Abstract More than 300m people below the poverty line in developing countries depend on root, tuber and banana crops for food and income, particularly in Africa, Asia, and the Americas. The CGIAR Research Program on Roots, Tubers and Bananas (RTB) is working globally to harness the untapped potential of those crops in order to improve food security, nutrition, income, and climate change and variability resilience of smallholder production systems. RTB is changing the way research centres work and collaborate, creating a more cohesive and multidisciplinary approach to common challenges and goals through knowledge sharing, multidirectional communications, communities of practice, and crosscutting initiatives. Participating centres work with an array of national and international institutions, non-governmental organisations, and stakeholders’ groups. RTB aims to promote greater cooperation among them while strengthening their capacities as key players. Because the impact of RTB research is highly dependent on its adoption by users, the programme’s research options are designed and developed together with partners, clients, and other stakeholders, and are informed by their needs and preferences. Climate change will have multiple impacts on poverty and vulnerability. Recent studies by the World Bank suggest that one of the most significant routes for this impact will be through increased food prices, which may undo progress in poverty reduction and will make achieving Sustainable Development Goals increasingly difficult. This underlines the urgency of investment in mid- to long-term strategic research to improve climate resilience. The presentation looks at progress in understanding the current trends and forecasting the changes that may occur to guide research; it examines some of the critical issues that will face potato and sweetpotato farmers; and ends with a plea for climate-smart research and breeding. And though this includes many of the things we already do, we need to do them faster, better, and smarter.

1. RTB planning for climate
resilience
Graham Thiele, Greg Forbes, Awais Khan, Jurgen Kroschel,
Bettina Heider, Dieudonné Harahagazwe, Maria Andrade,
Merideth Bonierbale, Michael Friedmann, Mihiretu Cherinet, and
Roberto Quiroz
APA - Addis Ababa
11 October 2016

2. RTB PROGRAM

3. A COLLABORATION OF:
• Broad based collaborative platform
• Around 350+ research-for-development
stakeholders & partners
• Including private sector

4. Banana
Plantain
Cassava Potato Sweetpotato Yam Other R&T
300 million small holder farmers and
processors depend on RTB crops
Buffering role in food systems
Our Crops

5. Biological constraints to breeding
Breeding
complexity
Potato Sweet
potato
Cassava Yam Banana
Multi-species + - - + +
Polyploidy ++ ++ - ++ +++
Clonal propagation + + + + +
Heterozygosity ++ ++ ++ ++ ++
Multiplication rate/year 1:10 1:15 1:5 1:20 1:10
Other constraints:
• Low seed setting
• Low germination
• Crossing difficulties
• Long generation time

6. RTB PLANNING FOR CLIMATE
RESILIENCE: POVERTY IMPACTS

7. Sub-Saharan Africa most vulnerable:
price rises and climate change
World Bank 2016 – Shock Waves: Managing the Impacts of Climate Change on Poverty

8. Per-capita food demand
IFPRI, IMPACT version 3.2, 8 September 2015
Cereals
Meat
Roots & tubers
Pulses
Oilseeds
Fruits & veg
WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean;
MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa;

9. Population at risk of hunger:
different climate change scenarios
IFPRI, IMPACT version 3.2, 8 September 2015
EAP = East Asia and Pacific; SAS = South Asia; FSU = Former Soviet Union;
MEN = Middle East and North Africa; SSA = Sub-Saharan Africa; LAC = Latin America and Caribbean

10. 1. Climate change will increase food prices
2. Increasing food prices worsens extreme poverty
3. Per capita demand for roots and tubers in SSA
significantly higher than cereals in 2050
4. High global emissions scenario, population at risk of
hunger declines markedly in most of world, but only
slightly in SSA
5. Technological change in roots and tubers essential
to dampen food price increases and risk of hunger under
any climate change scenario
Climate change, poverty and roots and
tubers
World Bank 2016

