica vegetable cultivars grown at the Muck Crops Research

Station, ON, in 2018 (n = 6).

Cultivar Crop Block Incidence

(%)

DSI (0–100) Fresh

weight (g)

Dry weight

(g)

Bejo 2962 Cabbage 1 0 0 1250 45.5

Bejo 2962 Cabbage 2 0 0 1187 42

Bejo 2962 Cabbage 3 0 0 968 36.5

Bejo 2962 Cabbage 4 0 0 673 30

Bejo 2962 Cabbage 5 0 0 1233 49

Bejo 2962 Cabbage 6 0 0 1074 42

Tekila Cabbage 1 0 0 626 25

Tekila Cabbage 2 0 0 878 36.5

Tekila Cabbage 3 0 0 737 32

Tekila Cabbage 4 0 0 489 25

Tekila Cabbage 5 0 0 482 21.5

Tekila Cabbage 6 0 0 . 25.5

Lodero Cabbage 1 6.666667 2.222222 610 20.5

Lodero Cabbage 2 0 0 548 22

Lodero Cabbage 3 3.333333 1.111111 620 23

Lodero Cabbage 4 0 0 437 18.5

Lodero Cabbage 5 20 11.11111 448 19.5

Lodero Cabbage 6 43.33333 17.77778 438 21.5

Bronco Cabbage 1 73.33333 34.44444 976 32.5

Bronco Cabbage 2 43.33333 24.44444 732 34.5

Bronco Cabbage 3 6.666667 3.333333 566 24

Bronco Cabbage 4 3.333333 2.222222 490 21

Bronco Cabbage 5 70.96774 52.68817 628 18.5

Bronco Cabbage 6 90 45.55556 826 30.4

Emerald

Jewel Broccoli 1 70 30 856 31

Emerald

Jewel Broccoli 2 13.33333 4.444444 837 39.5

Emerald

Jewel Broccoli 3 0 0 526 28

Emerald Broccoli 4 0 0 298 16

131

Jewel

Emerald

Jewel Broccoli 5 0 0 . 23

Emerald

Jewel Broccoli 6 43.33333 18.88889 754 36

Asteroid Broccoli 1 60 33.33333 683 34.5

Asteroid Broccoli 2 19.35484 11.82796 352 21

Asteroid Broccoli 3 40 22.22222 748 33.5

Asteroid Broccoli 4 53.125 36.45833 627 21

Asteroid Broccoli 5 36.66667 26.66667 768 32

Asteroid Broccoli 6 80 53.33333 758 28

Clarify Cauliflower 1 6.666667 3.333333 552 27

Clarify Cauliflower 2 0 0 557 26.5

Clarify Cauliflower 3 0 0 916 27.5

Clarify Cauliflower 4 0 0 624 30

Clarify Cauliflower 5 0 0 790 43

Clarify Cauliflower 6 0 0 802 36.5

Fremont Cauliflower 1 70.37037 29.62963 510 29.5

Fremont Cauliflower 2 36.66667 18.88889 283 19

Fremont Cauliflower 3 33.33333 18.88889 751 27

Fremont Cauliflower 4 20.68966 11.49425 474 23.5

Fremont Cauliflower 5 40 25.55556 523 31

Fremont Cauliflower 6 70 33.33333 752 38.5

Stokes Rutabaga 1 26.08696 8.695652 255 13.63

Stokes Rutabaga 2 0 0 212 15.65

Stokes Rutabaga 3 0 0 387 24.48

Stokes Rutabaga 4 23.80952 7.936508 535 22.28

Stokes Rutabaga 5 0 0 290 14.42

Stokes Rutabaga 6 . . . .

Wisconsin Rutabaga 1 11.53846 3.846154 316 16.17

Wisconsin Rutabaga 2 24.13793 8.045977 177 9.18

Wisconsin Rutabaga 3 16.66667 5.555556 359 15.55

Wisconsin Rutabaga 4 7.692308 2.564103 532 25.65

Wisconsin Rutabaga 5 0 0 199 10.28

Wisconsin Rutabaga 6 17.3913 11.5942 733 20.05

Yuki

Napa

cabbage 1 0 0 181 5.5

Yuki

Napa

cabbage 2 0 0 131 3.5

Yuki

Napa

cabbage 3 0 0 138 3.5

Yuki

Napa

cabbage 4 0 0 242 5.5

132

Yuki

Napa

cabbage 5 0 0 269 6.5

Yuki

Napa

cabbage 6 0 0 226 5

Blue

Napa

cabbage 1 96.42857 47.61905 295 12

Blue

Napa

cabbage 2 85.71429 60.31746 901 23

Blue

Napa

cabbage 3 88.88889 72.83951 736 11.5

Blue

Napa

cabbage 4 36.84211 15.78947 311 8.5

Blue

Napa

cabbage 5 57.14286 41.66667 184 7

Blue

Napa

cabbage 6 96.15385 91.02564 477 17

Mei Qing

Choi

Shanghai

pak choi 1 10 6.666667 54 2

Mei Qing

Choi

Shanghai

pak choi 2 6.666667 2.222222 136 3

Mei Qing

Choi

Shanghai

pak choi 3 0 0 74 2

Mei Qing

Choi

Shanghai

pak choi 4 23.33333 16.66667 128 3.5

Mei Qing

Choi

Shanghai

pak choi 5 0 0 69 1

Mei Qing

Choi

Shanghai

pak choi 6 51.6129 37.63441 145 2.5

Table A1.4 Clubroot incidence (CI, %), disease severity index (DSI), and fresh dry weight of

clubroot susceptible and resistant brassica vegetable cultivars grown at the Muck Crops Research

Station, ON, in 2019 (n = 6).

Cultivar Crop Block Incidence

(%)

DSI (0–100) Fresh

weight (g)

Dry weight

(g)

Bejo 2962 Cabbage 1 0 0 1250 45.5

Bejo 2962 Cabbage 2 0 0 1187 42

Bejo 2962 Cabbage 3 0 0 968 36.5

Bejo 2962 Cabbage 4 0 0 673 30

Bejo 2962 Cabbage 5 0 0 1233 49

Bejo 2962 Cabbage 6 0 0 1074 42

Tekila Cabbage 1 0 0 626 25

Tekila Cabbage 2 0 0 878 36.5

Tekila Cabbage 3 0 0 737 32

Tekila Cabbage 4 0 0 489 25

133

Tekila Cabbage 5 0 0 482 21.5

Tekila Cabbage 6 0 0 . 25.5

Lodero Cabbage 1 6.666667 2.222222 610 20.5

Lodero Cabbage 2 0 0 548 22

Lodero Cabbage 3 3.333333 1.111111 620 23

Lodero Cabbage 4 0 0 437 18.5

Lodero Cabbage 5 20 11.11111 448 19.5

Lodero Cabbage 6 43.33333 17.77778 438 21.5

Bronco Cabbage 1 73.33333 34.44444 976 32.5

Bronco Cabbage 2 43.33333 24.44444 732 34.5

Bronco Cabbage 3 6.666667 3.333333 566 24

Bronco Cabbage 4 3.333333 2.222222 490 21

Bronco Cabbage 5 70.96774 52.68817 628 18.5

Bronco Cabbage 6 90 45.55556 826 30.4

Emerald

Jewel Broccoli 1 70 30 856 31

Emerald

Jewel Broccoli 2 13.33333 4.444444 837 39.5

Emerald

Jewel Broccoli 3 0 0 526 28

Emerald

Jewel Broccoli 4 0 0 298 16

Emerald

Jewel Broccoli 5 0 0 . 23

Emerald

Jewel Broccoli 6 43.33333 18.88889 754 36

Asteroid Broccoli 1 60 33.33333 683 34.5

Asteroid Broccoli 2 19.35484 11.82796 352 21

Asteroid Broccoli 3 40 22.22222 748 33.5

Asteroid Broccoli 4 53.125 36.45833 627 21

Asteroid Broccoli 5 36.66667 26.66667 768 32

Asteroid Broccoli 6 80 53.33333 758 28

Clarify Cauliflower 1 6.666667 3.333333 552 27

Clarify Cauliflower 2 0 0 557 26.5

Clarify Cauliflower 3 0 0 916 27.5

Clarify Cauliflower 4 0 0 624 30

Clarify Cauliflower 5 0 0 790 43

Clarify Cauliflower 6 0 0 802 36.5

Fremont Cauliflower 1 70.37037 29.62963 510 29.5

Fremont Cauliflower 2 36.66667 18.88889 283 19

Fremont Cauliflower 3 33.33333 18.88889 751 27

Fremont Cauliflower 4 20.68966 11.49425 474 23.5

Fremont Cauliflower 5 40 25.55556 523 31

134

Fremont Cauliflower 6 70 33.33333 752 38.5

Stokes Rutabaga 1 26.08696 8.695652 255 13.63

Stokes Rutabaga 2 0 0 212 15.65

Stokes Rutabaga 3 0 0 387 24.48

Stokes Rutabaga 4 23.80952 7.936508 535 22.28

Stokes Rutabaga 5 0 0 290 14.42

Stokes Rutabaga 6 . . . .

