Physiological Phenotyping for Adaptation to Droughtprone and Low Phosphorus Environments in Cowpea
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1 Physiological Phenotyping for Adaptation to Droughtprone and Low Phosphorus Environments in Cowpea Nouhoun Belko, Kanako Suzuki, Jimmy Burridge, Patricio Cid, Omonlola Worou, Seyni Salack, Yonnelle Moukoumbi, Vincent Vadez, Jonathan Lynch, Thomas Sinclair, Christian Fatokun and Ousmane Boukar Pan-African Grain Legume & World Cowpea Conference 01 March 2016, Livingstone-Zambia
2 International Institute of Tropical Agriculture Established in 1967, Member of CGIAR. Work with partners to help smallholder farmers to raise agricultural production and productivity, improve food security, and increase incomes in SSA. Mandate on cassava, maize, yam, banana/plantain, soybean, Cowpea. Headquarters in Ibadan-Nigeria, research Hubs/Stations in West (Kano), East, Central and Southern Africa.
3 Frequent and Intense Droughts with Climate Change
4 Global P deficiency: primary constraint to life on earth Issue of accessibility and affordability of fertilizers by smallholder farmers
5 Potential Benefit from 21st century green revolution Benefit from 20th century green revolution Yield Can we develop genotypes with superior yield at low soil fertility and moisture levels? Dwarf genotypes respond to high fertility But no yield gain at low fertility (*) Traditional genotypes lodge at high fertility Soil Fertility/Moisture
6 Contrasting strategies for water and low P Objectives: Define environment, Understand mechanisms, genetic improvement Hypothesis: Soil water saving, soil foraging and nutrient acquisition H 2 O 5% 11% P 4ppm 10cm 2ppm 20cm 18% 23% 0.5ppm 30cm 0.25ppm 40cm
7 Phenotyping: bottleneck in modern breeding Physiologist-geneticist: precise information on some aspects of the cell, organ, plant level in large genetic populations Breeder: set of testing sites in a given target environment to evaluate performance - yield in promising breeding lines Agronomist: evaluate a given line across number of agro packages Field-based phenotyping of yield in target regions (Nigeria, Senegal) Trait-based phenotyping of key phenes identified in the modeling outputs
8 Field screening for drought tolerance and high yield potential in cowpea germplasm 348 lines + 12 checks under 2 water regimes with 3 replications Plant phenology (days to flowering and maturity), yield components (fodder, pod and grain), visual scoring for (i) Striga infestation and(ii) canopy leaf senescence under drought, and SPAD-CMR, NDVI and IR leaf temperature data on selected lines
9 Cowpea genotypes performance under WS/WW Drought-stressed grain yield (kg IT98K IT93K IT84S-2049 IT98K Mouride KVX-61-1 IT97K UCR-P-24 UC-CB27 Prima Sasaque IT95K IT95K-1491 Ife-Brown Bambey 21 IT95K-1479 Melakh Yacine UC-CB46 Apagbaala IT93K-2046 IT95M-190 IT85F IT82E-18 UC-524B Sh-50 IT84S-2246 IT95M-303 IT93K IT85F Drought-stressed grain yield (kg IT98K KVX KVX403 IT93K IT99K IT96D-610 Suvita 2 IT98K IT97K-207- N diambour Mougne IT89KD-288 IT00K IT98K IT98K IAR8/ Iron-Clay IT95K IT98K IT90K KVX-396 KVX-525 IT95K IT97K IT98K IT97K IT83D-442 Petite-n-grn Non-stressed grain yield (kg/ha) Non-stressed grain yield (kg/ha) A: Short duration genotypes B: Medium duration genotypes
