DISTRIBUTION, INTENSITY AND VARIABILITY OF

SEPTORIA BLOTCH (Septoria tritici) IN CENTRAL-

SOUTHEASTERN OROMIA, ETHIOPIA, AND SEEDLING

RESISTANCE OF WHEAT CULTIVARS

M.Sc. THESIS

GIRMA ABABA TARAFA

November, 2020

JIMMA, ETHIOPIA

ii

Distribution, Intensity and Variability of Septoria Blotch (Septoria

tritici) in Central-Southeastern Oromia, Ethiopia, and Seedling

Resistance of Wheat Cultivars

Girma Ababa Tarafa

A Thesis

Submitted to the School of Graduate Studies, Jimma University, College of

Agriculture and Veterinary Medicine, in Partial Fulfillment of the

Requirements for the Degree of Master of Sciences (M.Sc.) in Plant Pathology

Major- adviser: Girma Adugna Senbeta (Ph.D. Associate professor)

Co-adviser: Bekele Hundie (Ph.D. Senior plant pathologist)

November, 2020

Jimma, Ethiopia

ii

DEDICATION

I dedicate this thesis to my wife Desta Achalu Chemeda for her unrestricted love and support

during my study. Again, it is dedicated to my father Abebe Terefe, and my mother Shewaye

Gelasa. At the same, my grandfather Terefe Wakayo and grandmother Erbitu Soboka occupied

the role of my lost father when I was a teenager.

iii

STATEMENT OF AUTHOR

I declare that this thesis is my real work and that all sources of materials used for this thesis have

been duly acknowledged. This thesis has been submitted in partial fulfillment of the

requirements for an M.Sc. degree in plant pathology at Jimma University College of Agriculture

and Veterinary Medicine (JUCAVM). The Thesis is deposited at the University Library to be

made available to borrowers under the rules of the library. I seriously declare that this thesis is

not submitted to any other institution anywhere for the award of any academic degree, diploma,

or certificate. Brief quotations from this thesis are allowed without special permission provided

that accurate acknowledgment of the source is made. Requests for permission for extended

quotation from or reproduction of this manuscript in whole or in part may be granted by the head

of the department or the Dean of the School of Graduate Studies when in his or her judgment the

proposed use of the material is in the interests of scholarship. In all other instances, however,

permission must be obtained from the author of the Thesis.

iv

BIOGRAPHIC DRAFT

The author was born on January 23, 1991, from his father Abebe Terefe, and his mother

Shewaye Gelasa in Dandi District, West Shoa Zone, and Oromia Regional State. He completed

his elementary education at Gura Awash Elementary School in 2007. Then, he attended his high

school and preparatory education at Ginchi from 2008-2012. The author also took the Ethiopian

Higher Education Entrance Qualification Certificate (EHEEQC) in June 2012. In September

2013, he joined Adama Science and Technology University. In June 2015 he acquired a B.Sc.

degree in plant science.

Afterward, he was employed by the Ethiopian Institute of Agricultural Research on September

01, 2017, as a junior researcher at Pawe Agricultural Research Center (PARC). The author

served as a junior Sesame and Cotton breeder for two years in this center. In September 2019, he

joined Jimma University College of Agriculture and Veterinary Medicine (JUCAVM) to pursue

his M.Sc. study in plant pathology.

v

ACKNOWLEDGMENTS

First of all, I’m lucky to thanks my God, my father, the Highest and Almighty one, for letting me

through this journey of life. I feel your guidance day by day in every stage of this thesis. You are

the one who has done a great and tremendous job for this thesis. Thank you, Lord, for your

endless blessing that has showered upon me. I will always remain grateful to you God. Next to

my lord, I would like to appreciate my lovely wife Desta Achalu for her great appreciation

during all of my work.

First and foremost, I wish to place on records my heartfelt and sincere thanks to my major-

advisor Dr, Girma Adugna, and Co-adviser Dr, Bekele Hundie for providing me an opportunity

to complete my MSc thesis. I appreciate them for the contributions of time and ideas to make my

work productivity. They, valuable suggestions, comments, and guidance encouraged me to learn

more. They, deep insights helped me at various stages of my research. I am also indebted to them

for the generosity, selfless support, and especially for the excellent example and patience that

they have provided to me for the last year. Big thanks once again go to them for without them

this work would have never seen the light as it is today.

I am extremely grateful to Dr, Tilahun Mekonin for his invaluable insights and suggestions. I

appreciate his willingness to help and meet me whenever I need some clarification. He has been

a wonderful mentor and guidance for me and providing the wheat differential lines I used for my

thesis work. I am amazed that even during his busy schedule, he was never refused; instead, he

was always willing to help me with my thesis. The useful discussion and comments that he

suggests me widen my knowledge in various fields of the subject throughout my study. Thank

you, sir, for your valuable time, co-operation, and generosity which set this work possible as it is

till the end. Your support has been the most profitable experience for me.

I appreciate and thank the Ethiopian Institute of Agricultural Research (EIAR) for charitable me

the chance to pursue my M.Sc. degree with full sponsorship. I would like to thanks Dr,

Muhamed Yosef and Achalu Chemeda for the additional fund afforded for me during my work. I

also have deep thanks to Dr, Berhanu Fayisa for his discussion with the center for greenhouse

usage.

I have a deep thanks to Debrezeit Agricultural Research Center (DARC) for allowing me the

vi

laboratory, greenhouse, affording the facilities/services and durum wheat varieties seed during I

reside with them. My special thanks go to the staff of this center, Ashenafi Gemechu, Tolesa

Bedasa, and Worku Kebede for them facilities, unreserved support during the laboratory, and

greenhouse work. Also, I thank Aderaw Tsegaye for the allocation of the survey area by using

GIS. In the same, I thank Eresi Megersa, Behailu Abera, and Ketema Mengesha for their

collaboration, organizing, and mobilizing all the necessary facilities in the greenhouse and

laboratory during the study.

I truthfully, thank Kulumsa Agricultural Research Center (KARC) for providing me

transportation service to complete my survey work and bread wheat varieties seed. I give great

thanks to the staff of this center Tamirat Negash and Lidia Tilahun for their facilities and helping

me during my survey work. Also, I would like to thank Getenesh Demise, Girma Zewde, and

Samuel G/Mariam for the support of survey data records.

Also, I have great thanks to my beloved friends Yadesa Bayisa bear me during my survey data

proceedings work. I need to express great thanks to Zarihun Eshetu (Sinana Agricultural

Research Center) and Yitagesu Tadese (Holeta Agricultural Research Center) for the support

during survey data records and sample collection.

I am greatly thankful to the Holeta National Biotechnology Agricultural Research Center

(HNBARC) for the permission of laboratory and facilities/services during the isolation process.

Once more, I thank the staff of this center: Daniel Yimer, Lelise Legese, Mesele Mola, and

Diriba Guta, for their guidance during my isolation process and providing material. I have

special thanks to Kebede Gizachew, Kasaye Mamo, and Almaz Debele for their support in the

microbiology laboratory and providing me material.

At the last but not least I have a great thanks to My center Pawe Agricultural Research Center

and my staff Gezegn Tefera, Zewdineh Malke, and Mola Malede for them organized all

necessary facilities when I was out of the center for my study. Again, I like to thanks Mesfin

Kuma, Getachew Yilma, Mamo Bekele, and Asela Kesho for offering me laboratory material.

vii

ABBREVIATIONS AND ACRONYMS

ATA Agricultural transformation Agency

APR Adult plant resistance

CSA Central Statistical Authority

DARC Debrezeit Agricultural Research Center

EIAR Ethiopian Institute of Agricultural Research

FOA Food and Agricultural Organization

GS Growth stage

HA Hectares

HARC Holeta Agricultural Research Center

HR hypersensitive response

HNBARC Holeta National Biotechnology Agricultural Research Center

KARC Kulumsa Agricultural Research Center

m.a.s.l meters above sea level

MAPK Mitogen activated protein kinase

Mt Metric tons

µm Micrometer

PR Pathogenesis-related

PAMPs Pathogen-associated molecular patterns

QTL Quantitative trait locus

ROS Reactive oxygen species

STB Septoria tritici Blotch

SAS Statistical Analysis System

SNNPR Southern Nations Nationalities and People’s Region

viii

TABLE OF CONTENTS

CONTENTS PAGE

DEDICATION............................................................................................................................... ii

STATEMENT OF AUTHOR ..................................................................................................... iii

BIOGRAPHIC DRAFT............................................................................................................... iv

ACKNOWLEDGMENTS ............................................................................................................ v

ABBREVIATIONS AND ACRONYMS ................................................................................... vii

TABLE OF CONTENTS .......................................................................................................... viii

LIST OF TABLES ...................................................................................................................... xii

LIST OF FIGURES ................................................................................................................... xiv

LIST OF TABLE OF APPENDIX ........................................................................................... xvi

LIST OF FIGURE OF APPENDIX ........................................................................................ xvii

ABSTRACT .............................................................................................................................. xviii

1. INTRODUCTION..................................................................................................................... 1

2. LITERATURE REVIEW ........................................................................................................ 5

2.1. Origin of the wheat (Triticum spp.) ................................................................................... 5

2.1.1. Importance of the wheat (Triticum spp.) ........................................................................ 5

2.1.2. Wheat production constraints ......................................................................................... 5

2.2. Classification of the Septoria tritici .................................................................................... 6

2.3. Biology of the Septoria tritici .............................................................................................. 7

2.3.1. Asexual reproduction ..................................................................................................... 7

2.3.1.1. Vegetative growth and morphology of pathogen ..................................................... 7

2.3.2. Sexual reproduction........................................................................................................ 8

2.3.3. The pathogen lifestyle .................................................................................................... 9

ix

2.3.4. Infection process .......................................................................................................... 10

2.3.5. The life cycle of pathogen ............................................................................................ 11

2.3.6. Symptom ...................................................................................................................... 12

2.3.7. Epidemiology of the pathogen ..................................................................................... 13

2.3.7.1. Conducive environment ......................................................................................... 13

2.3.7.2. Susceptible host ..................................................................................................... 15

2.3.7.3. Inoculums ............................................................................................................... 15

2.3.8. Host range .................................................................................................................... 16

2.3.9. Physiological specialization of M. graminicola ........................................................... 17

2.4. Importance of septoria tririci blotch .............................................................................. 18

2.5. Distribution of septoria tririci blotch.............................................................................. 19

2.6. Disease measurement ....................................................................................................... 21

2.6.1. Disease severity assessment ......................................................................................... 21

2.7. Disease management......................................................................................................... 23

2.7.1. Host plant resistance..................................................................................................... 23

2.7.1.1. Adult plant resistance ............................................................................................. 23

2.7.1.2. Seedling resistance ................................................................................................. 25

2.7.2. Cultural ......................................................................................................................... 26

2.7.3. Biological ..................................................................................................................... 27

2.7.4. Chemical....................................................................................................................... 27

3. MATERIALS AND METHODS ........................................................................................... 29

3.1. Description of the survey areas ....................................................................................... 29

3.1.1. Sampling method and strategy ..................................................................................... 29

3.1.2. Diseases assessment ..................................................................................................... 30

3.1.2.1. Disease prevalence (%) .......................................................................................... 30

x

3.1.2.2. Disease incidence (%) ............................................................................................ 30

3.1.2.3. Disease severity ..................................................................................................... 31

3.1.2.3.1. Disease severity index .................................................................................... 31

3.1.3. Agronomic data ............................................................................................................ 31

3.1.4. Field elevation and coordinates .................................................................................... 31

3.2. Identification of Septoria tritici isolates ........................................................................... 32

3.2.1. Sample collection ......................................................................................................... 32

3.2.2. Direct Method of Isolation ........................................................................................... 32

3.2.3. Preservation of isolates................................................................................................. 33

3.2.4. Microscopic identification............................................................................................ 33

3.3. Determination of isolates variability ............................................................................... 33

3.3.1. Morphological variability ............................................................................................. 33

3.3.2. Virulence Variability .................................................................................................... 34

3.3.2.1. Description of differential lines ............................................................................. 34

3.3.2.2. Raising seedling of differential lines ..................................................................... 34

3.3.2.3. Inoculum multiplication ......................................................................................... 34

3.3.2.4. Inoculation ............................................................................................................. 35

3.3.2.5. Disease assessment on wheat differential lines ..................................................... 36

3.3.2.6. Virulence identification, variation and aggressiveness analysis ............................ 36

3.4. Evaluation of seedling resistance to septoria tritici blotch ........................................... 37

3.4.1. Description of wheat varieties ...................................................................................... 37

3.4.2. Raising seedling of wheat varieties .............................................................................. 38

3.4.3. Inoculum multiplication ............................................................................................... 39

3.4.4. Inoculation .................................................................................................................... 39

3.4.5. Disease assessment on wheat varieties......................................................................... 39

xi

3.4.6. Wheat varieties of resistance analysis .......................................................................... 39

3.5. Data analysis ..................................................................................................................... 40

4. RESULTS AND DISCUSSION ............................................................................................. 41

4.1. Assessment of septoria tritici blotch distribution .......................................................... 41

4.1.1. Disease prevalence within zones, districts, and kebeles .............................................. 41

4.1.2. Disease prevalence within different factors ................................................................. 43

4.1.3. Disease prevalence within varieties ............................................................................. 44

4.2. Disease intensity. ............................................................................................................... 46

4.2.1. Disease incidence and severity within zones, districts, and kebeles ............................ 46

4.2.2. Disease intensity within different factors ..................................................................... 49

4.2.3. Disease intensity within varieties ................................................................................. 53

4.3. Association of Disease intensity with altitude, and agronomic practice ...................... 54

4.4. Multiple regression ........................................................................................................... 55

4.5. Identification of Septoria tritici isolates ........................................................................... 56

4.5.1. Symptom and sign based identification ....................................................................... 56

4.5.2. Microscopic identification............................................................................................ 58

4.6. Determination of isolates variability ............................................................................... 58

4.6.1. Morphological variability ............................................................................................. 58

4.6.2. Virulence and virulence variability .............................................................................. 62

4.7. Evaluation of seedling resistance to septoria tritici blotch ........................................... 72

4.7.1. Resistance identification based on pycnidia and necrosis ............................................ 72

5. SUMMARY AND CONCLUSIONS ..................................................................................... 78

6. REFERENCE .......................................................................................................................... 81

7. APPENDICES ......................................................................................................................... 94

xii

LIST OF TABLES

TABLES PAGES

Table 1: Taxonomy of Septoria tritici .......................................................................................... 6

Table 2: Grain yield loss due to Septoria tritici disease of wheat ............................................ 19

Table 3: Modified Rosielle rating scale. .................................................................................... 22

Table 4: Origin and stb genes of differential lines used during the evaluation of pathogenic

variability in Septoria tritici population, in 2020 at DARC ..................................................... 34

Table 5: List of wheat cultivars with their pedigree and evaluated to septoria tritici blotch

at the seedling growth stage, in 2020 at DARC. ...................................................................... 37

Table 6: List and number of gene for virulent isolates used during wheat varieties

evaluation in 2020 in DARC ...................................................................................................... 39

Table 7: Septoria tritici blotch prevalence and double-digit of wheat septoria across by

Zones, and districts in 2019 main cropping season in Oromia region ................................... 41

Table 8: Septoria tritici blotch prevalence and double-digit of wheat septoria across by

kebeles in 2019 main cropping season in Oromia region ........................................................ 42

Table 9: Septoria tritici blotch prevalence and double-digit rating scale by agronomic

practice and fields planted to various cultivars in 2019 main cropping season in Oromia

region ............................................................................................................................................ 45

Table 10: The effect of four zones on disease severity in 2019 main cropping seasons in

2019 in the Oromia region .......................................................................................................... 47

Table 11: The effect of preceding crop on disease incidence in 2019 main cropping seasons

in the Oromoia region ................................................................................................................. 52

Table 12: The effect of growth stage on disease severity index in 2019 main cropping

seasons in the Oromoia region ................................................................................................... 53

Table 13: The effect of plowing frequency on disease intensity in 2019 main cropping

seasons in the Oromoia region ................................................................................................... 53

Table 14: Pearson’s correlation coefficients between disease intensity and agronomic

practice in 2019 main cropping season in the Oromoia region .............................................. 55

Table 15: Multiple regression of disease incidence over agronomic practice in 2019 main

cropping season in the Oromia region ...................................................................................... 56

Table 16: Multiple regression of disease severity over agronomic practice in 2019 main

xiii

cropping season in the Oromia region ...................................................................................... 56

Table 17: Morphological variability of isolates in four zones in 2019 main crop season at

Oromia region ............................................................................................................................. 60

Table 18: Collection area and varieties source of Septoria tritic isolates in 2019 main crop

season at Oromia region. ............................................................................................................ 60

Table 19: Pyicnidia percentage differential lines and virulence categories of Septoria tritici

isolates in 2020 in the DARC..................................................................................................... 66

Table 20: Necrosis percentage by differential lines and isolates of Septoria tritici in 2020 in

the DARC. ................................................................................................................................... 68

Table 21: Reaction of wheat differential lines to the different pathotypes of M. graminicola

based on pycnidia parameter in 2020 at DARC. ...................................................................... 69

Table 22: Reaction of wheat differential lines to the different pathotypes of M. graminicola

based on necrosis parameter in 2020 at DARC........................................................................ 70

Table 23: Pycnidia percentage of necrotic leaf area of wheat cultivars by Septoria tritici

isolates in 2020 at DARC. ........................................................................................................... 75

Table 24: Necrosis percentage of leaf area of wheat varieties covered by an isolate of

S.tritici in 2020 main crop season at DARC. ............................................................................. 76

xiv

LIST OF FIGURES

FIGURES PAGES

Figure 1: Septa of Septoria tritici (Source: Eyal et al., 1987) ..................................................... 7

Figure 2: Pycinidium, and pycidiospores of Septoria tritici (Source: Eyal et al., 1987) .......... 8

Figure 3: Pseudothecium, asci, and ascospores of Mycosphaerella graminicola (Source: Eyal

et al., 1987) ..................................................................................................................................... 9

Figure 4: The life cycle of Septoria tritici on wheat Source: Ponomarenko et al., 2011 ........ 12

Figure 5: Symptom of Septoria tritici on wheat ........................................................................ 13

Figure 6: Saari-Prescott (0-9) scale for appraising the intensity of foliar disease in wheat

(Eyal et al. 1987) .......................................................................................................................... 22

Figure 7: Modified Rosielle rating scale. Source: Richard (2011) .......................................... 23

Figure 8: Geographical locations of the different wheat septoria tritici survey zones in 2019

main crop season in the Oromia region .................................................................................... 29

Figure 9: The main protocol for isolation of isolate from the leaf at Holeta National

Biotechnology Agricultural Research Center (HNBARC): A. Placement of leaf segment on

a filter paper, B. Observation and digging of pycnidia embedded in the epidermis of leaves

in 2019-2020 at HNBARC .......................................................................................................... 33

Figure 10: The protocol for inoculums multiplication: A. Picking up of pure colony and

placing into 100-ml Erlenmeyer flasks, B. Mass incubation of inoculum in an orbitary

shaker in 2020 at DARC ............................................................................................................. 35

Figure 11: The protocols for inoculation of spores on wheat varieties to evaluate the

resistance in the greenhouse at DARC, Ethiopia; A. Inoculums suspension of each Isolate,

B. 10 µl inoculums addition into each of the two furrows of the hemacytometer,

C.Quantifinng of the spore from 25 groups of 16 small square, D and E. Spore inoculation

on wheat varieties in 2020 at DARC ......................................................................................... 36

Figure 12: Ziv-Eyal rough scale for estimating pycnidial coverage and FAO percent for

estimating of wheat septoria necrosis. ....................................................................................... 36

Figure 13: Septoria tritici blotch incidence, across four zones in 2019 main cropping season

in Oromoia region ....................................................................................................................... 48

Figure 14: Septoria tritici blotch disease intensity across districts in 2019 main cropping

season in Oromoia region ........................................................................................................... 48

xv

Figure 15: Septoria tritici blotch intensity in across the 36 kebeles in 2019 main cropping

seasons in the Oromoia region ................................................................................................... 49

Figure 16: Effects of agronomic and crop growth stages on disease intensity in 2019 main

cropping seasons in the Oromoia region ................................................................................... 52

Figure 17: Cultivars effect on disease intensity, in 2019 main cropping seasons in the

Oromoia region ........................................................................................................................... 54

Figure 18: A. Pycnidia of S.tritici, B and C. Macropycnidiospores and micropycnidiospores

of Septoria tritici (Own, 2020), D. Pycnidiospores of Septoria nodurum (Source: Eyal et al.,

1987) in 2020 at DARC. ............................................................................................................. 58

Figure 19: The geographical location of wheat Septoria tritici isolates in the 2019 main crop

season in the Oromia region....................................................................................................... 62

Figure 20: Dendrograms clustered of Mycosphaerella graminicola isolates based on

virulence variation of pycnidia parameter. The dendrogram clustered the isolates in this

order 1, 2, 5, 10, 17, 7, 12, 11, 16, 14, 18, 19, 8, 9, 6, 13, 3, 4, and 15 at similarity level of 92.7

in 2020 at DARC. ........................................................................................................................ 71

Figure 21: Dendrograms clustered of Mycosphaerella graminicola Isolates based on

virulence variation of necrosis parameter. The dendrogram clustered the isolates in this

order 1, 2, 9, 8, 6, 11, 20, 19, 21, 13, 14, 18, 22, 15, 12, 7, 10, 3, 4, 5, 17, 16, and 23 at

similarity level of 94.5 in 2020 at DARC. .................................................................................. 72

xvi

LIST OF TABLE OF APPENDIX

Appendix table 1: Nested ANOVA table for the disease intensity of wheat septoria in major

wheat in 2019 main crop season at Oromia region. ................................................................ 94

Appendix table 2: ANOVA table for disease intensity of wheat septoria among fixed effect

in 2019 main crop season at Oromia region. ............................................................................ 94

Appendix table 3: ANOVA table for disease intensity of wheat septoria for multiple

regression of four-factor in 2019 main crop season at Oromia region. ................................. 94

Appendix table 4: ANOVA table for pycnidia and necrosis on differential lines in 2019

main crop season at Oromia. ..................................................................................................... 94

Appendix table 5: ANOVA table for pycnidia and necrosis on wheat varieties in 2019 main

crop season at Oromia region. ................................................................................................... 95

xvii

LIST OF FIGURE OF APPENDIX

Appendix figure 1:The protocol for the double-digit disease measurement: A and B.

Throwing of the quadrant and random taking of the plant and observation of symptom on

wheat, C. Measuring the upward movement of the disease on wheat, D. Observation of the

disease severity on the upper four leaves from where the disease reaches, E. The

measurement method was produced by Eyal(1987), in the 2019 main crop season at

Oromia. ........................................................................................................................................ 96

Appendix figure 2: Overview of the growth forms and color of some virulent isolates of

wheat Septoria tritici on PDA in 2020 at DARC. ...................................................................... 97

Appendix figure 3:The four colors of Ethiopian Wheat Septoria tritici isolates on PDA. A.

