The document summarizes the work of the International Center for Agricultural Research in the Dry Areas (ICARDA) which focuses on science-based approaches for efficient conservation and use of genetic resources to address issues like increasing population, land degradation, water scarcity, loss of agrobiodiversity, and climate change. It provides examples of ICARDA's work on crop improvement, developing FIGS (Focused Identification of Germplasm Strategy) subsets to identify genetic resources with specific traits, transferring useful traits from wild relatives to crops, and developing new synthetic wheat varieties to introduce novel genetic diversity.
Science-based approaches for efficient conservation and use of genetic resources
1. International Center for Agricultural Research in the Dry Areas
icarda.org cgiar.org
A CGIAR Research Center
Science-based approaches for efficient
conservation and use of genetic resources
Ahmed Amri on behalf of ICARDA colleagues
✓ Increasing population
✓ Land degradation
✓ Water scarcity
✓ Loss of agrobiodiversity
✓ Climate change
2. icarda.org 2
Crop Improvement and Food Security
“ a situation that exists when all people, at all times, have physical,
social and economic access to sufficient, safe and nutritious food that
meets their daily healthy life style”
1. Availability: production ….
2. Access: reflect the demand side…
3. Utilization: make good use of food to which they have
access; dietary quality associated with malnutrition
Food is the moral right of all who are born into this world
Dr. Norman Borlaug
Dr. N. Borlaug:
(ICARDA, May 2005)
“There are many good genes in the
wild species and we should use them
more in breeding”
Hessian Fly Resistant
3. icarda.org 3
Approaches for conservation and use of
genetic resources
• How to add novel diversity to existing collections?
• How to efficiently mine the collections?
• Strengthening pre-breeding
4. Gap analysis to add novel diversity for
landraces
4
Scope: ICARDA, CIAT, and Crop
Trust will develop methods to
understand and map existing
diversity and determine
coverage and gaps of 22 ex situ
collections for crop landraces
and forages, using data from
Genesys and other sources.
• The Crop Trust to run crop
diversity trees
• CIAT to run spatial gap
analysis
• ICARDA to run trait gap
analysis.
Diversity tree for barley landraces
Gap classes for Naked Barley
5. Aegilops, Avena, Hordeum, Secale and Triticum species
Sources: Katherine Whitehouse, Holly Vincent, Ahmed Amri and Nigel Maxted (2012) and Maxted et al (2010)
Cicer, Lathyrus, Lens, Medicago, Pisum and Vicia species
Mapping of species richness for priority species
6. 6
Performance Measures k-NN SVM RF
Accuracy 0.885 0.882 0.895
95% CI (0.87, 0.899) (0.866, 0.896) (0.881, 0.908)
No Information Rate 0.831 0.831 0.831
P-Value [Acc > NIR] 0.00 0.00 0.00
Kappa 0.578 0.54 0.614
Sensitivity 0.625 0.546 0.649
Specificity 0.938 0.95 0.945
True Positive 205 179 213
False Positive 101 81 89
True Negative 1515 1535 1527
False Negative 123 149 115
Landraces gap analysis: Map of predicted
probability for frost tolerance in Barley
Modeling metrics for frost
7. Crop No of
accs.
Crop No of
accs.
Barley 30,214 Pisum spp. 6,132
Bread wheat 15,053 Trifolium spp. 5,936
Durum wheat 20,505 Vicia spp. 6,562
Primitive wheat 1,195 Faba bean 10,034
Aegilops spp. 5,157 Chickpea 15,195
Wild Triticum 1,962 Lentil 13,978
Wild Hordeum 2,575 Wild Cicer 554
Not mandate cereals 195 Wild Lens 619
Lathyrus spp. 4,451 Range & Pasture 7,406
Medicago annual 9,136 Others 50
Total 156,909
Regeneration of 600 strains
of rhizobium
Total taxa
Perennial
Cross-pollinated
718
> 100
> 130
% unique accessions 45
% landraces and
native species
85
% characterized 78
% safe duplicated 98
% stored in Svalbard 60
Collections held in-trust by ICARDA
Syria: Active and base
collections (250,000)
Second level Safety duplication at
Svalbard
Safety
duplication
Lebanon: Collections of faba
bean, Lathyrus, forage and
range species and crop wild
relatives (75,000)
Morocco: Collections
of cultivated species
of barley, wheat, lentil
and chickpea (45,000
acc.)
