" Harnessing agricultural biotechnology for resilience to climate change: A lesson from water efficient maize for Africa project" presentation by Yoseph Beyene, International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya

1. Yoseph Beyene (Ph.D)
Senor Maize Breeder, CIMMYT-Kenya
Email: y.beyene@cgiar.org
Harnessing Agriculture Biotechnology for Resilience to
Climate Change: A Lesson from Water Efficient Maize
for Africa (WEMA) Project

2. Outline
• WEMA Project
– Partners
– Objectives
– Approaches
• Progress by Breeding Approach
– Conventional Breeding
– Molecular Breeding
– Transgenic 4RD
• Highlights of Achievements

3. Maize is vital for food security
in Sub-Saharan Africa
• Over 300 million people
depend on maize in SSA
• Example: consumption in
Kenya 103 kg/ yr/ person
• Maize yield is low (1.8 t/ha
compared to world average of
4.5 t/ha)
• Major constraints:
• Drought
• Low soil nitrogen
• Diseases
• Lack of access to quality
seed Recorded droughts between 1971 and 2000, and
the number of people affected

4. Water Efficient Maize for Africa (WEMA)
• A public-private partnership to develop and deploy
drought-tolerant and insect-pest protection white
maize varieties to smallholder African farmers royalty-
free.
Expected Outputs
• Under moderate drought, WEMA maize expected to
increase yields by 25% over 2008 hybrids
• 15% conventional
• 10% transgenic
• Translates into additional 2 million MT maize during
drought years to feed about 14 to 21 million people in
the long-term.

5. AATF
African institution mandated to
access, develop, & deliver
appropriate agricultural
technologies to smallholder African
farmers royalty-free
Monsanto
World leader in gene
discovery and
commercialization of
Transgenic crops
CIMMYT
World leader for
breeding maize for
African agro-ecological
zones
WEMA Partnership Structure
NARS
• Expertise in field trials
• Breeding/Test DT maize
•Capacity building
opportunities
WEMA
KALRO; NARO; ARC;
COSTECH; & IIAM

6. ● Rapid development of completely homozygous
inbred lines and faster product identification
● Four steps:
o F1 is crossed with a haploid inducer
o Identification of kernels with haploid embryo
using visible anthocyanin marker
o Artificial genome duplication  generation D0
o Selfing  generating D1 seed
Accelerating Breeding Gains - Doubled haploids

7. DH technology is well-integrated in CIMMYT’s
product development strategy
• 26, 221 DH lines developed from
NARS, Monsanto and CIMMYT bi-
parental crosses through WEMA
Project
• The DH lines were evaluated for
per se, reaction to major leaf
diseases in Africa
• Testcross were developed and
evaluated in stages 1, 2&3 and
regional trials across locations in
five countries
• Hybrids were released in Kenya,
Uganda, Tanzania, South Africa
and nominated in Mozambique

8. WEMA has strong breeding pipelines
Stage Hybrids
Stage I 20, 900
Stage II 9, 349
Stage III 1, 761
WWT 246
Total 32, 256
Types of lines Total
DH lines 26, 221
Elite lines 1,949
Segregating lines 29,308
Total 57,478

9. DH lines compared to pedigree lines under
optimum
Pedigree Yield (t/ha)
% increase over
the best check
Anthesis
date
Ear
height
Plant
height
CKDHL0556 4.7 38.0 66.7 85.0 174.4
CKDHL0625 4.6 34.4 65.1 86.5 169.1
CKDHL0399 4.0 18.1 63.1 77.0 157.9
CKDHL0505 4.0 17.6 68.2 82.1 142.3
CKDHL0500 3.7 9.9 73.7 78.7 130.9
CML312 3.4 69.5 60.2 159.5
CML395 2.4 67.8 93.1 164.3
CML442 2.8 70.8 58.9 131.1
CML444 3.0 72.7 74.3 126.3
CML539 2.2 67.2 66.7 132.9
LSD 1.2 2.4 14.7 20.3
CV 20.6 1.7 8.9 6.7
Heritability 0.9 1.0 0.9 0.9

10. • Date of planting: 6 June 2012
• Date of last irrigation: 26 July
2012
• Date of harvesting: 10 Oct 2012
Evaluation of hybrids
under managed
drought stress
Date of planting: 25 May 2014
Date of last irrigation:19 July 2014
Date of harvesting: 28 Oct 2014