Pinkish color, B. Whitish color, C and D. Brown color, E and F. Black color in 2020 at

DARC. .......................................................................................................................................... 98

Appendix figure 4: Random placement of wheat differential lines seedlings in the

greenhouse chamber in 2020 at DARC .................................................................................... 98

Appendix figure 5: Random placement of wheat varieties seedlings in the greenhouse

chamber in 2020 at DARC. ....................................................................................................... 99

Appendix figure 6:The inoculums suspension of 43 isolates for inoculation in 2020 at

DARC. .......................................................................................................................................... 99

Appendix figure 7: Inoculation of differential lines with isolates of wheat Septoria tritici in

2020 at DARC. ........................................................................................................................... 100

Appendix figure 8: Making the high humidity by putting in the darkroom for 48 hours of

the inoculated seedling in 2020 at DARC. ............................................................................. 100

Appendix figure 9: The response of wheat varieties to Septoria tritici isolates in 2020 at

DARC. ........................................................................................................................................ 101

Appendix figure 10:Reaction of S.tritici on wheat varieties. A. Chlorosis around the dead

tissue and sunken lesions at leaf margin on Arendeto varieties, B. The first variety is

Hidasse which is susceptible (99.5%), the second variety is Wane which it also susceptible

(99.5%) and the third variety is Danda’a which is resistant (0.5%) severity for EtAm-23

virulent isolate, C. The responses of flame*longbow wheat cultivar to M.graminicola

isolates (Source: Brading, 2002) in 2020 at DARC. ............................................................... 103

xviii

Distribution, Intensity and Variability of Septoria Blotch (Septoria tritici) in Central-

Southeastern Oromia, Ethiopia and Seedling Resistance of Wheat Cultivars

ABSTRACT

Septoria tritici is a hemibiotrophic disease that causes a significant yield loss of wheat crops

including in Ethiopia. Knowing of the pathogen population structure and host resistance is very

important for manipulating effective and management strategies to control the disease. In

Ethiopia, studies on genetic, microscopic/ macroscopic such as pycnidiospores, ascospores and

colors variability of pathogen and horizontal/ vertical resistance are greatly lost. Therefore, this

study was intended to assess the current distribution, intensity, variability of wheat septoria

tritici and the reaction of bread and durum wheat cultivars against virulent isolates. A wheat

disease survey was carried out in major wheat-growing zones, districts, and kebeles of Oromia

by using a purposive multi-stage sampling method, and these random/fixed effects were

arranged by three stage nested design. The morphology and virulence variability study was done

based on the colors, growth, and texture colony of isolates and clusters/pathotypes analysis. The

isolates virulence and cultivars resistance were analyzed by using the LSD method. Forty-three

isolates were analyzed for virulence variability and thirty two wheat cultivars were evaluated for

seedling resistances. The treatements were arragenged in factorial CRD in three replications.

The assessments were done in 108 farmer fields. The study revealed % disease prevalence was

high:- 88.9-100, 90-96.6, 90.2-100, 81.2-97.8, 55.6-100, 80.8-100, 75-100, and 0-100 by zones,

altitude, weed infestation, type of cropping, plowing frequency, growth stage, cultivars, and

preceding crops, respectively. The plowing frequency showed a significant effect on disease

intensity. Preceding crop and altitude showed a significant effect on disease incidence and

zones, weed infection level, and growth stages on disease severity (P<0.05). % incidence was

high: - 87.4- 98.9 by zones and 100% sustained in Adaba, Dodola, Tokekutaye, Welmera,

Sinana, Goba, and Agarfa districts. Morphologic characterization of Forty four isolates showed

a clear difference between those isolates and between/within zones. Forty four isolates plated on

PDA were differentiated into four colors namely:-pink, white, brown, and black of which the

latter color was the most predominance with 63.6%, and followed by brown with 18.2% and

three textures, cream, moderate, and a very dough texture were registered. Significant

isolates*differential lines interaction (P<0.001) was recognized and isolates grouped into

virulent, and avirulent based on the percentage of necrosis and pycnidia. Furthermore, the

hierarchical classification/ differential selection of forty three isolates gave 19 and 23

clusters/pathotypes based on pycnidia and necrosis, respectively confirming pathogenic

variations of isolates. Significant cultivars *isolates interaction (P<0.001) was recognized and

cultivars grouped into resistant, and susceptible based on the percentage of necrosis and

pycnidia. Twenty-five wheat cultivars showed the high spectrum of resistance reaction and out of

those ten cultivars recommended for breeding /molecular program and adult plant resistance.

The virulence variability studies are significant by using isolates*wheat species specificity,

molecular analysis and spore variability. Continues disease assessment should be done for early

disease detection and morphological variability studies are important on different growth media.

Keywords: Intensity, Morphology, Prevalence, Resistance, Septoria tritici, Variability,Virulence,

Wheat

1

1. INTRODUCTION

Wheat (Triticum spp.) is one of the most important and major cereal crops worldwide in terms of

nutritional value, adaptability, and production. It is the leading source of cereal proteins and

primary staple food (Figueroa et al., 2017) and source of food, livelihoods for over 1 billion

people in developing countries (FAO, 2016; FAO, 2017b; CSA, 2017).

The ideal daily temperature for a different stage of wheat development varies from 20-25 0 C for

germination, 16-20 0 C for good tillering, and 20-23 0 C for proper plant development (Onwueme

and Sinha, 1999). The crop can be grown in most locations where annual rainfall ranges from

250-1750 mm.

Annually, seventy five percent of the wheat grown world-wide receives an average rainfall

between 375-875 mm (Onwueme and Sinha, 1999; Acevedo et al., 2002). Those, high mega

environment adaptability, production and importance of wheat, impose different countries to

produce the crops. Out of different countries, European Union, China (Mainland), India, Russian

Federation, and the United States of America, are the top five countries in terms of wheat

production FOA (2019). In the 2018 production year, worldwide wheat production was estimated

to 757 million tons of which 149 million tons were produced in the European Union. As

estimated by FOA (2019), 133.1 million tons of wheat was produced in Africa of which 8.4

million tons was produced in Nigeria, the largest wheat-producing and a leading country in

Africa.

In Ethiopia, wheat is used as human food, industrial crop, and animal feed (Hailu et al., 1991). It

is an important cereal crop and extensively cultivated in a wide range of altitudes of “Dega” and

“Woina Dega” regions; ranging from 1500 to 3000 m.a.s.l. although, the most suitable area falls

between 1700 and 2800 m.a.s.l (Ethiopan ATA, 2013).

In the 2018 production, 4.5 million tons of wheat was produced in Ethiopia, a leading country in

sub-Saharan Africa (FOA, 2019). Wheat is grown in the high land of Ethiopia and it is one of the

strategic food security and most important ones from cereal crops (Hill and Fuji, 2017). Wheat

ranks 4th next to teff, maize, and sorghum in area coverage and 3rd in total production next to

maize and teff (CSA, 2018). The largest wheat area coverage and production is in Oromia

National regional state. In the 2017 cropping season, about 5.7milion ha was cultivated and 1.5

million tons of wheat produced in the Oromia region (CSA, 2018). But, the national average

2

yield of wheat in Oromia was 3 t/ha (CSA, 2018) which is lower than the world's average yield

of 3.65 t/ha (FAO, 2017a: FAO, 2017b).

The genetic yield potential of wheat is hindered due to the prevalence of abiotic and biotic

production constraints (Haile et al., 2012). Nutrient deficiencies (poor soil fertility), drought

(moisture stress), waterlogging, climate change (extreme temperature), and low adoption of new

agricultural technologies are major wheat yield-reducing of abiotic factor types. Out of the biotic

factors, fungal diseases are the most important constraints (Abebe et al., 2012). Stem, Stripe, and

Leaf rusts, Septoria leaf blotches, Fusarium head blight, Tan spot, Smut, and Powdery mildew

are the most important diseases on wheat (Ayele et al., 2008). The former three diseases and the

latter are characterized by biotrophic nutrient absorption while the remaining has necrotic food

habit.

The causal agent of septoria tritici blotch is Mycosphaerella graminicola and Septoria tritici for

sexual state and asexual state, respectively (Quaedvlieg et al., 2011). Severe outbreaks of STB

have been reported in many countries (Ahmed et al., 1995; Chungu et al., 2001; Hardwick et al.,

2001), and the disease affects both the quality and quantity of wheat thereby reducing yield by

more than 40–50%, especially in areas with relatively high rainfall and moderate temperatures

(Eyal, 1981; Berraies et al., 2014; Fones and Gurr, 2015). The importance of STB increasingly

faced since the early 1970s, possibly due to a combination of improved genetic control of wheat

rusts and the promotion of conservation tillage that supports the over summering of M.

graminicola (Mergoum et al., 2007).

The occurrence of septoria tritici blotch was documented by Stewart and Dagnachew (1967) in

Ethiopia for the first time. A 25% yield loss was observed at Debre Zeit ARC with a high level

of septoria infection, especially on semi-dwarf varieties (Dagnachew, 1969). Nowadays, septoria

tritici blotch became the most important disease-causing 30-50% yield loss on wheat (Said and

Husain, 2016; Yitagesu et al., 2018) and 41% and 29% yield losses on susceptible and resistant

cultivars (Said and Husain, 2016). Again, the other finding demonstrates that without

management practice such as chemical control septoria disease causes up to 1.7t/ha yields loss

on wheat production in the central part of Ethiopia (Yitagesu et al., 2018).

The Septoria tritici importance is measured not only by yield losses but also by the disease

intensity in wheat crop and distribution in various agro-ecologies characterized by different areas

of wheat production types. Disease intensity varied from location to location and from season to

3

season and within a location in the highlands of the central part of Ethiopia (Ayele et al, 2008).

100% disease prevalence reported in North Gonder, East Shoa, and North Shoa zones in the

summer season (Asfawu et al., 2017; Yitagesu et al., 2018) and in the same manner 100%

disease prevalence reported in Bale zone during Belg season (Kasa et al., 2014). The disease is

high in high humidity, altitude, and moderate temperature environments (Asfawu et al., 2017).

The classical disease triangle suggests, a virulent pathogen is one of the components required for

the disease to occur, thus, a high disease epidemic is expected from the area of a high virulent

pathogen, susceptible host, and favorable environment combined over time and space. Due to

this virulence of Septoria tritici have been studied in the wheat-Septoria tritici pathosystem at

different times. The pathogen population structure studies of wheat Septoria tritici disease

illustrate that there is a presence of high virulence variability in Septoria tritici population (Eyal

and Levy, 1987; Kema et al., 1995; Kema et al. 1996a; Brading et al., 2002). Medini and Hamza

(2008) identified Tunisia, Algeria, and Canada Septoria tritici isolates virulence variation based

on the selection of wheat differential line and they suggested that there is great variability of

isolates virulence in those countries. In the area of different wheat varieties was cultivated high

virulence variability of isolates observed (Medini and Hamza, 2008). Limited samples of isolates

from limited areas, eleven isolates was collected from seven locations have suggested the

presence of high virulence variability in Septoria tritici population in Ethiopia (Kema et al.,

1996). The high diversity of the phenotypic and genotype of the pathogen on different media

growth reported (Harrat and Bouznad, 2018). However, phenotypic and genotype deduction of a

pathogen is very inadequate in Ethiopia.

The importance, high distribution, and virulence variability of Septoria tritici have been forcing

the scientist to conduct studies on disease management options (Torriani et al. 2009). Septoria

tritici is managed by agronomical practices, varietal resistance, and chemical option (Zhan et al.,

2006). But, frequent fungicides applications results in fungicide resistant pathogen that then

reduces the efficacy of fungicides (Eyal et al., 1987; Zhan et al., 2006) and has negative effects

on environments, human and animal health. Resistance breeding in wheat to STB that operates

based on pathogen variability is an effective, economical, and environmentally safe strategy for

disease management (Ferjaoui et al., 2011; Brown et al., 2015).

In Ethiopia, Eshetu (1985) was not gained the high level of wheat varieties resistance but, Yeshi

et al., (1990) invented bread wheat expresses partial and tolerance resistance than it expresses a

4

high level of resistance. Kebede and Payne (2000) identified six resistant bread wheat genotypes.

Ayele (2008) failed to identify genotypes with satisfactory resistance. Teklay (2015) evaluated

200 bread and durum wheat varieties under natural epidemics and reported that all genotypes

were susceptible except some breeding lines.

The disease is dynamic due to climate change, pathogen variability, and resistance breakdown in

time and space. Thus, regular STB intensity, pathogen variability survey, and resistance sources

identification and incorporation of effective resistance genes to high yielding cultivars is a major

strategy for sustaining wheat production in Ethiopia. Therefore, the present work was carried out

to attain the following objectives.

General objectives

Wheat Septoria (Septoria tritici) assessment, a variability of pathogen population in

Central-Southeastern of Oromia, Ethiopia and evaluation of wheat cultivars seedling

resistance.

Specific objectives

To quantify STB distribution and intensity from Central-Southeastern of Oromia,

Ethiopia

To determine morphologic variability of Septoria tritici population in Central-

Southeastern of Oromia

To determine a pathogenic/virulence variability of Septoria tritici population in Central-

Southeastern of Oromia

To evaluate seedling resistance of wheat cultivars to Septoria tritici

5

2. LITERATURE REVIEW

2.1. Origin of the wheat (Triticum spp.)

Fertile Crescent is a geographic range for the determination of the origin of wheat whose core is

within Central Asia and extends to Northern Africa through the Mediterranean (Harlan, 1981).

Wheat is mainly ancient of domesticated crops, with archaeological evidence of the cultivation

of various species in the Fertile Crescent dating back to 9,600 B.C (Feldman, 2008). Southeast

Asia region is the ancestral homeland of wheat (Vavilov et al., 1992). The place of origin is the

area known in early historical times as the Fertile Crescent a region with rich soils in the upper

reaches of the Tigris-Euphrates drainage basin” (Marshall, 1987). Wheat is grown in Nile Valley

around 500 B.C. and extended through India, China, and England during the same time (Jenkins

and Margan, 1969). East of the Mediterranean must have been the birthplace of wheat (Kiple,

2001).

2.1.1. Importance of the wheat (Triticum spp.)

Wheat is the most important for human being directly as economic gain, and diets. The indirect

importance of this crop is fodder for livestock. It is the source of proteins and is consumed as

40% of cereal crops (Hanson et al., 1982). Wheat is used for bread, macaroni, cakes, pasta,

cookies beer, as animal fodder, and for fermentation to make alcoholic beverages such as beer

and liquors (Tsegaye and Berg, 2007). Also, the carbohydrates, protein, and vitamins B and E

content of wheat are high. In the world, it is the source of calories for over one billion people.

Wheat is the important stable food crop in Ethiopia (CSA, 2017) and crop is cultivated for

various purposes including for food (bread, biscuits, pasta, macaroni, “dabokolo”, “genfo”, and

“kinche”), animal feed and income generation (Abera et al., 2015; Fanos and Gurr, 2015;

Tewodros et al., 2016).

2.1.2. Wheat production constraints

The genetic potential of wheat is hindered on account of biotic, abiotic, socio‐economic, and

these related to crop management factors. Drought (moisture stress), nutrient deficiencies (poor

soil fertility), waterlogging, climate change (extreme temperature), and low adoption of new

agricultural technologies are the pressure on the wheat production (Zegeye et al., 2001). In the

6

same, soil fertility and moisture stress are the main wheat production abiotic factors in Ethiopia

(Haile et al., 2012).

Of the biotic stress, diseases caused by fungal are among the most important hampering wheat

production. Stem rust (P. graminis f.sp. tritici), Yellow rust (Puccinia striiformis f.sp. tritici),

leaf rust (P. triticina), and Septoria diseases especially Septoria tritici blotch is prevalent

throughout the country (Eshetu, 1985). Again, out of these diseases, Septoria tritici blotch (STB)

caused by Septoria tritici is one of the major leaf diseases (Mengistu et al., 1991; Abraham et al.,

2008; Ethiopian ATA, 2013). From the foliar fungal disease, Septoria tritici blotch caused by

Mycosphaerella graminicola is the most important yield losses in durum and bread wheat. This

disease became a major challenge for bread wheat production following the exhaustion of the

resident germplasm in favor of the high-yielding, semi-dwarf, and current cultivars. The high

genetic diversity of the pathogen and its specialization features (durum vs. bread wheat) slowed

down the valuable resistance genes and causes the varieties of susceptible materials (West

Lafayette et al., 2012).

2.2. Classification of the Septoria tritici

Septoria tritici formerly called as Mycosphaerella graminicola or Septoria tritici (Vallet et

al., 2015) is a species of filamentous fungus that belongs to kingdom Mycota Phylum of

Ascomycota, Class Dothideomycetes (Testa et al., 2015) in the family Mycosphaerellaceae,

Genus.

Table 1: Taxonomy of Septoria tritici

Classification Nomenclature of Septoria tritici

Kingdom Fungi

Phylum Ascomycete

Class Dothideomycetes

Order Dothideales/ Caphnodiales

Family Dothideaceae

Genus Mycosphaerella

Species M. graminicola (FOckel) Schroeter

Disease Septoria tritici blotch

Pathogen Mycosphaerella graminicola

Host Bread wheat (Triticum aestivum L.), Durum wheat(T. turgidum L ssp.durum)

Source: Testa et al., 2015

7

2.3. Biology of the Septoria tritici

2.3.1. Asexual reproduction

Asexual propagation of the pathogen takes place by simple division of cells and this propagation

is called pycnidiospores. Asexual propagation is slight, elongated, hyaline, and enclosed within a

pycnidium. Asexual spore (conidia) is produced inside of a specialized structure in pycnidia. The

morphology of these asexual spores is threadlike and hyaline (clear). Each spore contains 3-7

indistinct septa. Spores (conidia) of M. graminicola able to germinate in free water from one or

both ends and intermediary cells. During germination, they exude from pycnidia in cirrhi (slimy,

tender like spore masses) which typically white to buff. They’re capable of many cycles of

asexual reproduction during the growing season (Ponomarenko et al., 2011).

2.3.1.1. Vegetative growth and morphology of pathogen

Septoria tritici is grown vegetatively in three forms (Sanderson et al., 1985). The most common

cell type, grown in laboratory conditions, is the macropycnidiospore with 3-5 septa (figure1).

Macropycnidiospore form has regularly referred at the ‘‘Yeast-like’’ stage. But, yeasts are uni-

cellular, macropycnidiospore are multi-cellular structures. The individual cells within this multi-

cellular structure are 1.5–3.5 µm wide and can be up to 40–100 µm long (Sanderson et al.,

1985). The germination of Macropycnidiospores is from the tip (end). This germination process

is the extending of tip growth to form thin hyphae, consisting of very elongated cells.

Figure 1: Septa of Septoria tritici (Source: Eyal et al., 1987)

The second vegetative growth form of M. graminicola is micropycnidiospores without small

8

septa ( ͂ 1µm wide, 5–10 µm long) and uni-cellular structures (Eyal et al., 1987). Therefore, they

fit the definition of‘‘Yeast-like ‘growth form. These cells are formed by lateral budding from

hyphae or macropycnidiospores. Both spore forms are equally able to infect wheat.

The other morphology form of M. graminicola which not use for infection is Pycnidia. Pycnidia

are asexual fruiting bodies, which neither macro- nor micropycnidiospores are dormant, and are

dispersed by rain splash (Sanderson et al., 1985). They vary in size, usually ranging from 60 to

200 µm, depending on the fungal strain, density of the infection, and stomata size variations of

wheat cultivars (Sanderson et al., 1985). The pycnidia are embedded in the epidermal and

mesophyll tissue on both sides of the leaf with an opening (ostiole) on top.

Figure 2: Pycinidium, and pycidiospores of Septoria tritici (Source: Eyal et al., 1987)

2.3.2. Sexual reproduction

Ascocarp is the general name of many asci produced in the fruiting body of this pathogen. This

ascocarp has a different form and present at different tissue areas of the host. Pseudothecia (ball

shape) is one of the ascocarp forms of this pathogen. It is produced inside of lesions in the below

of host epidermis and embedded in the protection of tissue- a stroma. A sexual mating system of

M. graminicola requires two compatible partners of opposite mating types to come together to

produce the sexual spores. Sexual fruiting bodies are called pseudothecia. This sexual stage was

identified 130 years later by Sanderson in New Zealand (Medini and Hamza, 2008).

Perithecia are also other forms which it’s a flask-shaped with a pore at its tip, and sub-epidermal

of the plant leaf. Pseudothecia forms a globose, dark brown color. The production of ascospores

appears after the macropycnidiospore or micropycnidiospore infected leaves (Kema et al.,

1996a; Eriksen et al., 2003). This means the sexual reproduction of this pathogen start after

9

asexual spore makes germination.

In the time of ascospores formation, eight ascospores produced in each ascus, and hyaline (clear)

consists of two cells of unequal length. Ascospores eject forcibly from the asci at maturity due to

fluctuations of relative humidity -subsequent moisture (Ponomarenko et al., 2011). The mating

system is heterothallic which means require two compatible partners to produce sexual spores

(Zhan et al., 2002). As two fungal strains of opposite mating type come together, they detect

each other’s presence in response to the mating pheromone produced by unlike mating types.

The homothallic ones are capable of sexual reproduction (Zhan et al., 2002). The two compatible

mating types should be present in the same geographical area at the same point at a time for

sexual reproduction. These two compatible haploid nuclei of different mating types come

together to produce ascospore.

Ascospores formation depends on the meeting of strains of opposite mating types (Kema et al.,

1996b) and, therefore, their appearance depends on the intensity of the epidemics. Ponomarenko

(2011) reported that the fungus has a bipolar, heterothallic mating system; Individuals of mating

types, designated mat1-1 and mat1-2, must come together to affect sexual reproduction.

Figure 3: Pseudothecium, asci, and ascospores of Mycosphaerella graminicola (Source: Eyal et

al., 1987)

2.3.3. The pathogen lifestyle

M. graminicola pathogen has a hemibiotrophic way of life during the infecting of the wheat and

alternative hosts. The pathogen starts its life on the host as a biotrophic in the early infection

process and receives its nutrition from the apoplast around living cells. Then, it kills the adjacent

host cells and becomes necrotrophic during the later stages of infection.

10

M. graminicola is infecting wheat which it characterized by biotrophic and necrotrophic stages

by having five phases (Ponomarenko et al., 2011). The first period in biotrophic stages is the

initial growth of the hyphae on the leaf surface; 0-24 hours after contact and go after by host

penetration via natural openings, the stomata; it takes place within 24-48 hours after contact. The

third phase is, intercellular biotrophic phase as hyphae extend within mesophyll tissue and obtain

nutrients from the plant apoplast; it is within 2- 12 days after contact. During the fourth phase,

M. graminicola made a rapid change to necrotrophic growth related to the appearance of lesions

on the leaf surface and collapse of the plant tissue; within approximately 12-14 days after

contact. To end with further colonization of mesophyll tissue and formation of pycnidia with

conidia in substomatal cavities of senescent tissue can take place within 14-28 days after contact

(Eyal, et al., 1987; Ponomarenko et al., 2011). Though, the time from infection to the production

of pycnidia based, on environmental conditions (moisture, temperature, and light), the cultivar,

and the septoria isolates (Eyal, et al., 1987). For the duration of the necrotrophic stage, the

hyphae mash host cells causing collapse. Activates of a switch from biotrophic to necrotrophic

growth is not known but, it is assumed that the association of a toxin that still hasn’t been

confirmed (Ponomarenko et al., 2011).

2.3.4. Infection process

Under favorable environmental conditions both the sexual ascospores and the asexual

pycnidiospores germinate and penetrate plant tissues after contact of host leaf (Palmer and

Skinner, 2002). Spores land on the leaf then, it penetrates almost completely through stomata

(Cohen and Eyal, 1993; Kema et al., 1996d; Duncan and Howard, 2000). After penetration, the

fungus colonizes the mesophyll tissue of the leaf by growing intercellularly but does not produce

any feeding structures such as haustoria (Palmer and Skinner, 2002). Kema (1996d) found that

fungal hyphae grow prolifically in a susceptible cultivar, while in a resistant cultivar fungal

colonization is restricted. He observed in the susceptible cultivar, condensation of chloroplasts

followed by intense swelling of cells in the process of the host response to soluble compounds

produced by the fungus. In addition to chloroplast alteration, starch granules were also released

from the chloroplasts (Kema et al., 1996d). The role of starch release is not known, but it may be

a response by the plant to prevent further colonization of the fungus (Kema et al., 1996d).