10 Higher SPAD and Lower leaf temp correlated with yield in WS Days to 50% Flowering Days to 90% Pod Maturity Fodder DW (g/plant) Pod DW (g/plant) Seed DW (g/plant) Seed Harvest Index (-) 100 Seed Weight (g) Genotype WS WW WS WW WS WW WS WW WS WW WS WW WS WW Achishiru Danila IT00K IT07K IT07K IT97K IT98K IT98K IT98K IT98K IT99K Tvu Mean SE F value Pr>F <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 CV Pod Load Score SPAD-CMR (-) NDVI (-) Leaf Temp (0C) Leaf Senesc. Score Striga Pres/Abs. Genotype WS WW WS WW WS WW WS WS WS WW Achishiru Danila IT00K IT07K IT07K IT97K IT98K IT98K IT98K IT98K IT99K Tvu Mean SE F value Pr>F <.0001 <.0001 <.0001 <.0001 < < <.0001 <.0001 CV Seed Yiled (g/pl) y = x R² = Seed Yiled (g/pl) y = x R² = SPAD-CMR (-) Leaf temperature ( 0 C)
11 Screening for water saving traits A: Outdoor (Exp. 1) B: Greenhouse (Exp. 2) C: Growth chamber (Exp. 3) Range of leaves temperatures Range of backgrounds temperatures B Number of pixels Temperatures ( C) T Canopy = Sum ((Ti x Pxi) / Pxt) Ig = (T dry leaf T Canopy ) / (T Canopy T wet leaf )
12 Drought tolerant cowpeas had lower TR under high VPD Greenhouse Outdoor Bambey 21 IT89KD-288 KVX-525 UC-CB46 IT93K IT93K Mouride Suvita 2 VPD (kpa) 6 TR (g H 2 O g -1 Leaf dw h -1 ) TR (g H 2 O g -1 Leaf dw h -1 ) TR (g H 2 O cm- 2 h -1 ) VPD (kpa) IT98K IT99K Mouride Danila IT98K IT95K SuVita2 IAR8/ UCR-P-24 KVx61-1 IT97K IT97K IT93K IT93K Apagbaala IT84S IT95K UC IT96D CB27 IT98K KVx403 Yacine IT98K IT93K Bambey 21 Genotypes IT90K UC - Prima IT89KD-288 CB46 IT85F-3139 IT95K IT82E-18 IT83D-442 IT98K IT97K KVx525 IT93K-2046 IT84S IT97K Danila UC KVx61-1 SuVita2 - CB27 IAR8/ IT93K IT98K Yacine IT95K Mouride IT95K IT93K IT85F-3139 IT97K IT99K KVx403 IT93K IT98K UCR-P-24 IT95K Apagbaala IT98K Prima IT84S-2049 IT96D-610 Genotypes IT98K IT90K IT98K UC - CB IT97K IT89KD-288 Bambey IT82E IT93K-2046 IT83D-442 IT84S-2246 KVx Outdoor 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 Time of the day (h) 1 0
13 Canopy TR correlates with leaf temp and stomatal conductance (A) (B) TR (g H 2 O cm -2 h -1 )_High VPD at 13h y = x R² = 0.85 TR (g H 2 O cm -2 h -1 )_High VPD at 13h y = ln(x) R² = Canopy temperature ( C) Index of stomatal conductance
14 Extent of genotypic variations in plant TR, SPAD-CMR, CTD and LA in cowpea
15 Lines with Lowest Values SPAD-CMR (-) Leaf TR (g cm -2 h -1 ) Leaf CTD ( o C) Leaf Area (cm 2 ) Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu IT99K Tvu Tvu Tvu Achishiru -3.3 Tvu Tvu Tvu IT97K Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu IT00K Tvu Tvu IT00K Tvu Danila Tvu Danila Tvu IT98K Lines with Highest Values IT98K Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Tvu Danila 67.6 Tvu Tvu Tvu Tvu Tvu Tvu Tvu
16 Shoot growth response to low P (KH2PO4) Shoot DW under 0 mg P/kg KH 2 PO 4 Decrease in shoot biomass in 0 mg P/kg relative to 30 mg P/kg KH 2 PO 4 Shoot DW under 90 mg P/kg Rock P Based on their shoot biomass production under both 0 mg P/kg KH 2 PO 4 and 90 mg P/kg Rock P: Iron Bean, IT87D-941-1, IT90K , IT95K-1543 and IT97K were consistently low P tolerant and rock P efficient lines Tvu-7778, Sanzi and IT97K were the most low P sensitive and rock P un-efficient lines Decrease in shoot biomass in 90 mg P/kg Rock P relative to 30 mg P/kg KH 2 PO 4
