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Automated discretization of ‘transpiration restriction to increasing VPD’ features from outdoors high-throughput phenotyping data

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Relation http://oar.icrisat.org/11648/
https://doi.org/10.1186/s13007-020-00680-8
doi:10.1186/s13007-020-00680-8
 
Title Automated discretization of ‘transpiration restriction to increasing VPD’ features from outdoors high-throughput phenotyping data
 
Creator Kar, S
Tanaka, R
Korbu, L B
Kholová, J
Iwata, H
Durbha, S S
Adinarayana, J
Vadez, V
 
Subject Crop Physiology
 
Description Abstract
Background: Restricting transpiration under high vapor pressure deficit (VPD) is a promising water-saving trait for
drought adaptation. However, it is often measured under controlled conditions and at very low throughput, unsuitable
for breeding. A few high-throughput phenotyping (HTP) studies exist, and have considered only maximum
transpiration rate in analyzing genotypic differences in this trait. Further, no study has precisely identified the VPD
breakpoints where genotypes restrict transpiration under natural conditions. Therefore, outdoors HTP data (15 min
frequency) of a chickpea population were used to automate the generation of smooth transpiration profiles, extract
informative features of the transpiration response to VPD for optimal genotypic discretization, identify VPD breakpoints,
and compare genotypes.

Results: Fifteen biologically relevant features were extracted from the transpiration rate profiles derived from load
cells data. Genotypes were clustered (C1, C2, C3) and 6 most important features (with heritability > 0.5) were selected
using unsupervised Random Forest. All the wild relatives were found in C1, while C2 and C3 mostly comprised high TE
and low TE lines, respectively. Assessment of the distinct p-value groups within each selected feature revealed highest
genotypic variation for the feature representing transpiration response to high VPD condition. Sensitivity analysis on a
multi-output neural network model (with R of 0.931, 0.944, 0.953 for C1, C2, C3, respectively) found C1 with the highest
water saving ability, that restricted transpiration at relatively low VPD levels, 56% (i.e. 3.52 kPa) or 62% (i.e. 3.90 kPa),
depending whether the influence of other environmental variables was minimum or maximum. Also, VPD appeared
to have the most striking influence on the transpiration response independently of other environment variable,
whereas light, temperature, and relative humidity alone had little/no effect.

Conclusion: Through this study, we present a novel approach to identifying genotypes with drought-tolerance
potential, which overcomes the challenges in HTP of the water-saving trait. The six selected features served as proxy
phenotypes for reliable genotypic discretization. The wild chickpeas were found to limit water-loss faster than the
water-profligate cultivated ones. Such an analytic approach can be directly used for prescriptive breeding applications,
applied to other traits, and help expedite maximized information extraction from HTP data.
 
Publisher BMC
 
Date 2020-10
 
Type Article
PeerReviewed
 
Format application/pdf
 
Language en
 
Identifier http://oar.icrisat.org/11648/1/s13007-020-00680-8.pdf
Kar, S and Tanaka, R and Korbu, L B and Kholová, J and Iwata, H and Durbha, S S and Adinarayana, J and Vadez, V (2020) Automated discretization of ‘transpiration restriction to increasing VPD’ features from outdoors high-throughput phenotyping data. Plant Methods (TSI), 16 (1). pp. 1-20. ISSN 1746-4811