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.