Wisconsin Rutabaga 1 11.53846 3.846154 316 16.17

Wisconsin Rutabaga 2 24.13793 8.045977 177 9.18

Wisconsin Rutabaga 3 16.66667 5.555556 359 15.55

Wisconsin Rutabaga 4 7.692308 2.564103 532 25.65

Wisconsin Rutabaga 5 0 0 199 10.28

Wisconsin Rutabaga 6 17.3913 11.5942 733 20.05

Yuki

Napa

cabbage 1 0 0 181 5.5

Yuki

Napa

cabbage 2 0 0 131 3.5

Yuki

Napa

cabbage 3 0 0 138 3.5

Yuki

Napa

cabbage 4 0 0 242 5.5

Yuki

Napa

cabbage 5 0 0 269 6.5

Yuki

Napa

cabbage 6 0 0 226 5

Blue

Napa

cabbage 1 96.42857 47.61905 295 12

Blue

Napa

cabbage 2 85.71429 60.31746 901 23

Blue

Napa

cabbage 3 88.88889 72.83951 736 11.5

Blue

Napa

cabbage 4 36.84211 15.78947 311 8.5

Blue

Napa

cabbage 5 57.14286 41.66667 184 7

Blue

Napa

cabbage 6 96.15385 91.02564 477 17

Mei Qing

Choi

Shanghai

pak choy 1 10 6.666667 54 2

Mei Qing

Choi

Shanghai

pak choy 2 6.666667 2.222222 136 3

Mei Qing

Choi

Shanghai

pak choy 3 0 0 74 2

Mei Qing Shanghai 4 23.33333 16.66667 128 3.5

135

Choi pak choy

Mei Qing

Choi

Shanghai

pak choy 5 0 0 69 1

Mei Qing

Choi

Shanghai

pak choy 6 51.6129 37.63441 145 2.5

Table A1.5 Clubroot incidence (CI, %) and disease severity index (DSI) of canola cultivars

inoculated with pathotype 2 of Plasmodiophora brassicae collected from the Muck Crops

Research Station in 2017 in a growth room study (n = 4).

Cultivar Block Incidence (%) DSI (0–100)

L2421C 1 0 0

L2421C 2 0 0

L2421C 3 0 0

L2421C 4 0 0

L255PC 1 0 0

L255PC 2 0 0

L255PC 3 0 0

L255PC 4 0 0

L135C 1 0 0

L135C 2 0 0

L135C 3 0 0

L135C 4 0 0

L233P 1 100 94.44444

L233P 2 100 91.66667

L233P 3 100 97.22222

L233P 4 100 100

L252 1 100 91.66667

L252 2 100 97.22222

L252 3 100 91.66667

L252 4 100 100

ACS N39 1 100 94.44444

ACS N39 2 100 100

ACS N39 3 100 94.44444

ACS N39 4 100 100

InVigor 5030 1 100 100

InVigor 5030 2 100 94.44444

InVigor 5030 3 100 100

InVigor 5030 4 100 100

L2421C 1 0 0

L2421C 2 0 0

L2421C 3 0 0

L2421C 4 0 0

136

L255PC 1 0 0

L255PC 2 0 0

L255PC 3 0 0

L255PC 4 0 0

L135C 1 0 0

L135C 2 0 0

L135C 3 0 0

L135C 4 0 0

L233P 1 100 88.88889

L233P 2 100 100

L233P 3 100 91.66667

L233P 4 91.66667 86.11111

L252 1 100 83.33333

L252 2 100 91.66667

L252 3 100 97.22222

L252 4 83.33333 69.44444

ACS N39 1 100 77.77778

ACS N39 2 100 88.88889

ACS N39 3 100 86.11111

ACS N39 4 83.33333 80.55556

InVigor 5030 1 100 86.11111

InVigor 5030 2 100 86.11111

InVigor 5030 3 100 86.11111

InVigor 5030 4 100 91.66667

Mei Qing Choi 1 100 100

Mei Qing Choi 2 100 94.44444

Mei Qing Choi 3 100 94.44444

Mei Qing Choi 4 100 94.44444

Table A1.6 Clubroot incidence (CI, %) and disease severity index (DSI) of canola cultivars

inoculated with pathotype 2 of Plasmodiophora brassicae collected from a commercial field in

Bruce County, ON (mineral soil) in a growth room study (n = 4).

Cultivar Block Incidence (%) DSI (0 – 100)

L2421C 1 0 0

L2421C 2 0 0

L2421C 3 0 0

L2421C 4 0 0

L255PC 1 0 0

L255PC 2 0 0

L255PC 3 0 0

L255PC 4 0 0

L135C 1 0 0

137

L135C 2 0 0

L135C 3 0 0

L135C 4 0 0

L233P 1 100 94.44444

L233P 2 91.66667 91.66667

L233P 3 100 97.22222

L233P 4 100 100

L252 1 100 91.66667

L252 2 100 97.22222

L252 3 100 91.66667

L252 4 100 100

ACS N39 1 100 94.44444

ACS N39 2 100 100

ACS N39 3 100 94.44444

ACS N39 4 100 100

InVigor 5030 1 100 100

InVigor 5030 2 100 94.44444

InVigor 5030 3 100 100

InVigor 5030 4 100 100

ACS N39 non-

inoculated

1 0 0

ACS N39 non-

inoculated

2 0 0

ACS N39 non-

inoculated

3 0 0

ACS N39 non-

inoculated

4 0 0

Table A1.7 Clubroot incidence (CI, %) and disease severity index (DSI) of canola cultivars

inoculated with pathotype 6 of Plasmodiophora brassicae in the 1st repetition of a growth room

study (n = 4).

Cultivar Block Incidence (%) DSI (0–100)

L2421C 1 0 0

L2421C 2 0 0

L2421C 3 0 0

L2421C 4 0 0

L255PC 1 0 0

L255PC 2 0 0

L255PC 3 0 0

L255PC 4 0 0

L135C 1 0 0

L135C 2 0 0

L135C 3 0 0

138

L135C 4 0 0

L233P 1 0 0

L233P 2 0 0

L233P 3 0 0

L233P 4 0 0

L252 1 0 0

L252 2 0 0

L252 3 0 0

L252 4 0 0

ACS N39 1 76.92308 30.76923

ACS N39 2 100 33.33333

ACS N39 3 100 36.11111

ACS N39 4 100 36.11111

InVigor 5030 1 0 0

InVigor 5031 2 0 0

InVigor 5032 3 0 0

InVigor 5033 4 0 0

Mei Qing Choi 1 100 100

Mei Qing Choi 2 100 100

Mei Qing Choi 3 100 100

Mei Qing Choi 4 100 100

L234PC 1 0 0

L234PC 2 0 0

L234PC 3 0 0

L234PC 4 0 0

45H29 1 0 0

45H29 2 16.66667 13.88889

45H29 3 8.333333 2.777778

45H29 4 16.66667 13.88889

Mei Qing Choi non-

inoculated

1 0 0

Mei Qing Choi non-

inoculated

2 8.333333 5.555556

Mei Qing Choi non-

inoculated

3 0 0

Mei Qing Choi non-

inoculated

4 8.333333 2.777778

Table A1.8 Clubroot incidence (CI, %) and disease severity index (DSI) of canola cultivars

inoculated with pathotype 6 of Plasmodiophora brassicae in the 2nd repetition of a growth room

study (n = 4).

Cultivar Block Incidence (%) DSI (0–100)

L2421C 1 0 0

139

L2421C 2 0 0

L2421C 3 0 0

L2421C 4 0 0

L255PC 1 0 0

L255PC 2 0 0

L255PC 3 0 0

L255PC 4 0 0

L135C 1 0 0

L135C 2 0 0

L135C 3 0 0

L135C 4 0 0

L233P 1 0 0

L233P 2 33.33333 7

L233P 3 16.66667 9.333333

L233P 4 16.66667 3

L252 1 8.333333 2

L252 2 8.333333 2

L252 3 16.66667 3

L252 4 0 0

ACS N39 1 100 25.33333

ACS N39 2 100 35

ACS N39 3 100 22.33333

ACS N39 4 100 15

InVigor 5030 1 25 10.33333

InVigor 5031 2 8.333333 8.333333

InVigor 5032 3 8.333333 1

InVigor 5033 4 8.333333 2

Mei Qing Choi 1 100 100

Mei Qing Choi 2 100 100

Mei Qing Choi 3 100 100

Mei Qing Choi 4 100 100

L234PC 1 0 0

L234PC 2 0 0

L234PC 3 0 0

L234PC 4 0 0

45H29 1 8.333333 2

45H29 2 0 0

45H29 3 0 0

45H29 4 0 0

Mei Qing Choi non-

inoculated

1 0 0

Mei Qing Choi non- 2 0 0

140

inoculated

Mei Qing Choi non-

inoculated

3 0 0

Mei Qing Choi non-

inoculated

4 0 0

Table A1.9 Clubroot incidence (CI, %) and disease severity index (DSI) of brassica vegetables

cultivars inoculated with pathotype 2 of Plasmodiophora brassicae in a growth room study (n =

4).

