Physiological Phenotyping for Adaptation to Droughtprone and Low Phosphorus Environments in Cowpea

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

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.

Frequent and Intense Droughts with Climate Change

Global P deficiency: primary constraint to life on earth Issue of accessibility and affordability of fertilizers by smallholder farmers

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

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

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

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

Cowpea genotypes performance under WS/WW Drought-stressed grain yield (kg 600 800 1000 1200 1400 1600 IT98K-1105-5 IT93K-693-2 IT84S-2049 IT98K-1111-1 Mouride KVX-61-1 IT97K-499-39 UCR-P-24 UC-CB27 Prima Sasaque IT95K-181-9 IT95K-1491 Ife-Brown Bambey 21 IT95K-1479 Melakh Yacine UC-CB46 Apagbaala IT93K-2046 IT95M-190 IT85F-867-5 IT82E-18 UC-524B Sh-50 IT84S-2246 IT95M-303 IT93K-93-10 IT85F Drought-stressed grain yield (kg 600 800 1000 1200 1400 1600 1800 58-53 IT98K-205-8 58-57 KVX-421-25 KVX403 IT93K-503-1 IT99K-124-5 IT96D-610 Suvita 2 IT98K-128-2 IT97K-207- N diambour Mougne IT89KD-288 IT00K-901-6 IT98K-698-2 IT98K-428-3 IAR8/7-4-5-3 Iron-Clay IT95K-1095-4 IT98K-498-1 IT90K-284-2 KVX-396 KVX-525 IT95K-1090-2 IT97K IT98K-317-2 IT97K-819-132 IT83D-442 Petite-n-grn 2400 2600 2800 3000 3200 3400 Non-stressed grain yield (kg/ha) 2600 2800 3000 3200 3400 Non-stressed grain yield (kg/ha) A: Short duration genotypes B: Medium duration genotypes

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 48 49 70 73 5.7 9.1 2.3 5.2 1.3 3.4 0.2 0.2 6.7 6.7 Danila 46 46 69 69 7.6 16.1 6.2 9.5 3.4 7.2 0.3 0.3 14.7 17.0 IT00K-1263 57 57 75 77 2.2 24.1 1.4 8.7 0.8 4.8 0.2 0.1 15.0 16.3 IT07K-292-10 50 50 71 73 5.0 22.3 4.9 11.2 3.0 8.0 0.3 0.2 15.7 18.3 IT07K-318-33 61 57 77 79 9.5 25.1 2.6 6.2 1.5 4.5 0.1 0.1 16.0 17.7 IT97K-499-35 56 55 75 80 15.3 24.1 7.9 16.4 5.1 12.5 0.2 0.3 15.0 15.7 IT98K-205-8 47 50 72 76 9.0 24.9 6.6 14.0 3.8 8.5 0.2 0.2 14.7 16.0 IT98K-503-1 51 51 75 77 10.7 18.0 11.6 14.8 6.1 9.6 0.3 0.3 15.7 15.7 IT98K-568-18 56 55 75 78 9.1 24.5 2.6 10.8 1.4 7.5 0.1 0.2 17.3 17.3 IT98K506-1 49 50 73 76 5.9 19.9 3.2 9.8 2.0 5.5 0.2 0.2 17.0 17.0 IT99K-573-2-1 52 51 76 78 5.4 22.1 3.3 9.8 1.7 7.7 0.2 0.2 12.7 17.0 Tvu-7778 52 50 73 75 6.9 16.4 2.6 12.0 1.4 7.7 0.1 0.3 9.7 8.0 Mean 52 52 73 76 7.7 20.5 4.6 10.7 2.6 7.2 0.2 0.2 14.2 15.2 SE 0.825 0.626 0.887 0.623 0.426 1.012 0.352 0.366 0.146 0.376 0.012 0.013 0.429 0.385 F value 30.21 30.72 7.97 25.21 62.04 23.13 71.42 82.08 130.9 43.35 23.37 16.21 52.55 96.45 Pr>F <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 CV 2.75 2.09 2.09 1.42 9.59 8.54 13.23 5.92 9.66 8.99 10.33 9.86 5.25 4.38 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 3.3 2.00 42.2 66.3 0.4 0.8 32.8 3.0 1 1 Danila 2.0 1.00 77.7 81.4 0.6 0.8 28.1 2.0 1 1 IT00K-1263 4.3 2.00 52.6 63.9 0.4 0.7 30.7 2.3 0 0 IT07K-292-10 2.0 1.00 49.6 64.6 0.4 0.7 29.9 3.0 0 0 IT07K-318-33 3.7 2.00 45.2 66.1 0.6 0.7 33.9 2.7 1 1 IT97K-499-35 2.0 1.00 65.2 74.6 0.5 0.8 26.8 1.7 0 0 IT98K-205-8 2.0 1.00 59.8 67.2 0.6 0.8 27.0 2.3 0 0 IT98K-503-1 1.3 1.00 63.9 68.9 0.5 0.7 28.3 2.0 1 1 IT98K-568-18 4.3 2.00 42.8 71.6 0.5 0.7 30.8 3.0 1 1 IT98K506-1 3.0 2.00 48.1 71.3 0.4 0.6 35.6 2.3 1 1 IT99K-573-2-1 4.3 2.00 47.7 67.4 0.5 0.7 29.2 2.7 0 0 Tvu-7778 4.7 2.00 34.0 60.9 0.3 0.7 35.2 3.3 1 1 Mean 3.1 1.58 52.4 68.7 0.5 0.7 30.7 2.5 1 1 SE 0.251 0.127 1.773 1.068 0.012 0.017 0.359 0.259 0.142 0.07 F value 22.12 24.24 47.08 26.13 43.73 4.88 72.97 3.74 11.5 26.3 Pr>F <.0001 <.0001 <.0001 <.0001 <.0001 0.0008 <.0001 0.0041 <.0001 <.0001 CV 14.11 13.28 5.86 2.69 4.26 3.94 2.03 17.78 49.24 34.05 7.0 7.0 Seed Yiled (g/pl) 6.0 5.0 4.0 3.0 2.0 y = 0.0991x - 2.5698 R² = 0.5182 Seed Yiled (g/pl) 6.0 5.0 4.0 3.0 2.0 y = -0.3697x + 13.971 R² = 0.459 1.0 1.0 0.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 SPAD-CMR (-) 0.0 25.0 27.0 29.0 31.0 33.0 35.0 37.0 Leaf temperature ( 0 C)

