1. Asian Maize Drought Tolerance
(AMDROUT) Project
SP3 PROJECT G4008.56
Principal Investigator: B. S. Vivek

2. Maize Area and Productivity in Asia
Area Production
(million ha) (million tons)
China 29.9 166.0 5.55
India 8.3 19.3 2.32
Indonesia 4.0 16.3 4.07
Philippines 2.7 6.9 2.6
Vietnam 1.1 4.5 4.02
Pakistan 1.1 4.0 3.61
Thailand 1.0 3.8 3.93
Nepal 0.9 1.9 2.15
Myanmar 0.4 1.1 3.22
Bangladesh 0.2 1.3 6.01
Laos 0.2 1.1 4.83
Cambodia 0.2 0.6 3.75
Sri Lanka 0.1 0.1 2.16
Malaysia 0.02 0.1 3.19
Total 50.0 227.1 3.7
Country Productivity
(tonnes/ha)

3. Maize in Asia
 Maize area (South and South-East Asia) expanding by 2.2%
annually. 16.5 m ha (2001) to 18.0 m ha (2006)
 Over 80% of the maize is rain fed where productivity is
half that of irrigated maize
 Erratic rainfall
600
700
800
900
1000
1100
1200
1979 1980 198 1 1 982 1983 19 84 1985 1986 1 987 1988 1989 1990
Year
Rainfall(mm)
1.0
1.2
1.4
1.6
1.8
2.0
Maizeyield(t/ha)
Rain fall
M aize yield

4. Grim Reality……of geographical climate
 Climatic change effect declining
ground water table => water
shortage => drought
 'India would have a water deficit
of 50 per cent by 2030 while
China would have a shortage of
25 per cent.„ – ADB
 Addressing the problem of
drought should provide the
highest technical returns to
rain-fed maize

5. Grim Reality……of geographical climate
 Each degree day spent above
30 C reduced the final yield
of maize by 1% under optimal
rain-fed conditions, and by
1.7% under drought
conditions
 … data generated by
international networks of
crop experimenters
represent a potential boon to
research aimed at
quantifying climate impacts …

6. Yield Gaps (t/ha) in Maize
(Source : Edmeades et al., 2003)
Attainable Yield
Actual Yield

7. Principle Outputs
 Yellow drought tolerant inbred lines
 Knowledge on drought tolerant donor lines and
MARS technology
 Scientists trained in molecular breeding

8. We thrive on collaboration ………
 Dr. B. S. Vivek, CIMMYT-India
 Dr. P. H. Zaidi, CIMMYT-India
 Dr. Fan Xingming, YAAS, Kunming,
China
 Dr. Pichet Grudloyma, NSFCRC,
Tak Fa, Thailand
 Dr. M. Azrai, ICERI, Maros,
Indonesia
 Dr. Le Quy Kha, NMRI, Vietnam
 Dr. Eureka Ocampo, Institute of
Plant Breeding, UPLB, Philippines
 Dr. I.S. Singh, Krishidhan Seeds,
India
 Dr. R.P. Singh, Syngenta, India

9. Project Details
 Grant Period:
(Start: Nov 08) (End: Oct 2013)

10. Technology
 Drought Screening Technology
 Marker Assisted Recurrent Selection

11. Managed Drought Stress
Irrigation for germination Last irrigation
Slide Courtesy: P. H. Zaidi
Genotypic variability

12. Not a shot in the dark ......
We have a history of breeding progress
under drought in CIMMYT
What has accelerated
breeding progress for DT
in CIMMYT?
● Managed drought screening
sites
● Collaboration through
regional trials
Average breeding progress (Banziger et al, 2006)
Percentage yield increase of experimental
hybrids (n=42) over checks (n=41)
0%
5%
10%
15%
20%
25%
0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 >9
Average trial yield (t/ha)
Yieldincreaseoverchecks
+
+* * ***
*** ***
***
***
***
Trial #: 18 41 38 48 31 27 21 22 20 7
Low yielding environments High yielding environments

13. Courtesy: P. H. Zaidi
Progress Under Drought

14. Technology
 Drought Screening Technology
 Marker Assisted Recurrent Selection

15. Inbred Line Development
S1
F2
F1
P1 P2x
S6
Genotype S1 families
Form S1 x tester
Evaluate test crosses
Form C1 using genotype & phenotype data
Genotype C1 plants
Form C2 using genotype data only
Marker Assisted Recurrent Selection (MARS)
Genome Wide Selection (GWS)
Pedigree Breeding
C2
AMDROUT