Cultivar Crop Block Incidence (%) DSI (0–100)

Bejo 2962 Cabbage 1 0 0

Bejo 2962 Cabbage 2 0 0

Bejo 2962 Cabbage 3 0 0

Bejo 2962 Cabbage 4 0 0

Tekila Cabbage 1 0 0

Tekila Cabbage 2 0 0

Tekila Cabbage 3 0 0

Tekila Cabbage 4 0 0

Lodero Cabbage 1 100 96.9697

Lodero Cabbage 2 100 100

Lodero Cabbage 3 100 100

Lodero Cabbage 4 100 100

Bronco Cabbage 1 100 100

Bronco Cabbage 2 100 100

Bronco Cabbage 3 100 100

Bronco Cabbage 4 100 100

Emerald Jewel Broccoli 1 100 100

Emerald Jewel Broccoli 2 100 100

Emerald Jewel Broccoli 3 100 100

Emerald Jewel Broccoli 4 100 100

Asteroid Broccoli 1 100 100

Asteroid Broccoli 2 100 100

Asteroid Broccoli 3 100 100

Asteroid Broccoli 4 100 100

Clarify Cauliflower 1 0 0

Clarify Cauliflower 2 0 0

Clarify Cauliflower 3 0 0

Clarify Cauliflower 4 0 0

Fremont Cauliflower 1 100 100

Fremont Cauliflower 2 100 100

Fremont Cauliflower 3 100 100

Fremont Cauliflower 4 100 100

141

Stokes Rutabaga 1 100 100

Stokes Rutabaga 2 100 100

Stokes Rutabaga 3 100 100

Stokes Rutabaga 4 100 100

Wisconsin Rutabaga 1 100 100

Wisconsin Rutabaga 2 100 100

Wisconsin Rutabaga 3 100 100

Wisconsin Rutabaga 4 0 0

Yuki Napa cabbage 1 8.333333 8.333333

Yuki Napa cabbage 2 0 0

Yuki Napa cabbage 3 9.090909 9.090909

Yuki Napa cabbage 4 0 0

Blues Napa cabbage 1 100 100

Blues Napa cabbage 2 100 100

Blues Napa cabbage 3 100 100

Blues Napa cabbage 4 100 100

Mei Qing Choi Shanghai pak

choi

1 100 100

Mei Qing Choi Shanghai pak

choi

2 100 100

Mei Qing Choi Shanghai pak

choi

3 100 100

Mei Qing Choi Shanghai pak

choi

4 100 100

Mei Qing Choi non-

inoculated

Shanghai pak

choi

1 0 0

Mei Qing Choi non-

inoculated

Shanghai pak

choi

2 0 0

Mei Qing Choi non-

inoculated

Shanghai pak

choi

3 0 0

Mei Qing Choi non-

inoculated

Shanghai pak

choi

4 0 0

Table A1.10 Clubroot incidence (CI, %) and disease severity index (DSI) of brassica vegetable

cultivars inoculated with pathotype 6 of Plasmodiophora brassicae in the 1st repetition of a

growth room study (n = 4).

Cultivar Crop Incidence (%) DSI (0 - 100)

Bejo 2962 Cabbage 0 0

Bejo 2962 Cabbage 0 0

Bejo 2962 Cabbage 0 0

Bejo 2962 Cabbage 0 0

Tekila Cabbage 0 0

Tekila Cabbage 0 0

142

Tekila Cabbage 0 0

Tekila Cabbage 0 0

Lodero Cabbage 0 0

Lodero Cabbage 0 0

Lodero Cabbage 25 8.333333

Lodero Cabbage 33.33333 11.11111

Bronco Cabbage 100 100

Bronco Cabbage 100 100

Bronco Cabbage 100 100

Bronco Cabbage 100 100

Emerald Jewel Broccoli 8.333333 5.555556

Emerald Jewel Broccoli 0 0

Emerald Jewel Broccoli 8.333333 2.777778

Emerald Jewel Broccoli 0 0

Asteroid Broccoli 100 100

Asteroid Broccoli 100 100

Asteroid Broccoli 100 100

Asteroid Broccoli 100 100

Clarify Cauliflower 0 0

Clarify Cauliflower 0 0

Clarify Cauliflower 0 0

Clarify Cauliflower 0 0

Fremont Cauliflower 100 100

Fremont Cauliflower 100 100

Fremont Cauliflower 100 100

Fremont Cauliflower 100 100

Stokes Rutabaga 0 0

Stokes Rutabaga 0 0

Stokes Rutabaga 0 0

Stokes Rutabaga 0 0

Wisconsin Rutabaga 0 0

Wisconsin Rutabaga 0 0

Wisconsin Rutabaga 16.66667 16.66667

Wisconsin Rutabaga 0 0

Yuki Napa cabbage 8.333333 8.333333

Yuki Napa cabbage 0 0

Yuki Napa cabbage 8.333333 8.333333

Yuki Napa cabbage 8.333333 8.333333

Blue Napa cabbage 100 100

Blue Napa cabbage 100 100

Blue Napa cabbage 100 100

Blue Napa cabbage 100 100

143

Mei Qing Choi Shanghai pak

choi

100 100

Mei Qing Choi Shanghai pak

choi

100 100

Mei Qing Choi Shanghai pak

choi

100 100

Mei Qing Choi Shanghai pak

choi

100 100

Mei Qing Choi non-

inoculated

Shanghai pak

choi

8.333333 8.333333

Mei Qing Choi non-

inoculated

Shanghai pak

choi

0 0

Mei Qing Choi non-

inoculated

Shanghai pak

choi

25 25

Mei Qing Choi non-

inoculated

Shanghai pak

choi

50 50

Table A1.11 Clubroot incidence (CI, %) and disease severity index (DSI) of brassica vegetable

cultivars inoculated with pathotype 6 of Plasmodiophora brassicae in the 2nd repetition of a

growth room study (n = 4).

Cultivar Crop Incidence (%) DSI (0–100)

Stokes Rutabaga 0 0

Stokes Rutabaga 0 0

Stokes Rutabaga 0 0

Stokes Rutabaga 0 0

Wisconsin Rutabaga 8.333333 8.333333

Wisconsin Rutabaga 20 20

Wisconsin Rutabaga 0 0

Wisconsin Rutabaga 10 10

Lodero Cabbage 0 0

Lodero Cabbage 0 0

Lodero Cabbage 0 0

Lodero Cabbage 0 0

Emerald Jewel Broccoli 0 0

Emerald Jewel Broccoli 0 0

Emerald Jewel Broccoli 0 0

Emerald Jewel Broccoli 0 0

Mei Qing Choi Shanghai pak

choi

83.33333 75

Mei Qing Choi Shanghai pak

choi

100 91.66667

Mei Qing Choi Shanghai pak

choi

100 100

Mei Qing Choi Shanghai pak 100 100

144

choi

Mei Qing Choi non-

inoculated

Shanghai pak

choi

0 0

Mei Qing Choi non-

inoculated

Shanghai pak

choi

0 0

Mei Qing Choi non-

inoculated

Shanghai pak

choi

0 0

Mei Qing Choi non-

inoculated

Shanghai pak

choi

0 0

Bejo 2962 Cabbage 0 0

Bejo 2962 Cabbage 0 0

Bejo 2962 Cabbage 0 0

Bejo 2962 Cabbage 0 0

Tekila Cabbage 0 0

Tekila Cabbage 0 0

Tekila Cabbage 0 0

Tekila Cabbage 0 0

Bronco Cabbage 91.66667 91.66667

Bronco Cabbage 100 94.44444

Bronco Cabbage 100 100

Bronco Cabbage 100 100

Asteroid Broccoli 100 100

Asteroid Broccoli 100 100

Asteroid Broccoli 100 100

Asteroid Broccoli 100 100

Clarify Cauliflower 0 0

Clarify Cauliflower 0 0

Clarify Cauliflower 0 0

Clarify Cauliflower 0 0

Fremont Cauliflower 100 100

Fremont Cauliflower 100 100

Fremont Cauliflower 100 100

Fremont Cauliflower 100 100

Yuki Napa cabbage 8.333333 8.333333

Yuki Napa cabbage 0 0

Yuki Napa cabbage 0 0

Yuki Napa cabbage 8.333333 8.333333

Blue Napa cabbage 100 100

Blue Napa cabbage 100 100

Blue Napa cabbage 100 100

Blue Napa cabbage 100 100

145

146

Appendix 2: Supplemental tables and figures, Chapter Three

Table A2.1 Correlation between field/cover crop root dry weight and Plasmodiophora brassicae

resting spore concentrations in soil after 8 weeks of growth (r) in Run 1 (n=6).

Crop Resting spore concentration (spores g-1)

Correlation coefficient (r)

Barley -0.84 ns1

Perennial ryegrass -0.76 ns

Field pea -0.40 ns

Wheat 0.37 ns

Total -0.06 ns 1ns = significant.