11. RTB PLANNING FOR CLIMATE
SMART BREEDING: FRAMEWORK

12. Steps in climate smart breeding
1. Looking into the future: downscaling climate change
models & crop modelling to drivers of yield loss
2. Identifying key traits: to respond to drivers and
estimating trait level needed to respond to climate
change
3. Genomic research and phenotyping: to incorporate
climate responsive traits
4. Varietal selection: for best bet climate smart varieties
5. Management options: for climate smart varieties
6. Scaling: seed system

13. RTB PLANNING FOR CLIMATE
SMART BREEDING: LOOKING
INTO THE FUTURE

14. Climate
suitability
studies
Temperature
change (°C)
model
ensemble:
2030s, 2050s &
2090s relative
to 1970-99
Source: Washington and Pearce, 2012

15. Model ensemble:
suitable area
sweetpotato

16. Model ensemble:
Suitable area sweetpotato
High Emissions Scenario
Current 20902050
Highly
Suitable
Not
suitable
Source: Washington and Pearce, 2012 – Ensemble sresb1 JAPRE Climatic Growth Area

17. Model ensemble:
Suitable area potato
High Emissions Scenario
Current 20902050
Highly
Suitable
Not
suitable
Source: Washington and Pearce, 2012 – Ensemble sresb1 JAPRE Climatic Growth Area

18. Late blight with climate change in sub-
Saharan Africa
LB severity - current LB severity - 2090 Legend
Ethiopia: increase in frequency of fungicide application from once a
month to once a week

19. Effect of climate change on the sweetpotato weevil
Cylas puncticollis
• Pest may expand to sweetpotato production regions of southern Africa and at
higher altitudes
• Overall pest abundance (damage potential) will increase by 2 generations per year
Change in
generation
Index by 2050

20. RTB PLANNING FOR CLIMATE
SMART BREEDING: TRAIT
IDENTIFICATION

21. General Decrease in Dry Matter with Heat
(meta-analysis from potato)
Amoros and Bonierbale 2016

22. Root System Architecture and its
Potential Role in Stress Tolerance in
RTB Crops
Awais Khan
December 8, 2015

23. Roots and Root System Architecture
Comas et al. 2013, Front. Plant Sci. 4:442.
Primary interaction with soil and microbiome, uptake of water and
nutrients
Traits under study for drought
tolerance
Maize Ryegrass
Oilseed rape Sugar beet
Root system
architecture
(RSA)
 Root Axes
 Root angles
 Root
Branching
 Root length
 Root volume/
density
 Root number

24. QTL for Days to Initiate Roots

25. Field Experiments for Stress Tolerance

26. Traits
Trait Component
traits
Variable
Drought
tolerance
Root traits Root length
Number of roots
Root fresh and dry weight
Root angle
Stolon traits Stolon number
Stolon diameter
Stolon fresh and dry weight
Tuber traits Tuber number
Tuber fresh and dry weight
Harvest Index Tuber Fresh Weight (FW) / Total
biomass (FW)* X 100
*Total biomass= FW(leaf + stem
+ stolon + tuber +root

27. Traits
Trait Component
traits
Variable
Drought
tolerance
Physiological
traits
Chlorophyll content
(SPAD)
Canopy temperature
Canopy reflectance
(NDVI)
Biochemical Metabolite profiling and NIRS

28. Note:
Bars=2-LOD support interval of QTL, terminal drought=red, well-
watered=green, greenhouse trial=striped fill and field=solid
Genetics: Identification of QTLs and markers
linked to drought stress related traits

29. Traits
1. Identifying other traits for consideration: dry matter
2. Looking at new traits: root architecture
3. Pinning down QTLs for drought stress to develop
markers

30. RTB PLANNING FOR CLIMATE
SMART BREEDING: GENOMICS
AND PHENOTYPING

31. Screening sweetpotato for heat tolerance
• Evaluation environments (N. Peru):
-heat stress (summer): Ø soil temp.
at night: 30 °C
-no-heat stress (winter): Ø soil
temp. at night 24 °C
• Plant material: 1973 germplasm
accessions CIP genebank.
• Key prioritized traits: heat tolerance
and early bulking, plant
performance and yield related traits
• Remote sensing fast throughput
method to screen effects of heat on
biochemical and physiological
processes
Experimental site in Piura during winter.
Yields of storage roots vs. pencil roots
represent an indicator for heat tolerance.

