Training : Phenotyping for disease resistance to increase genetic gain

1. Dr. Suresh L.M.
email : l.m.suresh@cigar.org
Training course on "Product Profile Based Breeding
for Increased Genetic Gains"
Phenotyping for disease resistance to increase
genetic gains
11-15 November 2019, Sunbird Capital Hotel, Lilongwe, Malawi

2. MLN
MLN
MCMV
SCMV MSV
TLB GLS DM Rust
Major Biotic stress in Sub Saharan Africa
Java downy mildew
(Peronosclerospora maydis) Disease : Rust
Causal Organism :Polysora rust – Puccinia polysora
FER

3. Losses to Maize Diseases
• Global losses to fungal maize diseases estimated to be 9%
• Almost 15% in SSA
• Diseases are more predominant in the tropics

4. Maize Diseases
 Maize production in sub-Saharan Africa is affected by a
wide array of diseases
 Environmental conditions prevalent in the different agro-
ecological zones are conducive to the growth and spread
of pathogens
 Different disease complexes affect maize production in
the lowlands and mid-high altitudes
 Diseases often reduce production and cause up to 100%
yield loss under severe epidemics depending on
environmental conditions

5. Topic covered
• Product profile – Trait matrix
• Why disease resistance
• What is disease [ Host-Pathogen-Environment]
• Source of disease resistance
• Screening methodology
• Methods of disease resistance
• Efficacy of disease resistance

6. Region
Target Agro-
ecology
Product Profile (with Basic Traits) TLB GLS CR FER MLN MSV
Eastern
Africa
Mid-altitude;
dry/wet
High-yielding, early-intermediate-maturing (300-500 series),
white maize varieties with drought-tolerance, nitrogen use
efficiency (NUE) and resistance to MLN, GLS, TLB, Fusarium Ear
rots, and MSV, suitable for food use in Eastern African dry/wet,
lower mid-altitude
Eastern
Africa
Upper Mid-
altitude; wet
High-yielding, late-maturing (500-600 series), white maize
varieties with drought tolerance, NUE, and resistance to GLS,
TLB, MSV, Common rust, and Fusarium ear rots, suitable for
food use in the Eastern African, wet upper mid-altitude
Eastern
Africa
Highland
Intermediate to late maturing (700 series), high-yielding, white,
Nitrogen -use efficient, and resistant to TLB, Common Rust and
GLS
Southern
Africa
Mid-altitude
(wet, dry)
High-yielding, intermediate-late maturing (500-700 series),
nitrogen-use efficient, drought- and heat-tolerant white maize
varieties adapted to dry/wet mid-altitude ecologies of Southern
Africa and used mainly for food purposes. resistant to MSV,
GLS, TLB, Common rust, and Fusarium ear rots
Southern
Africa
Mid-altitude
(wet, dry)
High-yielding, extra-early/early-maturing (300-400 series),
drought-, heat-, and low soil pH stress-tolerant white maize
varieties adapted to dry/wet mid-altitudes and lowlands of
Southern Africa and used mainly for food purposes. Tolerant to
MSV, GLS, TLB, and Fusarium ear rots
Southern
Africa
Across All
altitudes
Nutritious maize (high proA; QPM + high Zn), early-late
maturity, orange (proA)/white (QPM + high-Zn), high yielding,
tolerant to drought, NUE, heat and low soil pH stresses, and
resistance to MSV, GLS, TLB and Fusarium ear rots
Basic Traits Nice to have Traits
Maize Product profile – Traits (disease base traits)

7. Maize biotic stress phenotyping sites
GLS
Targeted
Countries
Hotspots
(AI) Screening sites
9 9 (2)
Targeted
Countries
Hotspots
(AI) Screening sites
5 3(1)
Targeted
Countries
Screening sites
9 1(1)
Targeted
Countries
Hotspots
(AI) Screening sites
9 9 (3)
Targeted
Countries
Hotspots
(AI) Screening sites
9 7
Targeted
Countries
Hotspots
(AI) Screening sites
9 9 (3)
FER
CR
TLB
MLN
MSV
Kiboko
Targeted
Countries
Hotspots
(AI) Screening sites
14 1(1)