Figure A2.1 The effect of three rates of lime (calcium hydroxide, Ca(OH)2) on the

concentration of Plasmodiophora brassicae resting spores in soil after growing pak choi

for 6 weeks (barley study). Resting spore concentrations were analyzed based on a

lognormal distribution and are presented as back transformed least square means. Capped

lines represent ± standard error. The line is linear regression based on lognormal

distribution.

0

20000000

40000000

60000000

80000000

100000000

120000000

140000000

160000000

180000000

200000000

6.4 6.8 7.2

Res

ting s

pore

s g

-1so

il

Target soil pH

ln(spores) = 39.78 – 0.34(pH), Pseudo R2 = 0.15

147

Figure A2.2 The effect of three rates of lime (calcium hydroxide, Ca(OH)2) on the

concentration of Plasmodiophora brassicae resting spores in soil after growing pak choi

for 6 weeks (wheat study). Resting spore concentrations were analyzed based on a

lognormal distribution and are presented as back transformed least square means. Capped

lines represent ± standard error. The line is linear regression based on lognormal

distribution.

Table A2.2 Concentration of resting spores of Plasmodiophora brassicae in soil under

controlled conditions in Run 1 of the field crop study (n = 6).

Crop Block Treatment Subsample Resting spore

concentration1

(spores g-1)

Barley 1 Control 1 43247.46

Barley 1 Control 2 6155.846

Barley 1 PMA 3 49320.44

Barley 1 PMA 4 178867.4

Barley 2 Control 1 .

Barley 2 Control 2 .

Barley 2 PMA 3 .

Barley 2 PMA 4 .

Barley 3 Control 1 24623.45

Barley 3 Control 2 21326.09

Barley 3 PMA 3 .

Barley 3 PMA 4 .

Barley 4 Control 1 .

0

50000000

100000000

150000000

200000000

250000000

300000000

350000000

400000000

6.4 7.0 7.6

Res

ting s

pore

s g

-1so

il

Target soil pH

ln(spores) = -171.24 – 55.90(pH) – 4.09(pH)2, Pseudo R2 = 0.005

148

Barley 4 Control 2 .

Barley 4 PMA 3 .

Barley 4 PMA 4 .

Barley 5 Control 1 .

Barley 5 Control 2 20023.2

Barley 5 PMA 3 24478.11

Barley 5 PMA 4 22642.5

Barley 6 Control 1 168649.9

Barley 6 Control 2 .

Barley 6 PMA 3 174645.8

Barley 6 PMA 4 185950.7

No-plant 1 Control 1 20992.01

No-plant 1 Control 2 25684.63

No-plant 1 PMA 3 148173.3

No-plant 1 PMA 4 109166.9

No-plant 2 Control 1 .

No-plant 2 Control 2 .

No-plant 2 PMA 3 12236.36

No-plant 2 PMA 4 12637.82

No-plant 3 Control 1 35723

No-plant 3 Control 2 154672.9

No-plant 3 PMA 3 .

No-plant 3 PMA 4 28906.22

No-plant 4 Control 1 .

No-plant 4 Control 2 63343.13

No-plant 4 PMA 3 .

No-plant 4 PMA 4 .

No-plant 5 Control 1 47567.18

No-plant 5 Control 2 22728.86

No-plant 5 PMA 3 380886.4

No-plant 5 PMA 4 31520.69

No-plant 6 Control 1 86064.82

No-plant 6 Control 2 245461.5

No-plant 6 PMA 3 75778.54

No-plant 6 PMA 4 59964.04

Pea 1 Control 1 .

Pea 1 Control 2 11688.23

Pea 1 PMA 3 148173.3

Pea 1 PMA 4 .

Pea 2 Control 1 171000.2

Pea 2 Control 2 11440.01

Pea 2 PMA 3 126046.7

Pea 2 PMA 4 82406.05

Pea 3 Control 1 96918.16

149

Pea 3 Control 2 .

Pea 3 PMA 3 16732.61

Pea 3 PMA 4 42603.62

Pea 4 Control 1 170336.5

Pea 4 Control 2 .

Pea 4 PMA 3 58633.25

Pea 4 PMA 4 106160.8

Pea 5 Control 1 180609

Pea 5 Control 2 219931.2

Pea 5 PMA 3 36767.75

Pea 5 PMA 4 78351.25

Pea 6 Control 1 42636.85

Pea 6 Control 2 189236

Pea 6 PMA 3 46995.16

Pea 6 PMA 4 .

Ryegrass 1 Control 1 47333.63

Ryegrass 1 Control 2 .

Ryegrass 1 PMA 3 .

Ryegrass 1 PMA 4 .

Ryegrass 2 Control 1 .

Ryegrass 2 Control 2 .

Ryegrass 2 PMA 3 18048.77

Ryegrass 2 PMA 4 .

Ryegrass 3 Control 1 542714.8

Ryegrass 3 Control 2 123019.5

Ryegrass 3 PMA 3 7326.104

Ryegrass 3 PMA 4 .

Ryegrass 4 Control 1 16575.81

Ryegrass 4 Control 2 .

Ryegrass 4 PMA 3 .

Ryegrass 4 PMA 4 .

Ryegrass 5 Control 1 .

Ryegrass 5 Control 2 .

Ryegrass 5 PMA 3 10781.5

Ryegrass 5 PMA 4 .

Ryegrass 6 Control 1 574695.7

Ryegrass 6 Control 2 562225.3

Ryegrass 6 PMA 3 164855.1

Ryegrass 6 PMA 4 172531.2

Ryegrass 1 Control 1 239313.6

Ryegrass 1 Control 2 85420

Spring wheat 1 PMA 3 54720.04

Spring wheat 1 PMA 4 62758.69

Spring wheat 2 Control 1 207136.2

150

Spring wheat 2 Control 2 .

Spring wheat 2 PMA 3 .

Spring wheat 2 PMA 4 .

Spring wheat 3 Control 1 10135.69

Spring wheat 3 Control 2 .

Spring wheat 3 PMA 3 27770.61

Spring wheat 3 PMA 4 75314.48

Spring wheat 4 Control 1 .

Spring wheat 4 Control 2 14170.45

Spring wheat 4 PMA 3 176659.7

Spring wheat 4 PMA 4 .

Spring wheat 5 Control 1 .

Spring wheat 5 Control 2 .

Spring wheat 5 PMA 3 16546.47

Spring wheat 5 PMA 4 .

Spring wheat 6 Control 1 40858.05

Spring wheat 6 Control 2 63244.66

Spring wheat 6 PMA 3 .

Spring wheat 6 PMA 4 298168.2

Spring wheat 1 Control 1 92522.05

Spring wheat 1 Control 2 89078.41

Pak choi 1 PMA 3 45535091

Pak choi 1 PMA 4 36500409

Pak choi 2 Control 1 .

Pak choi 2 Control 2 .

Pak choi 2 PMA 3 13696114

Pak choi 2 PMA 4 5819005

Pak choi 3 Control 1 .

Pak choi 3 Control 2 .

Pak choi 3 PMA 3 .

Pak choi 3 PMA 4 .

Pak choi 4 Control 1 .

Pak choi 4 Control 2 59930115

Pak choi 4 PMA 3 .

Pak choi 4 PMA 4 .

Pak choi 5 Control 1 7896492

Pak choi 5 Control 2 6290831

Pak choi 5 PMA 3 .

Pak choi 5 PMA 4 .

Pak choi 6 Control 1 .

Pak choi 6 Control 2 .

Pak choi 6 PMA 3 .

Pak choi 6 PMA 4 .

Pak choi 1 Control 1 .

151

Pak choi 1 Control 2 .

Table A2.3 Concentration of resting spores of Plasmodiophora brassicae in soil under

controlled conditions in Run 2 of the field crop study ( (n = 6).

Crop Block Treatment Subsample Resting spore

concentration1

(spores g-1)

Barley 1 Control 1 311093.7

Barley 1 Control 2 .

Barley 1 PMA 3 924119.8

Barley 1 PMA 4 228690.6

Barley 2 Control 1 844270.8

Barley 2 Control 2 859290.6

Barley 2 PMA 3 946015

Barley 2 PMA 4 711606

Barley 3 Control 1 712068.4

Barley 3 Control 2 390734

Barley 3 PMA 3 944703.5

Barley 3 PMA 4 847640.4

Barley 4 Control 1 .