During incompatible interactions, the fungus was restricted to sub stomata chambers and no

11

visible detrimental effect in the surrounding mesophyll cells was observed. This author also

suggested that soluble toxic compounds and pectin-degrading enzymes may be involved in the

pathogenicity of M. graminicola. At the time of compatible interactions, mesophyll cells were

severely affected in advance of the invasion by the fungus and cell collapse occurred within a

short time. Kema (1996d) did not observe papilla formation or thickening of the walls of the

mesophyll cells of the resistant cultivar. The author suggested that resistance does not rely on

defense responses to fungal cell wall-degrading enzymes, but rather on the production of

compounds that prevent fungal colonization and hence, pycnidium formation. Since the growth

of the fungus is strictly intercellular, it has been suggested that intercellular washing fluids need

to be analyzed to help understand the biochemical basis of resistance in this pathosystem (Kema

et al., 1996d).

2.3.5. The life cycle of pathogen

Inoculums (ascospores) and conidia are produced as fruiting bodies (perithecia) on the stubble of

previously infected wheat (Eyal et al., 1987). Also besides, the spores survive during crop free

periods primarily as pseudothecia and pycnidia on crop debris (Eyal et al., 1987; Ponomarenko

et al., 2011; Hollaway, 2014). These inoculums (conidia) are disseminated by rain splash to

leaves of the same or nearby plant and ascospore dispersed long distance by the wind to the crop

nearby, plot, and another field. From fruiting bodies that are produced on the stubble of wheat,

the pathogen starts primary infection (Hollaway, 2014). Ascospore is released by air and conidia

by rain splash (Eyal et al., 1987; Steinberg et al., 2015). When the environment becomes suitable

for the pathogen, ascospore and conidia are germinates on the wheat leaf inoculums lands.

Stomata attract the germ tube and hyphae or aspersorium like structure are entering through sub

stomata cavity and epidermal cells (Ponomarenko et al., 2011; Steinberg et al., 2015). Then,

hyphae colonize the area of leaf infection. Hyphae grow intercellularly then after it changed from

biotrophic to necrotrophic the crop cells collapse, and yellow lesions or blotch symptom is

formed. As cells collapse necrotic areas of the lesions exude conidia in the gelatinous

hygroscopic cirrhi, then from necrotic areas pycnidia are developed (Eyal et al., 1987;

Ponomarenko et al., 2011). In the end, pycnidia become matured and returned to inoculums

(Ponomarenko et al., 2011).

12

Figure 4: The life cycle of Septoria tritici on wheat Source: Ponomarenko et al., 2011

2.3.6. Symptom

The initial symptoms are forms chlorotic color and irregular or elliptical shape along the veins of

the seedling and young leaf. On the mature leaves color change to darker lesion fruiting bodies

and narrow shape form. Septoria leaf blotch is characterized by irregular necrotic lesions

interspersed with small black fruiting bodies (Pycnidia) on the leaves (Palmer and Skinner, 2002)

and stem (Ponomarenka et al., 2011).

These lesions reduce the green leaf area of the plant and which, particularly if present on the

upper leaves during grain filling, can reduce yield (Gooding et al., 2000). Mature lesions contain

black or brown fruiting structures, the asexual pycnidia, or sexual pseudothecia (figure 5).

Pycnidiospores carry by asexual fruiting bodies known as pycnidia; develop within the sub

stomata cavity on wheat leaf tissues which cover with chlorotic and necrotic lesions (Eyal et al.,

1987; Kema et al., 1996; Ponomarenko et al., 2011).

13

Figure 5: Symptom of Septoria tritici on wheat

Source: Ponomarenko et al., 2011

2.3.7. Epidemiology of the pathogen

The epidemics of Septoria tritici blotch of wheat are associated with favorable weather

conditions (frequent rains and moderate temperatures), specific cultural practices, availability of

inoculum, and the presence of susceptible wheat cultivars.

2.3.7.1. Conducive environment

The length of the latent period depends on cultivar and environmental conditions, such as

temperature and leaf wetness, and has been reported to vary from 14 to 21 days at the optimum

temperature (15-20°C) to 40 days at 5°C (Eyal et al., 1987; Shaw, 1990). Long latent periods

also mean that disease control measures may be necessary sometime before serious symptoms

occur (Viljanen-Rollinson et al., 2005). Infection by S. tritici is highly temperature-dependent

and requires rather cool, wet conditions to occur. If conditions are favorable, the infection will

occur at any stage of plant development. However, because of the temperature and moisture

requirements, infections by S. tritici are most common in early to mid-season when temperatures

14

are coolest. Infections usually start in the lowest portions of plants and move upward until, and

if, high temperatures become limiting (Lucas, 1998). Infection requires at least 6 hrs of wetness

(up to 16 hrs for S. nodorum), and secondary spores are produced in lesions within 10-20 days.

The activity of S. tritici is favored by temperatures between 15-20°C. Because of this specific

temperature and moisture requirements, wet, windy weather favors epidemics of leaf blotch,

while dry weather tends to slow or completely halt disease development (Hershman, 2012).

After infection conidia have pycnidia which spread into local due to rainfall splash. Because of

the splashing dispersal mechanism, exposed plants are often infected to a higher degree than

plants closely surrounded. Therefore, observing disease levels on plants on field borders usually

indicates the greatest infection level at a particular time during plant growth. Open areas within

the field that result from leaf out during machine sowing are also good areas to observe disease

occurrence. Rain-splashed pycnidiospores are transported vertically upward from the base of the

crop to the upper leaves where they germinate and penetrate through the stomata and course

infection. In areas facing the rain, the splashing effect is increased because the penetration of

drops is undisturbed. Long rain fewer intervals with high temperatures often interrupt Septoria

tritici blotch progress from lower infected leaves to the upper plant part (Eyal et al., 1987). The

secondary spread from conidia/ ascospore is effective for epidemics when the humidity high and

particularly if free water on the leaf. Ascospores discharges depend upon various environmental

factors such as rain duration and intensity, temperature, and wind. The symptoms are usually

developed under the strong influence of environmental conditions which are moisture, optimum

temperature, and light (Lovell et al., 2004). During growing season S.tritici can produce several

sexual cycles and ascospore generation (Kema et al., 1996).

The fungi survive on wheat stubble and other wheat residues and volunteer wheat plants. They

survive from one crop to the next as mycelium in living, volunteer plants, or as pycnidia on

wheat residues. The fungi can survive up to three years in the wheat stubble on the soil surface

(Patric and Dannis, 2012). Debris from heavily infected leaves and stems remains in fields after

harvest to produce inoculum for the next growing season (Eyal et al., 1987; Ponomarenko et al.,

2011). The fungi survive from year to year (overwinter) in the diseased wheat straw of previous

crops, volunteer wheat diseased seed, and other susceptible grasses. In seed, the fungi can remain

viable for a year or more. In infested straw, the fungi can remain viable for as long as three years.

Overwintered sources of the fungi provide spores (inoculum) for infection of the next wheat crop

15

grown. Spores that are produced from overwintered sources, as well as secondary spores

produced inactive lesions, are relatively resistant to adverse (dry) conditions because of a

protective coating. Spores of S. tritici can remain dormant for months at temperatures of 2.8-

10°C (Hershman, 2012). Thus, spores can be produced, blown, or splashed to wheat and remain

dormant on plant tissue until conditions become favorable for infection.

2.3.7.2. Susceptible host

The usual vertical progress of septoria from lower to upper leaves is affected by the distance

between consecutive leaves the "ladder effect." The distances between the first emerging three to

four leaves are similar for short and tall cultivars. On tall varieties, the distance between each

leaf is greater toward the flag leaf. In the dwarf cultivars (70-90 cm), the closeness of the upper

leaves to the lower leaves facilitates contact between newly emerging leaves and splashed

pycnidiospores. Movement of the pathogen from infected lower leaves is thereby made simpler.

As a result, pycnidia often appear earlier on upper plant parts of dwarf cultivars than they do on

leaves of taller cultivars. Thus both resistance- and morphology-related genetic factors influence

disease spread and resulting severity. Under severe epidemics, the differences in plant

architecture and stature of susceptible cultivars are of no importance to the pathogen. In

moderate to light epidemics, however, upper plant parts of dwarf cultivars are more receptive to

the pathogen than taller wheat as they are nearer to inoculum sources (Eyal, 1971). In wheat-

growing regions where septoria pathogens are a potential danger, plant architecture, especially

leaf placement, should be taken into account when new wheat cultivars are to be released.

2.3.7.3. Inoculums

Initial inoculum usually consists of airborne ascospores/conidia, which they cause the primary

infections on seedling leaves. Primary infections from an ascospore spell of rain will occur

consistently over a crop and give rise to lesions that bear pycnidia, the asexual structures that

allow for rapid dispersal of the secondary inoculum, is conidia (Eyal, 1999; Ponomarenko et al.,

2011). The secondary spread of STB is by conidia/ ascospores, which form readily in high

humidity, particularly if there is free water present on the leaves. Pycnidia with conidia are

produced roughly 14 to 40 days after infection, depending on the host and seasonal conditions.

These spores disperse through rain wash and splashing, causing the local spread of the disease to

16

uninfected leaves of the same and nearby plants. Production and dispersal of conidia occur quite

rapidly compared to pseudothecia with ascospores, which take several weeks until ripening. Thus

both conidia and ascospores contribute to the epidemic but the asexual cycle seems to dominate

during the growing season. The production of pseudothecia and spread from ascospore takes

time than that of the production and spread of pycnidia from conidia but pycnidia spread is takes

place within a short time (Eyal et al., 1987; Ponomarenko et al., 2011).

Ascospores can be airborne over large distances, while conidia are unlikely to travel far from

their site of origin by rain-splash dispersal. Conidia help to spread the disease upwards through

the canopy. Rain splash of conidia can lead to disease foci, which can give a patchy appearance

to the overall disease distribution in a field. A more uniform appearance of the disease is typical

when the airborne ascospores are plentiful during the initial infection (Ponomarenko et al.,

2011). Many cycles of sexual and asexual reproduction during the growing season allow

epidemics to develop rapidly.

2.3.8. Host range

There is no touchable fact reported on the alternative host of septoria disease. Sprague (1950a)

reported that S. tritici was a pathogenic to wheat and several kinds of grass as well. Hilu and

Bever (1957) suggested that S. tritici overwinters on alternative hosts, particularly on wild

grasses. Also besides, there are different plants reported as alternative hosts for overwintering of

S. tritici are; Bromus spp., Agrostis spp., Agropyron spp., Brachypodium spp., Dactylis spp.,

Festuca spp., Glyceria spp., Hordeum spp., Poa spp., Secale cereal, and Triticum spp (Eyal,

1987). However, no tangible evidence has been provided to support this hypothesis.

Weber (1922) obtained isolates of S. tritici from Triticum aestivum, Secale cereal, and Poa

pratensis, each of which was pathogenic on its host but not on the other cereals or wild grasses

tested. Seifbarghi (2009) described that Septoria species are pathogenic only on their host plant,

showing a very narrow host range. S. tritici isolates from bread wheat pathogenic only on T.

aestivum, T. dicoccum, T. durum, and T. compactum, but not on other cereals and grasses.

Septoria passerinii isolated from Hordeum vulgare and H. distichon. Isolates from Hordeum

only infect species and varieties of the genus Hordeum, but no other cereal or grass species.

17

2.3.9. Physiological specialization of M. graminicola

The virulence variability means the pathogen difference by causing of disease on the crop. M.

graminicola is a pathogen of wheat crop in which a different idea reported on its pathogenic

ability. The pathogenicity difference of a pathogen on wheat is a debatable idea for many years.

Some researchers suggested that there are no true or differences in the virulence of isolates, and

the only differences are in their degree of pathogenicity (aggressiveness). Marshall (1985)

reported that M. graminicola isolates collected from some part of the location is more aggressive

than other locations. Those isolates collected from 16 locations and testes on spring and winter

wheat cultivars and suggested that isolates from some parts of California, Indiana, and Ohi are

more aggressive than from isolates of other countries. Van Ginkel and Scharen (1988) collected

34 isolates of M. graminicola from different countries and testes on 13 durum wheat and one

bread wheat accessions. They found that only the disease severity but not cultivar*isolate

interaction, and suggest that the isolates varied in aggressiveness and the cultivars varied in race

non-specific resistance.

Van Ginkel and Rajaram (1995) suggested that under natural field conditions the difference

between pathogen populations is aggressiveness rather than virulence. But, the isolate virulence

variation is reported among the pathogen population (Eyal et al. 1973; Kema et al. 1995; Kema

et al. 1996a; Medini and Hamza, 2008). For the first time, the virulence difference of the

pathogen population was reported in Israel by Eyal (1973). In (1985), Eyal evaluated 97 isolates

of M. graminicola on seedlings of 35 wheat and triticale cultivars by collecting them from 22

countries. He found significant isolate x cultivar interactions and indicates the existence of the

specificity gene among cultivar and virulence genes among isolates. Later, in (1995), Kema

study the pathogen virulence variation among 78 isolates of M. graminicola on 22 differential

cultivars at the seedling and adult plant stages. Medini and Hamza (2008) studied the pathogen

population diversity based on differential lines selection. This study showed that there is an

interaction between Tunisia, Algeria, and Canada isolates with wheat differential lines. Canada

isolates have had high genetic diversity than the two countries isolate. This genetic variation of a

pathogen is correlated with disease severity. The genetic variability of the septoria pathogen is

very high due to the sexual reproduction of the pathogen (Razavi et al., 2003).

The genetic structure expresses the distribution and amount of genetic variation within and

among populations (Razavi et al., 2003). High levels of genetic variability of the pathogen

18

populations were more likely to adapt to resistant cultivars than populations with less genetic

variability (McDonald et al., 1995). Understanding of genetic variability is used for resistant

gene deployments. The local pathogen population that has high pathogenic variation can be

adapted to the resistant genes of wheat. Therefore, wheat has many major resistance genes useful

to control the disease. Genetic structures of pathogen populations have been characterized by

virulence analysis on a set of differential cultivars carrying different resistance genes (Medini

and Hamza, 2008). Ethiopia isolates also evaluated for virulence variation in 1996. Kema (1996)

found that the great virulence (pathogenicity) variation among Arsi and Holeta pathogen isolates.

Temesgen (1999) cited in Ayele (2008) reported that the virulence pattern of Septoria tritici in

our country. Afterward, one of the objectives of the present work was to study the virulence

variation of Septoria stritici isolates currently prevailing in the pathogen population in Shewa,

Bale, and Arsi Zone of Oromia regional state.

2.4. Importance of septoria tririci blotch

Septoria tritici Roberge is a serious leaf-spot pathogen of wheat throughout the world (Eyal et

al., 1987: Ziv et al., 1978). It is particularly important in some European countries and North

America. 40–50% yield loss was caused by the pathogen (Eyal, 1981; Berraies et al., 2014;

Fones and Gurr, 2015); in 1998 in the UK alone, estimated losses were as much as £ 35.5 million

(Hardwick et al., 2001). The pathogen causes premature senescence of leaves, thereby reducing

photosynthetic activity and yield losses have been caused. The pathogen is the most important

disease in Northern, Eastern Africa, and the Middle East (Benbelkacem, 2016).

The occurrence of STB in Ethiopia was documented by Stewart and Dagnachew (1967), Getnet

et at. (1990). A 25% yield loss was observed at Debre Zeit ARC with a high level of septoria

infection, especially on semi-dwarf varieties (Dagnachew, 1969). In a field experiment

conducted at Holeta ARC, 82% grain yield loss was recorded due to this disease under natural

infection (IAR, 1971). Currently, in Ethiopia, a significant yield loss is caused by Septoria leaf

blotch (Kasa et al., 2015; Said and Husain, 2016; Yitagesu et al., 2018).

At different growth stages of wheat and without chemical control, a pathogen caused a

considerable yield reduction (Kasa et al., 2015; Said and Husain, 2016; Yitagesu et al., 2018).

None of the varieties completely resistant to the Septoria but have different degrees of resistance

(Teklay et al., 2015).

19

Grain yield loss was recorded at critical points and multiple points (Said and Husain, 2016).

Alidoro and Galama varieties were affected at one critical point of the growth but the Gambo

variety was affected at different growth stages (Said and Husain, 2016). Up to 1.72t/ha yield loss

was scored due to Septorial disease without fungicide treatments (Said and Husain, 2016). At

different time intervals of chemical application, the yield of wheat varieties was affected by

septoria disease. Berraies (2014) suggested that a single fungicide application at the booting

stage of the crop is used for controlling septoria disease and increased the susceptible and

resistant varieties yield by 44.34% and 7.31%, respectively. In the other season, in the time of

high disease pressure and the single fungicide application was caused by 50.06% on susceptible

varieties and 8.6% on resistant varieties (Berraies et al., 2014).

Table 2: Grain yield loss due to Septoria tritici disease of wheat

Varieties of difference Yield loss %

41

Source

Said and Husain, 2013.

Gambo

Galama 29

Alidoro 12

Varieties without chemical used

40.6 Gambo

Galama 28.5

Alidoro 11.8

Varieties without chemical used at Holeta Yield loss (t/ha)

1.72

Yitagesu et al., 2019

Alidoro Without tilt

Kekeba Without Moncozeb 1.7

Madawalabu Without MMTT 1.59

Varieties without chemical used at Kulumsa

1.57 Madawalabu

Madawalabu

Without Moncozeb

Without tilt 1.88

Varieties without chemical used Yield loss (kg/ha)

2459

Berraies et al., 2014. Without chemical

Cultural practice Yield loss (kg/ha)

905

Krupinsky et al., 2001 Without nitrogen fertilizer

No-tillage 317

2.5. Distribution of septoria tririci blotch

Out of wheat pathogen septoria tritici blotch is a widely distributed throughout the globe and is a

serious problem in many regions (Jenkins and Margan, 1969). It is also the major problem in

many regions and it has the potential to cause serious loss if environmental conditions are

20

favorable for its spread (Van Ginkkel et al., 1999). STB occurs throughout the world in countries

as diverse as the Mediterranean region, South Eastern and Eastern Africa (including Ethiopia),

Argentina, Iran, Russia, New Zealand, Western Europe, Australia and South and North

Americas. In the USA, Brazil, the Netherlands, the United Kingdom and Australia, the sexual

state (ascospores: Mycosphaerella graminicala) has been identified (Eyal et al., 1987;

(Ponomarenko et al., 2011). STB occurs in wheat producing areas of all continents and results in

serious crop losses in many wheatgrowing regions of the world with crop losses in some areas,

such as North Africa and southern Brazil, being devastating (Zillinsky, 1983).

Different assessment reports have been shown that Septorial disease is distributed in Oromoia,

Amhara, SNNPR, and Tigray region of Ethiopia (Asfawu et al., 2017; Yitagesu et al., 2018). In

the same to this, different survey assessments have been described the pathogen profile based on

agroecology, soil type, cultural practice, management practice such as chemical usage and

varieties.

Septoria disease is distributed in all areas of wheat production in North and North West Gonder

(Asfawu et al., 2017). Different factor plays a role in the occurrence of septoria disease. Those

factors are; Location, varieties, growth (dough stage, flowering stage), biological, physical,

altitude, and soil type Vertisol. 100% disease severity was recorded in North and North West

Gonder of at all six surveyed areas. 34.7% incidence and 75% severity was scored in North

Gonder. Below 2300 m.a.s.l altitude 26% and above 2300 m.a.s.l altitude 54% a disease

incidence was scored. In this case, disease intensity is increased with altitude increment.

In the central part of Ethiopia, wheat septoria distribution profiles were illustrated by (Yitagesu

et al., 2018). From 27 districts, 100% disease prevalence was reported with South-West Shewa,

West Shewa, and North Shoa. This shows that all wheat fields were affected by septoria disease.

The maximum 93% disease severity at South-west Shewa from Becho district and 100%

incidence at west Shewa from Welmera district were recorded. Altitudes of 2589m.a.s.l were the

highest incidence and severity score of 100% and 74%, respectively. This could be a favorable

condition for disease onset, development, and spread. The Authors gave the direction that all of

the varieties at a current time becomes under production and improved varieties vulnerable to

this disease in the central part of Ethiopia (if confirmed by other studies) (Yitagesu et al., 2018).

Furthermore, Ayele et al, (2008) reported that the highland of Shewa is the most common area

for the distribution of Septorial disease. In the case of distribution, there is the variability of

21

disease intensity from the location to location and within the location from season to season.

Some of Bale and Arsi districts are similar by altitude, temperature, and humidity with the

highland of Shewa.

In the area of wheat production, Septorial disease is distributed majorly in favorable

environments for infection and development. So, the disease assessment is necessary for the area

where the current survey is not conducted. The survey of Belg season describes that in the

selected districts, 100% disease incidence, and 22% disease severity was recorded in the Arsi

robe. Also besides, at the Bale zone, 100% disease incidence and 51-83% disease severity was

reported (Kasa et al., 2015). But, the disease needs continuous assessments of its status due to

population structure change by sexual reproduction. Therefore, the present work was proposed

based on this gap and the disease was assessed.

2.6. Disease measurement

2.6.1. Disease severity assessment

Disease severity assessments are important to apply disease control methods, to study the

pathogen, and evaluate genotype for resistance. The selection of a more appropriate assessment

method is necessary.

Necrosis area, pycnidial density, and its combination are used for disease assessment (Cuthbert

et al., 2011). Disease rating is used for disease visual evaluation. The host morphology that

shows the symptom as necrosis of tissue death or apoptosis (Cohen and Eyal, 1993) and the

pathogen shows (pycnidial) on a plant is used for rating. Necrosis during M. graminicola

infection may be due to growth and colonization of the pathogen, or a diffuse host response

(Cuthbert et al., 2011). Histological analysis studies show that minimal colonization of pathogen

resulted in extensive necrosis phenotypes with minimal pycnidia formation (Kema et al. 1996a).

Therefore, the pycnidia presence is used to measure resistant and susceptible reactions to M.

graminicola.

From different visual rating scales, that have been developed and used, the most common rating

scale is a quantitative scale and measures of percent leaf area bearing pycnidia(Kema et

al.,1996a; Chartrain et al., 2009). Eyal and Brown (1976) developed a quantitative scale to

quantify the pycnidial density on leaves using a television scanner. Several studies have been

22

used this scale to estimate pycnidial coverage on four to six upper leaves during the soft dough

development stage. Also besides, Saari and Prescott (1975) developed a scale ranging from 0-9

for evaluating the severity of foliar diseases (except rusts) on wheat, barley, and triticale. Later,

this scale was changed to a double-digit scale (00-99) (Eyal et al., 1987). The first digit (D1) is a

measurement of the height of the disease on the plant (Figure 6) and the second digit (D2) is a

rating of the severity of the disease in percentage (0 = 0%, 1=10%, and 9 = 90%) (Eyal et al.,

1987).

Figure 6: Saari-Prescott (0-9) scale for appraising the intensity of foliar disease in wheat (Eyal et al. 1987)

D1=maximum plant height disease about to with concerning plant height. E. If plant height is

80cm, and the disease reaches 1cm, 2cm. 40cm (half) of the total plant height from the soil,

represent D1 as 1, 2, 3, and 5 in the double-digit disease noting scale respectively.

Percent disease severity index estimated based on the formula by D1/Y1*D2/Y2*100

Sharma and Duveiller (2007) were used the d1or d2 and y1or y2 represents the scoring record

(00-99 scale) and the maximum score on the scale (9 and 9) respectively. Subsequently, d1 or d2

and y1 or y2 represent the scoring record (00-99 scale) and the maximum score on the scale (9

and 9) in that order.

Rosielle (1972) developed a qualitative Septoria tritici blotch rating scale (figure7). The scale

ranges from 0 to 5 and is based on rating the extent of hypersensitive flecking, coalescence of

lesions, and pycnidial density. Later, McCartney (2002) modified this method to ratings 0-

3(chlorosis) as resistant and ratings 4 and 5(necrotic or presence of pycnidia) as susceptible.

Table 3: Modified Rosielle rating scale.