16. Why is MARS successful?
 Objective: maximize the frequency
of favorable alleles in the resulting
population, from which inbreds are
extracted.
 “By changing the favorable allele
frequency from 0.5 to 0.96, the
probability of recovering the ideal
genotype for 20 independent
regions increases from one per
trillion to one in five.” (Eathington
et al. 2007)
 Advantage of MARS is greatest for
traits controlled by many genes.
Mean
Lines developed by pedigree
selection
Lines selected for recombination
from C0 phenotyping
Cycle 3 MARS lines
Population of random lines
extracted from a cross
MARS moves the mean of
the selected population in
advanced cycles beyond
the original distribution by
greatly increasing the
frequency of favorable
alleles

17. Not a shot in the dark ......
Evidence for MARS
 Moreau et al. 2004. Experimental evaluation of several cycles of
marker-assisted recurrent selection in maize. Euphytica 137:111
 Podlich et al. 2004. Mapping as you go: an effective approach to
marker-assisted selection for quantitative traits. Crop Sci.
44:1560
 Bernardo and Charcosset. 2006. Usefulness of gene information
in marker-assisted recurrent selection: a simulation appraisal.
Crop Sci. 46:614
 Bernardo and Yu. 2007. Prospects for genome-wide selection for
quantitative traits in maize. Crop Sci. 47:1082
 Eathington et. al. 2007. Molecular markers in a commercial
breeding program. Crop Sci 47:S-154-S-163 (2007)
 Bernardo, R. 2008. Molecular markers and selection for complex
traits in plants: learning from the last 20 years. Crop Sci.
48:1649–1664.

18. Use of MARS
 MARS is being implemented by several multinational
breeding companies to accelerate breeding progress in
maize
 An increasing number of maize hybrids in Europe and
the US originate from MARS approaches
 MARS is currently not being implemented in the public
sector, partly due to lack of access to high-
throughput genotyping and data processing facilities
 In collaboration with the GCP, IITA, Cornell University
and Monsanto, CIMMYT has initiated the world-wide
largest public sector MARS breeding approach

19. Suite of Supplementary project/s
 Drought Tolerant Maize for Africa (DTMA) Project
 Mega pan-African project
 Biggest public sector MARS effort
 MARS know-how trickling in
 Affordable, Accessible, Asian (AAA) Drought Tolerant
Maize Project
 Asian Project
 Association mapping, MARS
 Bigger in scope
We are not alone…………..

20. ACHIEVEMENTS …………..SO FAR

21. Key Milestones: Donor and Recipient Lines
 Donors (Drought
Tolerance)
 CML312
 CML395
 CML440
 CML441
 CML442
 CML443
 CML444
 CML445
 CML488
 CML489
 CZL04006
 CZL03014
 CZL00003
 CZL03007
 Elite Asian Lines
 CML427
 CML429
 CML451
 CML470
 CML472
 CML473
 CML474
 CA00106
 CA03118-1
 CA03147
 CA14522
 CA14701
 (CTS013050/(AMATLC0H
S167-B)

22. Entry Pedigree
GrainYiel
d
RankNo
Anthesis
Date
GrainYiel
d
RankNo
GrainYiel
d
RankNo
GrainYiel
d
RankNo
t/ha # d t/ha # t/ha # t/ha #
Entries with anthesis date between 58 - 62 days
10
(CA00310 / AMATLC0HS71-1-1-2-1-1-1-B*6-B- B-B-
B)/ZM621A-10-1-1-1-2-B*7-B-B-B
6.47 6 60.8 2.06 7 7.96 2 9.38 8
11
(CA00310 / AMATLC0HS71-1-1-2-1-1-1-B*4-B-B-B-B-B-
B)/ZM621A-10-1-1-1-2-B*7-B-B-B
6.06 8 62.1 2.31 3 7.54 3 8.32 17
12
(CTS013058 / (AMATLC0HS167-1-1-1-2F/R)-
BBBBB/Nei402011-B-B-B-B)/ZM621A-10-1-1-1-2-B*7-B-B-
B
5.95 9 59.1 1.88 11 6.28 11 9.68 6
25
(CTS011072 / P31C4S5B-38-#-#-2-B-B-B-B/P31DMR-88-
3#-B*14-B-B-B-B)/CML444
6.88 12 59.8 1.77 15 5.91 19 12.95 1
Entries with anthesis date > 62 days
20 P31C4S5B-6-#-#-B-B-B-B-B-B-B-B/CML444 6.24 6 62.5 2.14 6 6.45 10 10.13 3
Mean 5.93 17 62.3 1.62 17 5.93 17 8.39 17
LSD (0.05) 1.34 10 2.5 1.32 10 1.71 10 3.49 10
p 0.414 0.003 0.171
Min 3.30 1 58.7 0.43 1 3.61 1 5.87 1
Max 6.88 33 66.2 2.48 33 8.14 33 12.95 33
OPTIMAL: 09CAGCP1
Across Pusa Ind Hanoi Vie Jinghong Chi
Key Milestones: Breeding Starts
CML470 x CML444 (AMDROUT1)
VL1012767 x CML444 (AMDROUT2)
VL1012764 x CML444 (AMDROUT5)
CML472 x CML440 (AMDROUT6)