8. Product Profile with basic disease traits
Disease Name Causal Organism Abbreviation Target Score
Maize Lethal Necrosis Maize Chlorotic mottle Virus +
Sugarcane Mosaic Virus
MLN <3 MLN score (on 1-9 scale)
Maize Streak Virus Maize Streak Virus MSV <3 MSV score (on 1-9 scale)
Turcicum Leaf Blight Exserohilum turcicum TLB <4.0 TLB score (on 1-9 scale)
Grey Leaf Spot Cercospora zeina GLS <4.0 GLS score (on 1-9 scale)
Fusarium Ear Rot Fusarium verticillioides FER Less than 10% incidence
Common rust Puccinia sorghi CR ≤4.0 Common Rust score (on 1-9 scale)
Sorghum Downy Mildew Peronosclerospora sorghi SDM <4.0 SDM score (on 1-9 scale)

9. Maize Disease Screening protocol
https://inside.cimmyt.org/globalmaizeprogram/GMP%20Documents/Forms/All
Items.aspx?RootFolder=%2Fglobalmaizeprogram%2FGMP%20Documents%2FP
rotocols%20and%20Procedures%2FBiotic%20Stress%20Trait%20Protocols&Fol
derCTID=0x012000FA9582D1C5522B438CC5ADF310C54823&View=%7B5B107F
CC-C65A-4FA7-863B-BD1FB185BAE3%7D
All Maize disease screening protocol : Here
• Harmonized maize disease screening protocol updated as on November-2018
Contributors : GMP Pathology Team and Breeding Team

11. Selection of parents
F1 nursery
Evaluation of Stage I TCs
Pedigree breedingDH breeding
Evaluation of Stage II TCs
Evaluation of Stage III TCs
Regional Trials evaluation
NPT/Commercial hybrids
Seed increase
Disease screening Developing TCs
Yr.
1A
1B
2A
2B
3A
3B
4A
4B
5A
5B
6A
6B
7A
7B
Product
Development
Linebreeder+DHspecialist
Stages of disease screeningStages of BreedingSeason
Pedigree breeding DH breeding
BC1F2
DH
LINES TC
LINES TC
TC
DH
LINES
LINES
TC
TC
F1
F2
F3
F4
F5
F6
F6
F7
F8
DiseaseIndexing/Screening
Depends on breeding
program, Product
profile

12. Disease Scoring and data recording – key notes
• Field severity :
– Disease pressure should be uniform and consistent to differentiate the resistant and susceptible disease reaction
• Trait Check :
– Resistant, Tolerant and Susceptible trait designated check should be included in each trial to understand and compare the
disease reaction of the trait check.
• Disease incidence:
– Disease reaction is observed and recorded based on per plant basis especially wilt diseases
• Disease Severity :
– Disease reaction is observed and recorded based on plant or plot basis, most of the foliar, and MLN, MSV disease
• Plot Score :
– Disease reaction is observed and recorded based on plot per se
• Individual Plant Score :
– Similar to disease incidence
• Number of Scores :
– Normally as many as 2 to 3 scores are recorded, but in case of MLN, four scores are taken, but finally 4th scores is analysed,
which coincides with maturity
• Critical stage – Disease score
– Same as above, but 3rd or 4th scores is considered as it coincides with maturity
• Multiple season Score
– In order to compare the consistent disease resistant / tolerant reaction of a selected trials, is good to analyse multiple season under similar
disease pressure
• Multiple Site score
– In order to under stand the disease reaction of a line or hybrids from various hot spots, is good to consider the trials under natural hot spot
with similar disease pressure.
• Indexing
– Disease reaction for a line trial or hybrid trial is recorded, just to confirm the disease reaction
• Screening
– Disease reaction is recorded for a hybrid or line trial, but yield is also harvested under disease pressure.

13. Need to manage disease in maize
• Prevent economic losses
– Reduced yields
– Increased production
costs
– Poor quality grain
• Reduce or eliminate the
risks associated with
presence of a disease
• Guarantee food security

14. A field heavily infected with GLS

15. A field heavily infected with TLB –Kakamega,
Kenya

16. Objective
• Identify superior disease resistant germplasm for
incorporation into breeding programs
• Collect good disease phenotypic data
• Use association mapping approaches to understand
the organization of disease resistance genes in the
maize genome
• Develop markers for marker assisted selection breeding

17. Research Strategy
• High precision multi-location phenotyping:
– identify good sources of resistance for use as donors
– Validate stability of resistance genes
• Association mapping studies
– Leverage the STMA set to identify chromosomal regions
involved in disease resistance
– Organization of disease resistance genes on maize genome
• Fine mapping pipeline to develop functional markers
– DH lines
– F2.3, BC1, BC2, BC3 populations