23

Scale(05) Reaction of wheat

0 immune characterized by an absence of pycnidial formation, an occasional

hypersensitive fleck, or no visible symptoms

1 highly resistant with hypersensitive flecking

2 resistant with small chlorotic or necrotic lesions, typically no pycnidial formation

3 intermediate characterized by coalescence of chlorotic or necrotic lesions normally

evident toward the leaf tips and to a lesser extent elsewhere on the leaf blade, very

light pycnidial formation

4 susceptible to the moderate pycnidial formation, coalesced necrotic lesions

5 very susceptible with large, abundant pycnidia, necrotic lesions extensively

coalesced

Figure 7: Modified Rosielle rating scale. Source: Richard (2011)

2.7. Disease management

2.7.1. Host plant resistance

2.7.1.1. Adult plant resistance

The wheat crop has a different mechanism of defense for resistance to septoria disease at the

adult stage. Wheat recognizes a septoria pathogen attack and shows basal resistance as the first

line of defense (Jones and Dangl, 2006). The molecule that wheat can recognize to send basal

defense is pathogen-associated molecular patterns (PAMPs). The other, the defense is a series

(consecutive) of events, termed innate immunity, which is initiated to defend against the

pathogen (Jones and Dangl, 2006). However, the pathogen has various strategies to neutralize

this basal defense, including the delivery of effector proteins into the plant.

These proteins suppress the innate immune response and change the physiological and cellular

24

state of the plant to make it more beneficial for pathogen colonization (Gururani et al., 2012;

Boyd et al., 2013). This process makes the crop to develop and initiate another gene for defense.

Wheat has been used many genes for resistance at the different growth stages. For these types of

genes, the effects are often small individually, but when combined with other APR genes, an

additive effect could be observed. This is where the concept of pyramiding genes has proven

beneficial. One or two APR genes may increase resistance slightly but combining three, four, or

five could have the potential for even more significant resistance. Moreover, for APR gene there

is no gene-for-gene interaction, which means there is no host and pathogen effectors recognition.

Without this interaction, the pathogen cannot easily overcome the host’s defenses making this

type of resistance more durable (Vanderplank, 1984).

Quantitative trait locus (QTL) showed that this type of plant resistance gene was identified on

the chromosome number of 2B and 7B (Arraiano et al., 2007). Also besides, this crop has other

resistance which is synonyms to horizontal resistance. Parlevliet (1979) mentioned the partial

resistance components such as infection frequency, latent period, and spore production and

infection period that retarding the epidemic on wheat. Partial resistance is expressed as a reduced

epidemic development and is supposed to be durable.

Four factors conditioned partial resistance; necrosis and reduction of spore production, lesion

size and latent period together, and the combined effects of infection frequency, incubation

period, and lesion size (Jeger et al., 1983). It is not isolate-specific and is controlled by several

genes or by quantitative traits loci (QTL) (Chartrain et al., 2004). In this case, the severity of

symptoms caused by different strains of Z. tritici varies between wheat cultivars, leading to a

wide range of susceptibility/resistance levels.

In Ethiopia, the varieties screening result showed that almost all wheat genotype is susceptible

out of 200 varieties evaluated and some breeding line resistant to this pathogen in natural

infection (Teklay et al., 2015). Kebede and Payne (2000) screened five advanced lines that have

a resistant gene to this disease. Other host plant resistance studies show that wheat genotype in

our country can’t fully resist rather than partial and tolerant resistance to this disease (Eshetu,

1985; Yeshi et al., 1990; Ayele et al., 2008). However, in Ethiopia, the resistance studies of

wheat varieties at the adult stage (field resistance) are not more studied.

25

2.7.1.2. Seedling resistance

Wheat has a gene for septoria disease resistance at seedling. In contrast to basal defense, wheat

can develop a second line of defense, termed effectors-triggered immunity, where R proteins in

the plant interact with the effector’s proteins in the pathogen. This mechanism is called R gene-

mediated pathogen resistance. The pathogen genes encoding the corresponding effector’s

proteins are often termed avirulence (Avr) genes. The interaction between R and Avr possesses a

gene-for-gene relationship, i.e. a plant containing an R gene is resistant to a pathogen with the

corresponding Avr gene (Gururani et al., 2012). Quantitative trait locus (QTL) analysis, identify

seedling resistance with minor effects on the chromosome of 3BL. QTL with minor and major

effects of a gene in the seedling stage was mapped to Stb6 (Eriksen et al., 2003). Also besides,

QTL for seedling resistance were found the gene for seedling resistance located on chromosomes

1D, 2D, and 7DS(Arraiano et al., 2007).

Seedling resistance is a type of resistance that is controlled by one gene that presents resistance

against a particular race of a pathogen. It is also known as isolate-specific resistance, vertical

resistance, and major gene resistance. Seedling resistance can be responsible for a large amount

of resistance to a particular race of a pathogen in their action, and effective through all plant

growth stages. Brading and his colleagues in 2002 report an isolate-specific resistance of wheat

to septoria tritici blotch suggesting a probable gene relationship. In recent years, 18 major genes

(Stb1 to Stb18) have been identified which confer resistance to Septoria tritici. Specific

resistance is observed during incompatible interactions and is controlled by gene-for-gene

relationships.

Wheat defense mechanism for specific resistance, early expression, before penetration, of host

genes encoding for PR1, chitinases, glucanases, and peroxidases was suggested to contribute to

wheat resistance during incompatible interactions (Adhikari et al., 2007; Yang et al., 2013).

Pathogenesis-related (PR) proteins, reactive oxygen species (ROS) metabolism, cell wall

reinforcement with callose, and signaling via the MAPK pathway are also the defense

mechanism of specific resistance (Adhikari et al., 2007). However, no evidence of hypersensitive

response is reported during the first steps of the Septoria trtitici infectious (Kema et al., 1996).

Generally, the resistance of wheat to this pathogen is inherited as quantitative, incomplete, and

non -specific to fungal isolates, as well as qualitative, monogenic or oligogenic, and complete

(Chartrain et al., 2004). Rosielle and Brown (1979) reported one or two dominant or partially

26

dominant genes and two to three recessive genes. Simon and Cordo (1998) express several genes

with additive and dominant gene effects.

STB is a major devastating disease on wheat crops worldwide. Thus, the management of STB by

using chemical and host plant resistance is possible but now a day the pathogen becomes to

develop a resistance gene to fungicide. For this reason, host resistance becomes the best solution

for disease control (Adhikari et al., 2015). However, Wheat genotype evaluation for this disease

at a specific growth stage is much limed in our country.

2.7.2. Cultural

Ascospores from infected stubble are released early in high number in the evening of the season

so; avoiding early sowing makes this pathogen ineffective. If late sowing not possible destroying

stubble by grazing, cultivation will reduce the number of spores available to infect the new

season’s crop (Hollaway et al., 2014).

On another hand, agronomic practice such as fertilizer application is the main factor for Septorial

disease development. If the amount of N application increased up to 150kg/ha the disease

severity can also be increased. The reason behind this is N fertilizer able to increase the biomass

of Wheat crop. As leaf numbers, population density increased the environment becomes

conducive for this pathogen development. Indirectly if, an N increase above 150kg/ha the disease

severity decrease because of the crop height limited the spread of disease on an upper leaf

(Joseph et al., 2007: Ansar et al., 2010).

Krupinsky (2001) described that Septorial disease severity is lower in the application of N but it

is high without N application. In addition to this, there is a 905kg/ha yield increase with N

application. Tillage system is the other factor for Septorial disease development. When no-tillage

compared with conventional or minimum tillage there is higher disease severity to that of no-

tillage. Higher precipitation with no-tillage resulted in higher disease and low yield (Krupinsky

et al., 2001; Krupinsky et al., 2007). Although, crop rotation prevents the wheat from sowing on

the paddocks with that high level of stubble born inoculums this can break the disease. Crop

rotation and tillage can reduce the inoculums in the stubble, but its efficacy is based on the air

dispersal of the disease (Hollaway et al., 2014; Mehra et al., 2018).

27

2.7.3. Biological

Lynch (2016) expressed biological organisms such as lactic bacterial strains have a strong

inhibitory activity to spoilage fungi and human pathogenic fungi. Additionally, He reported that

LAB can inhibit the development of Mycosphaerella graminicola pathogen. Biological control

skilled by beneficial micro-organisms such as Lact brevis JJ2P, Lactobacillus arizonensis R13

and Lactobacillus reuteri R2 caused significant fungal inhibition as observed by large mycelium

clearing on modified MRS (De Man, Rogosa and Sharpe) agar. In preliminary dual culture

assays Lact. Brevis JJ2P and Lact. Reuteri R2 inhibited Z. tritici 46-10 growth on PDA formed a

clear cut zone. Sexual reproduction of Zymoseptoria tritici can create great high variability and

its population increased. This provides the pathogen to adapt to environmental change and

resistant to pesticides.

To overcome the resistant development of this pathogen there is a need to develop alternative

control such as biological control. There is a possible environmentally friendly plant protection

by using synthetic chemicals (Lynch et al., 2016).

Different findings showed that Trichoderma spss has been the ability to control the growth and

severity under field colony on PDA of SLB. Perelló (1997) evaluated Trichoderma harzianum

and Gliocladium roseum as biological control under the greenhouse and in vitro and its result

showed that SLB severity was effectively reduced. Trichoderma harzianum highly inhibited the

growth of SLB than Gliocladium roseum did. Both of the biocontrol can complete growth and

cover over the colony growth of SLB.

2.7.4. Chemical

The diverse articles showed that septoria disease incidence becomes high without chemical use.

98% of disease incidence on the unsprayed Kekeba variety resulted (Yitagesu et al., 2018).

Yitagesu (2019) study showed that spraying wheat fields could be an effective measure to reduce

STB levels even on susceptible varieties. For the control of septoria disease, the chemicals that

were verified by this study based on its efficacy were mancozeb and propiconazole.

Another study again described that at different chemical spray intervals the disease epidemics is

variable and in the same to these different varieties was variable epidemics without the use of a

chemical. The disease severity increased on an unsprayed variety of Gambo. This indicates that a

combination of resistant varieties and chemical use is the most important to control this disease.

28

Disease control before 70 DP resulted in considerable yields recovery because, this pathogen

more affect the wheat varieties especially at 70DP (Said and Husain et al., 2013). For early sown

susceptible varieties application of fungicide at different growth stages is effective to control

S.tritici . At 31-32 and 39 days of sowing the fungicide application was the effective time for the

control of septoria disease (Hollaway et al., 2014).

Different application methods such as seed dressing and the foliar application were used to

control the pathogen that attacks wheat crops at different growth stages but, the foliar

application was a common one to use (Ponomarenko et al., 2011; Hollaway et al., 2014). Seed

dressing fungicide such as triticonazole can be used to control the pathogen attack at the seedling

stage. But, the major problem of this pathogen is its evolving chemical resistance especially to

the strobilurin class (Ponomarenko et al., 2011). Also besides, due to mutation septoria tritici

blotch evolving resistance to triazole fungicides and these mutations reduce the effectiveness of

fungicide (Hollaway et al., 2014).

29

3. MATERIALS AND METHODS

3.1. Description of the survey areas

The STB was conducted in Arsi, West Arsi, Bale zones in southeastern Ethiopia and West

Shewa zone, in central Ethiopia in Oromia regional state. Geographical locations of the survey

zones located in Oromia national regional state are shown in figure 8.

Figure 8: Geographical locations of the different wheat septoria tritici survey zones in 2019 main crop season

in the Oromia region

3.1.1. Sampling method and strategy

Wheat disease survey was conducted from flowering to maturity growth stages of the crop using

purposive multi-stage sampling techniques and based on wheat area coverage. The four zones

were selected based on a purposive sampling method from the region and three districts were

selected based on wheat area coverage. Farmer’s field was selected using a systematic sampling

30

method along the main, available, and accessible roadsides on pre-planned routes in areas where

wheat is predominantly grown. Three kebeles within each district and three farms within each

kebele were assessed at 5-10 km interval. In addition to farmer’s fields, Farmers’ Training

Centers (FTC) and research stations were simultaneously surveyed.

3.1.2. Diseases assessment

Bypassing along each field in “W” shape routes; 1m2 quadrant was thrown at three-five points at

random depending on the size of the field, by having 15 meters interval along the segment

(Yitagesu et al., 2018). Fourteen plants were randomly picked from each 1m2 quadrants and

assessed for disease incidence and severity (Eyal et al., 1987). Disease parameters from each

farmer field, plot, and a research station were represented with the averages of three quadrants.

3.1.2.1. Disease prevalence (%)

Diseases prevalence: proportion or percentage infected areas/ fields from the total assessed areas.

Diseases prevalence tells us the geographic distribution of the diseases. The percent diseases

prevalence is calculated as follows.

Disease Prevalence (%) =No of field infested

Total number of field assessed∗ 100

3.1.2.2. Disease incidence (%)

Diseases incidence: is the proportion or percentage of diseased leaves in a plant, diseased stalks

or tillers, or diseased seedlings in afield. It is the diseased percentage of parts or plants in the

sample or population. Disease incidence generally tells about the prevalence of the disease in a

given area or host population. The percent of disease incidence is calculated as follows (Cooke et

al., 2006).

Disease Incidence(%) =Number of diseased plants

Total number of plants assessed ∗ 100

31

3.1.2.3. Disease severity

Septoria leaf blotch severities were recorded using a double digit-scale (Saari and Prescott,

1975). This scale(00-99) measures overall foliar infection on the whole plant where the first

digit, with 0-9, represents the height of infection up the plant, and the second digit, 0-9 points

determines disease severity, area of plants occupied by chlorosis and necroses were given in 0-9

scale. In the first step, the height at which disease upward movement reach on the plant was

fixed. Next to this, the leaf at the fixed plant height was assessed and four leaves below that fixed

plant height were taken for severity measurement. In the case of disease upward movement fixed

6 was given in a 0-9 scale in the first digit and the four leaves below the fixed plant height 7

disease severity was given on 0-9 scale and 67 disease score was given on 00-99 scale(Appendix

figure1e) (Eyal et al., 1987).

3.1.2.3.1. Disease severity index

The disease severity index was determined by the formula

Disease severity index (%)=𝐷1

𝑌1∗

𝐷2

𝑌2∗ 100, where, D1 representing disease reaches upward the

plant in height, and D2 is representing the disease severity. Y1 represents the maximum disease

upward movement and Y2 represents the maximum severity (Sharma and Duveiller, 2007).

3.1.3. Agronomic data

To do an association of septoria tritici blotch severity, incidence, information of the plow

frequency/fallow, name of the preceding crop/ previous crop, weeding practices, crop growth

stages, wheat types, and name of varieties grown, etc were gathered in consultation or

interviewing farmers and development workers. Crop stands/management was judged

qualitatively as excellent, good, fair, and poor.

3.1.4. Field elevation and coordinates

The Altitude and the Coordinates (Longitude and Latitude) of each Field were taken using

Global Positioning System (GPS).

32

3.2. Identification of Septoria tritici isolates

3.2.1. Sample collection

Infected wheat leaf tissues were collected from different wheat fields of Arsi, West Arsi, Bale,

and West Shewa zones in 2019. Ninety one green leaves that had pycnidia and few dried samples

were collected from 108 farmer’s fields in paper bags for isolation of the pathogen. Collected

samples were labeled with the name of the zone, district, kebele, variety, altitude, latitude,

longitude, and date of collection. The sample was dried under natural air at about 25oc to prevent

secondary infection, and kept at room temperature.

3.2.2. Direct Method of Isolation

The isolation process was carried out in the Microbiology Laboratory at Holeta National

Biotechnology Research Center. In the first step, the filter paper was placed on the petri dish and

wetted by distilled water and a segment of wheat leaves of 5cm consisting Septoria tritici blotch

pycnidia was placed on wetted filter paper (figure: 9a), incubated at 24oC for 2-8 hours for

enhancing oozing of pycnidiospores through an opening of the pycnidium (ostiole), cirrhus (Eyal

et al., 1987). The oozes were observed with the aid of a dissecting microscope or stereoscope

and transferred to PDA supplemented with antibiotics (figure: 9b). Pycnidia embedded in the

epidermis or did not produce oozes were removed from the epidermis by sterile needle and

transferred to PDA plates (figure: 9b).

Seven to ten-day spores were stained on a glass slide by distilled water and looked for

micropcnidiospore /macropcnidiospore of Septoria tritici structure under 40X magnification

using a dissecting microscope. The micropcnidiospore/macropcnidiospore structure was

confirmed according to Eyal (1987) and the spore was picked by sterile loops and streaked onto

potato dextrose agar plate prepared in supplementation with chloramphenicol succinate 250mg

for 1 litter distilled water (Eyal et al., 1987).

The streaked plates were incubated in the incubation chamber adjusted at 24 oC for 10 days for

enhancing fungal growth. The single pinkish-orange, dark hard, or black color colonies that

corresponding with Harrat and Bouznad(2018) were further streaked on PDA plates and then

single colonies picked and were spread on new PDA plates without antibiotics and kept

according to Eyal et al.,(1987).

33

Figure 9: The main protocol for isolation of isolate from the leaf at Holeta National Biotechnology

Agricultural Research Center (HNBARC): A. Placement of leaf segment on a filter paper, B. Observation

and digging of pycnidia embedded in the epidermis of leaves in 2019-2020 at HNBARC

3.2.3. Preservation of isolates

Cultures of septoria on PDA or YMA slants were kept in cold storage (4°C) or in regular

refrigerators. The test tubes were carefully sealed, by cotton are being used. Cultures stored in

this manner tend to dry up but keep viability for several months (Eyal et al., 1987).

3.2.4. Microscopic identification

After isolation of Septoria tritici isolates the macropycnidiospores with its four septa and

micropycnidiospores without septa under 40X magnification was proved, and its erect shape was

observed to identify Septoria tritici from nodurum (Sanderson et al., 1985). After six days of

mass multiplication on the orbitary shaker, the ascospore with two cells was confirmed by using

a hemocytometer under 100X magnification (Eyal et al., 1987).

3.3. Determination of isolates variability

3.3.1. Morphological variability

Macroscopic/: The color of colonies, textures, and growth forms was observed and isolates of

Septoria tritici were streaked on solid PDA medium (Harrat and Bouznad, 2018).

A B

34

3.3.2. Virulence Variability

3.3.2.1. Description of differential lines

Seven differential lines with known resistance genes in their genetic backgrounds and originated

from five countries and one international research institute (CIMMYT) (Table4) were obtained

from Addis Ababa University Biotechnology Department.

Table 4: Origin and stb genes of differential lines used during the evaluation of pathogenic variability in

Septoria tritici population, in 2020 at DARC

Sr. No Differential lines Country of Origin stb gene

1 SALAMOUNI Canada Stb13+ Stb14

2 VERANOPOLIS Brazil Stb2 +Stb6

3 ISRAEL-493 Israel Stb3 +Stb6

S TADINIA USA Stb4 +Stb6

5 ESTANZUELA FEDERAL Uruguay Stb7

6 Kavkaz-K4500 CIMMYT Stb10 +Stb12+ Stb6 +Stb7

7 KM7 Stb16

3.3.2.2. Raising seedling of differential lines

The experiment was carried out in the Greenhouse at Debrezeit Agricultural Research Center for

the study of pathogenic variability in Septoria tritici population. Seven seeds of each seven

differential lines were sown in 15cm diameter pots containing mixtures of sterile sand, clay, and

compost soils at a ratio of 2:1:1(Appendix figure 4) in three replications. Forty three isolates with

seven differential lines were combined to gain a treatement combination since the factorial

disegn was used. A total of 301 treatment combinations with three replications were arranged in

the factorial arrangement in a complete randomized design (CRD).

3.3.2.3. Inoculum multiplication

Fresh or six-day inoculums, a pure colony preserved on PDA and stored at -40c temp in the

refrigerator was picked up by sterilized loop and placed into 100-ml Erlenmeyer flasks

containing 50 ml of yeast-sucrose liquid medium prepared from 10 g sucrose and 10 g yeast

extract in 1:1 ratio mixed with 1 liter distilled water (figure 10a). Flasks were covered with

aluminum foil and incubated on an orbital shaker at 150 rpm for 7days at room temperature

(figure 10b).

35

Figure 10: The protocol for inoculums multiplication: A. Picking up of pure colony and placing into 100-ml

Erlenmeyer flasks, B. Mass incubation of inoculum in an orbitary shaker in 2020 at DARC

3.3.2.4. Inoculation

Forty three isolates was used for the analysis of virulence variation is presented in (table18). The

inoculums were adjusted to 7.9*107 spores/ml from seven days inoculums multiplication. Then,

0.00395ml Tween 20 (polyoxyethylene-sorbitan monolaurate, Sigma-Aldrich, St. Louis), a

surfactant (María et al., 2016) was added into 7.9ml inoculum suspensions.7.9ml for single

isolate used and inoculated using hand spray, on to 105 seedlings (7differential lines*five

seedling for single differential line *three replication) of 10-days-old kept in the transparent

plastic and humified with spraying tap water using hand spray (figure 11a and 11b). Inoculated

plants were covered with transparent plastic and misted with tap water to maintain near 100%

relative humidity (María et al., 2016) preventing cross-contamination (Mohammad, 2003).

Inoculated seedlings were kept in a dark environment for 48 hours being covered with materials

not allowing light (Appendix figure 8). Two days after inoculation, inoculating seedlings were

left uncovered as previously used by María et al., (2016) and the pots were distributed randomly

on the greenhouse benches adjusted at 22.5°C and 95% humidity (Eyal et al., 1987).

A B

36

Figure 11: The protocols for inoculation of spores on wheat varieties to evaluate the resistance in the

greenhouse at DARC, Ethiopia; A. Inoculums suspension of each Isolate, B. 10 µl inoculums addition into

each of the two furrows of the hemacytometer, C.Quantifinng of the spore from 25 groups of 16 small square,

D and E. Spore inoculation on wheat varieties in 2020 at DARC

3.3.2.5. Disease assessment on wheat differential lines

The Ziv-Eyal rough scale was used for estimating percentage pycnidial coverage (Figure 12a)

and the FAO scale for estimating percentage necrosis of the infected leaf area (Figure12b). The

first and second leaves of each seedling were assayed for the percentage of lesions and pycnidial

coverage (Cowger et al., 2000) at 28 days post-inoculation.

Eyal et al., 1987 FAO, 2016

Figure 12: Ziv-Eyal rough scale for estimating pycnidial coverage and FAO percent for estimating of wheat

septoria necrosis.

3.3.2.6. Virulence identification, variation and aggressiveness analysis

Least significant differences used for comparing means of differential lines X isolates interaction

values. Plants did not show symptoms were considered represents high resistance and used also

as controls, and isolates with means lower than the LSD values at P< 0.01 were considered

A

A B

B

37

resistant/avirulent, and with means lower than the LSD values at P<0.05 were considered highly

resistant/avirulent and those with more than the LSD values at P< 0.01 were considered

susceptible/virulent. The virulence similarities determined by cluster analysis presented by using

dendrogram trees. The virulence variability is also identified by using pathotype observation.

Besides, the aggressiveness of the isolates on wheat genotypes was calculated as mean disease

severity, after removing data for any resistant responses between specific genotype–isolate

interactions as described previously (Makhdoomi et al., 2015).

3.4. Evaluation of seedling resistance to septoria tritici blotch

3.4.1. Description of wheat varieties

Thirteen durum and 19 bread wheat cultivars were evaluated for seedling resistance which is also

termed specific resistance. Durum wheat cultivars were obtained from Debrezeit Agricultural

Research Center (DARC) whereas bread wheat cultivars were received from Kulumsa

Agricultural Research Center (KARC). Test materials include old and recently released cultivars

developed at federal and regional research centers (Table5).

Table 5: List of wheat cultivars with their pedigree and evaluated to septoria tritici blotch at the seedling

growth stage, in 2020 at DARC.

Sr.