11. Accelerating Breeding Gains: Forward breeding
Entry Entry
Yield
(t/ha)
increase over
best check (%) AD EA ET
1 (CKDHL0089/CKDHL0333)//CKL14001 8.84 56.0 64.85 1.58 2.00
2 (CML395/CML444)//CKL14002 8.82 55.6 65.26 1.92 1.75
3 (CML395/CML444)//CKL14001 8.68 53.2 65.31 1.81 2.00
4 (CKDHL0159/CKDHL0295)//CKL14003 8.66 52.7 66.06 1.90 2.00
5 (CKDHL0089/CKDHL0333)//CKL14002 8.62 52.2 66.32 2.25 2.00
6 (CML395/CML444)//CKL14005 8.55 50.9 65.30 2.16 2.00
7 (CKDHL0089/CKDHL0295)//CKL14001 8.52 50.3 65.43 1.75 2.00
8 (CKDHL0089/CML395)//CKL14001 8.39 48.0 65.20 1.74 2.00
9 (CKDHL0089/CKDHL0295)//CKL14006 8.34 47.2 68.68 1.92 2.00
10 (CKDHL0159/CKDHL0295)//CKL14002 8.28 46.2 65.44 2.34 2.00
Pioneer 3253 (Pioneer) 5.67 66.48 3.07 2.25
DK8053 (Monsanto) 5.27 65.03 2.75 3.00
DH04 (Kenya seed) 5.01 65.77 3.00 2.50
DK8031 (Monsanto) 3.45 65.88 3.84 2.50
nlocs 6 6 6 2
Gmean 7.42 65.70 2.35 2.25
LSD 1.10 1.32 0.49 0.69
CV 7.53 1.02 10.7115.40
Heritability 0.85 0.89 0.79 0.55

12. Hybrids Release and Commercialization
Nominating country
Hybrid Kenya Uganda Tanzania
WE5101 Yes Yes Yes
WE5107 Yes Yes Yes
WE5109 Yes Yes Yes
WE5103 Yes Yes
WE5108 Yes Yes
WE5111 Yes Yes
WE5117 Yes Yes
0
5
10
15
20
25
2012 2013 2014 2015
1
16
18
24
Numberofhybrid
Year of release

13. Timeline for delivery pathway of products
13
2013 2014 2015 2016 / 2017
Introduction of first
WEMA Hybrid
MON810
application
in Kenya
MON810 Approvals
For commercialization
MON87460
Approvals (allows
for Stacks with
MON810)
Ramp up of WEMA
Hybrids

14. Molecular Breeding

15. Use of Breeder-friendly Markers for Maize
Streak Virus (MSV) Resistance
msv1
GWAS in a panel of 300 lines, genotyped
with GBS (~700K SNPs) Validation of SNP markers in 660 DH lines (biparental
populations)
• Three SNP markers identified and
validated within the Msv1 region
• MAS for this region increases resistance to
MSV by 25% (1.2 units on a 1-5 scale)
0
50
100
150
200
250

16. Forward breeding: Using markers for MSV
resistance at early stage of testcross formation
Sampling leaf tissue in the DH nursery, Sept 2015
SNP Trait Chr SNP RR SS
PZE0186065237 MSV 1 C/T C:C T:T
PZE0186365075 MSV 1 C/A C:C A:A
PZE-10109395
MSV
1 A/G A:A G:G
Population PZE-
101093951
PZE01860
65237
PZE01863
65075
Comment on msv1 data Decision
CML312/INTA-F2-192-2-1-1-1-B*7-2-B-10-B-B-B:@ A:A C:C C:C Homozygous for favorable alleles at 3 loci Select
CML312/INTA-F2-192-2-1-1-1-B*7-2-B-10-B-B-B:@ A:A C:C C:C Homozygous for favorable alleles at 3 loci Select
CML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ A:A C:C C:C Homozygous for favorable alleles at 3 loci Select
CML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ A:A C:C C:C Homozygous for favorable alleles at 3 loci Select
CML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ G:G T:T A:A Homozygous for unfavorable alleles at 3 loci Reject
CML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ G:G T:T A:A Homozygous for unfavorable alleles at 3 loci Reject
CML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ G:G T:T A:A Homozygous for unfavorable alleles at 3 loci Reject
CML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ G:G T:T A:A Homozygous for unfavorable alleles at 3 loci Reject

17. Large-scale implementation of GS/MARS in Africa
• In 2008, CIMMYT started the largest public GS/MARS
projects in SSA
• Over 35 bi-parental maize populations advanced
through MARS/GS
• Genetic gain studies completed for 18 populations
using two protocols:
– using a subset of markers significantly associated
with QTLs for grain yield and ASI
– Using all markers distributed across maize genome
without test for association with QTLs

18. Self selected
Plants
Self selected
Plants
Self selected
Plants
Cycle 1
Genotype
Self or
recombine
selected
Plants
Cycle 2
Genotype Self or
recombine
selected
PlantsCycle 3
Crossed with Tester
F4
Inbred A x Inbred B
F1
F2
F3 = Cycle 0 F3 x Tester
F5
F6
Evaluate TC
under target
environments
Phenotypic Selection Cycle 0 Cycle 1 Cycle 2 Cycle 3
Genotype,
Select Best
Families Based
on Phenotypic
and Genotypic
Data and
Recombine
Genotyping:
All markers or
a subset of
significant
markers
QC/QA
genotyping
Develop
DH pop
MARS work flow
Genetic gain studies
Polymorphis
m screening

19. Genetic Gain Studies on C0-C3 from MARS
Cycle Design
C0 Made balanced bulk from each F2:3
family within a population
C1 Made balanced bulk from the selected
individuals/families
C2 Made balanced bulk from the selected
individuals /families
C3 Made balanced bulk from selected
individuals /families
Lines from
Pedigree
6 random F6 lines from each population
selected through pedigree breeding
Reference
entries (3)
2 parents and F1
Single cross
testerx
+ Best currently
available
commercial
hybrids (checks)

