Research results suggests it is important to design an integrated strategy combining plant phenomics, genomics, agronomy and modeling to maximize crop productivity in a given environment or stress scenario and to develop guidelines for farming options in the face of climate variability in sub-Saharan Africa.

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Phenotypic variability of drought-avoidance shoot and root phenes and
their relationships with yield under drought and low P conditions in cowpea
Belko N¹*, Boukar O¹, Burridge J3, Chamarthi S¹, Togola A¹, Moukoumbi Y¹, Lynch J 3, Abberton M², Fatokun C²
1 International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, NIGERIA
2 Plant Root Biology Lab, Department of Plant Science, Penn State University (PSU), USA
Rationale and Objective
Cowpea (Vigna unguiculata (L.) Walp.) is an important food and cash crop in the semi-arid
regions of sub-Saharan Africa where it is widely cultivated on marginal lands under rain-fed
condition by small-scale farmers. Although the crop is relatively adapted to drought prone
agro-ecologies, it could benefit from genetic improvement aimed at improving its tolerance
multiple abiotic stresses (Boukar et al., 2016). Collaborative experimental research was
therefore conducted by IITA and PSU with the objective to assess cowpea germplasm for its
genetic variation in (i) water-saving shoot traits and (ii) root system architecture for superior
adaptation to drought and low phosphorus environments. The identified lines with traits of
interest will be incorporated into the cowpea breeding program for developing new high
yielding cultivars with enhanced tolerance individual or combined environmental stresses.
The cowpea germplasm mini-core collection (374 lines) and 50 selected breeding lines were
phenotyped in both screen-house and field conditions for their variation in drought and low P
tolerance related shoot and root traits.
Whole plant transpiration was estimated gravimetrically and indirectly using infrared
thermography (Photo 1: Belko et al., 2013). Plant root system architecture was evaluated
using a field base phenotyping technique “Shovelomics” for adaptation to both drought and
low phosphorus (Photo 2: Burridge et al., 2016).
Results and Discussion
There was large genotypic variation among the cowpea germplasm for (i) plant transpiration
and canopy temperature under non-limiting water and high VPD conditions (Fig. 2a,b) and
(ii) grain yield under relatively low P conditions (Fig. 2c). Root phenes i.e. adventitious and
basal root numbers (ARN, BRN) and growth angles (ARGA, BRGA) and branching density
(BD) also significantly discriminated between tested lines (Table 1).
IT86D-1010, IT98K-205-8, IT97-499-35, IT99K-573-2-1, TVu-9486, TVu-14788, TVu-15391,
TVu-11986, and TVu-14676 with conservative water-use attributes and steep root system are
potential for adaptation to drought while IT98K-506-1, IT99K-494-6, IT07K-318-33, IT99K-
494-6, Tvu-2731, Tvu-5415, TVu-9797, TVu-11982 and TVu-15055 with seedling basal root
number and shallow root system are potential for adaptation to low P (Table 1a,b).
Conclusion and Recommendation
The results reveal the possibility for improving the productivity of cowpea in drought-prone and poor
soil environments through exploiting its genetic resources.
It is important to design an integrated strategy combining plant phenomics, genomics, agronomy and
modeling to maximize crop productivity in a given environment or stress scenario and to develop
guidelines for farming options in the face of climate variability in sub-Saharan Africa.
References
1. Boukar et al. 2016: Front Plant Sci. 2016; 7: 757
2. Belko et al. 2013: Plant Biology 15: 304 – 316
3. Burridge et al. 2016: Field Crops Research 192: 21 – 32
Hypotheses and Methods
Edaphic resources i.e. water and P are stratified in contrasting patterns into the soil profile:
Restricted leaf transpiration under high VPD (Fig.1a) and steep/profuse root system (Fig.1b)
are important for adaptation to terminal drought while shallow/dense root system (Fig.1b) is
beneficial for sub-soil foraging and enhanced water and phosphorus acquisition.
TCanopy = Sum ((Ti x Pxi) / Pxt) Ig = (Tdry leaf – TCanopy) / (TCanopy – Twet leaf)
Photo 1: Thermal image (a) and distribution of number of pixels over a range of plant canopy and background temperatures (b) for indirect
estimation of plant canopy temperature (Tcanopy) as a proxy for whole plant transpiration rate in cowpea.
Numberofpixels
Temperatures ( C)
Rangeofleavestemperatures Rangeof backgroundstemperatures
B
(b)(a)
Photo 2: Shallow (a) and steep (b) root systems evaluated for their difference in adventitious and basal root numbers,
growth angles and branching densities using a visual scoring board.
(a) (b)
RootSystemArchitecture/Potentialfor
adaptationtodroughtandlowPstress
environements
Genotype ARGA BRGA ARN BRN BD5-10cm
Grainyield
(kg/ha)
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
….
….
….
….
….
….
….
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(33geno) 50 40 9 7 11 1928
ShallowRootSystem(ARGA<45,BRGA<45,
ARN>8)potentialforadaptationtolow
phosphorusenvironment
SteepRootSystem(ARGA>45,BRGA>45,
BD5-10cm>8)potentialforadaptationto
drought-proneenvironment
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(33geno) 16.7 9.4
Fvalue 34.22 23.44
Pr>F <.0001 <.0001
CV 9.32 13.31
LOWHIGH
Table 1: Classification of cowpea genotypes with contrasting adult plant morphology (a: shallow and steep root system) and seedling
stage root traits (b: total primary root length (TPRL) and basal roots number (BRN)) and their hypothesized contribution to adaptation
to drought and low P. Plant genotypes with TPRL and high BRN are potential for adaptation to low P and early vegetative stage drought.
(a) (b)
Water spender
under high VPD
Water saver
under high VPD
Fig. 1: Difference in leaf water losses in response atmospheric vapor pressure deficit (VPD) (a) and root system architecture (b) for water and P acquisition.
H2O P
5%
18%
11%
23%
10 cm
20cm
30cm
4ppm
2ppm
0.5ppm
0.25ppm
40cm
(a) (b)
Fig.2: Genotypic variation in plant TR (a) and canopy temperature depression (b) and grain yield (c) among the cowpea germplasm.
(b)
(a) (c)
Plant traits might be dynamic and interact with one another and with their environment.
Agronomic crop management could influences their expression. Therefore, crop-climate-
management modeling becomes an essential tool for navigating the biological complexity
and testing the effects and probability of success of specific plant trait or traits combination.
Acknowledgment and Collaborators