No

Cultivars Year of

release

Developers

and breeder

seed

maintainer

Pedigree Response

to wheat

Septoria

tritici

1 Bakalacha 2005 SARC/OIAR 98OSNGEDIRAF/GWEROU#15) MS

2 Yerer 1994 DARC/ EIAR CHEN/TEZONTLE/3/GUILLEMOT

//CANDEAL-II

R

3 Malefia ADET/ARARI ALTAR-84/STERNA,MEX/LAHN

[3589]

HS

4 Hitosa 2001 DARC/ EIAR CHEN/ALTAR-84 MR

5 Lelliso 2002 SARC/OIAR COCORIT 71/3/GERARDO//61-

130/GLL'S'/4/BOOHAI/HORA//GE

RARDO/3/BOOHAI

S

6 Tate 2009 SARC/OIAR CD94523 MR

7 Arendeto 1958 DARC/ EIAR Landrace S

8 Mossobo NA SARC/OIAR NA MS

9 Ilani 2004 SARC/OIAR IMLO/RAHUM//A4#72/3/Gerado HS

10 Ejersa 2005 SARC/OIAR LABUD/NIGERIS3/GAN(CD98206) HS

38

11 Mangudo 2004 DARC/ EIAR MRF1/STJ2|/3/1718/BT//KARIM,T

UN

R

12 Robe 1999 DARC/ EIAR HORA/COCORIT-71//JORI-

69/GANSO/3/SOME/4/HORA-

RASPINEGRO//CM-

9908/3/RAHUM[4247];

13 Alemtena 2009 DARC/ EIAR Icasyr-1/3/Gcn//Sti/Mrb3

14 Kingbird 2015 KARC/EIAR TAM-200/TUI/6/PABON-F-

76//CARIANCA

422/ANAHUAC75/5/BOBWHITE/C

ROW//BUCKBU CK/ PAVON-F

S

15 Ogolcho 2012 KARC/EIAR WORRAKATTA/2*PASTOR HS

16 K6295-4A 1980 KARC/EIAR Romany X GB-GAMENYA MR

17 Kakaba 2010 KARC/EIAR Kititati//Seri/Rayon MS

18 Lemu NA NA NA NA

19 Paven-76 1982 KARC/EIAR VCM//CNO"S"/7C/3/KAL/BB HS

20 Digalu 2005 KARC/EIAR Sha 7 / Kauz R

21 Danda'a 2010 KARC/EIAR Kiritati//2*PBW65/2*Seri.1B S

22 ET-13A2 1981 KARC/EIAR UQ 105 SEL. X ENKOY S

23 Hidasse 2012 KARC/EIAR YANAC/3/PRL/SARA//TSI/VEE#5/

4/CROC

1/AE.SQUAROSA(224)//OPATTA

R

24 Wane NA NA NA NA

25 Hulluka 2011 KARC/EIAR UTQE96/3/PYN/BAU//Milan S

26 Enkoy 1974 KARC/EIAR (HEBRARDSel/WIS245XSUP51)X

FRFN/YA

HS

27 Dashen 1984 KARC/EIAR VEE 17/KUZ/BUHO"S"//KAL/BB HS

28 Shorima 2011 KARC/EIAR UTQE96/3/PYN/BAU//Milan MS

29 Mitike 1994 KARC/EIAR (FSYR20.6/87BOW28) X (RBC

(ET1297))

R

30 Hoggana 2011 KARC/EIAR PYN/BAU//MILAN HR

31 Biqa NA NA NA NA

32 Laketch 1967 KARC/EIAR PJ"S"/GB55 NA

HR- Highly Resistant, R- Resistant, MR- Moderately resistant, MS-Moderately Susceptible, S- Susceptible,

and HS-Highly Susceptible(Source: Teklay et al., 2015; Tesfaye, 2018; DARC; KARC).

3.4.2. Raising seedling of wheat varieties

Fifteen seeds of each 32 wheat cultivars were sown in 8-cm diameter pots filled with sterile soil

mixture: sand, clay, and compost at a ratio of 2:1:1 and maintained in a controlled climate

39

chamber/greenhouse at Debrezeit Agricultural Research Center adjusted at 22°C and 88%

humidity. 288 (32 cultivars* 9 isolates) treatments combination was considered in the factorial

arrangement in complete randomized design (CRD) with three replications (Appendix figure4).

3.4.3. Inoculum multiplication

Of pure isolates preserved on PDA culture as a colony and maintained at -40c temp in the

refrigerator, nine isolates selected based on the pycnidia parameter (Table6) were picked and

transferred to100-ml Erlenmeyer flasks containing 50 ml of a yeast-sucrose liquid medium using

a sterilized loop. Flasks were covered with aluminum foil and incubated on an orbital shaker at

150 rpm for 7-days at room temperature.

Table 6: List and number of gene for virulent isolates used during wheat varieties evaluation in 2020 in

DARC

Sr.No Isolates No of a gene for virulence

1 EtAm-21 Two

2 EtAm-23 Five

3 EtAm-26 Five

4 EtAm-28 Two

5 EtA-11 Three

6 EtA-19 Seven

7 EtSh-1 Four

8 EtSh-2 Four

9 EtSh-4 Four

3.4.4. Inoculation

The method and step followed for inoculating seedlings of wheat cultivars are similar to

procedures used in inoculating wheat differential lines for pathogenic variability study.

3.4.5. Disease assessment on wheat varieties

The method and step used were the same with wheat differential lines.

3.4.6. Wheat varieties of resistance analysis

Means of cultivars X isolate interaction values were compared using the least significant

differences (LSD). Cultivars not showing STB symptoms were considered highly resistant and

controls for grouping cultivars to other resistance groups. Cultivars with means were lower than

40

the value of LSD at P< 0.01 considered resistant and cultivars with means lower than LSD at P<

0.05 value are regarded highly resistant whereas, cultivars with means more than the LSD values

at P< 0.01are placed in the susceptible group (Makhdoomi et al., 2015).

3.5. Data analysis

The SAS version 9.3 statistical software (SAS, 2012) packages were used to analyze the data

variance and mean comparison. The survey and greenhouse data showed nonnormal distribution

as checked by Kolmogorov-Smirnov since the number of fields assessed and treatments more

than 50. Kolmogorov-Smirnov analysis confirmed significant differences among the data as

revealed with a p-value of 0.05. To normalize the data, the experimental and survey data was

transformed using arcsine (Tabib Ghaffary, 2011).

The farmer’s field was treated as a random effect and other factors were treated as a fixed effect.

Kebeles nested under districts and districts nested under zones. Proc GLM procedure was used to

analyses the variance. The mean comparison of the three fixed effects such as zones, districts,

and kebele was analyzed by Tukey but, another fixed effect was used by LSD. The association

between independent and dependent variables was analyzed by Pearson correlation. Multiple

regression of disease intensity with four predictor factors was observed.

Proc GLM procedure analyses of variance (Mohammad, 2003) and mean comparison tests

(LSD) was used for the Leaf area covered with pycnidia (LACP) and necrosis percent during

virulence analysis and wheat varieties resistance evaluation. The significant mean of the

differential lines and isolates interaction was taken into the average linkage clustering method for

identifying the virulence variability (Tabib Ghaffary, 2011) by using Minitab16. 92.7 and 94.5

similarity level for pycnidia and necrosis respectively, was used during cluster number

identification.

41

4. RESULTS AND DISCUSSION

4.1. Assessment of septoria tritici blotch distribution

4.1.1. Disease prevalence within zones, districts, and kebeles

The Septoria tritici disease was observed in 103 on a wheat field in the area of a surveyed area in

Arsi, Bale, and west Shewa of Oromia national regional state, Ethiopia. 95.4% disease

prevalence was recorded in the fields from the surveyed zones by the Septoria tritici disease. The

disease was more prevalent in the Bale zone, of (100%) as compared to West Shewa (96.3%),

West Arsi (96.3%), and Arsi (88.8). In Arsi zone, the disease occurred in twenty four out of

twenty seven fields assessed in which the lowest prevalence was scored in this zone. But, the

same result twenty six out of twenty seven field’s prevalence was scored in West Shewa and

West Arsi zones (table7). The high prevalence of STB in the surveyed areas is attributable to

weather conditions that are suitable to the disease development (frequent rains and moderate

temperature) (Gilchrist and Dubin, 2002; Teklay et al., 2015).

At the district level, the disease prevalence was 100% at eight districts and the lowest disease

prevalence of 77.8% was scored at Lemunabilbilo district from the Arsi zone (Table7). The

lowest disease prevalence was 66.7% at Kuregatira, Edobelo, Shashe, Sirbo, and Lemuania

kebeles and the rest all 31 Kebeles were sustained 100% disease prevalence (Table8).

Table 7: Septoria tritici blotch prevalence and double-digit of wheat septoria across by Zones, and districts in

2019 main cropping season in Oromia region

Zones Districts Altitude ranges

(m.a.s.l)

No of

the

fields

assessed

Infected

fields

Prevalence

(%)

Double-

digit

West Shewa Wolemera 2252-2577 9 9 100.0 56

Toke kutaye 2245-2792 9 9 100.0 77

Ambo 2463-2988 9 8 88.9 45

Subtotal 2252-2988 27 26 96.3 61

West Arsi Adaba 2357-2498 9 9 100.0 64

Dodola 2410-2573 9 9 100.0 66

Asasa 2386-2573 9 8 88. 9 51

Subtotal 2357-2573 27 26 96.3 59

Arsi Sire 2018-2366 9 8 88. 9 61

Hetosa 2123-2244 9 9 100.0 53

42

Lemunabilbil

o

2602-2938 9 7 77. 8 31

Subtotal 2018-2938 27 24 88. 9 48

Bale Goba 2481-2625 9 9 100.0 74

Agarfa 2392-2472 9 9 100.0 71

Sinana 2344-2462 9 9 100.0 71

Subtotal 2344-2625 27 27 100.0 72

Mean

27 25.75 95.4 59

Table 8: Septoria tritici blotch prevalence and double-digit of wheat septoria across by kebeles in 2019 main

cropping season in Oromia region

Zones Districts Kebele Field

Assessed

Infected

fields

Prevalence

(%)

Double-

digit

West Shewa Wolemera Tadema 3 3 100.0 72

Gelgalkuyu 3 3 100.0 62

Tuluarbu 3 3 100.0 35

Tokekutaye Malkedera 3 3 100.0 75

Maruf 3 3 100.0 79

Adersa 3 3 100.0 76

Ambo Yaichebo 3 3 100.0 35

Bilo 3 3 100.0 44

Kuregatira 3 2 66.7 57

West Arsi Adaba Wosha 3 3 100.0 64

Ejersa 3 3 100.0 71

Herero 3 3 100.0 65

Dodola Edo 3 3 100.0 63

Bekola 3 3 100.0 64

Kechema 3 3 100.0 59

Asasa Huruba 3 3 100.0 58

Debara 3 3 100.0 55

Edobelo 3 2 66.7 38

Arsi Sire Borerachirao 3 3 100.0 64

Shashe 3 2 66.7 45

Kolebashameda 3 3 100.0 73

Hetosa Hatehandode 3 3 100.0 63

Shorima 3 3 100.0 46

Dawes 3 3 100.0 48

Lemunabilbil

o

Sirbo 3 2 66.7 25

Lemuania 3 2 66.7 27

43

Dawahursa 3 3 100.0 41

Bale Goba Sinja 3 3 100.0 81

Misira 3 3 100.0 68

Dawe 3 3 100.0 73

Agarfa Ilani 3 3 100.0 81

Odachafo 3 3 100.0 54

Alodenficho 3 3 100.0 78

Sinana Amelama 3 3 100.0 76

Robezuria 3 3 100.0 68

Shalo 3 3 100.0 68

Overall

mean

27 24 95.4 59.75

4.1.2. Disease prevalence within different factors

The distribution of Septoria tritici disease was observed within different independent factors.

The fields surveyed fall within altitude ranges of 2018-2988 m.a.s.l, mostly, 2330-2625 m.a.s.l in

Bale, 2018-2938 m.a.s.l in Arsi, 2357-2610 m.a.s.l in west Arsi, and 2245- 2988 m.a.s.l in west

Shewa zones (table7). According to Ferede et al, (2013), three traditional agro-ecological zones

are known, namely lowland, midland, and highland that are falling in 500-1500 m, 1500-2300 m,

and 2300-3200 m altitude ranges in the given order. Of the total 108 fields surveyed, 89 (82.4%)

farmer’s fields fallen in highland ranging from 2357-2988 m.a.s.l and 19(17.6%) of them into

midland ranging from 1018-2291 m.a.s.l. In both highlands and midlands, the disease prevalence

was invariably 96.6% and 90% for the former agro-ecologies indicating that STB is more

distributed in the highlands (Table9), especially high in the highlands of West Shewa, Bale, west

Arsi, and Arsi zones. The present finding is in line with the work of Ayele et al., (2008) that

detected more STB prevalence in the central highland of Ethiopia. The authors suggested that the

disease was varied from location to location and season to season within locations. The main

reason for the variation of this disease in such away is the low-temperature and high relative

humidity of the zones causes a favorable environment. Because of 18-25oC temperature and 90%

relative humidity is the optimum environmental condition. For germination, infection,

penetration and colonization of the pathogen such environmental condition can make a high

distribiton (Eyal et al., 1987).

The weed infestation effect on STB prevalence was analyzed by grouping the surveyed fields

into bad, fair, and good fields corresponding to high, medium, and low weed infestation. High

44

distribution of 100% of disease prevalence was scored in field’s considered bad and fair weed

infestation whereas disease prevalence in good fields with low weed infestation was

90.2%(table9) indicating that this disease is almost high in all infestation levels although it was a

bit lower in the well-managed fields. In the cultivated wheat fields, the high plant population of

wheat with weed may cause an appropriate environment for the pathogen. As a result, this causes

the presence of septoria tritici symptom at the field which it is not managed.

The plowing frequency played a major role in the disease prevalence. The fields which plowed

two and three times had a prevalence of 100% whereas fields plowed five times reduced the

prevalence down to 55. 6 % (table9). The plowing frequency can be remove the stubble and plant

debris and it is used for disease management. The primary infection that pycnidium are survive

in the wheat stubble can be exposed to the sun light. The more soil exposition to the sunlight

may be reducing the amount of pycnidium in the soi (Krupinskyl et al., 2001).

Types of preceding crops to wheat affected disease prevalence (Table9). Wheat fields that

preceded by wheat, barley, maize teff, and kept fallow in the previous year sustained 100 %

disease prevalence, whereas disease prevalence in fields proceeded with cabbage and onion crop

was zero. Crop rotation also can play a significant role on the management of this disease.

Fields surveyed fall in flowering, milk, dough, and maturity growth stages. The disease

prevalence of the former wheat growth stage was 80.8% whereas 100% disease prevalence was

recorded at the rest three crop growth stages (Table9). This finding suggests that SLB prevalent

by 100% invariably wheat growth stages following the flowering growth stage, this is not a good

disease parameter to assess STB and measure the level of fields infested in all these growth

stages.

4.1.3. Disease prevalence within varieties

In the survey zones, farmers were produced improved and local cultivars of bread wheat. Out of

fields assessed, 21(19.4%) were covered by local varieties whereas 87(80.5%) fields were

planted by improved cultivars. Eight improved and local varieties were encountered and assessed

during survey and surveillance work (table9). Ogelcho variety was produced in 31(29%) of

farmer’s fields and followed by the Hidasse variety grown in 22(20.4%) of farmers’ fields.

Biratama and Wane were the cultivars least encountered.

Almost fields planted to seven cultivars sustained high infestation as measured by prevalence

45

(Table9), of which fields planted by five cultivars were infested of 100% disease prevalence. The

disease was less prevalent (75 %) in the fields planted by Huluka variety. 100% prevalence was

scored on Biratama variety however; the score was done only from one farmer field. Next to the

Biratama variety, the highest prevalence (100%) was scored on the local, Danda’a, Wane, and

Digalu varieties (Table9). The variation of the disease prevalence among fields planted to

various varieties was due to the variation of management practices employed by farmers in

various fields, a variation of inherited resistances, pathogen, and differences in weather

parameters.

Table 9: Septoria tritici blotch prevalence and double-digit rating scale by agronomic practice and fields

planted to various cultivars in 2019 main cropping season in Oromia region

Altitude

Range

Class name Number

of field

assessed

Infected

fields

Prevalence

(%)

Double-

digit

2018-2291 Midland 20 18 90.0 62

2341-2988 Highland 88 85 96.6 54

Weed status Bad 19 19 100.0 58

Fair 32 32 100.0 62

God 57 52 91.2 59

Type of cropping Broad cast 92 89 97.8 62

Row 16 13 81.3 57

Plowing frequency Two ways 4 4 100.0 83

Three ways 45 45 100.0 68

Four ways 50 49 98.0 59

Five ways 9 5 55.6 64

Previous crop Wheat 43 43 100.0 66

Barley 26 26 100.0 69

Maize 3 3 100.0 73

Teff 3 3 100.0 52

Unknown 13 12 92.3 49

Fallow 11 11 100.0 53

Potato 4 3 75.0 45

Fababean 3 2 66.7 21

Onion 1 0 0 0

Cabbage 1 0 0 0

Growth stage Maturity 13 13 100.0 74

Dauph 42 42 100.0 66

Milking 27 27 100.0 57

46

Flowering 26 21 80.8 46

Varieties Biratama 1 1 100.0 85

Huluka 4 3 75.0 62

Local 21 21 100.0 67

Digalu 2 2 100.0 55

Hidase 22 20 90.9 59

Ogolcho 31 30 96.8 66

Kubsa 13 12 92.3 54

Danda'a 13 13 100.0 42

Wane 1 1 100.0 52

4.2. Disease intensity.

4.2.1. Disease incidence and severity within zones, districts, and kebeles

The ANOVA result revealed that the disease intensity did not significantly differ by factors of

agro-ecologies(p < 0.05) except for disease severity by zone (p < 0.05) (Appendix table1)

indicating that both incidence and severity did not vary statistically by districts and kebeles. The

Tukey mean comparison tells us the mean of West Shewa and West Arsi zones had similar

disease severity index although the disease severity index of the aforementioned zones was

significantly different from Bale and Arsi zones which also significantly differed between them

for the mentioned disease parameter (Table10). The mean severity index of four zones surveyed

was 28.4%. The highest disease severity index of 34.6% and the lowest disease severity index of

19.7% were recorded in Bale and Arsi zones, respectively. West Shewa also had the next highest

disease severity index of 31.7% and the West Arsi zone had a severity of 27.5 %.

Although disease incidence by zones was not significantly different (Appendix table1), they

varied quantitatively (Figure13) with 94.0% overall mean disease incidence the highest disease

incidence of 98.9% was scored in Bale zone followed by West Shewa with 95.5% whereas the

lowest disease incidence of 87.36% in Arsi and 94.7 % in West Arsi zone.

The highest 72 double-digit scores were registered in the Bale zone in which this 7 result shows

that the disease upward movement was riched above half of the plant height and 20% severity

represented by 2 in the second digit in 00-99 rating scale. 59 in West Shewa and West Arsi and

48 in Arsi by double-digit were recorded and the same to this the overall 59 double-digit of the

four zones was evidenced. 59 double-digit value described that 5 is an upward movement of the

47

disease were riched half of the plant height and 9 is the highest disease severity 90% were

observed in four zones during survey work.

The disease intensity that was measured by disease severity and incidence was not significantly

different among the districts which observed from ANOVA (Appendix table1). The highest

disease incidence and severity index of 100% and 41.7% were recorded in Tokekutaye,

respectively and the lowest disease incidence and severity index of 74.6% and 11.5% was

recorded in the Lemunabilbilo district (figure14). Yitagesu (2018) also demonstrated variation of

disease severity index by districts, 30% and 43% in Tokekutaye and Ambo, respectively

although his finding is not inline with the present which 26.3% in Ambo and 41.6% in

Tokekutaye in which the present work indicates the highest disease severity was in Tokekutaye.

A district also varied by incidence, 100% was scored in Tokekutaye and Dodola districts and

99% in Welmera district. The incidence for the latter district is almost the same as 100% disease

incidence reported by Yitagesu (2018). The lowest disease incidence and severity indexes were

74.6 and 11.3 respectively, at Lemunabilbilo district. The reason behind the lowest disease

intensity at this district may be the low temperature due to the highest altitude reaching more

than 2700a.s.l. during our disease assessment; the disease occurrence was reduced above

2700a.s.l. This means the altitude 2700a.s.l. may be the optimum condition for this disease.

The disease intensity also didn’t significantly differ between kebeles at (p < 0.05) (Appendix

table1) but, mathematically they different (figure15). Kebeles were differed by disease incidence

and severity, 49% disease severity index was documented for Malkedera and Maruf kebeles of

Tokekutaye district whereas it was null at Sirbo kebele in Lemunabilbilo district. Likewise, a

high level of incidence e.i 100% incidence was scored in 18 kebeles out of 36 kebeles surveyed

(figure15).

Table 10: The effect of four zones on disease severity in 2019 main cropping seasons in 2019 in the Oromia

region

Zones Disease severity index (%)

West Shewa 31.69ab

West Arsi 23.50ab

Arsi 15.64b

Bale 34.57a

CV (%) 40.7

48

Figure 13: Septoria tritici blotch incidence, across four zones in 2019 main cropping season in Oromoia

region

Figure 14: Septoria tritici blotch disease intensity across districts in 2019 main cropping season in Oromoia

region

98.9 95.5 94.787.4

Bale West Shewa West Arsi Arsi

Dis

eas

e I

nci

de

nce

(%)

Zones

Disease Incidence(%)

4235 34 34

27 26 26 24 22 2114 12

100 100 99 98 9988

100 99 99

85 89

75

Dis

eas

e I

nte

nsi

ty(%

)

Districts

Disease Severity Index Disease Incidence(%)

49

Figure 15: Septoria tritici blotch intensity in across the 36 kebeles in 2019 main cropping seasons in the

Oromoia region

4.2.2. Disease intensity within different factors

Effects of fixed factors such as cropping system and weed infection level were not significantly

24

40

16

28

49

49

20

44

18

25

25

16

11

6

18

21

11

9

39

40

25

28

38

36

47

35

24

32

18

22

26

9

28

30

20

28

99

67

97

100

100

100

100

100

97

100

99

97

63

61

100

100

100

67

96

100

100

98

100

97

100

99

100

99

100

99

98

60

95

100

100

100

Bilo

Kuregatira

Yaichebo

Adersa

Malkedera

Maruf

Gelgalkuyu

Tadema

Tuluarbu

Dawes

Hatehandode

Shorima

Lemuania

Sirbo

Dawahursa

Borerachirao

Kolobashameda

Shashe

Alodenchifo

Ilani

Odachafo

Dawe

Misira

Sinja

Amalama

Robe

Shalo

Ejersa

Wosha

Herero

Debara

Edobelo

Huruba

Bekola

Edo

Kechama

Disease Intensity(%)

Ke

be

les

Disease Incidence( %)

Disease Severity Index

50

differed for disease incidence at (p < 0.05) whereas three fixed factors altitude (p < 0.05),

previous crop (p < 0.001), and plowing frequency (p < 0.01), affected disease incidence as

confirmed by analysis of variance. Weed infection and the plowing frequency at (p < 0.01) were

significantly different for disease severity index while, altitude, type of cropping, and previous

crop were no significant different at (p < 0.05) (Appendix table 2).

Incidence of septoria tritici blotch was low as 89% in the midland and high as 95.3 %( table11)

in the highland in which of the effect of midland on incidence was significantly different from

highland agro-ecologies in other words, disease incidence was more affected the crop in

midland. The disease severity index of 28% and 19.3% was recorded in the highland and

midland agro-ecologies respectively, in which the disease severity index of highland didn’t

significantly different from midland (Figure16). Likewise, Asfawu (2017) reported high septoria

leaf blotch disease incidence in the highland of Gonder, northwestern Ethiopia.