Safety
duplication
9. User define a
trait and set
size
No data
available
Data available
Data assembly
Filtering to
mimic selection
pressure
Subset
formation
maximizing
environmental
diversity
Data assembly
Machine
learning
algorithms
Metrics for
validation
Trait prediction
for unobserved
accessions →
assign a
probability to an
accession
Evaluation
Evaluation
• Environnement
• Trait (disease score)
FIGS subset
Filtering
Modeling
FIGS approach links adaptive traits, environments (and
associated selection pressures) with genebank accessions (e.g.
landraces and crop wild relatives)
Focused Identification of Germplasm Strategy:
Definition and pathways
10. Trait
Barl
ey
Brea
d
whe
at
Chic
kpea
Duru
m
whe
at
Faba
bean
Lenti
l Pea
AB x x
Acid x
Asco
chyt
a
x
BGM x x
Botr
ytis
x
Bruc
hid
x
BYD
V
x
Chill x
Cold x x
CR x
CSN x
Drou
ght
x x x x x
Fros
t
x x
Fusa
rium
x
Heat x x x x
Heat
Cool
x
Hess
ian
Fly
x
HotC
old
x
Leaf
Min
er
x
Leaf
Rust
x x
Low
pH
x x x x
LR x
Net
Blotc
h
x
pH x
Phos
phor
ousU
seEf
ficie
ncy
x
Phyt
opht
hora
x x
Pod
Bore
r
x
Pow
dery
Mild
ew
x x
PUE x
Rust x
RW
A
x
Salin
ity
x x x
Salt x x x
Scal
d
x
Sept
oria
x
Spot
Blotc
h
x
Ste
m
Gall
x
Ste
m
Rust
x x x
Sun
Pest
x
Sunn
Pest
x
TurA
fglrn
x
Viru
s
x x
WB x
Wet
Dry
x
10
Crop Trait
Barley
BYDV
CSN
Drought
Frost
Heat
Leaf Rust
NA
Net Blotch
pH
Powdery Mildew
Salinity
Scald
Stem Gall
Stem Rust
Bread
wheat
CR
Drought
Frost
Heat
Cold
Hessian Fly
Low pH
LR
Phosphorous Use Efficiency
Powdery Mildew
RWA
Septoria
Spot Blotch
Stem Rust
Sun Pest
Durum
wheat
Hot
Leaf Rust
Low pH
Salt
Stem Rust
Sunn Pest
Drought
Crop Trait
Chickpea
AB
BGM
Chill
Cold
Drought
Fusarium
Heat
Leaf Miner
Low pH
Pod Borer
Salinity
Virus
Faba bean
Acid
Botrytis
Bruchid
Cold
Drought
Heat
Low pH
Phytophthora
Rust
Salt
Lentil
AB
Ascochyta
BGM
Drought
Phytophthora
Salt
Virus
Pea Salinity
FIGS subsets developed and shared with partners
• Up to know more than 80 FIGS
subsets were formed and shared
with users.
• Confirmed traits include salinity (all
crops), all rusts (barley), Sunn pest
(wheat), spot and net blotch
(barley)…
• Only traits not yet found using FIGS
are resistance to gall midge in barley
and resistance to ascochyta blight in
chickpea
11. Verified
under controlled conditions
534 accessions screened at ICARDA
Two QTLs have
been identified
on 5B and 6A for
Sunn Pest
8 landrace accessions from
Afghanistan and 2 from Tajikistan
identified as resistant at juvenile stage
3 Mapping populations developed and
phenotyped during three years.
Genetic analysis finalized.