17 Shoot growth response to low P (KH2PO4) Rate of decrease of SDM in 0P to 30P (%) IT04K a IT06K IT07K Iron bean IT10K IT07K IT09K-456 IT08K IT00K-1148 IT10K IT07K IT98K IT07K SDM in 0P (kg/ha) IT06K IT07K IT08K IT98K IT99K IT98K-697 IT90K IT07K IT98D-1399 IT10K IT10K IT06K-124 IT89KD IT84S IT83S IT07K IT99K IT07K IT09K IT97K IT10K IT99K b IT07K IT98K IT04K IT07K IT07K IT83S Iron bean IT04K Iron bean IT09K-456 IT10K IT89KD IT99K IT06K IT00K-1148 IT10K IT89KD IT95K-1543 IT07K IT04K IT99K IT98D-1399 IT07K IT07K IT06K IT99K IT90K IT09K-456 IT07K IT IT06K IT82D-812 TVX F IT08K IT07K IT06K IT98K IT98D-1399 IT83S IT98K IT07K IT00K-1148 IT07K IT07K IT99K IT07K
18 Field, lab and image based phenotying of root traits for adaptation to drought and low P Shovelomics
19 Field and lab trials for evaluating genotypic differences in root system architecture and anatomy at the ARBC Willcox-AZ with PSU partners Fifty lines planted in single row plot under WW conditions in 5 reps 5 plants per plot excavated and visually scored for root traits (Shovelomics: angle, number, density, diameter) and root samples taken for cross section anatomy analysis 5 seedlings per line for analysis of root hairs density and length using DIRT & ImageJ
20 Roots traits at seedling stage LOW HIGH Genotype TPRL BRN TVu ± ± 0.0 IT81D ± ± 0.5 TVu ± ± 1.2 IT89KD ± ± 1.7 TVu ± ± 0.8 TVu ± ± IT98K ± ± 0.8 IT98K ± ± 0.5 IT96D ± ± 1.2 IT07K ± ± 1.2 IT99K ± ± 1.2 IT98K ± ± 0.8 Mean (33 geno) F value Pr>F <.0001 <.0001 CV Total Primary Root Length (cm) TVu-6443 IT81D-985 DanIla TVu-9797 TVu-7778 IT99K IT89KD-288 IT90K TVu-1438 IT99K TVu IT90K-76 BornoBrown TVu TVu-1436 TVu-6707 TVu-79 TVu IfeBrown Kanannado TVu-2736 Sanzi TVu-5415 IT97K IT98K IT98K IT97K IT99K IT07K IT96D-610 IT98K IT98K Tvu-2731 Genotype Nomber of Basal Root (-) TVu-6443 TVu-1438 IT97K Sanzi TVu-9797 IT89KD-288 TVu-2736 IT97K TVu TVu-79 IT81D-985 Tvu-2731 DanIla TVu TVu-6707 IfeBrown TVu IT90K IT98K Kanannado TVu-1436 IT07K IT99K TVu-7778 IT99K IT90K-76 IT98K IT99K IT98K IT96D-610 TVu-5415 IT98K BornoBrown Genotype
21 Classification of cowpea root phenotypes Root System Architecture / Potential for adaptation to drought and low P stress environements Genotype ARGA BRGA ARN BRN BD5-10cm Grain yield (kg/ha) Shallow Root System (ARGA<45, BRGA<45, ARN>8) potential for adaptation to low phosphorus environment IT98K ± ± ± ± ± ± 380 TVu ± ± ± ± ± ± NA TVu ± ± ± ± ± ± 422 TVu ± ± ± ± ± ± NA IT07K ± ± ± ± ± ± 239 IT99K ± ± ± ± ± ± 627 Steep Root System (ARGA>45, BRGA>45, BD5-10cm>8) potential for adaptation to drought-prone environment... IT86D ± ± ± ± ± 0.29 NA TVu ± ± ± ± ± ± 196 TVu ± ± ± ± ± ± 533 IT98K ± ± ± ± ± ± 48 IT ± ± ± ± ± ± 104 Tvu ± ± ± ± ± ± 591 Mean (33 geno)
22 SUMMARY Hypothesis for genetic improvement Water savers (stomatal sensitivity to VPD, root xylem and anatomy) Water explorers (Deep and steep root system) Top soil foragers (shallow system, root hairs) Methods Physiology study to identify/understand the mechanisms Modeling the effect of traits across env. and stress scenarios Partners Penn State University with ARBC/ Howard Buffet Foundation and ICRISAT for high throughput phenotyping of shoot/root traits for adaptation to drought and low P ICRISAT-India, NCSU-USA, (IMK-IFU-KIT)-Germany, WASCAL-Burkina Faso, for modeling to develop guidelines for farming options in response to climate variability
23 MERCI DE VOTRE ATTENTION
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