The level of weed infestation highly significantly affected the disease severity index. In the well-

weeded fields, the mean disease severity index was less. The microclimate such as the high

moisture was always available in the dense plant population which makes a good environment

for the pathogen. The greater disease development in the high plant density may be due to a more

favorable microclimate produced within the leaf canopy produced (Ansar et al., 2010). The

plant’s canopy bringing closer wheat leaves which makes it easier to rain splashes spores

dispersal and by influencing the pathogen`s life cycle itself(Ponomarenko et al., 2011). From the

LSD-test mean separation of disease severity index, the mean of fair weed is significantly

different from bad and good weed status (table12). But, the disease incidence was not

significantly different at a p-value of 0.05 among the different weed status (Appendix table 1).

The highest 100% and lowest 89% disease incidence was scored in bad and good weedy fields

respectively (figure16).

The mean severity of septoria leaf blotch in two times plowing was varied from three times of

plowing and the three times plowing was significantly differed at(p < 0.05) from four times

plowing, and four times plowing differed from five times plowing frequencies. Also, five times

plowing frequencies sustained different incidence from two, three, and four times plowing

frequencies (table13). But, two, three, and four times plowing frequencies not differed for

disease incidence. This result was different from the results of some studies that confirmed low

Septoria tritici incidence in the farmer’s fields of zero tillage (Gilbert et al., 2001; Biruta et al.,

51

2018). Biruta (2018) reported the tan spot and mildew reducing trend with increasing plowing

frequency and Septoria tritici increasing trend in farmer’s fields plowed frequently (Krupinsky

et al., 2007). However, conservation tillage supports the over summering of M. graminicola

(Mergoum et al., 2007).

Crop rotation was reduced the disease incidence by making the unavailable host and alternative

host for the pathogen. Like the assessment, the result is revealed septoria disease intensity

varying from low infection to high infection in various wheat fields might be due to variation in

management practices such as crop rotation, sanitation, resistances, chemical option, and agro

ecological differences. In the study area, mono-cropping has been a common practice for many

years and remained the main cause for the pathogen build up in the field using remaining stable

from the preceding wheat field, and that consequently results in the highest disease epidemics.

Almost all varieties always evaluated for rust disease and used for many years become

susceptible to septoria disease.

Crop rotation, for example rotating wheat with non-host highland legume crops, improves the

management of plant diseases such as septoria tritici blotch by interruption of disease cycles.

Farmers understand that mono-cropping is one of the causes for septoria tritici blotch disease

distribution (farmer’s interview results). Fungicide application and sanitation such as removal of

weeds, volunteer crop plants, and alternative hosts reduce disease intensity (Ponomarenko et al.,

2011).

The effects of preceding crop effect on the mean incidence of Septoria tritici were significantly

different. The mean incidence of septoria tritici blotch in wheat planted following barley, maize,

teff, and fallow was not significantly different. The mean disease incidence in wheat fields

planted following potato, onion, and cabbage was low was not significantly different among

themselves (table11). In this case, the type of preceding crop played a great role to reduce the

disease incidence and this finding is the same with the finding of Biruta et al., (2018).

Statistically, the disease severity index was not significantly (p < 0.05), affected by preceding

crops but varied quantitatively. The highest disease severity index of 37.1% was scored in wheat

after wheat crops and the lowest disease severity index of 0% was scored wheat crops followed

onion and cabbage crop (figure16).

52

Figure 16: Effects of agronomic and crop growth stages on disease intensity in 2019 main cropping seasons in

the Oromoia region

Table 11: The effect of preceding crop on disease incidence in 2019 main cropping seasons in the Oromoia

region

Preceding crop Disease incidence

Wheat 99.48a

Barley 98.78a

Maize 96.67ab

Teff 96ab

Unknown 90.28ab

Fallow 97.85a

100 100 97

79

1

Maturity Dauph Milking Flowerin

Dis

eas

e I

nci

de

nce

(%)

Growth stages

Disease Incidence(%)

37

29

20

15 1412 12

30 0

Dis

eas

e S

eve

rity

In

de

x

Preceding Crops

Disease Severity Index

100 100

89

Bad Fair Good

Dis

eas

e I

nci

de

nce

(%)

Weed Infection Levels

Disease Incidence(%)

28

19.3

Highland Midland

Dis

eas

e S

eve

rity

In

de

x

Altitude(m)

Disease Severity Index

53

Potato 73.25bc

Fababean 65.77c

Onion 0d

Cabbage 0d

LSD (0.05) 23.7

CV (%) 15.17

Altitude Disease incidence

Midland 89b

Highland 95.3a

LSD (0.05) 6.1

CV (%) 15.2

Table 12: The effect of growth stage on disease severity index in 2019 main cropping seasons in the Oromoia

region

Weed status Disease severity index

Bad 52.76a

Fair 31.79b

Good 14.49c

LSD (0.05) 5.1

CV (%) 37.15

Growth stage Disease severity index

Maturity 55.6a

Dough 31b

Milking 22.22c

Flowering 9.54d

LSD (0.05) 6

CV (%) 37.15

Table 13: The effect of plowing frequency on disease intensity in 2019 main cropping seasons in the Oromoia

region

Plowing frequency Disease incidence Disease severity index

Two ways 100a 71.61a

Three ways 99.78a 37.81b

Four ways 95.91a 16.2c

Five ways 53.19b 5.35d

LSD (0.05) 12.76 8.7

CV (%) 15.17 37.15

4.2.3. Disease intensity within varieties

The disease severity index was significantly different and disease incidence was not significantly

54

different at (p < 0.05) on the different growth stages of wheat (Appendix table 2). The result of

the mean separation indicated that the four growth stages: flowering, milking, dough, and

maturity growth stages were significantly different from each other for septoria tritici blotch

severity (Table 12). Disease incidence was not significantly affected by crop growth stages

(Appendix table 2) although the incidence of 100% was scored at the dough and maturity crop

stages and the lowest being 78.8% at the flowering growth stage (figure16). Previous studies also

confirmed that incidence is low at the early crop stage, at the booting stage, and high at the latter

crop stages, dough growth stage (Asfawu et al., 2017).

Disease incidence and severity were not significantly different from cultivars (p< 0.05)

(Appendix table2). However, quantitatively, the lowest severity index of 10% was scored on the

Danda’a variety. The highest 55.5% disease severity index was scored on the Hidasse variety.

100% disease incidence was scored on the Digalu and Biratama varieties (figure17). Variation in

varietal effect on septoria tritici blotch is most probably due to resistance incorporated into

cultivars to manage the disease.

Figure 17: Cultivars effect on disease intensity, in 2019 main cropping seasons in the Oromoia region

4.3. Association of Disease intensity with altitude, and agronomic practice

The current study showed that the linear correlation of disease incidence with disease severity of

wheat Septoria tritici disease. As corr procedure exposed that, there was a significant (P < 0.001)

(table14) and positive strong correlation between disease incidence and disease severity

100

75

100

89

100 96 9791

86

4940

32 30 28 2519 18

12

Biratama Huluka Local Hidasse Digalu Ogolcho Danda'a Kubsa Wane

Dis

eas

e I

nte

nsi

ty(%

)

Cultivars

Disease Incidence(%0 Disease Severity Index

55

indicating that the increase of disease severity followed by increasing disease incidence. There

were significant at (P < 0.001) and positive strong(r = 0.78) correlation between weed infection

level, negative strong (r=-0.77) correlation between plowing frequency, and positive

strong(r=0.72) between growth stages with disease severity index.

The positive relationship between wheat growth stages, weed infection level, and disease

severity index of wheat Septoria tritici reflected that as the wheat growth and weed increase the

development of the pathogen become more severe. In other, the increment of plowing frequency

was reduced the disease severity index is also reported by (Mergoum et al., 2007).

In addition, a significant at (P < 0.05) and positive week(r = 0.2) correlation between weed

infection level and disease incidence. The significant (P < 0.001) negative week (r=-0.43)

correlation between plowing frequency, and positive week(r=0.36) between growth stage with

disease incidence. Moreover, there was a non-significant (P < 0.05) of correlation between

altitudes and both disease incidence and disease severity index this indicates that increment of

altitude in (m) didn’t affect the disease intensity.

Table 14: Pearson’s correlation coefficients between disease intensity and agronomic practice in 2019 main

cropping season in the Oromoia region

Variables ALT WIL PF GS DSI DI

ALT 1 0.01ns 0.012ns -0.002ns -0.008ns -0.14ns

WIL 1 -0.66*** 0.69*** 0.78*** 0.2*

PF 1 -0.68*** -0.77*** -0.43***

GS 1 0.72*** 0.36***

DSI 1 0.36***

DI 1

DI - Disease incidence, DSI - Disease severity index, WIL-Weed infestation level, PF-Plowing frequency, ALT

- Altitude, and GS - Growth stage. *Significant level at p<0.05 ** Significant level at 0.01 and ***Significant

level at 0.001.

4.4. Multiple regression

Disease incidence (Table15) regressed over four independent factors using multiple regression

analysis procedures and the analysis also revealed high significance at (P< 0.01) for plowing

frequency and no significant for other factors at (P< 0.05) (Appendix table3). A negative

relationship was observed among disease incidence and plowing frequency, this indicates that

the disease incidence was reduced by 11.84% amount as plowing frequency increased. No

significancy of other factors demonstrates that disease incidence is more affected by plowing

frequency than other factors such as altitude, weed infection, and growth stage. The increment of

56

altitude in meter didn’t affect the disease incidence.

Table 15: Multiple regression of disease incidence over agronomic practice in 2019 main cropping season in

the Oromia region

Predictor Parameter estimate Standard error t Value

Constant 167 29.80 5.64

GS 4.44 2.830 1.57

PF -11.8 3.820 3.10

WIL -4.54 3.544 -1.28

ALT -0.0141 0.0095 -1.48

Disease Incidence = 168 + 4.44 GS - 11.8 PF - 4.54 WIL - 0.0141 ALT,

Determination coefficient R2 = 0.22

WIL-Weed infestation level, PF-Plowing frequency, ALT - Altitude, and GS - Growth stage

From the regg model results, the disease severity was highly significant with weed infestation,

plowing frequency (P<0.001), and significant with crop growth stages (P<0.05) but, no

significant with altitude at (P<0.05) (Appendix table3). The disease severity was increased by

9.73% amount as weed infection levels increased however, the disease severity decreased by

10.42% amount as plowing frequency increased. In other factors, disease severity was increased

by 3.19% amount as the growth stage of wheat increased (from flowering to maturity). The

increment of altitude in meter didn’t affect the disease severity.

Table 16: Multiple regression of disease severity over agronomic practice in 2019 main cropping season in the

Oromia region

Predictor Parameter estimate Standard error t Value

Constant 42 15.16 2.77

GS 3.19 1.440 2.22

PF -10.4 1.943 -5.36

WIL 9.73 1.803 5.40

ALT -0.00075 0.0048 -0.16

Disease severity index = 42.0 + 3.19 GS - 10.4 PF + 9.73 WIL - 0.00076 ALT

Determination coefficient R2= 0.74

WIL-Weed infestation level, PF-Plowing frequency, ALT - Altitude, and GS - Growth stage

4.5. Identification of Septoria tritici isolates

4.5.1. Symptom and sign based identification

Necrosis: The Septoria tritici isolates were formed irregular to rectangular chlorotic lesions

between veins of a leaf during greenhouse work and this symptom was taken during sample

collection. Again, the isolates were developed grayish-green, and necrotic (dead tissue) lesions

on the chlorotic sites of the leaf (Appendix figure10a). The necrotic lesions of Septoria tritici

57

isolates were produced sunken on the leaves (Appendix figure10a). But, the lesions of Septoria

nodurum are lens shape and yellow-green around the dead tissue area of leaves (Bronnimann,

1968: Eyal et al., 1987).

The symptom of M. graminicola isolates inoculation on wheat in the greenhouse showed some

modification than natural infection under the field conditions that were similar to the infection

type observed by Eyal et al, (1987), an advanced symptom of Septoria tritici. The isolates have

affected the leaves and the host response was completely dry (Appendix figure10b). This is

maybe the number of inoculums was inoculated in the greenhouse and the random infection of

inoculums in the field is completely different. The number of pycnidispores adjusted for

inoculation in artificial infection is a sufficient amount to forms the advanced symptom but, the

number of spores in natural infection may be not sufficient to produce such symptoms. At 21

days after inoculation, the leaves became curl and no green part was observed on the first and

second leaves. Wane and Hidasse varieties showed a similar symptom with (Brading’s et al.,

2002) (Appendex figure10c).

Pycnidia: The leaf became curl down after 21 days of inoculation. The isolates were produced

pycnidia that are black inside of the necrosis on both sides of the leaf (figure 18a). However,

pycnidia of Septoria nodurum regularly appear on the glumes, nodes, and stems of the wheat

(Eyal et al., 1987). The pycnidia were produced by isolates on the culture media that inline with

(Harrat and Bouznad et al., 2018)

A

58

Figure 18: A. Pycnidia of S.tritici, B and C. Macropycnidiospores and micropycnidiospores of Septoria tritici

(Own, 2020), D. Pycnidiospores of Septoria nodurum (Source: Eyal et al., 1987) in 2020 at DARC.

4.5.2. Microscopic identification

The identification of Septoria tritici isolates spores differentiated from Septoria nodurum spores

in the laboratory-based on the number of septations, shape, and thickness of the germinated

spores. The Septoria tritici isolates were produced macropycnidiospores of very thin, and more

than three septations and erect in shape (figure 18b and c). Also, the isolates were produced

micropycnidiospores in those are without septa in which differentiated from pycnidiospore of

Septoria nodurum that had thick, less than three septations and curve shape according to Eyal et

al., (1987) (figure 18d). The isolates of Septoria tritici were produced macropycnidiospores with

its four septa and micropycnidiospores without septa and this is inline with (Sanderson et al.,

1985) but three septa for Septoria nodurum. The ascospore of the Septoria tritici isolates was

produced two cells and in which four cells in Septoria nodurum (Eyal et al., 1987).

4.6. Determination of isolates variability

4.6.1. Morphological variability

Based on the colony, cultural characteristics as texture, growth, and color of 44 isolates were

studied on potato dextrose agar (PDA). Phenotypic clarification of colonies stemming, from

isolates of Septoria tritici on solid PDA medium showed a great diversity of textures, growth,

and colors. Six isolates of the pinkish colony had a creamy texture. These isolates of the pinkish

colonies had different growth forms: dense and sparse growth forms. Harrat and Bouznad(2018)

not reported the whitish color isolates which are that un separated growth and the ooze rush the

lines of sowing that was obtained in the current work. The isolates of whitish color also had a

B C D

59

creamy texture. The isolates of dark colors are solid, compact, dense, sparse growth on PDA

(Appendix figure2 and 3). The isolates of brown color are the intermediate, solid, and creamy

texture and sparse, dense growth (Appendix figure2 and 3).

The isolates of whitish colony color were two in number and 4.5% of the total isolates. Twenty-

eight isolates, 63% of the total isolates, produced a colony of black color (Appendix figure2 and

3). Isolates produced colonies of black color are the most dominant ones. Colonies of 8 isolates

were brown and consist of 18.2% and 6 isolates produced pinkish color (14%) out of the total

isolates studied.

Four, three and two isolates derived from Bale samples produced colonies of pinkish, brown, and

black, color in this order. One and two isolates isolated from samples collected from the Arsi

zone had whitish and pinkish respectively, whereas three other isolates yielded colonies of black

color. The isolates from West Arsi had one brown, and five black colors. Eighteen isolates from

West Shewa had colonies of black color whereas one and four isolates resulted in colonies of

pinkish and brown colors, respectively (table17).

EtAm-14 and EtA-4 had the pinkish color similar to Bale Zone and EtA-3, EtA-8, and EtSh-

1also had the black color similar to the West Shewa zone, thus, the location may not affect the

outcome of colonies of various colors resulting from isolates plated on PDA media, meaning that

the isolates collected from different locations and plated on PDA could have the same or various

colors, or the isolates from the same location had different colors and from the same location

again have the same color(Said et al., 2012). This study revealed that Septoria tritici isolates

colonies varied morphologically being plated on the PDA growth media. This shows that the

Septoria tritici has high genetic diversity in growth morphology which is reported for the first

time in our country. From the current observation, the morphologic characterizations of wheat

Septoria tritic isolates in Ethiopia were confirmed (Bentata et al., 2011; Harrat and Bouznad.

2018).

Forty-four Septoria tritici isolates were derived from 91 samples collected from different zones

of the Oromia region (figure19), 23, 9, 6, 6 isolates from West Shewa, Bale, west Arsi, and Arsi

zones in order (table18).

60

Table 17: Morphological variability of isolates in four zones in 2019 main crop season at Oromia region

Zones No of

isolates

Colony color Colony

growth

Texture

West Shewa 23 Dark, pinkish, and

brown colors

Dense and

intermediate

sparse

Daugh, cream, and intermediate

West Arsi 6 Brown, dark colors Dense

intermediate

and sparse

intermediate and daugh

Arsi 6 Whitish, pinkish,

and dark color

Dense

intermediate

and sparse

Cream and daugh

Bale 9 Pinkish, brown,

and dark color

Dense

intermediate

and sparse

Cream, intermediate, and daugh

Table 18: Collection area and varieties source of Septoria tritic isolates in 2019 main crop season at Oromia

region.

Sr.No Isolate code Geographical source Varieties

source

Zone District Kebele Names

1 EtAm-1 West Shewa Welmera Holeta research

center in the station

Alidoro

2 EtAm-2 West Shewa Tokekutaye Hadersa Danda’a

3 EtAm-3 West Shewa Tokekutaye Maruf Digalu

4 EtAm-4 West Shewa Ambo Bojibilo Danda’a

5 EtAm-5 West Shewa Ambo Yaechebo Hidasse

6 EtAm-6 West Shewa Tokekutaye Malkedera Danda’a

7 EtAm-9 West Shewa Ambo Kuregatira

8 EtAm-10 West Shewa Ambo Bojibilo Danda’a

9 EtAm-11 West Shewa Ambo Bojibilo Danda’a

10 EtAm-12 West Shewa Ambo Bojibilo Danda’a

11 EtAm-13 West Shewa Ambo Bojibilo Danda’a

12 EtAm-14 West Shewa Ambo Bojibilo Danda’a

13 EtAm-16 West Shewa Ambo Kibakube Kingbird

14 EtAm-19 West Shewa Ambo Yaechebo Danda’a

15 EtAm-20 West Shewa Tokekutaye Malkedera

16 EtAm-21 West Shewa Tokekutaye Maruf Hidasse

17 EtAm-22 West Shewa Tokekutaye Maruf Digalu

18 EtAm-23 West Shewa Tokekutaye Maruf Huluka

19 EtAm-26 West Shewa Tokekutaye Gorobiyo Gololcha

61

20 EtAm-27 West Shewa Tokekutaye Adersabila Hidasse

21 EtAm-28 West Shewa Tokekutaye Adersabila Danda’a

22 EtAm-29 West Shewa Tokekutaye Adersabila Hidasse

23 EtAm-30 West Shewa Tokekutaye Adersabila Hidasse

24 EtB-1 Bale Goba Sinja Hidasse

25 EtB-2 Bale Sinana Shalo Ogolcho

26 EtB-3 Bale Agarfa

27 EtB-4 Bale Goba Sinja Candidate

28 EtB-5 Bale Agarfa Ilani Ogolcho

29 EtB-6 Bale Sinana Amalama Ogolcho

30 EtB-7 Bale Sinana Robearea Ogolcho

31 EtB-8 Bale Gasera Wute

32 EtB-10 Bale Goba Misira Ogolcho

33 EtA-3 Arsi Hetosa Hatehandode Ogolcho

34 EtA-4 Arsi Hetosa Hatehandode Kubsa

35 EtA-7 Arsi Hetosa Seruanketo Ogolcho

36 EtA-8 Arsi Lemunabilbil

o

Kulumsa research

center in sb-station

37 EtA-11 Arsi Hetosa Hatehandode Kubsa

38 EtA-19 Arsi Tiyo Dosha Danda’a

39 EtSh-1 West Arsi Asasa Debara Ogolcho

40 EtSh-2 West Arsi Dodola Bekola Paven-76

41 EtSh-4 West Arsi Dodola Kechamachare Ogolcho

42 EtSh-5 West Arsi Asasa Edobelo Kubsa

43 EtSh-6 West Arsi Asasa Tuse Kubsa

44 EtSh-7 West Arsi Asasa Kulumsa research

center in sb-station

62

Figure 19: The geographical location of wheat Septoria tritici isolates in the 2019 main crop season in the

Oromia region.

4.6.2. Virulence and virulence variability

Significant isolate X differential lines interaction difference confirms pathogenic variations

governed by the gene for gene hypothesis. Isolates X differential line interaction was confirmed

using the GLM (Appendix table 4) (p<0.001). Then, isolates were differentiated to virulent and

avirulent based both on percent mean pycnidia (Table19) and necrosis (Table20) using LSD

values.

Virulence/percent pycnidia: virulence is the ability of pathogen to overcome host defenses or

degree of pathogenicity. Of 301 interactions, 72 and 229 were produced compatible and

incompatible interactions, respectively (table19). Thirteen isolates were produced incompatible

interaction/avirulent with all differential lines and eleven isolates were produced a single gene

for compatible interactions with differential lines afterward, those eleven isolates had major gene

63

for virulence. One isolate resulted from the compatible interactions with all differential lines

whereas; eighteen isolates were produced compatible interaction with more than two differential

lines. In general, 19 isolates had more than two genes to infect the wheat varieties subsequently,

considered as the most important virulent isolates. Isolates virulent to more than two differential

lines expected to have more than two virulence genes for one or more Stb septoria resistance

genes in wheat genotypes. Nine and four virulent isolates were collected from West Shewa and

Bale zone respectively. Three and two virulent isolates were collected from west Arsi and Arsi in

that order.

EtA-19 derived from samples collected from Arsi (Tiyo district) was produced virulent gene on

all of the differential lines and followed by EtAm-23 and EtAm-26 produced virulent gene on

five differential lines. EtSh-1, EtSh-2, and EtSh-4 were produced virulent genes on four

differential lines whereas EtA-11 virulent to three differential lines (table19). The last isolate was

taken from Arsi zones, Hetosa districts, Hatehandode kebele, and Kubsa variety.

Pathotypes/percent pycnidia: Based on differential lines X isolate interaction and mean

separation using LSD values, isolates could be typed to 19 (Table 21) using the criteria of

percent pycnidia. Thirteen isolates derived from samples collected from various locations such

EtAm-2, EtAm-3, EtAm-4, EtAm-6, EtAm-10, EtAm-12, EtAm-13, EtAm-16, EtSh-7, EtA-7

and EtB-5, EtB-6, and EtB-7 grouped to pathotype1, expressed avirulence to all differential

lines.

EtA-19 belonged to pathotype 20, virulent to all seven differential lines invariably with number

of resistance genes (Stb13+ Stb14), (Stb2 +Stb6), (Stb3 +Stb6), (Stb4 +Stb6), (Stb7), (Stb10

+Stb12+ Stb6 +Stb7) and (Stb16) and followed by EtAm-23 and EtAm-26 isolates, belonged to

pathotype 8 and 18, respectively (table21). Those two latter isolates sustained virulent reaction to

five differential lines various possess Stb resistance genes, former isolate being virulent to

(Stb13+ Stb14) (Stb3 +Stb6), (Stb4 +Stb6), (Stb7), (Stb16) and the latter being virulent to

(Stb13+ Stb14), (Stb2 +Stb6), (Stb3 +Stb6), (Stb4 +Stb6), (Stb7). EtSh-1, EtSh-2 and EtSh-4

isolates are belonging to pathotypes 13, 14 and 15, respectively.

Clusters/percent pycnidia: The Minitab assigned the isolates into different clusters based on the

mean of interaction with differential lines and virulence dissimilarity. As analyzed by the

average linkage method procedure, the pycnidia parameter was classified as the isolates into 19

groups at 92.7 similarity level (figure20). Kema (1996) and Temesgen (1999), (cited by Ayele et

64

al, 2008) previously documented virulence variability in Septoria tritici population in Ethiopia.