Barley 4 Control 2 94482.23

Barley 4 PMA 3 403977.7

Barley 4 PMA 4 154268.9

Barley 5 Control 1 168384.2

Barley 5 Control 2 36701.96

Barley 5 PMA 3 485131.9

Barley 5 PMA 4 444882.4

Barley 6 Control 1 339578.1

Barley 6 Control 2 555943.7

Barley 6 PMA 3 476817.3

Barley 6 PMA 4 128143

No-plant 1 Control 1 562791.1

No-plant 1 Control 2 537491.9

No-plant 1 PMA 3 568279.9

No-plant 1 PMA 4 803034.3

No-plant 2 Control 1 1070711

No-plant 2 Control 2 538374

No-plant 2 PMA 3 1032981

No-plant 2 PMA 4 614075.3

No-plant 3 Control 1 376915.6

No-plant 3 Control 2 395137.4

No-plant 3 PMA 3 675466.5

No-plant 3 PMA 4 528804.3

No-plant 4 Control 1 1170686

152

No-plant 4 Control 2 2035810

No-plant 4 PMA 3 715674.3

No-plant 4 PMA 4 937199.7

No-plant 5 Control 1 790886.2

No-plant 5 Control 2 535350.2

No-plant 5 PMA 3 806913.7

No-plant 5 PMA 4 275661

No-plant 6 Control 1 861869.3

No-plant 6 Control 2 777825.8

No-plant 6 PMA 3 688718.3

No-plant 6 PMA 4 587981.8

Pea 1 Control 1 15576.8

Pea 1 Control 2 25283.27

Pea 1 PMA 3 647125.1

Pea 1 PMA 4 35620.05

Pea 2 Control 1 662547.5

Pea 2 Control 2 862277.5

Pea 2 PMA 3 671638

Pea 2 PMA 4 759895.7

Pea 3 Control 1 352539.4

Pea 3 Control 2 120191

Pea 3 PMA 3 436379.4

Pea 3 PMA 4 405038.4

Pea 4 Control 1 809809.2

Pea 4 Control 2 .

Pea 4 PMA 3 501623.4

Pea 4 PMA 4 309086.6

Pea 5 Control 1 749446.4

Pea 5 Control 2 746944.6

Pea 5 PMA 3 322456.7

Pea 5 PMA 4 563650.4

Pea 6 Control 1 859186.7

Pea 6 Control 2 356266

Pea 6 PMA 3 242316.1

Pea 6 PMA 4 985769.9

Ryegrass 1 Control 1 284879.5

Ryegrass 1 Control 2 720545.6

Ryegrass 1 PMA 3 857094.5

Ryegrass 1 PMA 4 396229.8

Ryegrass 2 Control 1 1055357

Ryegrass 2 Control 2 753156.4

Ryegrass 2 PMA 3 373369.3

Ryegrass 2 PMA 4 1615775

Ryegrass 3 Control 1 629376.7

153

Ryegrass 3 Control 2 34600.22

Ryegrass 3 PMA 3 472318

Ryegrass 3 PMA 4 1001062

Ryegrass 4 Control 1 171765.3

Ryegrass 4 Control 2 68346.76

Ryegrass 4 PMA 3 245546.2

Ryegrass 4 PMA 4 93582.89

Ryegrass 5 Control 1 901670.4

Ryegrass 5 Control 2 387384.3

Ryegrass 5 PMA 3 33148.26

Ryegrass 5 PMA 4 357460.8

Ryegrass 6 Control 1 219872.4

Ryegrass 6 Control 2 187985.6

Ryegrass 6 PMA 3 204077.5

Ryegrass 6 PMA 4 153942.1

Soybean 1 Control 1 1605492

Soybean 1 Control 2 313418.8

Soybean 1 PMA 3 479956.2

Soybean 1 PMA 4 928071.8

Soybean 2 Control 1 1646370

Soybean 2 Control 2 967709.5

Soybean 2 PMA 3 401475

Soybean 2 PMA 4 1081240

Soybean 3 Control 1 778359.4

Soybean 3 Control 2 838261.6

Soybean 3 PMA 3 547268

Soybean 3 PMA 4 1051559

Soybean 4 Control 1 1299594

Soybean 4 Control 2 212192.8

Soybean 4 PMA 3 1618138

Soybean 4 PMA 4 655862.5

Soybean 5 Control 1 1912373

Soybean 5 Control 2 2601756

Soybean 5 PMA 3 1637512

Soybean 5 PMA 4 1052628

Soybean 6 Control 1 851057.3

Soybean 6 Control 2 609142.3

Soybean 6 PMA 3 640445.7

Soybean 6 PMA 4 674050.5

Spring wheat 1 Control 1 157696.8

Spring wheat 1 Control 2 747504.1

Spring wheat 1 PMA 3 224086

Spring wheat 1 PMA 4 496056.6

Spring wheat 2 Control 1 489835.1

154

Spring wheat 2 Control 2 223606.5

Spring wheat 2 PMA 3 1036704

Spring wheat 2 PMA 4 206232.2

Spring wheat 3 Control 1 26464.5

Spring wheat 3 Control 2 686948.3

Spring wheat 3 PMA 3 107550.3

Spring wheat 3 PMA 4 518342.2

Spring wheat 4 Control 1 219809.1

Spring wheat 4 Control 2 .

Spring wheat 4 PMA 3 .

Spring wheat 4 PMA 4 161722.6

Spring wheat 5 Control 1 926544.4

Spring wheat 5 Control 2 575282.9

Spring wheat 5 PMA 3 516632.5

Spring wheat 5 PMA 4 419837.9

Spring wheat 6 Control 1 406110.3

Spring wheat 6 Control 2 113186.9

Spring wheat 6 PMA 3 2023895

Spring wheat 6 PMA 4 205110.5

Pak choi 1 Control 1 31257410

Pak choi 1 Control 2 21970703

Pak choi 1 PMA 3 8269908

Pak choi 1 PMA 4 16781173

Pak choi 2 Control 1 44437354

Pak choi 2 Control 2 20472128

Pak choi 2 PMA 3 51437765

Pak choi 2 PMA 4 11522043

Pak choi 3 Control 1 .

Pak choi 3 Control 2 .

Pak choi 3 PMA 3 .

Pak choi 3 PMA 4 .

Pak choi 4 Control 1 9205735

Pak choi 4 Control 2 8223986

Pak choi 4 PMA 3 1483354

Pak choi 4 PMA 4 1783818

Pak choi 5 Control 1 17104571

Pak choi 5 Control 2 9139697

Pak choi 5 PMA 3 6490878

Pak choi 5 PMA 4 12858286

Pak choi 6 Control 1 30071465

Pak choi 6 Control 2 21594999

Pak choi 6 PMA 3 32370451

Pak choi 6 PMA 4 27416497

155

Table A2.4 Concentration of resting spores of Plasmodiophora brassicae in soil under

controlled conditions in Run 3 of the field crop study (n = 6).

Crop Block Subsample Resting spore

concentration1

(spores g-1)