18. Breeding for resistance to diseases
 Use of disease resistant cultivars is the most valuable and
practical means to control diseases
 It is also inexpensive, effective, and simple to apply over a
wide area in a target production zone
Requirements for development of disease resistant maize cultivars
1. Diverse germplasm
2. Screening tools
3. Test locations with consistently high disease pressure

19.  Resistance is available for most of the economically important diseases in
maize
 Resistance is controlled mainly by
 One or a few genes (monogenic or oligogenic)
 Many genes (polygenic)
 With additive and dominance effects
1.Vertical resistance
 Complete resistance of a host to a specific race of a pathogen
 The host plant exhibit hypersensitive reaction that prevents the
establishment and multiplication of the pathogen
 Controlled by one (monogenic) or a few (oligoginic) genes
 Plants show distinct resistant and susceptible categories
Selection is thus easy in segregation populations
 Transfer from source to other germplasm is also easy
 It is less durable
 Has been used to control very few disease in maize
Types of resistance

20. 2. Horizontal resistance
Effect of resistance on the survival and reproduction of the pathogen is less
complete
Provides less selection pressure on the pathogen
It retards the infection process and slows down the spread of the disease
Controlled by many genes (polygenic) each with small effect
Resistance shows continuous variation
It is more durable and stable due to the buffering effect of polygenes
Has been used for controlling most diseases in maize
The two types of resistance can co-exist
Types of resistance

21. Factors affecting disease occurrence
* Climate change impacts the host, agent (pathogen) and environment
Environment
(favorable)
Pathogen
(virulent)
Host (Susceptible)
Time
•Temperature
•Relative humidity
•Rainfall
•Dew
•Solar radiation

22. Disease Triangle Components
• Pathogen
– Strains or pathotypes
– Period of interaction/introduction
• Host
– Breeding for host resistance
• Environment
– Conducive to disease dev – usually high humidity and low
standing water
• Time
– Infection prior to grain filling is most vulnerable stage

23. Environment
• Temperature
• Rain
• Moisture
• Wind
• Insect vectors
• Humans
• Agronomic practices

24. Host Resistance
• Vertical vs Horizontal
• Major gene vs Minor gene
• Qualitative vs Quantitative
• Genes vs QTLs
• Resistance vs Tolerance
• Resistance vs Escape

25. Breeding for Disease Resistance
Basic Requirements
1. Understanding of Pathogen Variability
2. Germplasm Diversity and Genetic basis for R
3. Reliable Phenotyping Protocols and Networks

26. Major disease of Maize in ESA
• Foliar Diseases
• Ear Rots
• MLN
• MSV

27. Boom and Bust Cycles – Major Genes
Stakman, 1957
Plant pathogen interactions evolve over time

28. Mechanisms for disease resistance
1. Resistance to pathogen establishment
• Immunity
– Prevent pathogen from establishing itself due to innate
structural or functional properties of the host
• Hypersensitivity
– Prevents pathogen survival and reproduction due to rapid
death of the host plant cells
2. Resistance to an established pathogen
– Restricts the ability of the pathogen to spread and reproduce
after becoming established in a host
3. Tolerance
– The plant exhibits severe disease symptoms without a serious
loss in yield

29. Availability of diverse germplasm for screening as
sources of resistance
• Sufficient genetic variation exists for most of the diseases
in maize
• Locally adapted or introduced maize germplasm
• Old varieties and breeding stocks
• Landrace collections
• Resistance alleles in these genetic resources can occur at low
or high frequencies
• Resistance genes occurring at low frequencies can be
gradually increased
• Genes at high frequency are easy to transfer

30.  Based on reliable identification of good sources of
resistance
 This can be done through:
 Development of standardized, highly efficient inoculation
techniques and disease rating systems for major maize
diseases that include:
 Fusarium ear rot (FSR); Fusarium stalk rot (FSR); Gray leaf
spot (GLS); and Turcicum leaf blight (TLB)
 Establishment of misting systems at key and crucial sites to
create microclimatic conditions suitable for disease
development.
 Identification of disease hot spot sites, known for consistent,
uniform and reliable disease incidence and pressure.
Approach to minimizing production losses from
diseases