The virulence variability was observed between each cluster from the result of the dendrograms

tree. The virulence of EtAm-5, EtAm-6, and EtSh-7 isolates are the same, and those assigned

into the same cluster five even if they collected from different locations. Our investigation inline

with Kema(1996) suggested that location didn’t affect the virulence variability, since Cluster 11

accommodates isolates collected from four zones. The virulence variability due to ascospore

dispersal in Km, and in genetic equilibrium as well as in drift migration equilibrium Chen(1994)

attributed to a high rate of sexual recombination. The virulence similarities of those isolates in

cluster five are 92.7 levels nevertheless virulence similarities of cluster five from other clusters

are less than 92.7 levels. As a result, different isolates were collected from different locations

assigned in the same cluster. This indicates that the geographical location is not affecting the

virulence variability of isolates. A large number of isolates are allocated into cluster 11 in which

this cluster accommodates Bale, Arsi, West Arsi, and West Shewa isolates. Harrat (2018),

considered cluster number as pathotype number in which our experiment resulted from a

different grouping of isolates by dendrogram and pathotypes. Based on pathotype, EtSh-7 was

assigned in different groups from EtAm-5 and EtAm-6 but the dendrogram classified them into

the same groups.

Aggressiveness/percent pycnidia: Isolates also varied by aggressiveness measured by the

magnitude of the mean of overall differential lines where the isolates with high percent pycnidia

are considered the most aggressive. Isolates sustained percent pycnidia mean stretching from

39.6 to 86.6% depending on the isolates’ capacity to enhance disease development (Table 19).

Four isolates EtAm-5, EtSh-4, EtSh-6, and EtA-11 of the 43 isolates confirmed high

aggressiveness with percent pycnidia values of 80.8 %, 82%, 83.5%, and 88.6% in ascending

orders.

Virulence/percent necrosis: Percent necrosis parameter enabled to identify 99 compatible

interaction from 27 isolates and 202 incompatible interaction from seven isolates of 301(43

isolates* 7 differential lines) total interactions (table20). Ten isolates were produced in a single

gene for compatible interactions with differential lines and considered as virulent isolates. Then

from the current result, 16 avirulent isolates and 27 virulent isolates registered from the necrosis

parameter.

65

Pathotypes/ percent necrosis: Based on differential lines X isolate interaction and mean

separation using LSD values, isolates could be typed to 23 (Table 22) pathotypes using the

criteria of percent necrosis. Pathotypes 1- 3 and 8, consisted of 7, 3, 4, and 3 isolates in order and

pathotypes 4-7, 9-11 each consisted of 2 isolates, and pathotypes 13-23 each consisted of 1

isolate(figure21).

Aggressiveness/percent necrosis: Isolates also varied by aggressiveness measured by the

magnitude of the overall differential lines mean where the isolates with high percent necrosis are

considered the most aggressive isolates. Isolates tested sustained mean percent necrosis

stretching from 50 to 97.2% depending on the isolates’ capacity to enhance necrosis and disease

development (Table 20). Seven isolates EtSh-4, EtAm-19, EtB-2, EtB-10, EtAm-5, EtSh-6, and

EtA-11 confirmed high aggressiveness with percent necrosis values of 83.4%, 84.3%, 85.5%,

88.8%, 90.2%, 94.4 and 97.2% in ascending orders. Isolate EtAm-5 is common in being virulent

with 80.8% pycnidia and with 90.2% necrosis production. Some of the Stb genes are ineffective

against Ethiopia populations.

In particular, Stb7 (Estanzuela Federal) is completely ineffective against above 20 isolates

tested, again similar to previous reports of their ineffectiveness against all isolates tested

(Abrinbana et al., 2012; Hosseinnezhad et al., 2014; Makhdoomi et al., 2015). Some wheat

differential lines, including Veranapolis, Tadinia, and Kavkaz-K4500, have been introduced for

cultivation in the United States and Europe as sources of resistance to STB (Abrinbana et al.,

2012). Our result also suggested that Veranapolis and Kavkaz-K4500 are susceptible to only four

and two isolates respectively, from 43 isolates tested. In contrast, the results illustrated that these

lines have only limited protection against one or a few isolates of S. tritici in Iran (Makhdoomi et

al., 2015) once more consistent with other findings that these lines are susceptible to most of the

isolates tested (Hosseinnezhad et al., 2014), which might be due to differences in the virulence

spectra between their isolates and ours.

The S. tritici virulence variability was identified by the different scientists. Van Ginkle and

scharen(1988) did not find interactions between wheat and pathogen genotype in their

experiments that primarily dealt with durum wheat cultivars. Therefore, they suggested that the

lack of interactions could be due to the disappearance interaction of isolates from bread wheat

with bread wheat differential lines which contrast with the findings of Kema et al., (1996) who

reported the presence of bread wheat isolates interactions with bread wheat differential lines.

66

The wide genetic variation for virulence in Septoria tritici matched information on genetic

variation discovered by RFLP analysis (Boeger et al., 1993). A high frequency of RFLP

observed in a sample of Septoria tritici isolates that was mainly collected from one limited area,

indicating significant genetic variation within local populations and even between isolates

derived from lesions in the same leaf (McDonald et al., 1990). We find that the isolates collected

from different locations had the same virulence, as well as isolates from the same location, had

different virulence that was aligned with (Kema et al., 1996; Medini and Hamza, 2008). Division

of two Kenyan isolates that were initiated from the same leaf, in significantly different clusters

indicating the presence of genetic variation for virulence at the micro-level(Kema et al., 1996).

11 isolates were sampled at seven locations from Ethiopia, which were assigned to seven

significantly different clusters and Assassa isolates were merged with three Lemunabilbilo

isolates (Kema et al., 1996). The mobility of Septoria tritici spore over location may be the

causal agent for the virulence similarity of isolates from different locations.

The different result from pycnidia and necrosis parameter was, some isolates resulted in the

compatible group for necrosis but they grouped into incompatible for pycnidia parameter. The

different results derived from pycnidia and necrosis parameter gave some isolates that resulted in

a compatible group based on percent necrosis although based on pycnidia percentage grouped

into incompatible interaction. The severity of differential lines resulted in 99.5% of necrosis it

grouped into susceptible for differential lines and virulent for isolates but, in the necrotic area,

the pycnidia may not be produced thus, qualify for incompatible interaction for the pycnidia

parameter. In incompatible reactions could be due to the fungus is restricted to sub stomata

chambers and thus detrimental effect in the surrounding mesophyll cells is not observed(Kema et

al.,1996).

Table 19: Pyicnidia percentage differential lines and virulence categories of Septoria tritici isolates in 2020 in

the DARC.

Sr.

No

Isolates Differential lines

SALA

MOUN

I

VERAN

OPOLIS

ISRAEL

-493

TADIN

IA

ESTANZ

UELA

FEDERA

L

Kavkaz

-K4500

KM7

Mea

n

1 EtAm-1 39.6 12.3a 8.3a 0a 5a 16.7a 14.0a 39.6

2 EtAm-2 22.3a 8.3a 8.3a 10.0a 3.33a 19.3a 4.33a -

67

3 EtAm-3 5a 1a 2.67a 5a 5.67a 11.0a 11.0a -

4 EtAm-4 10.0a 4.33a 0.67a 0.33a 0.33a 22.3a 13.0a -

5 EtAm-5 29.3b 0.33a 3.33a 3.67a 7b 4.33a 80.8 80.8

6 EtAm-6 24.3a 3.33a 0a 0a 6.67a 6.67a 29.2b -

7 EtAm-10 12.7a 4.67a 5a 22.3a 6.67a 8.7a 0.67a -

8 EtAm-11 3.33a 13.3a 41.6 0.67a 3.33a 10.3a 14.3a 41.6

9 EtAm-12 31.7b 2a 27.0a 1.67a 5a 4a 24.3a -

10 EtAm-13 25.7a 5.67a 26.3a 17.0a 0.33a 10.7a 11.3a -

11 EtAm-14 20.3a 24.0a 47 6a 0.33a 6a 26.3a 47

12 EtAm-16 14.3a 7a 5a 6.67a 0.33a 0.67a 11.7a -

13 EtAm-19 3.67a 3.67a 16.3a 0a 62.5 0a 20.3a 62.5

14 EtAm-20 22.3a 16.7a 38.7 5a 83.3 0.33a 51.3 57.8

15 EtAm-21 17.3a 8.3a 49.3 6.67a 87.6 10.0a 19.3a 61

16 EtAm-22 8.3a 12.0a 60 28.3b 82.9 28.5b 28.0b 71.4

17 EtAm-23 43.0 8.3a 54.7 48.3 88.0 22.0a 48.0 56.4

18 EtAm-26 47.0 47.0 44.3 40.7 87.9 26.7a 11.7a 53.4

19 EtAm-27 18.7a 0.33a 64.2 43.3 2.67a 16.7a 41.7 50

20 EtAm-28 0.33a 3.67a 41.7 8.3a 88.3 12.0a 13.3a 65

21 EtAm-29 21.0a 10.0a 53.3 50.3 57.8 12.3a 21.7a 54

22 EtAm-30 16.3a 15.7a 65.7 13.3a 27.7a 26.7a 46.5 56

23 EtB-1 7b 3.33a 23.7a 69.5 0.67a 1a 25.3a 69.5

24 EtB-2 1.67a 0.33a 0.33a 9.0a 56.5 8.3a 58.3 57.4

25 EtB-3 0.33a 0a 42.7 23.3a 39.7 3.33a 6.67a 41

26 EtB-4 0a 10.3a 45.3 8.7a 3.33a 0a 42 44

27 EtB-5 5a 0.33a 10.7a 5a 6.67a 23.3a 0.67a -

28 EtB-6 0.33a 0.67a 0.33a 0.33a 6.67a 3.33a 1a -

29 EtB-7 28.0b 0.33a 0.33a 8.3a 25.0a 11.3a 18.3a -

30 EtB-8 5.33a 5a 45.3 10.0a 55.7 15.0a 41.7 47.6

31 EtB-10 12.7a 18.0a 15.7a 13.3a 70.0 5.67a 7.3a 70

32 EtA-3 5a 52.3 25.7a 19.3a 16.7a 0.33a 0.67a 52.3

33 EtA-4 11.7a 0a 75.0 15.3a 24.3a 3.33a 29.2b 75

34 EtA-7 3.33a 1.67a 1.67a 0.33a 19.3a 0.33a 1.67a -

35 EtA-8 15.0a 0a 47.7 56.7 78.5 0a 23.3a 61

36 EtA-11 21.0a 25.0a 88.3 88.6 89.0 11.7a 23.3a 88.6

37 EtA-19 59.8 57.4 89.4 41.3 89.4 42.3 39.3 60

38 EtSh-1 18.3a 0.33a 56.8 41.3 89.2 55.7 21.7a 60.7

39 EtSh-2 10.0a 10.0a 53.5 40.0 89.4 23.3a 67.5 62.6

40 EtSh-4 15.0a 89.4 89.3 60 89.5 0.3a 0a 82

41 EtSh-5 0.33a 8.7a 3.67a 11.3a 76.3 0.33a 0a 76.3

42 EtSh-6 0a 0.67a 0a 83.5 0a 0a 0.67a 83.5

68

43 EtSh-7 0.67a 0.67a 0a 0a 0.33a 1a 10.0a -

LSD1 %= 36.114

LSD5 %= 27.448 b Resistant: means not significantly different from zero, or means less than 36.114 (according to LSD1 %) a Highly resistant: means not significantly different from zero or means less than 27.448 (according to LSD5

%)

a and b. Represented for avirulent isolates, non-grade represented for virulent isolates

Table 20: Necrosis percentage by differential lines and isolates of Septoria tritici in 2020 in the DARC.

Sr.

No

Isolates Differential lines

SALA

MOUN

I

VERA

NOPO

LIS

ISRA

EL-

493

TADIN

IA

Df9

ESTAN

ZUELA

FEDER

AL

Kavkaz-

K4500

KM7

Mean

1 EtAm-1 61.7 18.7a 10.0a 5a 12.7a 19.3a 31.3a 61.7

2 EtAm-2 27.3a 11.7a 28.7a 17.3a 5a 25.7a 31.3a -

3 EtAm-3 59 1a 10.0a 5a 6.7a 13.3a 27.3a 59

4 EtAm-4 22.0a 6.3a 7.3a 1.3a 3.7a 25.7a 24.7a -

5 EtAm-5 34.7b 3.3a 8.0a 4.3a 10.0a 12.0a 90.2 90.2

6 EtAm-6 31.0a 5.3a 10.3a 2.7a 12.3a 15.7a 64 64

7 EtAm-10 16.0a 15.3a 22.0a 25.3a 8.7a 25.3a 14.0a -

8 EtAm-11 5a 17.3a 56.3 0.7a 1.3a 17.3a 70 63.2

9 EtAm-12 49 4a 55.3 18.0a 24.7a 9.0a 27.0a 52.2

10 EtAm-13 29.7a 8.3a 31.0a 20.3a 4.3a 24.0a 14.0a -

11 EtAm-14 56.3 27.7a 74 8.0a 3.7a 16.3a 60 63.4

12 EtAm-16 62.0 11.3a 53 48.7 21.7a 20.3a 51 63.7

13 EtAm-19 3a 5.7a 17.3a 0a 84.3 4.7a 29.7a 84.3

14 EtAm-20 66.3 30.7a 56.3 5.7a 92.7 9.3a 69.3 71.1

15 EtAm-21 63.3 11.3a 75.3 72.3 94.5 12.3a 57.3 72.5

16 EtAm-22 16.0a 15.3a 70.1 68 93.4 31.3a 50.5 70.5

17 EtAm-23 47.7 17.3a 55.0 61.0 99.5 33.5b 56.7 64

18 EtAm-26 56.3 55.7 49.0 47.7 99.5 29.7a 15.3a 61.6

19 EtAm-27 23.7a 2a 91.8 52.7 19.0a 22.3a 58.7 67.7

20 EtAm-28 5.7a 19.0a 54.3 12.3a 94.4 16.3a 64.7 71.1

21 EtAm-29 26.3a 11.7a 72.7 48.0 71.3 21.0a 29.3a 64

22 EtAm-30 20.7a 17.0a 74.0 16.0a 79.3 68.3 72.7 73.6

23 EtB-1 9.0a 26.7a 26.7a 59.3 4.3a 1a 29.0a 59.3

24 EtB-2 10.0a 0.3a 6a 32.3a 97.8 11.7a 67.3 85.5

25 EtB-3 5.3a 4a 57.7 28.7a 71.5 5.3a 20.7a 64.6

26 EtB-4 7a 20.0a 51.0 11.7a 18.7a 6a 50.7 50.7

27 EtB-5 13.7a 4a 20.0a 8.7a 15.3a 27.3a 1a -

28 EtB-6 4.3a 0.7a 3a 0.3a 52.3 5.7a 1a -

69

29 EtB-7 32.3a 12.3a 10.0a 17.0a 63.7 14.3a 23.3a 63.7

30 EtB-8 8.0a 7a 50.3 29.3a 97.2 20.0a 28.7a 74

31 EtB-10 26.3a 20.3a 20.3a 30.7a 88.8 11.7a 34.7b 88.8

32 EtA-3 17.3a 63 62.7 33.8b 64 0.3a 30.7a 63.2

33 EtA-4 29.7a 0a 84.3 68.3 49.3 6.7a 33.8b 67

34 EtA-7 8.0a 2.7a 5.7a 0.3a 50.0 2a 6.3a 50

35 EtA-8 51 9.7a 57 64.7 99.5 8.7a 29.0a 68

36 EtA-11 26.3a 31.7a 96.1 96.1 99.5 13.3a 31.0a 97.2

37 EtA-19 66.3 41.7b 94.4 51 99.5 50.3 50 68.6

38 EtSh-1 21.7a 3.7a 67.5 53 94.5 64.3 28.7a 70

39 EtSh-2 27.3a 25.7a 63.3 62 96.1 28.7a 74.0 73.8

40 EtSh-4 60 94.4 94.4 68.7 99.5 19.3a 16.7a 83.4

41 EtSh-5 5.7a 8.7a 5a 24.3a 80.5 3.7a 45.7 63.1

42 EtSh-6 21.5a 1a 2.7a 94.4 25.0a 0a 1a 94.4

43 EtSh-7 1a 1a 13.0a 7.7a 13.0a 1a 16.2a -

LSD1 %=43.016

LSD5 %= 32.693 b Resistant: means not significantly different from zero or means less than 43.016 (according to LSD1 %) a Highly resistant: means not significantly different from zero or means less than 32.693 (according to LSD5

%)

a and b. Represented for avirulent isolates, non-grade represented for virulent isolates

Table 21: Reaction of wheat differential lines to the different pathotypes of M. graminicola based on pycnidia

parameter in 2020 at DARC.

Pathoty

pes

Isolates Differential lines

SAL

AMO

UNI

VERA

NOPO

LIS

ISR

AEL

-493

TAD

INI

A

ESTAN

ZUELA

FEDER

AL

Kavka

z-

K4500

KM7

1 EtAm-2, EtAm-3 EtAm-

4, EtAm-6, EtAm-10,

EtAm-12, EtAm-13,

EtAm-16, EtSh-7, EtA-7,

EtB-5, EtB-6, and EtB-7

- - - - - - -

2 EtAm-21, EtAm-22,

EtAm-28, and EtB-3

- - + - + - -

3 EtAm-29, EtA-8, and

EtA-11

- - + + + - -

4 EtAm-19, EtB-10, and

EtSh-5

- - - - + - -

5 EtAm-11, EtA-4 and

EtAm-14

- - + - - - -

70

6 EtAm-30, and EtB-4 - - + - - - +

7 EtSh-6, and EtB-1 - - - + - - -

8 EtAm-20 and EtB-2 - - - - + - +

9 EtAm-23 + - + + + - +

10 EtAm-27 - - + + - - +

11 EtB-8 - - + - + - +

12 EtA-3 - + - - - - -

13 EtSh-1 - - + + + + -

14 EtSh-2 - - + + + - +

15 EtSh-4 - + + + + - -

16 EtAm-1 + - - - - - -

17 EtAm-26 + + + + + - -

18 EtAm-5 - - - - - - +

19 EtA-19 + + + + + + +

+ and – sign indicates the virulent and avirulent respectively

Table 22: Reaction of wheat differential lines to the different pathotypes of M. graminicola based on necrosis

parameter in 2020 at DARC.

Pathoty

pe

Isolates Differential lines

SAL

AMO

UNI

VERA

NOPO

LIS

ISR

AEL

-493

TAD

INI

A

ESTAN

ZUELA

FEDER

AL

Kavka

z-

K4500

KM7

1 EtAm-2, EtAm-4, EtAm-

10, EtAm-13, EtB-5,

EtB-6 and EtSh-7

- - - - - - -

2 EtAm-5, EtAm-6 and

EtAm-11

- - - - - - +

3 EtAm-19, EtB-7 EtB-10

and EtA-7

- - - - + - -

4 EtAm-29, EtA-11 and

EtA-4

- - + + + - -

5 EtAm-20 and EtAm-21 + - + - + - +

6 EtAm-1 and EtAm-3 + - - - - - -

7 EtAm-22 and EtSh-2 - - + + + - +

8 EtAm-26 and EtSh-4 + + + + + - -

9 EtB-1 and EtSh-6 - - - + - - -

10 EtB-2 and EtSh-5 - - - - + - +

71

11 EtB-3 and EtB-8 - - + - + - -

12 EtAm-12 + - + - - - -

13 EtAm-14 + - + - - - +

14 EtAm-16 + - + + - - +

15 EtAm-23 + - + + + - +

16 EtAm-27 - - + + - - +

17 EtAm-28 - - + - + - +

18 EtAm-30 - - + - + + +

19 EtB-4 - - + - - - +

20 EtA-3 - + + - + - -

21 EtA-8 + - + + + - -

22 EtA-19 + - + + + + +

23 EtSh-1 - - + + + + -

Figure 20: Dendrograms clustered of Mycosphaerella graminicola isolates based on virulence variation of

pycnidia parameter. The dendrogram clustered the isolates in this order 1, 2, 5, 10, 17, 7, 12, 11, 16, 14, 18, 19,

8, 9, 6, 13, 3, 4, and 15 at similarity level of 92.7 in 2020 at DARC.

.

EtB-5

EtAm-4

EtAm-3

EtSh-6

EtB-1

EtAm-10

E tAm-13

EtAm-12

EtSh-4

EtA-3

EtB-2

E tB-6

E tA-19

EtSh-2

E tB-8

EtSh-1

EtB-3

EtA-8

EtA-11

E tAm-29

EtAm-23

EtAm-26

E tAm-22

EtAm-28

EtAm-21

EtA-7

EtSh-5

EtB-10

EtAm-20

EtAm-19

E tAm-27

EtAm-14

EtB-4

EtA-4

EtAm-30

E tAm-11

EtB-7

EtAm-16

EtAm-6

E tSh-7

EtAm-5

EtAm-2

E tAm-1

77.44

84.96

92.48

100.00

Isolates

Sim

ilarit

y

Dendrogram

Pycnidia

72

Figure 21: Dendrograms clustered of Mycosphaerella graminicola Isolates based on virulence variation of

necrosis parameter. The dendrogram clustered the isolates in this order 1, 2, 9, 8, 6, 11, 20, 19, 21, 13, 14, 18,

22, 15, 12, 7, 10, 3, 4, 5, 17, 16, and 23 at similarity level of 94.5 in 2020 at DARC.

4.7. Evaluation of seedling resistance to septoria tritici blotch

4.7.1. Resistance identification based on pycnidia and necrosis

Seedling resistance of wheat cultivars was evaluated using nine virulent isolates of Septoria

tritici. Percent pycnidia and percent necrosis analyzed by the GLM model resulted in both

pycnidia in percent X genotypes and percent necrosis X genotype interactions significant at

P<0.001 (Appendix table 5). The cultivar X isolate interaction was large, indicating that isolate-

resistance was a highly significant sou (Rosielle et al., 1979). Cultivars varied in their responses

to S. tritici infection.

In total, 123 varieties resistances were found among all interactions (n = 288) (table23). Wheat

varieties from this, 123 incompatible interactions, 165 compatible which were observed based on

the pycnidia. The 123 incompatible interactions have a gene for resistance whereas, 165

compatible interactions of wheat varieties with M. graminicola isolates have a gene of

susceptible. Nine isolates are affecting five cultivars and these causing 45 compatible

interactions (susceptible) whereas, 27 cultivars produced resistance with at least one isolates.

Resistance by pycnidia coverage: Wheat cultivars showed resistance to some isolates although

none of the cultivars showed resistance to all nine test virulent isolates of Septoria tritici. Out of

EtSh-6

EtB-1

EtB-5

E tAm-10

E tAm-6

EtAm-5

EtAm-4

EtAm-16

EtAm-12

EtAm-20

EtAm-30

EtSh-4

EtA-3

EtAm-27

E tAm-26

EtSh-1

E tA-4

E tA-19

EtAm-23

EtA-8

EtAm-21

EtSh-7

EtA-11

E tSh-2

EtAm-28

EtSh-5

EtB-2

EtB-7

EtB-3

EtAm-29

E tB-8

EtAm-22

EtB-10

EtA-7

EtB-6

E tAm-19

EtB-4

EtAm-11

E tAm-13

EtAm-14

EtAm-2

EtAm-3

E tAm-1

76.78

84.52

92.26

100.00

Isolates

Sim

ilarit

yDendrogram

Necrosis

73

13 durum wheat test cultivars, eleven (85%) cultivars have expressed the resistance to more than

two isolates (minor gene) in terms of pycnidia percentages. Moreover, Out of 19 bread wheat

cultivars evaluated, 14(74%) cultivars were resistant to more than two isolates. One cultivar from

durum wheat and four cultivars from bread wheat are susceptible to all isolates. Two cultivars

from durum wheat and bread wheat had the major genes for resistance. 11.3 % resistance to

Septoria tritici is more in durum wheat cultivars than in bread wheat cultivars.