Barley 1 1 201774.7

Barley 1 2 367566.4

Barley 1 3 243910

Barley 2 1 172872.9

Barley 2 2 218350.1

Barley 2 3 247112.1

Barley 3 1 124055

Barley 3 2 65339.38

Barley 3 3 33140.26

Barley 4 1 40970.85

Barley 4 2 122019.6

Barley 4 3 99824.69

Barley 5 1 51389.38

Barley 5 2 67411.57

Barley 5 3 141290.8

Barley 6 1 142294.5

Barley 6 2 152109.2

Barley 6 3 173462.2

Pea 1 1 224512

Pea 1 2 127145.8

Pea 1 3 207107.6

Pea 2 1 152959.5

Pea 2 2 357395.8

Pea 2 3 190743.2

Pea 3 1 125695.5

Pea 3 2 101464.2

Pea 3 3 85871.22

Pea 4 1 103904.3

Pea 4 2 114853.3

Pea 4 3 209712.4

Pea 5 1 110284.9

Pea 5 2 31415.75

Pea 5 3 297820.7

Pea 6 1 78303.39

Pea 6 2 236833.6

Pea 6 3 120711.2

No-plant 1 1 181496.5

No-plant 1 2 309035.5

156

No-plant 1 3 359117.9

No-plant 2 1 532061.2

No-plant 2 2 259751

No-plant 2 3 344345.7

No-plant 3 1 211594.5

No-plant 3 2 58687.73

No-plant 3 3 54889.02

No-plant 4 1 150268.4

No-plant 4 2 590712.3

No-plant 4 3 390546.5

No-plant 5 1 50512.42

No-plant 5 2 128487.4

No-plant 5 3 242759.7

No-plant 6 1 142193.4

No-plant 6 2 329392.2

No-plant 6 3 336778.6

Pak choi 1 1 1.41E+08

Pak choi 1 2 39429588

Pak choi 1 3 58751438

Pak choi 2 1 39143758

Pak choi 2 2 17326601

Pak choi 2 3 12117642

Pak choi 3 1 3084000

Pak choi 3 2 17380547

Pak choi 3 3 5557784

Pak choi 4 1 6687090

Pak choi 4 2 16861039

Pak choi 4 3 5799820

Pak choi 5 1 415031.5

Pak choi 5 2 1543575

Pak choi 5 3 491607.8

Pak choi 6 1 4449372

Pak choi 6 2 2852897

Pak choi 6 3 7288746

Ryegrass 1 1 286777.9

Ryegrass 1 2 333457.3

Ryegrass 1 3 476228

Ryegrass 2 1 477785.8

Ryegrass 2 2 247950.1

Ryegrass 2 3 338720.3

Ryegrass 3 1 41170.75

Ryegrass 3 2 38305.26

Ryegrass 3 3 37882.12

Ryegrass 4 1 166867.8

157

Ryegrass 4 2 92581.42

Ryegrass 4 3 54995.53

Ryegrass 5 1 166017.9

Ryegrass 5 2 210290.7

Ryegrass 5 3 35280.07

Ryegrass 6 1 37322.06

Ryegrass 6 2 150000.4

Ryegrass 6 3 27208.33

Soybean 1 1 268538.8

Soybean 1 2 112140.1

Soybean 1 3 238515.1

Soybean 2 1 316114.2

Soybean 2 2 293596.4

Soybean 2 3 268495

Soybean 3 1 165368.8

Soybean 3 2 351556.4

Soybean 3 3 104331.3

Soybean 4 1 325563.4

Soybean 4 2 307983.5

Soybean 4 3 405095.5

Soybean 5 1 110046.7

Soybean 5 2 64070.91

Soybean 5 3 248191.7

Soybean 6 1 82499.56

Soybean 6 2 703668.2

Soybean 6 3 95308.13

Spring wheat 1 1 360890.4

Spring wheat 1 2 75624.6

Spring wheat 1 3 347713.7

Spring wheat 2 1 15679.54

Spring wheat 2 2 125427.7

Spring wheat 2 3 200557.3

Spring wheat 3 1 10755.35

Spring wheat 3 2 164415.3

Spring wheat 3 3 129914.6

Spring wheat 4 1 118245.6

Spring wheat 4 2 24527.61

Spring wheat 4 3 22155.66

Spring wheat 5 1 24759.79

Spring wheat 5 2 132970.6

Spring wheat 5 3 37511.97

Spring wheat 6 1 178940.4

Spring wheat 6 2 9995.591

Spring wheat 6 3 51920.91

158

Table A2.5 Concentration of resting spores of Plasmodiophora brassicae in soil after growing

barley and a no-plant control and application of three rates of lime (calcium hydroxide, Ca(OH)2)

under controlled conditions (n = 6).

Crop Rate of

Ca(OH)2 g-1

Target

pH

Block Treatment Subsample Resting spore

concentration1

(spores g-1)

Barley 0 mg 6.4 1 Control 1 2296057

Barley 0 mg 6.4 1 Control 2 2572159

Barley 0 mg 6.4 1 PMA 3 14102242

Barley 0 mg 6.4 1 PMA 4 469299.6

Barley 0 mg 6.4 2 Control 1 7674358

Barley 0 mg 6.4 2 Control 2 886794.7

Barley 0 mg 6.4 2 PMA 3 2581156

Barley 0 mg 6.4 2 PMA 4 2753733

Barley 0 mg 6.4 3 Control 1 3187910

Barley 0 mg 6.4 3 Control 2 4550404

Barley 0 mg 6.4 3 PMA 3 1819706

Barley 0 mg 6.4 3 PMA 4 3252067

Barley 0 mg 6.4 4 Control 1 1868156

Barley 0 mg 6.4 4 Control 2 5510326

Barley 0 mg 6.4 4 PMA 3 3803870

Barley 0 mg 6.4 4 PMA 4 2366077

Barley 0 mg 6.4 5 Control 1 8696562

Barley 0 mg 6.4 5 Control 2 5105730

Barley 0 mg 6.4 5 PMA 3 1809179

Barley 0 mg 6.4 5 PMA 4 1990565

Barley 0 mg 6.4 6 Control 1 4501343

Barley 0 mg 6.4 6 Control 2 2978037

Barley 0 mg 6.4 6 PMA 3 334857

Barley 0 mg 6.4 6 PMA 4 24304100

Barley 0.077 mg 6.8 1 Control 1 5047923

Barley 0.077 mg 6.8 1 Control 2 3108120

Barley 0.077 mg 6.8 1 PMA 3 594036

Barley 0.077 mg 6.8 1 PMA 4 6356221

Barley 0.077 mg 6.8 2 Control 1 2212258

Barley 0.077 mg 6.8 2 Control 2 2346978

Barley 0.077 mg 6.8 2 PMA 3 1494321

Barley 0.077 mg 6.8 2 PMA 4 2620350

Barley 0.077 mg 6.8 3 Control 1 4948248

Barley 0.077 mg 6.8 3 Control 2 45251396

Barley 0.077 mg 6.8 3 PMA 3 2657357

Barley 0.077 mg 6.8 3 PMA 4 571860.7

Barley 0.077 mg 6.8 4 Control 1 22120719

159

Barley 0.077 mg 6.8 4 Control 2 .

Barley 0.077 mg 6.8 4 PMA 3 1664995

Barley 0.077 mg 6.8 4 PMA 4 9489874

Barley 0.077 mg 6.8 5 Control 1 594783.6

Barley 0.077 mg 6.8 5 Control 2 4353879

Barley 0.077 mg 6.8 5 PMA 3 1376636

Barley 0.077 mg 6.8 5 PMA 4 96687.09

Barley 0.077 mg 6.8 6 Control 1 8478992

Barley 0.077 mg 6.8 6 Control 2 832678.4

Barley 0.077 mg 6.8 6 PMA 3 .

Barley 0.077 mg 6.8 6 PMA 4 4085395

Barley 0.30 mg 7.2 1 Control 1 2113692

Barley 0.30 mg 7.2 1 Control 2 5056287

Barley 0.30 mg 7.2 1 PMA 3 2406570

Barley 0.30 mg 7.2 1 PMA 4 145731.7

Barley 0.30 mg 7.2 2 Control 1 2042352

Barley 0.30 mg 7.2 2 Control 2 4395808

Barley 0.30 mg 7.2 2 PMA 3 6996415

Barley 0.30 mg 7.2 2 PMA 4 2645479

Barley 0.30 mg 7.2 3 Control 1 .

Barley 0.30 mg 7.2 3 Control 2 3233912

Barley 0.30 mg 7.2 3 PMA 3 1531955

Barley 0.30 mg 7.2 3 PMA 4 34555810

Barley 0.30 mg 7.2 4 Control 1 6607192

Barley 0.30 mg 7.2 4 Control 2 30261.88

Barley 0.30 mg 7.2 4 PMA 3 3140238

Barley 0.30 mg 7.2 4 PMA 4 3083919

Barley 0.30 mg 7.2 5 Control 1 676538.1

Barley 0.30 mg 7.2 5 Control 2 1564540

Barley 0.30 mg 7.2 5 PMA 3 2386622

Barley 0.30 mg 7.2 5 PMA 4 1130296

Barley 0.30 mg 7.2 6 Control 1 6037787

Barley 0.30 mg 7.2 6 Control 2 8261775

Barley 0.30 mg 7.2 6 PMA 3 .

Barley 0.30 mg 7.2 6 PMA 4 7066137

No-plant 0 mg 6.4 1 Control 1 2826714

No-plant 0 mg 6.4 1 Control 2 4395103

No-plant 0 mg 6.4 1 PMA 3 1578390

No-plant 0 mg 6.4 1 PMA 4 37198.75

No-plant 0 mg 6.4 2 Control 1 9493029

No-plant 0 mg 6.4 2 Control 2 .

No-plant 0 mg 6.4 2 PMA 3 13974503

No-plant 0 mg 6.4 2 PMA 4 6473208

No-plant 0 mg 6.4 3 Control 1 2203208

160

No-plant 0 mg 6.4 3 Control 2 1352619

No-plant 0 mg 6.4 3 PMA 3 3045527

No-plant 0 mg 6.4 3 PMA 4 11378485

No-plant 0 mg 6.4 4 Control 1 788835

No-plant 0 mg 6.4 4 Control 2 1235802

No-plant 0 mg 6.4 4 PMA 3 541983.3

No-plant 0 mg 6.4 4 PMA 4 4198504

No-plant 0 mg 6.4 5 Control 1 .

No-plant 0 mg 6.4 5 Control 2 1126383

No-plant 0 mg 6.4 5 PMA 3 3777012

No-plant 0 mg 6.4 5 PMA 4 3361818

No-plant 0 mg 6.4 6 Control 1 615996.4

No-plant 0 mg 6.4 6 Control 2 .

No-plant 0 mg 6.4 6 PMA 3 2419840

No-plant 0 mg 6.4 6 PMA 4 1817849

No-plant 0.077 mg 6.8 1 Control 1 34695.13

No-plant 0.077 mg 6.8 1 Control 2 5452206

No-plant 0.077 mg 6.8 1 PMA 3 868664.9

No-plant 0.077 mg 6.8 1 PMA 4 38257.5

No-plant 0.077 mg 6.8 2 Control 1 .