31. Resistance screening methods
• Field, greenhouse (screenhouse) and laboratory-based
screening techniques are available for the major diseases of
maize
• Use established screening techniques
Effective
Cheap
Easy to handle depending on available facilities and personnel
High throughput for screening a large number of breeding
materials
• Field screening of breeding nurseries at hot-spot locations /
artificially inoculated condition with consistently high
disease pressure is also effective
• Evaluate selected resistant genetic materials in one location
(greenhouse, laboratory) at multiple-locations to expose
them to different populations (races) of the pathogen

32.  Test entries are exposed to adequate and uniform
disease pressure.
 Guarantee greatest differentiation of genotypes.
Objective of disease evaluations

33.  Rate of progress to develop stable and durable disease
resistance or marker development depends on:
 the use of reliable screening techniques
 use of as wide a spectrum of the pathogen as possible and at an
appropriate disease pressure
 Take note that:
 Low disease pressure
 Unreliable results that slow down rate of genetic gain
 High or severe disease pressure
 Eliminate low level resistance inherent in adapted
germplasm and may drastically narrow the germplasm
base
Disease screening methods

34. Two major groups:
1. Naturally occurring epidemics
2. Artificially created epidemics
Disease screening techniques

35. Naturally occurring epidemics
 Hot spots
 Use of a location known for its high level of infection for a
particular disease
 Used for a pathogen with a local concentration of alternate
hosts
Advantages
 Cheap and easy to manage
 Test materials are exposed to all pathogen races
Disadvantages
 Success depends on year– to– year consistent expression of
epiphytotic
 adequate and uniform natural infections can rarely be
achieved in most locations
 Disease might not be evenly distributed within the field

36. Naturally occurring epidemics
 Enhanced natural infections to ensure adequate
disease levels
 Manipulation of planting dates
 Create favorable environmental conditions (e.g.
irrigation, enhanced drought etc)
 Use of spreader rows & use susceptible checks every
few rows (e.g. every tenth row)
 Sufficient replications (minimum of three)
 Multiple locations

37. Resistance to Plant Diseases
• Quantitative versus Qualitative
• Qualitative
– Single gene
– Easily overcome
– Characterized by hypersensitive response
to restrict pathogen spread
• Quantitative
– Multiple genes
– More durable
• Resistance is conferred by ‘R-Genes’

38. Major Foliar Disease in ESA
• Grey Leaf Spot (Cercospora zeina)
• Turcicum Leaf Blight / Northern Corn Leaf Blight
(Exserohilum turcicum)
• MSV (maize streak virus)
• Maize Lethal Necrosis

39. Disease Resistance in Cereals
• Unlike wheat and rice, most resistance in Maize is quantitative
(exceptions for Ht and Rp) due to the wide germplasm base
• Over 50 major R genes have been identified from various cereal
crops – most are dominant
• If R is dominant
– Good prospects for hybrid formation
R S R

40. 1 3 5 7 9
Foliar disease
Diseases rating keys / scales

41. Disease Scoring
• CIMMYT uses a 9 point scale (entire plot score)
1 3 5 7 9

42. Ear Leaf Disease %
Some researchers prefer a leaf % score but this is cumbersome and highly
correlated to whole plant scores

43. Correlation between plot level and ear
leaf % scores
Das, 2008

44. Increasing phenotyping accuracy and efficiency
Accuracy :
• Protocol optimization
• Capturing the host defense mechanism to improve the
genetic gain
• Epidemiological studies for emerging diseases
• Exploring proximal phenotyping in controlled
environments
• Management practices
• Capacity building
• Leveraging the internal capacity
Efficiency :
• Increasing the frequency of phenotyping
• Using remote sensing / Image analysis

45. Foliar Disease Screening with artificial inoculation
Year TLB GLS
2016 210 210
2017 295 295
2018 1249 1249
2019 1875 1903
Good lines(1-3) 25 12
Total 3629 3657
Lines screened for TLB & GLS
Turcicum leaf blight Grey leaf spot
Disease Screening Location : Kakamega, Kenya
Partner : KALRO
Planting season : March – April
Disease severity – Foliar disease

46. Disease phenotyping
GLS TLB
(H ranges from 0.79 to 0.95)
H
Entries
MLN

47. Breeding progress from 2014-
2018
Year
# lines
evaluated
2014 2876
2016 1522
2018 909
Total 5307

48. Grey Leaf Spot
• More prevalent under warm,
humid conditions and CA
• Sporadic in nature but can
account for upto 30% yield
loss
• R is additive with minor effect
QTLs
Disease cycle of GLS. Source: Ward et al. (1999).