Durum wheat cultivars, Ejersa showed eight resistance genes, and Alemtena, Mossobo, and

Hitosa showed resistance genes to seven isolates as measured necrotic leaf area covered by

pycnidia. Robe and Lelisso cultivars are resistant to six isolates as well as, Bakalcha, Tate and

Mangudo showed that was invariably resistant gene to five isolates as confirmed by low

coverage of pycnidia (table 23). Ilani and Malefia cultivars are resistant to four and three isolates

respectively. Those are of more interest in that they possess resistance(s) of broad-spectrum or a

combination of diverse yet-unknown Stb resistance genes.

Similar to the durum cultivars, bread wheat cultivars were varied by resistance to septoria tirici

blotch. Danda’a was resistant to seven isolates and it has also expressed susceptibility to two

isolates such as EtA-11 and EtSh-1 (table 24). Honkolo, Digalu, and Dashen expressed resistance

to six and susceptible to three isolates. Four bread wheat cultivars namely Biqa, Enkoy, Hidasse,

and Shorima had express resistance to four isolates. Similarly, groups of bread wheat cultivars

namely Paven-76, Kingbird, Kakaba, Mitike, and Ogolcho expressed resistance to three isolates

whereas Hulluka expressed resistance only to two isolates. Although one bread wheat cultivars

are expressing a major gene and five cultivars expressed susceptible gene to all isolates as a

result, those cultivars are vulnerable to S.tritici disease.

The more resistance cultivar was found in durum wheat could be due to durum wheat cultivars

have most probably more resistance genes inherited from landraces and thus become genetically

more diverse than improved bread wheat. Durum wheat types have some resistance inherited

from landraces, thus most probably, more diverse resistance genes in improved durum cultivars

than in improved bread wheat cultivars as suggested previously by Belayneh et al., (2009).

Genotypes and pathogen co-evolution overcame bread wheat cultivar resistance. The more

specific interaction of bread wheat isolates with bread wheat and durum wheat isolates with

durum wheat were reported (Kema et al.1996). Durum wheat species were reported to be more

resistant to M. graminicola isolates than bread wheat (Brokenshire, 1976). Test cultivars in the

74

present study showed resistance to most of the isolates, therefore resistance sources to several

isolates, justifying the need for further evaluation of several wheat genotypes against Septoria

tritici regularly.

Makhdoomi et al., (2015) recommended five wheat genotypes for breeding programs those

which are resistant to six isolates evaluated in Iran. However, Ethiopian wheat genotypes

evaluated against nine isolates didn’t confirm resistance to all isolates. Consequently, Danda’a,

Honkolo, Digalu, and Dashen from bread wheat and Ejersa, Alemtena, Mossobo, Hitosa, Robe,

and Leliso from durum wheat had more than six genes for resistance. Out of 32 genotypes

evaluated for resistance, ten bread and durum wheat genotypes had more than six genes for

resistance.

The present study is controversial in that two cultivars Danda’a and Ejersa expressed resistance

in the present study whereas expressed susceptibility to Septoria tritici in a previous study

conducted by Abebe (2015) which could be explained by pathogenic variation in Septoria tritici

population the exposed to under field condition. Abebe(2015) reported susceptible at the adult

plant growth stage in contrast to resistance reaction noted in the present study(Appendix

figure10a) being the difference most probably attributing to various isolates of Septoria tritici

used in the greenhouse and complex field condition. In contrast to the present study, different

authors (Eshetu, 1985; Yeshi et al., 1990) did not encounter durum and bread wheat cultivars

possessing high resistance to M. graminicola isolates. Cultivars such as Ejersa and Danda’a

which revealed high resistance to 8 and 7 M. graminicola isolates, respectively, are the recent

release developed under recent pathosystem (table23).

The high pathogenic diversity of M. graminicola could be the cause for the absence resistance of

major effect and sustaining resistance to all isolates and therefore, commonly, cultivars

remaining at risk that emanating from the lack of resistance to some virulent isolates prevailing

in the wheat production system. This fact urges pathologists and breeders to combine various

resistance sources into high yielding cultivars through conventional breeding procedures such as

gene pyramiding and molecular marker-assisted breeding procedures and sustains wheat

production. Resistance based on seedling resistance may fail due to the sudden emergence of

virulent isolates resulted from sexual reproduction or mutation that consequently results in

resistance breakdown and epidemic outbreak under favorable weather conditions.

Some of the durum and bread wheat cultivars did not produce resistance interaction with M.

75

graminicola isolates and showed susceptibility to all isolates at the seedling crop stage. These

genotypes lack resistance at seedling crop stages could possess adult plant resistance that is

expressed at adult plant growth stages which likely to be affected by climate changes. Cultivars

Lemu, K6295-4A, Yerer, Laketch, ET-13A2, Wane, and Arendeto showed susceptible to 8-9

isolates invariably with percent pycnidia and percent necrosis criteria could be postulated for

adult plant resistance.

Resistance identified by percent pycnidia and percent necrosis predominantly did not result in

similar resistance outcomes. Nevertheless, by percent pycnidia and percent necrosis criteria used,

cultivars Robe and Mossobo had demonstrated resistance to 6-7 isolates whereas cultivars

Danda’a and Ejersa held resistance to 7-9 isolates.

Table 23: Pycnidia percentage of necrotic leaf area of wheat cultivars by Septoria tritici isolates in 2020 at

DARC.

Sr.

No

Varieties Isolates

EtAm

-21

EtAm

-23

EtAm-

26

EtAm-

28

EtA-

11

EtA-

19

EtSh

-1

EtSh

-2

EtSh

-4

Mea

n

1 Bakalacha 0.3a 51.7 0a 35 46.7 2.3a 11.7a 31 2.3a 33.0

2 Yerer 31.6 40 88.7 85 86 49.8 27.6 86.3 70 65.1

3 Malefia 86.8 86.7 31.7 5a 85.7 6.7b 65 0.3a 86.5 73.7

4 Hitosa 45 0.3a 0.7a 8.3a 2a 13.3a 3a 8.3a 55 26.0

5 Leliso 3a 56.7 5a 5a 25.6 5a 16.7b 23.3 10a 25.3

6 Tate 5.7a 89.5 1.3a 53.3 89.5 2a 0.3a 85.8 13.3a 66.3

7 Arendeto 34.3 29.6 73.3 85.3 89.5 5a 28.3 34.5 86.8 54.1

8 Mossobo 13.3a 11.7a 6.7a 48.3 50 0a 2a 0.7a 0a 30.8

9 Ilani 4a 29.3 0a 30 35 20.7 2a 0.3a 32.7 29.5

10 Ejersa 1a 89.5 0.3a 0a 0.3a 0a 0a 7.3a 10a 35.6

11 Mangudo 87.5 2.3a 5a 0.9a 86.8 28.2 16.7 1a 15a 45.2

12 Robe 0a 60 5a 0.2a 60 65 0a 0a 1.7a 61.7

13 Alemtena 2a 2.7a 0.7a 2a 85.1 13.3a 87.3 1a 0.7a 61.9

14 Kingbird 1.3a 1.7a 23.3 88.7 86.1 80 0.9a 30 86.5 65.8

15 Ogolcho 13.3a 23.3 81.3 89.5 50 60 6.7a 1a 89.5 58.1

16 K6295-4A 28 30.7 83.3 29.3 50 88.7 58.3 22.3 85.7 50.3

17 Kakaba 29.7 0.3a 21.7 86.8 60 6a 23.3 60 13.3a 42.1

18 Lemu 29.8 68 88 89.5 85.5 35.7 89.5 86 88.3 69.4

19 Paven-76 5a 5.3a 45 87.5 30 50 55 1a 88 59.3

20 Digalu 0.7a 5.3a 44.7 16.7b 50 10a 1a 10a 23.3 25.8

21 Danda'a 5a 0a 1a 0a 30 0.3a 30 1a 3a 30.0

22 ET-13A2 36.7 88.7 87.3 46.7 88.8 89.5 88 25 88 71.0

23 Hidasse 0a 88.7 89.2 16.7b 89.5 13.3a 1a 85.3 41.7 60.6

76

24 Wane 3.3a 79.1 89.5 36.7 85.3 89.5 89.5 86.7 88 78.5

25 Hulluka 4.3a 86 13.3a 23.3 50 83.2 80 88.7 30.6 55.5

26 Enkoy 5a 50 37.3 11.7a 32 86.5 16.7b 58.3 2a 37.4

27 Dashen 11.7a 0a 1a 85 31 65 10a 10a 8.3a 30.0

28 Shorima 5a 28.3 89.5 38.3 0.5a 41.7 51.7 1a 5a 49.9

29 Mitike 8.3a 86.6 63.3 0.7a 50 16.7b 47.3 50 40.3 39.2

30 Honkolo 6.7b 61.7 16.7b 50 0.7a 5a 3a 5a 89.5 54.5

31 Biqa 5.7a 5.3a 86.5 23.3 10a 25 25 38.3 10a 31.2

32 Laketch 29 39.7 58.2 58..2 39.7 49.7 61.7 66.5 27.7 46.5

31.2 57.3 59.6 49.4 58.2 47.8 46.1 46.1 49.9

LSD1 %= 19.943

LSD5 %= 15.156 b Resistant: means not significantly different from zero, or means less than 19.943 (according to LSD1 %) a Highly resistant: means not significantly different from zero or means less than 15.241 (according to LSD5

%)

a and b. Represented for avirulent isolates, non-grade represented for virulent isolates

Table 24: Necrosis percentage of leaf area of wheat varieties covered by an isolate of S.tritici in 2020 main

crop season at DARC.

Sr.

N

Varieties Isolates

EtA

m-21

EtAm

-23

EtAm

-26

EtA

m-28

EtA-

11

EtA-

19

EtSh

-1

EtSh

-2

EtSh

-4

Mea

n

1 Bakalacha 0.7a 54.3 5.3a 99.5 47.7 8.3a 65 99.4 99.5 78

2 Yerer 42.3 57 99.5 98.7 10a 60.2 13.7a 98.6 98.3 85

3 Malefia 69.3 98.7 60.3 98.3 50 6.7a 73.7 0.7a 70.5 77

4 Hitossa 47.5 4a 1a 8.7a 7.7a 98.7 10a 15a 70.7 72

5 Lelliso 13.3a 64 52 67.6 44.7 45 17.3a 27 11a 45

6 Tate 6.7a 99.5 1.3a 43.67 99.5 22.7a 1.3a 65.1 15.7a 77

7 Arendeto 35.3 41.6 98.7 98 98.7 37.3 39 45.3 39 69

8 Mossobo 20a 12a 7.3a 99.5 51 0a 4.7a 1.2a 0.5a 75

9 Ilani 4.7a 45.3 0a 43.8 36 80.7 8.7a 1.7a 33.7 50

10 Ejersa 6a 99.5 0.83a 1.3a 1.3a 0.5a 0a 21.3a 11a 100

11 Mangudo 98 2.3a 5a 93 99.5 99.5 20a 10a 38.7 86

12 Robe 0.5a 73.3 4a 1a 64.3 99.4 0a 0.7a 2.3a 79

13 Alemtena 9.3a 81.7 3.9a 98 37.3 76.7 99.4 1.3a 1.3a 79

14 Kingbird 1.2a 16.7a 98.7 99.5 99.4 91 13.3a 47.3 98.3 89

15 Ogelcho 40.2 42.7 73.3 98.7 73.3 64.3 6a 2.7a 86.3 79

16 K6295-4A 43.6 66.7 94 40 50 99.5 84.7 45.6 44.8 69

17 Kakaba 40.7 1a 44.6 98 64 6.7a 44.3 64.3 14.3a 75

18 Lemu 11a 76.7 99.5 99.5 67.1 21a 43.2 99.5 99.5 84

19 Paven-76 8.3a 41.3 98 98 34.3 51 70.3 48 99.5 75

20 Digalu 42 41.7 52.3 86.5 51 17a 1.3a 39.4 99.4 66

21 Danda'a 14.7a 0.5a 1a 1.3a 31b 0a 21a 1.3a 16.7a -

77

22 ET-13A2 71.3 99.5 98 47 99.5 66.7 80.7 98.6 99.5 85

23 Hidasse 7.7a 99.5 99.5 99.4 99.5 14.3a 2.3a 98.7 99.5 99

24 Wane 40.2 99.5 99.5 99.5 99.5 99.5 99.5 99.4 56.5 88

25 Hulluka 37.6 99.5 50 63.3 67 93 98.6 98.7 43.5 81

26 Enkoy 46.3 99.5 98 43.6 39.6 59.8 56.7 71.7 3a 77

27 Dashen 44.3 0a 1a 98 40 79 16.7a 38.6 16.7a 72

28 Shorima 7.7a 50 99.5 42.3 1.3a 46 76.6 2.3a 86.7 67

29 Mitike 14.3a 99.5 76.7 1.3a 60 17.3a 35.7 66.8 40.3 68

30 Honkolo 52 99.5 17.7a 98 1.3a 16.7a 5.7a 38.3 99.5 99

31 Biqa 7a 4.3a 66.5 40.3 16.7a 55 37 57 11a 55

32 Laketch 64 46 68.8 65.3 47.3 54.5 71.7 77.8 34.3 58

60 80 89 83 67 76 71 76 77

LSD1 %=33.278

LSD5 %= 25.291 b Resistant: means not significantly different from zero, or means less than 33.278 (according to LSD1 %) a Highly resistant: means not significantly different from zero or means less than 25.291 (according to LSD5

%)

a and b. Represented for avirulent isolates, non-grade represented for virulent isolates

78

5. SUMMARY AND CONCLUSIONS

Wheat is one of the most important mega environment cereal crops. Different countries are

producing the crop due to its adaptability and nutrition values. Different biotic and abiotic factors

can hinder wheat production and productivity of which biotic is the most damaging constraint.

Wheat rusts and STB are the top four fungal foliar diseases that can affect wheat production and

that have national and worldwide importance. STB surveys conducted and pathogenic variability

determined and wheat cultivars evaluated to virulent isolates Septoria tritici at seedling crop

stages. The overall mean disease prevalence in four zones surveyed and located in the Oromia

region was 95.4%. The prevalence of STB was as high as 100% in Bale, 96.3% in west Shewa,

and 88.9% in both Arsi zones. Likewise, disease incidence was as high as100% in Dodola and

Tokekutaye districts whereas the severity index was 41.6% in Tokekutaye, 35.3% in Sinana, and

34.3% in Goba districts.

Similarly, the intensity of STB was also high in regions, zones, districts, and kebeles, and

altitude ranges, weeds infestation, and cultivars covered as measured by both disease incidence

and severity index although showed variation in several circumstances. The main possible

reasons for the importance of the disease could be due to the cultivation of susceptible cultivars,

mono cropping presence of a new virulent strain of STB that evolve through sexual reproduction

and mutation, and the presence of favorable weather conditions that embedded in the classical

disease triangle.

The influence of agronomic practices on S.titici incidence and severity depend on parameters:

Weed infection level, plowing frequency, and growth stages were strongly associated with

disease intensity. In contrast, the altitude was not significantly correlated with the variation in

S.tritici incidence.

Moreover, from the current study, pathogenic variation was recognized in the population of

Septoria tritici structure of the pathogen was shown that the high genetic diversity of STB

disease in the Oromia region of four zones. Forty-four isolates plated on PDA media have

resulted in various colonies growth forms and four different colors and two textures. Three

textures, cream, moderate, and a very dough texture were registered.

Analysis of variance revealed that isolate X differential interaction is statistically significant and

the isolates produced 72 compatible and 229 incompatible interactions with differential lines

79

based on the pycnidia parameter. From gene to gene hypothesis 19 virulent and 24 avirulent

isolates of STB with differential lines were documented based on the pycnidia parameter from

the current study. Nine virulent isolates from west Shewa, three virulent isolates from Hetosa,

Tiyo, and Dodola districts were detected for the first time in Ethiopia.

Based on percent and percent derived from seven differential lines and mean separation by LSD

values, 19 and 23 pathotypes were recognized in the population of Septoria tritici derived from

samples collected the surveyed four zones in the Oromia region. 19 and 23 pathotypes were

identified based on pycnidia and necrosis in that order, in 43 M. graminicola isolates based on

the reaction of seven wheat genotypes. These differential hosts were effective and appropriate for

characterizing M. graminicola virulence types because they all gave clear reactions to the

pathogen.

Cluster analysis employed the average linkage clustering method differentiated the isolates into

19 and 23 similarity groups based on percent pycnidia and necrosis, respectively. Both

pathotypes and clusters show isolates diversity in the pathogen population that may be affected

by the diversity of the isolates that may be affected by the spore dissemination from one location

to another, cultivar difference, and gene mutation rather than the effect of location.

Durum and bread cultivars evaluated using nine isolates. Eleven Durum wheat cultivars have

expressed resistance to more than two isolates as measured with pycnidia percentages of which

six cultivars, namely Mangudo, Robe, Leliso, Mossobo, Alemtena, and Hitosa were resistant to

5-7 isolates. Durum wheat cultivars, Ejersa showed resistance to 8 whereas Ilani and Malefia

cultivars showed resistance to 3-4 isolates. These cultivars are of more interest in that they may

possess resistance(s) of broad-spectrum/ combination of diverse resistance yet unknown Stb

resistance genes that inhibit pycnidia production.

Similar to the durum cultivars, bread wheat cultivars were varied by resistance to septoria tritici

blotch as measured with percent necrosis. Fourteen cultivars were resistant to more than two

isolates of which four cultivars namely Biqa, Enkoy, Hidasse, and Shorima had expressed

resistance to 4 isolates. Danda’a was resistant to 7 isolates and it has also expressed susceptibility

to two isolates such as EtA-11 and EtSh-1 (table 24). Honkolo, Digalu, and Dashen expressed

resistance to six and susceptibility to three isolates.

However, Ejersa, Alemtena, Mossobo, Hitosa, Robe, and Lelisso cultivars from durum wheat

and Danda’a, Honkolo, Digalu, and Dashen from bread wheat those had resistance genes more

80

than six are recommended for breeding purpose.

Resistance identified by percent pycnidia and percent necrosis predominantly did not result in

similar resistance outcomes. Nevertheless, by percent pycnidia and percent necrosis criteria used

cultivars Robe and Mossobo had demonstrated resistance to 6-7 isolates whereas cultivars

Danda’a and Ejersa held resistance to 7-8 isolates although predominantly they varied with

specific isolates they resisted to. In contrast, Cultivars Lemu, K6295-4A, Yerer, Laketch, ET-

13A2, Wane, and Arendeto showed susceptible to more than eight isolates. Those cultivars need

the incorporation of resistance genes using breeding programs.

The present study confirmed that STB is important that deserves management and research as

measured by its intensity, distribution, and pathogenic variability and diversity of virulence to

diverse wheat cultivars in which resistance in the same inhibiting pycnidia and necrosis, such as

Danda’a and Ejersa(this study) is hardly found. Danger from STB is expected due to wheat

production intensification and the creation of diverse new virulences in Septoria tritici

population that emerged from mutation and sexual reproduction that resulted in resistance break

down contained in commercial wheat cultivars whereby this means productivity and production

significantly reduced. Such a pathosystem scenario of STB calls for periodical disease survey,

pathotyping, resistance source identification, and postulation of Stb resistance genes. As

breeding concept incorporating these resistance sources into commercial cultivars, gene stacking

procedures from different cultivars (this study), and being assisted by molecular markers

available. The morphological variability studies such as pycnidiospores and ascospores are

important on different growth media. Isolates/differential lines specificity interaction and

molecular analysis should be done for virulence variability analysis.

81

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7. APPENDICES

Appendix table 1: Nested ANOVA table for the disease intensity of wheat septoria in major wheat in 2019

main crop season at Oromia region.

Source of variation Degree of freedom Mean square

Disease Incidence Disease Severity

Model 35 478.04ns 401.2ns

Zone 3 637.6ns 1969.9**

District(Zone) 8 611.7ns 245.9ns

Kebele(Zone*District) 24 413.6ns 256.8ns

Error 72 426.5 313.1

Corrected Total 107

Appendix table 2: ANOVA table for disease intensity of wheat septoria among fixed effect in 2019 main crop

season at Oromia region.

Source of variation Degree of freedom Mean square

Disease Incidence Disease Severity

Model 27 31127.1*** 1071.1***

Altitude 1 1123.6* 24.3ns

Weed infection level 2 42.8ns 899.8**

Type of cropping 1 13.1ns 3.7ns

Plowing frequency 3 1015.2** 633.3**

Preceding crop 9 794.0*** 20.1ns

Growth stage 3 221.3ns 231.0*

Varieties 8 408.6ns 65.8ns

Error 80 203.9 95.8

Corrected Total 107

Appendix table 3: ANOVA table for disease intensity of wheat septoria for multiple regression of four-factor

in 2019 main crop season at Oromia region.

Source of variation Degree of freedom Mean square

Disease Incidence Disease Severity

Regression 4 2621.4*** 6755.4**

Growth stages 1 6152.9ns 18727.5*

Plowing frequency 1 2918.2** 5588.5***

Weed Infestation 1 623.5ns 2703.3***

Altitude 1 790.8ns 2.3ns

Error 103 358.7 92.8

Corrected Total 107

Appendix table 4: ANOVA table for pycnidia and necrosis on differential lines in 2019 main crop season at

95

Oromia.

Source of variation Degree of freedom Mean square

Pycnidia Necrosis

Model 601 1847.6*** 2437.1***

Differential lines 6 13541.0*** 23757.5***

Isolates 42 4236.6*** 4985.3***

Differential lines * Isolates 252 1171.0*** 1504.8***

Error 602 293 415.7

Corrected Total 902

Appendix table 5: ANOVA table for pycnidia and necrosis on wheat varieties in 2019 main crop season at

Oromia region.

Source of variation Degree of freedom Mean square

Pycnidia Necrosis

Model 287 3301.7*** 3941.8***

Varieties 31 9059.0*** 9253.9***

Isolates 8 8728.5*** 11177.0***

Varieties * Isolates 248 2407.0*** 3044.4***

Error 576 89.3 247

Corrected Total 863

A B

96

Appendix figure 1:The protocol for the double-digit disease measurement: A and B. Throwing of the

quadrant and random taking of the plant and observation of symptom on wheat, C. Measuring the upward

movement of the disease on wheat, D. Observation of the disease severity on the upper four leaves from where

the disease reaches, E. The measurement method was produced by Eyal(1987), in the 2019 main crop season

at Oromia.

C D E

97

Appendix figure 2: Overview of the growth forms and color of some virulent isolates of wheat Septoria tritici

on PDA in 2020 at DARC.

A B

98

Appendix figure 3:The four colors of Ethiopian Wheat Septoria tritici isolates on PDA. A. Pinkish color, B.

Whitish color, C and D. Brown color, E and F. Black color in 2020 at DARC.

Appendix figure 4: Random placement of wheat differential lines seedlings in the greenhouse chamber in

2020 at DARC

C D

E F

99

Appendix figure 5: Random placement of wheat varieties seedlings in the greenhouse chamber in 2020 at

DARC.

Appendix figure 6:The inoculums suspension of 43 isolates for inoculation in 2020 at DARC.

100

Appendix figure 7: Inoculation of differential lines with isolates of wheat Septoria tritici in 2020 at DARC.

.

Appendix figure 8: Making the high humidity by putting in the darkroom for 48 hours of the inoculated

seedling in 2020 at DARC.

101

Appendix figure 9: The response of wheat varieties to Septoria tritici isolates in 2020 at DARC.

A

B

102

B

A

103

Appendix figure 10:Reaction of S.tritici on wheat varieties. A. Chlorosis around the dead tissue and sunken

lesions at leaf margin on Arendeto varieties, B. The first variety is Hidasse which is susceptible (99.5%), the

second variety is Wane which it also susceptible (99.5%) and the third variety is Danda’a which is resistant

(0.5%) severity for EtAm-23 virulent isolate, C. The responses of flame*longbow wheat cultivar to

M.graminicola isolates (Source: Brading, 2002) in 2020 at DARC.

C