grm 2011: asian maize drought tolerance (amdrout) project
DESCRIPTION
TRANSCRIPT
Asian Maize Drought Tolerance (AMDROUT) Project SP3 PROJECT G4008.56
Principal Investigator: B. S. Vivek
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)
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
Ra
infa
ll (
mm
)
1 .0
1.2
1.4
1.6
1.8
2.0
Ma
ize
yie
ld (
t/h
a)
R ain fal l
M a ize yield
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
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 …
Yield Gaps (t/ha) in Maize
(Source : Edmeades et al., 2003)
Attainable Yield
Actual Yield
Principle Outputs
Yellow drought tolerant inbred lines
Knowledge on drought tolerant donor lines and MARS technology
Scientists trained in molecular breeding
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
Project Details
Grant Period:
(Start: Nov 08) (End: Oct 2013)
Technology
Drought Screening Technology
Marker Assisted Recurrent Selection
Managed Drought Stress
Irrigation for germination Last irrigation
Slide Courtesy: P. H. Zaidi
Genotypic variability
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
Av erage trial yie ld (t/ha)
Yie
ld i
nc
re
as
e o
ve
r c
he
ck
s
+
+* * ***
*** ***
******
***
Trial #: 18 41 38 48 31 27 21 22 20 7
Low yielding environments High yielding environments
Courtesy: P. H. Zaidi
Progress Under Drought
Technology
Drought Screening Technology
Marker Assisted Recurrent Selection
Inbred Line Development
S1
F2
F1
P1 P2 x
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
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
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.
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
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…………..
ACHIEVEMENTS …………..SO FAR
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)
Entry Pedigree
GrainYiel
dRankNo
Anthesis
Date
GrainYiel
dRankNo
GrainYiel
dRankNo
GrainYiel
dRankNo
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-B6.47 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-B6.06 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)/CML4446.88 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)
SNP genotyping for MARS
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
AMDROUT: Challenges
Phenotyping
Low heritabilities for many trials
Germplasm Exchange
Obtaining permits
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
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
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.
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.
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?
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.
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.