20. Gain in grain yield using genome-wide SNPs
under drought environments in SSA
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Grainyield(Mg/ha)
Populations
Cycle0 Cycle1 Cycle2 Cycle3
Genetic gain from conventional breeding in Africa
18 kg ha-1 yr-1 (Edmeades, 2013)
32 kg ha-1 yr-1 (B. Masuka, submitted)
Genetic gain GS is 2- 4 times higher than from
conventional breeding reported in sub-Saharan Africa.
Overall gain in GY : 70.5 kg ha-1 year-1
Beyene et al. (2015) Crop Sci. 55:154–163

21. Performance of hybrids developed from GS-C3-DH
lines, founder parents and commercial checks
under optimum
Yield;t/ha
Populations
0
1
2
3
4
5
6
7
8
9
Pop1-GWS Pop2-GWS Pop3-GWS Pop4-GWS Pop5-GWS
Top 5 hybrids Parents Commercial checks
Phenotyped at 3 optimum locations
Gain over the commercial checks= 8.7 to 20.8%
Gain over the parents = 9.0 to 91.1%

22. Gain in grain yield under drought and optimum
across 10 MARS pops
Beyene et al. (2016) Crop Sci. 56:1–10
Genetic gain from conventional breeding in Africa
18 kg ha-1 yr-1 (Edmeades, 2013)
32 kg ha-1 yr-1 (B. Masuka, submitted)
Genetic gain GS is 1.6- 2.8 times higher than from
conventional breeding reported in sub-Saharan Africa.
Overall gain in GY : 51 kg ha-1 year-1

23. Performance of hybrids developed from individual
C1S2 of MARS and pedigree breeding under drought
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
1008 1015 1016 1017 1018 1019 1020 1021 1023 1028
Grainyield(t/ha)
Populations
Best C1S2
Pedigree
Check
Parents
Beyene et al. (2015) Euphytica : online first
Heritability = 0.32 to 0.75

24. Improved inbred lines and hybrids developed
through rapid-cycle GS
Fixed lines
Drought tolerant hybrids

25. Transgenic R&D

26. The effect of CspB gene on grain yield of maize
under field condition in the USA
Grain yield of 3 hybrids
with CspB gene
evaluated in yield trials
across the western
dryland USA - averaged
across locations that
experienced water-
deficit stress during the
late vegetative or grain
fill periods of the
season.
Castiglioni et al., 2008

27. MON87460 yield differences between positive & negative
across locations in South Africa (2008-2014)
• Hybrids showed significant benefit of trait (MON87460) under drought
stress in general and under severe, high and moderate drought stress.
• The more severe the stress the higher the differences between positive
and negative (up to 360 kg/ha).
*
*
%Delta
0
1
2
3
4
5
6
7
8
9
*
*
Stress N Positive N Negative
Optimum 2472 2593
Stressed 7076 7019
Severe 277 279
High 3022 2951
Moderate 2383 2348
Low 1394 1441

28. 0
2
4
6
8
10
12
Positive Mean Negative Mean
Yield[t/ha]
*
24%
• The gene has a positive and
significant effect on yield.
• The gene significantly reduced
numbers of exit holes and
tunnel length after artificial
C. partellus infestation.
• The gene significantly reduced
B. fusca larvae survival and leaf
area consumed.
ProportionB.fuscalarvaealive
0.00
0.10
0.20
0.30
Positive Mean Negative Mean
*
-81%
LeafAreaConsumed[mm2]
0
10
20
30
40
50
Positive Mean Negative Mean
*
-73%
Tunnellength[mm]
0
1
2
3
4
5
Positive Mean Negative Mean
*
-96%
0
1
2
3
4
Positive Mean Negative MeanNumberofExitHoles
*
-96%
MON810 Kenya CFT1-3 Executive Summary

29. Highlights of Achievements
• A total of 59 hybrids released in in Kenya, Tanzania, Uganda and
South Africa
• Successfully integrated molecular markers and DH technology into
product development
• We have conducted the largest public MARS/GS projects and
demonstrated 2-3 fold higher grain yield using MARS and GS than
pedigree methods in tropical maize
•
• Meta analysis of MON87460 indicated significant benefits of DT
trait under drought stress
• Combined analysis of MON810 in Kenya indicated positive and
significant effects on grain yield under artificial infestation

30. Other contributors to the studies
(in alphabetical order)
• Amsal Tarekegne
• Barbara Meisel
• Bindiganavile S. Vivek
• Boddupalli M. Prasanna
• Gregorio Alvarado
• Jose Crossa
• Kassa Semagn
• Lewis Machida
• Pierre Sehabiague
• Raman Babu
• Stephen Mugo
• Sudha Nair
• CIMMYT research assistants at different locations

31. Acknowledgements
• WEMA Partners
• Bill and Melinda Gates Foundation (BMGF)
• United States Agency for International
Development (USAID)
• Howard G. Buffet Foundation (HGBF)