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 )

Drought tolerant cowpeas had lower TR under high VPD 16 14 Greenhouse 16 14 Outdoor 0.050 Bambey 21 IT89KD-288 KVX-525 UC-CB46 IT93K-503-1 IT93K-693-2 Mouride Suvita 2 VPD (kpa) 6 TR (g H 2 O g -1 Leaf dw h -1 ) 12 10 8 6 4 2 TR (g H 2 O g -1 Leaf dw h -1 ) 12 10 8 6 4 2 TR (g H 2 O cm- 2 h -1 ) 0.045 0.040 0.035 0.030 0.025 0.020 0.015 5 4 VPD (kpa) 3 2 0 IT98K-317-2 IT99K-124-5 Mouride Danila IT98K-428-3 IT95K-1090-2 SuVita2 IAR8/7-4-5-3 UCR-P-24 KVx61-1 IT97K-499-39 IT97K-207-15 IT93K-693-2 IT93K-503-1 Apagbaala IT84S-2049 58-53 IT95K-181-9 UC IT96D-610 - CB27 IT98K-1105-5 KVx403 Yacine IT98K-1111-1 58-57 IT93K-93-10 Bambey 21 Genotypes IT90K-284-2 UC - Prima IT89KD-288 CB46 IT85F-3139 IT95K-1095-4 IT82E-18 IT83D-442 IT98K-128-2 IT97K-556-6 KVx525 IT93K-2046 IT84S-2246 0 IT97K-499-39 Danila UC KVx61-1 SuVita2 - CB27 IAR8/7-4-5-3 IT93K-93-10 IT98K-428-3 Yacine IT95K-181-9 Mouride IT95K-1090-2 IT93K-503-1 IT85F-3139 IT97K-207-15 IT99K-124-5 KVx403 IT93K-693-2 58-57 IT98K-317-2 UCR-P-24 IT95K-1095-4 Apagbaala IT98K-1111-1 Prima IT84S-2049 IT96D-610 Genotypes IT98K-1105-5 IT90K-284-2 IT98K-128-2 UC - CB46 58-53 IT97K-556-6 IT89KD-288 Bambey IT82E-18 21 IT93K-2046 IT83D-442 IT84S-2246 KVx525 0.010 0.005 0.000 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

Canopy TR correlates with leaf temp and stomatal conductance 0.050 (A) 0.050 (B) TR (g H 2 O cm -2 h -1 )_High VPD at 13h 0.045 0.040 0.035 0.030 0.025 y = -0.002x + 0.110 R² = 0.85 TR (g H 2 O cm -2 h -1 )_High VPD at 13h 0.045 0.040 0.035 0.030 0.025 y = 0.0062ln(x) + 0.0339 R² = 0.8655 0.020 30 32 34 36 38 40 Canopy temperature ( C) 0.020 0.0 1.0 2.0 3.0 4.0 5.0 Index of stomatal conductance