49. Standard Area Diagram to use with the 1-9 Disease Rating Scale for Grey
Leafspot (Cercospora zeae-maydis, C. zeina)
8 = 41-80%5 = 6-10%2 = 1%
3 = 2%
1 = 0%
6 = 11-20%
4 = 3-5%
9 = 81-100%
7 = 21-40%
The percent area affected is recorded as the accumulative leaf area
with lesions beginning on the leaf below the primary ear. Individual
leaf data is not recorded, but the diagrams above assist in estimation
of leaf area affected. Data is recorded at four weeks post-flowering.
Image from hdimage.com

50. Grey leaf spot Screening overview

51. When to Score for foliar diseases?
Most appropriate time is during grain filling when the effect of infection is most
pronounced (4 to 6 weeks post anthesis)

52. Gray leaf spot phenotyping data for
molecular mapping resistance genes
Three values are recorded in this order
% infection, hypersensitive reaction, lesion type
1. % infection is based on visual estimate
2. Hypersensitive reaction (1-9 scale) chlorotic or yellow spots observed on the leaf
1 = no or very few chlorotic spots
3 = small spots, little area is affected on the leaf
5 = larger spots, moderate coverage on the leaf
7 = larger spots, extensive coverage of the leaf
9 = large spots, most of the leaf area covered
3. Lesion type (1-9 scale) based on lesion size, chlorotic response, and necrotic or dry tissue
1 = no lesion or chlorotic tissue
3 = leaf chlorosis, no necrotic tissue
5 = leaf chlorosis, little necrotic tissue
7 = necrotic tissue, small lesions
9 = necrotic tissue, large lesions with tissue drying between adjacent lesions

53. Grey leaf spot phenotyping data for
molecular mapping resistance genes
Hypersensitive Reaction 1 Hypersensitive Reaction 2 Hypersensitive Reaction 3
Hypersensitive Reaction 4 Hypersensitive Reaction 5

54. Grey leaf spot phenotyping data for
molecular mapping resistance genes
Lesion Type 1 Lesion Type 2 Lesion Type 3
Lesion Type 4 Lesion Type 5

55. Turcicum Leaf Blight
• Can account for up to 50% yield
loss
• Qualitative and dominant R gene
available therefore TLB is
generally a problem in inbred
maintenance and seed
production but not in final hybrids
• Global problem and thrives in
moderate temps and high
temperatures.
• Qualitative and dominant
strain specific R genes

56. Various degree of TLB infection on
different genotypes of maize despite of
using same inoculum, same inoculation
and observation time. Therefore, it
requires standardized disease rating
scale.
Disease evaluation

57. 1 2 3 4
5 9876

58. Turcicum leaf blight – Screening overview
CML 444CML 543 CML 546

59. Turcicum leaf blight phenotyping data for
molecular mapping resistance genes
Three values are recorded in this order
% infection, hypersensitive reaction, lesion type
1. % infection is based on visual estimate
2. Hypersensitive reaction (1-9 scale) chlorotic or yellow spots observed on the leaf
1 = no or very few chlorotic spots
3 = small spots, little area is affected on the leaf
5 = larger spots, moderate coverage on the leaf
7 = larger spots, extensive coverage of the leaf
9 = large spots, most of the leaf area covered
3. Lesion type (1-9 scale) based on lesion size, chlorotic response, and necrotic or dry tissue
1 = no lesion or chlorotic or red tissue
3 = leaf chlorosis or reddening, little to no necrotic tissue
5 = leaf chlorosis or reddening extensive, non elliptical reduced necrotic tissue
7 = necrotic tissue, small elliptical lesions
9 = necrotic tissue, large elliptical lesions with tissue drying between lesions

60. Turcicum leaf blight phenotyping data for
molecular mapping resistance genes
Lesion Type 5
Lesion Type 1 Lesion Type 2 Lesion Type 3
Lesion Type 4

61. Standard Area Diagram to use with the 1-9 Disease Rating Scale
for Turcicum Leaf Blight (Exserohilum turcicum)
8 = 41-80%5 = 6-10%2 = 1%
3 = 2%
1 = 0%
6 = 11-20%
4 = 3-5%
9 = 81-100%
7 = 21-40%
The percent area affected is recorded as the accumulative leaf area
with lesions beginning on the leaf below the primary ear. Individual
leaf data is not recorded, but the diagrams above assist in estimation
of leaf area affected. Data is recorded at four weeks post-flowering.
Image from hdimage.com