No-plant 0.077 mg 6.8 2 Control 2 5107533

No-plant 0.077 mg 6.8 2 PMA 3 3618342

No-plant 0.077 mg 6.8 2 PMA 4 514193.1

No-plant 0.077 mg 6.8 3 Control 1 4136800

No-plant 0.077 mg 6.8 3 Control 2 5293113

No-plant 0.077 mg 6.8 3 PMA 3 1358876

No-plant 0.077 mg 6.8 3 PMA 4 7469125

No-plant 0.077 mg 6.8 4 Control 1 2700965

No-plant 0.077 mg 6.8 4 Control 2 3999318

No-plant 0.077 mg 6.8 4 PMA 3 46347.61

No-plant 0.077 mg 6.8 4 PMA 4 34021.16

No-plant 0.077 mg 6.8 5 Control 1 835512.6

No-plant 0.077 mg 6.8 5 Control 2 22462397

No-plant 0.077 mg 6.8 5 PMA 3 743347.6

No-plant 0.077 mg 6.8 5 PMA 4 117232.8

No-plant 0.077 mg 6.8 6 Control 1 3207256

No-plant 0.077 mg 6.8 6 Control 2 7170175

No-plant 0.077 mg 6.8 6 PMA 3 2005119

No-plant 0.077 mg 6.8 6 PMA 4 3026105

No-plant 0.30 mg 7.2 1 Control 1 1644120

No-plant 0.30 mg 7.2 1 Control 2 473650.6

No-plant 0.30 mg 7.2 1 PMA 3 1817124

No-plant 0.30 mg 7.2 1 PMA 4 7334739

No-plant 0.30 mg 7.2 2 Control 1 2169725

161

No-plant 0.30 mg 7.2 2 Control 2 17675.21

No-plant 0.30 mg 7.2 2 PMA 3 5889501

No-plant 0.30 mg 7.2 2 PMA 4 331546.6

No-plant 0.30 mg 7.2 3 Control 1 .

No-plant 0.30 mg 7.2 3 Control 2 1235802

No-plant 0.30 mg 7.2 3 PMA 3 1401058

No-plant 0.30 mg 7.2 3 PMA 4 4148982

No-plant 0.30 mg 7.2 4 Control 1 3401217

No-plant 0.30 mg 7.2 4 Control 2 979981.6

No-plant 0.30 mg 7.2 4 PMA 3 .

No-plant 0.30 mg 7.2 4 PMA 4 8678740

No-plant 0.30 mg 7.2 5 Control 1 1231015

No-plant 0.30 mg 7.2 5 Control 2 1581181

No-plant 0.30 mg 7.2 5 PMA 3 630598.6

No-plant 0.30 mg 7.2 5 PMA 4 .

No-plant 0.30 mg 7.2 6 Control 1 1093564

No-plant 0.30 mg 7.2 6 Control 2 5493891

No-plant 0.30 mg 7.2 6 PMA 3 29444.87

No-plant 0.30 mg 7.2 6 PMA 4 .

Pak choi 0 mg 6.4 1 Control 1 1.87E+08

Pak choi 0 mg 6.4 1 Control 2 84439841

Pak choi 0 mg 6.4 1 PMA 3 1.04E+08

Pak choi 0 mg 6.4 1 PMA 4 64876987

Pak choi 0 mg 6.4 2 Control 1 6.42E+09

Pak choi 0 mg 6.4 2 Control 2 4.91E+09

Pak choi 0 mg 6.4 2 PMA 3 5.11E+09

Pak choi 0 mg 6.4 2 PMA 4 5.45E+09

Pak choi 0 mg 6.4 3 Control 1 55554582

Pak choi 0 mg 6.4 3 Control 2 59778650

Pak choi 0 mg 6.4 3 PMA 3 94690096

Pak choi 0 mg 6.4 3 PMA 4 7.81E+08

Pak choi 0 mg 6.4 4 Control 1 10245367

Pak choi 0 mg 6.4 4 Control 2 6476326

Pak choi 0 mg 6.4 4 PMA 3 8258575

Pak choi 0 mg 6.4 4 PMA 4 7297449

Pak choi 0 mg 6.4 5 Control 1 6.69E+08

Pak choi 0 mg 6.4 5 Control 2 52297024

Pak choi 0 mg 6.4 5 PMA 3 5E+08

Pak choi 0 mg 6.4 5 PMA 4 94252524

Pak choi 0 mg 6.4 6 Control 1 3069753

Pak choi 0 mg 6.4 6 Control 2 13703903

Pak choi 0 mg 6.4 6 PMA 3 47568955

Pak choi 0 mg 6.4 6 PMA 4 6263259

Pak choi 0.077 mg 6.8 1 Control 1 1.48E+09

162

Pak choi 0.077 mg 6.8 1 Control 2 1.09E+09

Pak choi 0.077 mg 6.8 1 PMA 3 1.08E+09

Pak choi 0.077 mg 6.8 1 PMA 4 1.07E+09

Pak choi 0.077 mg 6.8 2 Control 1 6606793

Pak choi 0.077 mg 6.8 2 Control 2 9906702

Pak choi 0.077 mg 6.8 2 PMA 3 4620430

Pak choi 0.077 mg 6.8 2 PMA 4 4675583

Pak choi 0.077 mg 6.8 3 Control 1 5.28E+08

Pak choi 0.077 mg 6.8 3 Control 2 473547.2

Pak choi 0.077 mg 6.8 3 PMA 3 3.75E+08

Pak choi 0.077 mg 6.8 3 PMA 4 5.08E+08

Pak choi 0.077 mg 6.8 4 Control 1 7089902

Pak choi 0.077 mg 6.8 4 Control 2 8389977

Pak choi 0.077 mg 6.8 4 PMA 3 5824757

Pak choi 0.077 mg 6.8 4 PMA 4 4047650

Pak choi 0.077 mg 6.8 5 Control 1 8224122

Pak choi 0.077 mg 6.8 5 Control 2 14982196

Pak choi 0.077 mg 6.8 5 PMA 3 21688468

Pak choi 0.077 mg 6.8 5 PMA 4 4703302

Pak choi 0.077 mg 6.8 6 Control 1 45029768

Pak choi 0.077 mg 6.8 6 Control 2 270710.7

Pak choi 0.077 mg 6.8 6 PMA 3 6908022

Pak choi 0.077 mg 6.8 6 PMA 4 1127385

Pak choi 0.30 mg 7.2 1 Control 1 1832331

Pak choi 0.30 mg 7.2 1 Control 2 1299673

Pak choi 0.30 mg 7.2 1 PMA 3 2658132

Pak choi 0.30 mg 7.2 1 PMA 4 3568576

Pak choi 0.30 mg 7.2 2 Control 1 7.02E+08

Pak choi 0.30 mg 7.2 2 Control 2 2.29E+08

Pak choi 0.30 mg 7.2 2 PMA 3 3.42E+08

Pak choi 0.30 mg 7.2 2 PMA 4 4.85E+08

Pak choi 0.30 mg 7.2 3 Control 1 2615419

Pak choi 0.30 mg 7.2 3 Control 2 1.15E+08

Pak choi 0.30 mg 7.2 3 PMA 3 1289753

Pak choi 0.30 mg 7.2 3 PMA 4 1.08E+08

Pak choi 0.30 mg 7.2 4 Control 1 8671820

Pak choi 0.30 mg 7.2 4 Control 2 4838235

Pak choi 0.30 mg 7.2 4 PMA 3 1412102

Pak choi 0.30 mg 7.2 4 PMA 4 1514753

Pak choi 0.30 mg 7.2 5 Control 1 .

Pak choi 0.30 mg 7.2 5 Control 2 39234.07

Pak choi 0.30 mg 7.2 5 PMA 3 2708983

Pak choi 0.30 mg 7.2 5 PMA 4 4489404

Pak choi 0.30 mg 7.2 6 Control 1 3262255

163

Pak choi 0.30 mg 7.2 6 Control 2 6347981

Pak choi 0.30 mg 7.2 6 PMA 3 2093279

Pak choi 0.30 mg 7.2 6 PMA 4 3556858

Table A2.6 Concentration of resting spores of Plasmodiophora brassicae in soil after growing

spring wheat and a no-plant control and application of three rates of lime (calcium hydroxide,

Ca(OH)2) under controlled conditions (n = 6).