23. SNP genotyping for MARS

24. AMDROUT: Current Status
 Test cross phenotypic data from one season
available for 2 populations
Heritability over 0.6 for grain yield attainable
 Genotypic data available
 Analysis is in progress
Debate on QTL vs. GWS approaches

25. AMDROUT: Challenges
 Phenotyping
Low heritabilities for many trials
 Germplasm Exchange
Obtaining permits

27. Projects
 AMDROUT, B Vivek
 Maize in Indonesia M Azrai, ICeRI, Indonesia
 Maize reference set composition and evaluation, J Gethi
 Maize acid soil tolerance, C Guimaraes & D. Ligeyo
 MSV resistance in maize, J Derera
 Outline of the maize programme at IITA, M Gedil
 Outline of the Maize programme at Seed Co, E Tembo
 Outline of the Maize programme at Krishidhan, IS Singh
 Outline of the Maize programme at Syngenta, RP Singh
 Introducing the Syngenta Foundation AAA project, B Vivek

28. Group Members
 Jean-Marcel Ribaut, GCP
 Bindiganavile Vivek, CIMMYT
 Azrai, Muhammad, ICERI, Indonesia
 Bennet, Andrew, GCP Executive Board
 Danquah, Eric, WACCI –Ghana
 Danson, Jedidah Wamuyu, ACCI, South Africa
 Derera, John, ACCI, South Africa
 Gedil, Melaku, IITA
 Gethi, James, KARI – Kenya Agricultural Research Institute
 Guimaraes, Claudia Teixeira, EMBRAPA, Brazil
 Krishna, Girish Kumar, CIMMYT
 Robinson, Mike, Syngenta Foundation for Sustainable Agriculture
 Singh, I.S, Krishidhan Seeds, India
 Singh, RP, Syngenta, India
 Tembo, Elliot, Seed Co, Zimbabwe
 Vengadessan, V, CIMMYT

29. Data Sharing
 All participants agreed to test the phenotypic database.
(IMIS)
 GCP will help in putting existing files in database if
necessary, either through visits by informatics groups or by
email
 Participants agreed to fill data file requests and share it
with GCP.
 All were enthusiastic about Samsung Galaxy tablets
 GCP will collect requests and distribute tablets (reasonable
number)
 Tools will be provided through IBP on the condition that
participants will use it.
 Most people were willing to share data amongst themselves.
 GCP will take care of the implementation especially for
accessing database tools of the platform.

30. Breeding activities
 Fingerprinting exercise was presented.
 All participants were invited to submit their lines
for fingerprinting. It was recommended to target
elite and popular lines; about 30 lines per program.

31. Ontology
 After presentation of the maize crop dictionary and
ontology, Rosemary committed to indicate to participants the
information that she would need, mainly to see if any major
traits are missing and to see if the definitions for existing
traits made sense.
 Group agreed that the trait list available on central database
should focus on those that are used routinely by breeders.
Since this is based on Maize Finder and Fieldbook there are
ample number of traits which need to be properly
categorized. Need to make sure that DUS traits are
included. Trait definitions are well defined in maize and this
should be built upon.
 Groups were expecting some simple protocols to use the crop
ontology finder and curator system for eg. How do you
search if your trait is already in the database?

32. Capacity building
 Eric and Jedidah presented about WACCI and
ACCI.
 Jean Marcel presented the 3 year capacity
building proposal.
 Participants were asked to think about nominations
in their programs and neighbouring programs on
who would contribute to this training.
 Whether one week would be sufficient for such
training should be considered. Also, more thought
needs to be put on grouping by country or teams.

33. Communities of Practice (COP)
 Why would one want to be in a COP?
 Crop was primary motivation.
 Inability to do certain tasks, need for mentorship,
socializing, expertise.
 Components: confidence, trust, mobilize, support, openness,
sharing, clear added value, good use of time, knowledge.
 Mike Robinson made the comment that delivery chain could
be important in a COP implying that farmers should be a part.
 If crop COP is the entry point then people agreed that there
was a need for a regional component.
 If delivery chain is the key driver of a COP then it would
have to be region specific.
 COP based on language was suggested to be an important.
 The group present was not representative of the maize
community; therefore that linkages to DTMA and WEMA are
required to ensure that more people are brought on board.