62. GLS
Leaf number Estimate Estimate Actual
1 73
2 40
3 34
4 73
5 24
6 31
7 82
8 79
9 33
10 63
correlation Leaf 6 of 10
The percent area affected is recorded
as the accumulative leaf area with
lesions beginning on the leaf below
the primary ear. Individual leaf data is
not recorded, but the diagrams assist
in estimation of leaf area affected.
Diagrams generated in Corn Pro v3.4
by Forrest Nutter copyright© Iowa
State Research Foundation, Inc.
Leaf 1 of 10
Leaf 2 of 10
Leaf 3 of 10 Leaf 4 of 10
Leaf 5 of 10
Leaf 7 of 10 Leaf 8 of 10
Leaf 9 of 10
Leaf 10 of 10

63. Ear Rots
• Significant yield damage
• Mycotoxin risk
• Highly environmentally variable
• Major Ear Rots
1. Aspergillus ear rot (Aspergillus flavus)
2. Fusarium Ear Rot (Fusarium moniliforme and other
species (Gibberella))
3. Diplodia Ear Rot (Stenocarpella maydis)

64. Aspergillus ear rot
University of Illinois
Most serious under high temp and drought
Production of aflatoxins
Overwinters in crop debris and spores are
dispersed by wind or insects
Host resistance offers best control. Rotation has
minimal effect as a lot of alternate hosts
Difficult to phenotype. R is likely to be
quantitative but difficult to phenotype reliably

65. Fusarium Ear Rot
• Common in all maize growing ecologies
• Hot dry weather after flowering favors Fusarium ear rot
• Symptoms
– Whitish/pink mycelium on/between kernels
– Starburst symptoms on kernels
• Fungi overwinters in crop debris and airborne conidia
infect silks at flowering
• Control through host resistance and proper storage
• Quantitative Resistance (composition of kernel is
important)

66. Fusarium Ear
rot
Pioneer
Hibred
Intl

67. Diplodia Ear Rot
• Prevalent when wet weather follows silking
• White / grey mycelial growth over husks and kernels
• Infected kernels may be very light and appear to be
glued together
• Infected ears are very light
• Black pycnidia are produced late in the season
• Fungi overwinters in infected stalks

68. Diplodia ear rot
Source: Iowa State University

69. Scoring ear rots
• Not possible to distinguish ear rots in most cases
because of need for speed during harvest and
scoring
• Count the total number of infect ears to enable % to
be calculate

70. Naturally occurring epidemic of common rust
Puccinia sorghi

71. Standard Area Diagram to use with the 1-9 Disease Rating Scale
for polysora rust (Puccinia polysora)
8 = 41-80%5 = 6-10%2 = 1%
3 = 2%
1 = 0%
6 = 11-20%
4 = 3-5%
9 = 81-100%
7 = 21-40%
The percent area affected is recorded as the accumulative leaf area
with lesions beginning on the leaf below the primary ear. Individual
leaf data is not recorded, but the diagrams above assist in estimation
of leaf area affected. Data is recorded at four weeks post-flowering.
Image from hdimage.com

72. Parameter Batan
(2008)
Batan
(2009)
Batan
(2010)
Combined
location
Entry Variance 0.92 0.69 1.28 0.45
Residual variance 0.39 0.31 0.17 0.28
Heritability 0.82 0.87 0.96 0.85
LSD -05 1.24 0.92 0.66 0.91
CV 22.53 25.50 12.12 20.40
Resistant Susceptible
Replications =3
Number of entries = 300 genotypes
Good phenotyping data across locations –
Common Rust (Puccinia sorghi)
Oxalis sp. – an alternative host for Puccinia sorghi

73. Maize Steak Virus
Symptoms appear on the leaves 3-7 days after inoculation as pale spots or flecks, 0.5-2 mm in diameter. Symptomatology may vary
depending on the host, cultivar or virus isolate. In severe cases, the initial pale spots become longer streaks which eventually
coalesce. Maize plants infected before the 4-5 leaf stage can be severely stunted. In milder instances, the lesions do not develop to
more than a few sparse flecks or dots. Isolates which infect grain crops cause an abnormal bunching of flowers and shoots. Some
isolates from South Africa induce a reddish pigmentation on those leaves initially infected.