Extent of genotypic variations in plant TR, SPAD-CMR, CTD and LA in cowpea

Lines with Lowest Values SPAD-CMR (-) Leaf TR (g cm -2 h -1 ) Leaf CTD ( o C) Leaf Area (cm 2 ) Tvu-1016 31.4 Tvu-9486 0.006 Tvu-15391-4.1 Tvu-2027 404.8 Tvu-2723 31.8 Tvu-8656 0.009 Tvu-16449-3.7 Tvu-3817 467.7 Tvu-12873 32.2 Tvu-14788 0.011 IT99K-573-2-1-3.5 Tvu-4669 475.2 Tvu-1656 32.3 Tvu-1727 0.013 Achishiru -3.3 Tvu-5307 532.7 Tvu-2769 32.4 Tvu-8262 0.014 IT97K-499-35 -3.1 Tvu-8123 596.5 Tvu-2968 32.7 Tvu-1330 0.014 Tvu-13305-2.8 Tvu-870 620.8 Tvu-8059 32.9 Tvu-201 0.014 Tvu-14635-2.7 Tvu-1016 627.5 Tvu-14633 34.0 Tvu-14533 0.014 IT00K-1263-2.5 Tvu-5957 635.5 Tvu-1886 40.3 IT00K-1263 0.021 Tvu-16403-2.4 Danila 721.7 Tvu-14635 41.4 Danila 0.022 Tvu-14558-2.2 IT98K-503-1 768.6 Lines with Highest Values IT98K-205-8 61.2 Tvu-10408 0.040 Tvu-9257 7.5 Tvu-9256 1866.0 Tvu-16486 61.5 Tvu-2322 0.041 Tvu-1886 7.6 Tvu-109 1870.6 Tvu-10973 63.0 Tvu-7625 0.041 Tvu-2027 7.6 Tvu-1583 1922.4 Tvu-9095 63.1 Tvu-15926 0.042 Tvu-9031 7.6 Tvu-8631 1930.5 Tvu-5721 64.0 Tvu-7755 0.044 Tvu-6356 7.8 Tvu-13388 1932.8 Tvu-5307 65.4 Tvu-14633 0.055 Tvu-1916 8.0 Tvu-8656 1949.6 Tvu-3817 67.0 Tvu-8059 0.055 Tvu-4963 8.1 Tvu-2500 1965.4 Tvu-6959 67.2 Tvu-8389 0.061 Tvu-3830 8.3 Tvu-7971 1983.6 Danila 67.6 Tvu-8123 0.063 Tvu-2845 10.3 Tvu-1330 2120.7 Tvu-15639 73.0 Tvu-10281 0.067 Tvu-16465 10.7 Tvu-16368 2122.5

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- 284-2, IT95K-1543 and IT97K-499-38 were consistently low P tolerant and rock P efficient lines Tvu-7778, Sanzi and IT97K-499-35 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

Shoot growth response to low P (KH2PO4) Rate of decrease of SDM in 0P to 30P (%) 30 20 10 0-10 -20-30 -40-50 IT04K-332-1 a IT06K-137-1 IT07K-188-49 Iron bean IT10K-836-2 IT07K-249-1-11 IT09K-456 IT08K-126-19 IT00K-1148 IT10K-832-3 IT07K-304-9 IT98K-506-1 IT07K-274-2-9 SDM in 0P (kg/ha) IT06K-147-1 IT07K-568-11 IT08K-180-11 2000 1800 1600 1400 1200 1000 800 600 400 200 0 IT98K-412-13 IT99K-573-2-1 IT98K-697 IT90K-284-2 IT07K-298-15 IT98D-1399 IT10K-817-1 IT10K-834-3 IT06K-124 IT89KD-374-57 IT84S-2246-4 IT83S-728-13 IT07K-297-13 IT99K-573-1-1 IT07K-292-10 IT09K-231-1 IT97K-499-38 IT10K-815-5 IT99K-491-7 50 40 30 20 10 0-10 -20-30 -40 b IT07K-298-15 IT98K-131-2 IT04K-332-1 IT07K-274-2-9 IT07K-292-10 IT83S-728-13 Iron bean IT04K-332-1 Iron bean IT09K-456 IT10K-836-2 IT89KD-374-57 IT99K-491-7 IT06K-147-1 IT00K-1148 IT10K-836-2 IT89KD-374-57 IT95K-1543 IT07K-188-49 IT04K-217-5 IT99K-573-2-1 IT98D-1399 IT07K-298-15 IT07K-297-13 IT06K-147-1 IT99K-573-2-1 IT90K-372-1-2 IT09K-456 IT07K-304-9 IT10-819-4 IT06K-137-1 IT82D-812 TVX 1948-01F IT08K-150-24 IT07K-188-49 IT06K-137-1 IT98K-506-1 IT98D-1399 IT83S-728-13 IT98K-506-1 IT07K-292-10 IT00K-1148 IT07K-304-9 IT07K-274-2-9 IT99K-491-7 IT07K-297-13 2014 2015