Entomology: Sunn Pest example FIGS Outcomes
12. Screening of NB-FIGS with Net blotch and
Spot blotch
1
17
12
24
9
0
5
10
15
20
25
30
#ofbarleyaccessions
§Infection responses
Response of NB-FIGS subset to Net
Blotch
Immune
Resistant
Medium Resistant
Medium
susceptible
0 2
15
28
38
0
10
20
30
40
Numberof
accessions
¥Infection responses
Response of NB-FIGS to Spot Blotch
Immune
Resistant
Medium
Resistant
NB- FIGS subset seems
to be specific to NB
Focused Identification of Germplasm Strategy:
Specificity of FIGS sets
95
11
23
54
36 30
23 21
0
10
20
30
40
50
60
70
80
90
100
0
<50
>50-<100
>100-<
200
>200-<
400
>400-<
800
>800-<
1500
>1500
95 / 293
Immu
ne
183/293 Slow
rusting
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Value of genetic resources in lentil improvement
Trait of interest
CWR
screened
Donors identified
Fusarium wilt 435 ILWLs76, 79 37, 113, 138
Salinity tolerance 100
ILWL297, ILWL368, ILWL371, ILWL417,
IG136670
Earliness 285 ILWL 118
Fe and Zn contents 285 ILWL74, IG135395, IG 135403
Orobanche 31 ILWL367, ILWL240
Lens orientalis derivative lines
14. Assessment of Lathyrus germplasm for ODAP content and
Resistance to Orobanche
0.087
0.045
0.335
0.133
0.024 0.045
0.093 0.093 0.093
0.049 0.030
0.086
0.229
0.162
0.105
0.131
0.096
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
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Value of wild relatives in durum wheat
improvement
Germplasm
1,000-Kernel weight
(g)
Grain protein content
(%)
SDS sedimentation test
(ml)
Yellow index
(b*)
Average Max Average Max Average Max Average Max
Varieties 44.8 c 47.5 b 14.9 a 15.6 b 35.4 a 46.8 a 20.7 a 22.7 a
Elites 47.3 b 48.4 b 14.7 a 14.9 c 24.6 b 29.6 b 17.4 b 18.2 c
Wide cross 51.9 a 56.6 a 15.0 a 16.1 a 34.4 a 44.0 a 18.3 b 20.2 b
Grand Mean 50.1 14.9 33.3 18.6
LSD 2.3 0.6 5.9 1.0
1
Wide-crosses (WC) obtained by
“top-crossing” with wild
relatives have better yield
potential + stability, and good
end-use quality
Wide crosses of durum wheat reveal good disease resistance, yield stability, and industrial quality across Mediterranean sites.
Zaim et al. 2017. Field Crop Research, 214:219-227.
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Releases of « wide » varieties
• Among 125 varieties released, 8% were derived from CWR, and 30% by landraces
• Lately, wild relatives are becoming even more common
• Omrabi (Jori/Haurani) has been released in 15 countries and is in the pedigree of 17 cultivars
0
2
4
6
8
10
Numberofreleases
CWR Landraces
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Genetic diversity for breeding
Cluster ID N
Allelle segr. (%)
Common Rare
1. Middle East 11 0.13 0.00
2. T. abyssinicum 18 0.42 0.01
3. Mediterranean 26 0.65 0.06
4. C. and S. Asia 27 0.84 0.62
5. ‘Om Rabi’ 13 0.19 0.00
6. Italian 26 0.46 0.01
7. Exchange 58 0.58 0.04
8. Developed 30 0.43 0.01
9. ICARDA 119 0.51 0.03
10. CIMMYT 42 0.44 0.21
Kabbaj et al. 2017. Frontiers in Plant Sciences, 8:1277.
21. Using high density DartSeq markers for a better
conservation and use of genebank accessions
Mis-classified
accessions
Tunisian
durum
landraces
Different diversity:
New genepool
24. Conservation and
sustainable use of
Agrobiodiversity
Status and threats
assessed
Awareness increase
and information sharing
Appropriate policies
and legislations
Low-cost technologies
for in situ conservation/
management
Collection and ex situ
Conservation/management
Alternative sources
of income
Add value
technologies
Improvement of income/
Livelihoods of custodians
Regional and international
collaboration
Benefit sharing
and funding
Actions for complementary actions for effective in situ and
ex situ conservation of genetic resources
25. icarda.org 25
• IPM of Cactus Cochineal: Good progrees since
September 2016:
• Through surveys, the initial pest
distribution data and map.
• Out of 320 cactus ecotypes tested,
eight were found resistant to the
cochineal. These resistant ecotypes
have been registered in the Moroccan
catalogue.
• Three bio-insecticides were identified
with high level of efficiency against the
cochineal.
• Cryptolaeumus montrozieri identified
as a potential predator.
Diversification and intensification of farming
systems