Crop Rate of

Ca(OH)2 g-1

Target pH Block Subsample Resting spore

concentration1 (spores

g-1)

Spring wheat 0 mg 6.4 1 1 1568587.744

Spring wheat 0 mg 6.4 1 2 32542789.02

Spring wheat 0 mg 6.4 1 3 9703665.377

Spring wheat 0 mg 6.4 2 1 4315408.889

Spring wheat 0 mg 6.4 2 2 6788222.862

Spring wheat 0 mg 6.4 2 3 8259953.848

Spring wheat 0 mg 6.4 3 1 3806044.068

Spring wheat 0 mg 6.4 3 2 3746754.161

Spring wheat 0 mg 6.4 3 3 5153572.487

Spring wheat 0 mg 6.4 4 1 2081378.128

Spring wheat 0 mg 6.4 4 2 1988986.48

Spring wheat 0 mg 6.4 4 3 2070733.941

Spring wheat 0 mg 6.4 5 1 2506101.823

Spring wheat 0 mg 6.4 5 2 2694901.577

Spring wheat 0 mg 6.4 5 3 3121312.254

Spring wheat 0 mg 6.4 6 1 1307741.562

Spring wheat 0 mg 6.4 6 2 1149857.224

Spring wheat 0 mg 6.4 6 3 1747892.896

Spring wheat 0.24 mg 7 1 1 27174997.06

Spring wheat 0.24 mg 7 1 2 8508407.397

Spring wheat 0.24 mg 7 1 3 2364292.97

Spring wheat 0.24 mg 7 2 1 4019657.748

Spring wheat 0.24 mg 7 2 2 2859560.294

Spring wheat 0.24 mg 7 2 3 2890748.233

Spring wheat 0.24 mg 7 3 1 4554643.457

Spring wheat 0.24 mg 7 3 2 3914153.874

Spring wheat 0.24 mg 7 3 3 3519451.791

Spring wheat 0.24 mg 7 4 1 1975974.694

Spring wheat 0.24 mg 7 4 2 2213195.085

Spring wheat 0.24 mg 7 4 3 2242105.567

Spring wheat 0.24 mg 7 5 1 2489262.77

Spring wheat 0.24 mg 7 5 2 3051278.922

Spring wheat 0.24 mg 7 5 3 3621221.963

Spring wheat 0.24 mg 7 6 1 689115.577

164

Spring wheat 0.24 mg 7 6 2 1019039.589

Spring wheat 0.24 mg 7 6 3 593442.9486

Spring wheat 0.52 mg 7.6 1 1 1107783.715

Spring wheat 0.52 mg 7.6 1 2 1613477.286

Spring wheat 0.52 mg 7.6 1 3 7012251.47

Spring wheat 0.52 mg 7.6 2 1 2100433.73

Spring wheat 0.52 mg 7.6 2 2 2175892.687

Spring wheat 0.52 mg 7.6 2 3 2292639.531

Spring wheat 0.52 mg 7.6 3 1 3326562.803

Spring wheat 0.52 mg 7.6 3 2 3404965.639

Spring wheat 0.52 mg 7.6 3 3 3826224.504

Spring wheat 0.52 mg 7.6 4 1 3059275.036

Spring wheat 0.52 mg 7.6 4 2 1660970.349

Spring wheat 0.52 mg 7.6 4 3 1159828.672

Spring wheat 0.52 mg 7.6 5 1 2909300.868

Spring wheat 0.52 mg 7.6 5 2 2357717.31

Spring wheat 0.52 mg 7.6 5 3 1943913.485

Spring wheat 0.52 mg 7.6 6 1 895951.9234

Spring wheat 0.52 mg 7.6 6 2 1518112.648

Spring wheat 0.52 mg 7.6 6 3 698552.661

No plant 0 mg 6.4 1 1 20720413.25

No plant 0 mg 6.4 1 2 19083478.49

No plant 0 mg 6.4 1 3 18245078.56

No plant 0 mg 6.4 2 1 10366469.14

No plant 0 mg 6.4 2 2 7197568.993

No plant 0 mg 6.4 2 3 10801250.91

No plant 0 mg 6.4 3 1 4385109.489

No plant 0 mg 6.4 3 2 5892955.737

No plant 0 mg 6.4 3 3 5073016.152

No plant 0 mg 6.4 4 1 1863686.944

No plant 0 mg 6.4 4 2 2441082.441

No plant 0 mg 6.4 4 3 2478957.035

No plant 0 mg 6.4 5 1 3700575.82

No plant 0 mg 6.4 5 2 3897514.41

No plant 0 mg 6.4 5 3 5236422.288

No plant 0 mg 6.4 6 1 728046.5263

No plant 0 mg 6.4 6 2 1087097.561

No plant 0 mg 6.4 6 3 2291637.237

No plant 0.24 mg 7 1 1 11333335.84

No plant 0.24 mg 7 1 2 15097920.25

No plant 0.24 mg 7 1 3 46574510.24

No plant 0.24 mg 7 2 1 3507089.22

No plant 0.24 mg 7 2 2 3666770.186

No plant 0.24 mg 7 2 3 4302107.962

165

No plant 0.24 mg 7 3 1 4335499.342

No plant 0.24 mg 7 3 2 4986999.471

No plant 0.24 mg 7 3 3 5800256.905

No plant 0.24 mg 7 4 1 1786666.469

No plant 0.24 mg 7 4 2 2217500.194

No plant 0.24 mg 7 4 3 2465105.933

No plant 0.24 mg 7 5 1 3365763.895

No plant 0.24 mg 7 5 2 3493497.391

No plant 0.24 mg 7 5 3 3003741.41

No plant 0.24 mg 7 6 1 1430529.958

No plant 0.24 mg 7 6 2 944544.1755

No plant 0.24 mg 7 6 3 1335510.536

No plant 0.52 mg 7.6 1 1 11497237.94

No plant 0.52 mg 7.6 1 2 2272579.142

No plant 0.52 mg 7.6 1 3 39499523.64

No plant 0.52 mg 7.6 2 1 3356413.753

No plant 0.52 mg 7.6 2 2 3767620.413

No plant 0.52 mg 7.6 2 3 3640353.268

No plant 0.52 mg 7.6 3 1 4122093.874

No plant 0.52 mg 7.6 3 2 5035976.23

No plant 0.52 mg 7.6 3 3 4985080.324

No plant 0.52 mg 7.6 4 1 1486513.264

No plant 0.52 mg 7.6 4 2 1255727.282

No plant 0.52 mg 7.6 4 3 1191752.357

No plant 0.52 mg 7.6 5 1 2225642.097

No plant 0.52 mg 7.6 5 2 2581265.55

No plant 0.52 mg 7.6 5 3 2237966.3

No plant 0.52 mg 7.6 6 1 .

No plant 0.52 mg 7.6 6 2 .

No plant 0.52 mg 7.6 6 3 .

Pak choi 0 mg 6.4 1 1 300891938.7

Pak choi 0 mg 6.4 1 2 373939691.8

Pak choi 0 mg 6.4 1 3 152497839.5

Pak choi 0 mg 6.4 2 1 51110587.49

Pak choi 0 mg 6.4 2 2 69107203.79

Pak choi 0 mg 6.4 2 3 152824789.6

Pak choi 0 mg 6.4 3 1 410154346.8

Pak choi 0 mg 6.4 3 2 286969921.3

Pak choi 0 mg 6.4 3 3 215147860.4

Pak choi 0 mg 6.4 4 1 118796990.1

Pak choi 0 mg 6.4 4 2 133293133.5

Pak choi 0 mg 6.4 4 3 111291102.4

Pak choi 0 mg 6.4 5 1 74855107.5

Pak choi 0 mg 6.4 5 2 67558900.64

166

Pak choi 0 mg 6.4 5 3 83334848.93

Pak choi 0 mg 6.4 6 1 398201256

Pak choi 0 mg 6.4 6 2 187448972.9

Pak choi 0 mg 6.4 6 3 168613792.3

Pak choi 0.24 mg 7 1 1 120559854.7

Pak choi 0.24 mg 7 1 2 109999810.7

Pak choi 0.24 mg 7 1 3 104174625.2

Pak choi 0.24 mg 7 2 1 241098481.5

Pak choi 0.24 mg 7 2 2 303659073.9

Pak choi 0.24 mg 7 2 3 283940538.8

Pak choi 0.24 mg 7 3 1 295982290

Pak choi 0.24 mg 7 3 2 96113027.26

Pak choi 0.24 mg 7 3 3 175740811.2

Pak choi 0.24 mg 7 4 1 3587800735

Pak choi 0.24 mg 7 4 2 5176381998

Pak choi 0.24 mg 7 4 3 2920371308

Pak choi 0.24 mg 7 5 1 455902603.3

Pak choi 0.24 mg 7 5 2 124167667.7

Pak choi 0.24 mg 7 5 3 198970940.4

Pak choi 0.24 mg 7 6 1 145740811.2

Pak choi 0.24 mg 7 6 2 189473688.3

Pak choi 0.24 mg 7 6 3 .

Pak choi 0.52 mg 7.6 1 1 97296493.22

Pak choi 0.52 mg 7.6 1 2 78247481.59

Pak choi 0.52 mg 7.6 1 3 59806413.35

Pak choi 0.52 mg 7.6 2 1 43912616.04

Pak choi 0.52 mg 7.6 2 2 31354787.36

Pak choi 0.52 mg 7.6 2 3 24209456.27

Pak choi 0.52 mg 7.6 3 1 9469850.488

Pak choi 0.52 mg 7.6 3 2 12042907.53

Pak choi 0.52 mg 7.6 3 3 17069898.03

Pak choi 0.52 mg 7.6 4 1 22518088.58

Pak choi 0.52 mg 7.6 4 2 31203499.22

Pak choi 0.52 mg 7.6 4 3 26424431.02

Pak choi 0.52 mg 7.6 5 1 286108788.3

Pak choi 0.52 mg 7.6 5 2 260728756.7

Pak choi 0.52 mg 7.6 5 3 198576691.6

Pak choi 0.52 mg 7.6 6 1 1493050.512

Pak choi 0.52 mg 7.6 6 2 1539252.141

Pak choi 0.52 mg 7.6 6 3 .