74. MSV
Sheperd et al., 2010
Severity depends on genotype
R gene identified on Chr 2 – molecular markers
available
Transmitted by leafhoppers
Epidemics are sporadic but devastating
Symptoms: chlorotic spots that coalesce into stripes
occupying the entire leaf
Host resistance is the most suitable means of control

75. High-throughput Phenotyping – MLN

76. Classes
Remaining Green leaf
area
100% Senesced
leaves
Yellow leaf area
Leaf Senescence
RGB imaging

77. RGB-based Imaging for MLN

78. Artificially created epidemics
 Environmental conditions favorable for optimal
disease development rarely occur every year
 Great variation in the severity of the disease within a
location in a year
 Ensure adequate epidemic development
 Versatile - Can be done in laboratory, greenhouse and
field

79.  Inoculum production in the maize
pathology laboratory in CIMMYT.
The inoculum is produced on
colonized sorghum grain and used
for artificial inoculations of leaf
diseases of maize (TLB, MLB).
 Inoculations done at the 6-8 leaf
stage. Colonized sorghum seed
serves as sources of inoculum for 7
weeks under field.

80.  Disease phenotyping hubs
 Harare
 Kakamega / Embu
 Misting system
 Environment conditions that
inherently favors expression of
plant diseases
 Protocols
 Well developed and available
for many disease
 Issues
 Common checks
 Limits harmonization of data
from different organizations
Protocols for reliable disease phenotyping

81. Evaluation – Resistance vs. susceptible
Data loggers Inoculation technique
Fieldbook and fieldlog
Parameters for reliable disease phenotyping

82. In the case of Fusarium ear rot -
Steps for preparing inoculum

83. Inoculating with Fusarium ear rot -
Silk channel inoculation technique Kernel puncher inoculation technique
(pin prick method)

84. Evaluating ear rots

85. Maize streak virus – Artificial screening
• MSV-A strain – economic
importance among 6 MSV
strains
• It can infect 80 other
species in the family
Poaceae
• Cicadulina mbila Naude
and C. Storeyi – Vectors
• Acquisition : 24 hrs.
• 3-4 hoppers plants
• 3-4 weeks for symptom
expression
• Disease rating 1-9 scale
Inoculum
Leaf hopper
Leaf hopper rearing
Leaf hopper rearing
Viruliferous Leaf hopper acquisition

86. P = 0.0001
EM-KN BA-Mex1 BA-Mex2 SL-Mex
EM-KN 1
BA-Mex1 0.86 1
BA-Mex2 0.87 0.96 1
SL-Mex 0.99 0.99 0.98 1
Phenotypic correlations between sites for
common rust

87. Parameter San Pedro
Lagunillas
(Nayarit)
Acatic
(Jalisco)
Santa
Catalina
(Colombia)
Paraguacito
(Colombia)
Entry
Variance
0.80 0.6 0.99 0.80
Residual
variance
0.25 0.15 0.36 0.11
Heritability 0.86 0.89 0.89 0.95
LSD -05 1.13 0.76 0.98 0.55
CV 22.60 14.14 19.84 9.61
Replications =3
Number of entries = 300 genotypes
Good phenotyping data across locations –
Gray Leaf Spot (GLS)

88. Good phenotypic data across locations
GLS (6) MSV (3) E. Turcicum
(12)
P. Sorghi
(5)
Var (Entry) 0.27 0.209 0.188 0.492
Var(LocxEntry) 0.45 0.121 0.182 0.079
Var(Resid) 0.22 0.795 0.269 0.320
Grand_Mean 2.66 2.780 2.605 2.153
LSD_0.5 0.87 2.510 0.729 1.399
H 0.76 0.62 0.91 0.91
#Sites 6 3 17 3
Combined Analysis Across Location: four adaptive diseases

89. Conclusions
• A large number of inbred lines, open-pollinated
varieties, hybrids, and source population with
resistance to the major diseases are available for
use
– As sources of alleles to breed maize for resistance to the
major diseases
• Other disease for which artificial inoculations are
conducted / protocols available
– Ear rots (Fusarium and Aspergillus), Stalk Rots, turcicum
blight, southern corn leaf blight, common rust.

90. Conclusions
 Information on sources of disease resistance on
CIMMYT website & available to collaborators
 Establishing diseases phenotyping network comprised
of different institutions and seed companies etc.
 Build capacity of collaborators on use of harmonized
disease evaluation protocols

91. Thank you
for your
interest!