32. Aerial picture Thermographic image
Summer 2014 heat stress
exposure at maximum storage
root bulking.

33. Results
• Large fraction
sweetpotato germplasm
heat stress tolerant (i.e.,
305 clones with yields
>12.2 t ha-1 under
stress).
• Considerable genetic
variation heat stress
• Large pool favorable
alleles to heat stress
• Large and sustainable
genetic gains expected
Bettina Heider1, Elisa Romero1, Raul Eyzaguirre1, Wolfgang Grüneberg1, Emile
Faye2, Stef de Haan1,3 and Merideth Bonierbale1
1= CIP, 2=IRD (Institut de recherche pour le développement), 3=CIAT

34. RTB PLANNING FOR CLIMATE
SMART BREEDING: BREEDING
AND VARIETAL SELECTION

35. Breeding and varietal selection: challenges
 Combining multiple traits
Drought and heat seldom sole stress factor at
farmer field
Not yearly event
Plants different physiological mechanisms
Market & consumption preference variation

36. Region Target traits Target level 2022
African and
Andean
highland tropics
Drought tolerance; late blight
resistance; biofortification
with Fe, Zn;
Table-potato preference
90–110 days maturity;
drought tolerance in 20% of
clones;
late blight susc. score 2-3;
45-ppm Fe and 35-ppm Zn;
vitamin C, 130 mg/100g fresh
weight
African and
Asian mid-
elevation
tropics
Resistance to late blight and
PVY;
chipping ability
Heat tolerance;
low anti-nutrient content
90 day
PVY extreme resist. PLRV
resistance
Late blight rate 3-4
tuberization & Bulking under
warm day temps
.
80% clones no glycoalkyloid
formation under stress
Breeding targets potato – CIP-RTB

37. Breeding to extend day and night temperature limits for
potato production
80 – 100
days
10
14
18
22
26
30
34
38
Oct Nov Dec Jan Feb Mar
(Midmore, 1992)
AirTemperatureºC
Max Day Tº
Max Night Tº
Target tuber production at >28 oC day and > 18 oC night
Earliness to fit in production window

38. LD-33.100
LD-80.78
0
10
20
30
40
50
tn/ha
Clones
UNICA
REICHE
REVOLUCION
New generation of clones: higher yielding with a shorter
growing period
LD-33.58LD-
22.58
LD-
92.42
LD-88.104LD-
16.72
LD-19.90
Evaluation of yield (San
Ramon, harvest at 70 dap)
Clones
Yield
(t/Ha)

39. Understanding downstream adoption
challenges (Asrat et al 2015)
 Breeding informed by dynamics of
adoption for heat or drought tolerance
 What drives the dynamics?
 Key processes in crop management
related to climate: variety use,
perception and adaptation strategies
 Gender differences in knowledge and
preferences for climate related traits

40. RTB PLANNING FOR CLIMATE
SMART BREEDING:
MANAGEMENT OPTIONS

41. Management options
• Climate smart breeding one element in
climate smart agriculture
• Magnitude of climate change makes
adaptation in crop management essential
• Underdeveloped in RTB!
• Critical backward linkage to breeding

42. RTB PLANNING FOR CLIMATE
SMART BREEDING: SCALING

43. Scaling (seed systems)
Triple S root based
vine multiplication
system

44. RTB PLANNING FOR CLIMATE
SMART BREEDING: NEW
PARADIGM

45. NEW PARADIGM OF GENOMICS-ASSISTED CLIMATE SMART
BREEDING
Varshney et al. 2014
Foresight, models and
metrics for climate smart
breeding
Do what we were
already doing but:
Faster
Better
Cleverer

46. Wrap up
1. Climate change increase food prices and poverty
2. Largest effect SSA: roots and tubers primary staple
3. Complex picture of climate change impacts
4. Direct, indirect and collateral effects of CC!
5. Good news: promising traits & progress in breeding
6. Climate smart breeding: faster, better, cleverer
7. High priority for RTB to support teaming up!