Field, lab and image based phenotying of root traits for adaptation to drought and low P Shovelomics

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

Roots traits at seedling stage LOW HIGH Genotype TPRL BRN TVu-6443 4.0 ± 0.8 0.0 ± 0.0 IT81D-985 7.7 ± 0.9 7.3 ± 0.5 TVu-9797 13.0 ± 1.6 6.3 ± 1.2 IT89KD-288 13.0 ± 1.4 6.7 ± 1.7 TVu-15055 14.0 ± 1.6 7.0 ± 0.8 TVu-1438 13.7 ± 1.7 5.3 ± 0.5... IT98K-205-8 22.3 ± 1.2 12.0 ± 0.8 IT98K-506-1 22.3 ± 0.5 12.3 ± 0.5 IT96D-610 22.0 ± 0.8 12.7 ± 1.2 IT07K-318-33 21.0 ± 2.2 10.3 ± 1.2 IT99K-494-6 20.3 ± 0.5 11.7 ± 1.2 IT98K-1111-1 19.0 ± 1.4 15.0 ± 0.8 Mean (33 geno) 16.7 9.4 F value 34.22 23.44 Pr>F <.0001 <.0001 CV 9.32 13.31 Total Primary Root Length (cm) 40 30 20 10 0 TVu-6443 IT81D-985 DanIla TVu-9797 TVu-7778 IT99K-216-24-2 IT89KD-288 IT90K-277-2 TVu-1438 IT99K-573-1-1 TVu-15055 IT90K-76 BornoBrown TVu-11986 TVu-1436 TVu-6707 TVu-79 TVu-15058 IfeBrown Kanannado TVu-2736 Sanzi TVu-5415 IT97K-568-18 IT98K-1111-1 IT98K-1092-1 IT97K-499-35 IT99K-494-6 IT07K-318-33 IT96D-610 IT98K-506-1 IT98K-205-8 Tvu-2731 Genotype Nomber of Basal Root (-) 25 20 15 10 5 0 TVu-6443 TVu-1438 IT97K-499-35 Sanzi TVu-9797 IT89KD-288 TVu-2736 IT97K-568-18 TVu-15055 TVu-79 IT81D-985 Tvu-2731 DanIla TVu-11986 TVu-6707 IfeBrown TVu-15058 IT90K-277-2 IT98K-1092-1 Kanannado TVu-1436 IT07K-318-33 IT99K-573-1-1 TVu-7778 IT99K-494-6 IT90K-76 IT98K-205-8 IT99K-216-24-2 IT98K-506-1 IT96D-610 TVu-5415 IT98K-1111-1 BornoBrown Genotype

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-1111-1 40.00 ± 5.28 40.00 ± 2.00 12 ± 3.61 9 ± 1.20 10 ± 1.26 1207 ± 380 TVu-11982 41.11 ± 4.84 33.33 ± 3.33 11 ± 1.28 6 ± 0.56 10 ± 0.91 818 ± NA TVu-9797 43.33 ± 3.33 27.77 ± 4.01 13 ± 5.28 10 ± 2.41 11 ± 2.02 1349 ± 422 TVu-15055 41.66 ± 4.41 35.55 ± 2.94 10 ± 1.53 5 ± 0.73 10 ± 1.60 2683 ± NA IT07K-318-33 36.66 ± 1.92 28.88 ± 5.56 8 ± 0.51 7 ± 0.59 10 ± 0.68 3344 ± 239 IT99K-494-6 43.33 ± 6.67 36.66 ± 6.02 8 ± 1.00 4 ± 0.60 10 ± 1.76 1932 ± 627 Steep Root System (ARGA>45, BRGA>45, BD5-10cm>8) potential for adaptation to drought-prone environment... IT86D-1010 57.77 ± 7.77 47.77 ± 7.77 8 ± 1.06 6 ± 1.01 10 ± 0.29 NA TVu-11986 50.00 ± 0.00 50.00 ± 10.00 6 ± 1.45 9 ± 0.67 8 ± 0.88 1509 ± 196 TVu-6443 63.33 ± 3.33 50.00 ± 5.77 9 ± 3.21 7 ± 1.20 12 ± 2.03 1369 ± 533 IT98K-205-8 50.00 ± 0.00 46.66 ± 6.66 6 ± 0.88 5 ± 0.67 8 ± 2.20 1083 ± 48 IT97-499-35 56.66 ± 3.33 46.66 ± 6.66 10 ± 3.06 5 ± 0.58 10 ± 0.58 1391 ± 104 Tvu-14676 55.55 ± 4.44 51.11 ± 8.88 7 ± 0.33 7 ± 2.51 15 ± 3.71 2790 ± 591 Mean (33 geno) 50 40 9 7 11 1928....

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

MERCI DE VOTRE ATTENTION