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Open AccessArticle

Affordable Phenotyping of Winter Wheat under Field and Controlled Conditions for Drought Tolerance

Department of Plant Breeding, Swedish University of Agricultural Sciences (SLU), Box 101, SE-230 53 Alnarp, Sweden
National Institute of Animal Biotechnology, Hyderabad 500032, India
Institute of Agriculture, Lithuanian Research Centre for Agriculture and Forestry, LT-583 44 Akademija, Lithuania
Centre for Energy and Environment, Malaviya National Institute of Technology, Jaipur 302017, India
Nordic Genetic Resource Center, Box 41, SE-230 53 Alnarp, Sweden
Lantmännen Lantbruk, SE-268 31 Svalöv, Sweden
Author to whom correspondence should be addressed.
Current address: Department of Soil, Plant and Food Science, University of Bari “Aldo Moro”, 70126 Bari, Italy.
Agronomy 2020, 10(6), 882;
Received: 9 May 2020 / Revised: 11 June 2020 / Accepted: 15 June 2020 / Published: 19 June 2020
(This article belongs to the Special Issue Translational Research in Plant Breeding)
Drought stress is one of the key plant stresses reducing grain yield in cereal crops worldwide. Although it is not a breeding target in Northern Europe, the changing climate and the drought of 2018 have increased its significance in the region. A key challenge, therefore, is to identify novel germplasm with higher drought tolerance, a task that will require continuous characterization of a large number of genotypes. The aim of this work was to assess if phenotyping systems with low-cost consumer-grade digital cameras can be used to characterize germplasm for drought tolerance. To achieve this goal, we built a proximal phenotyping cart mounted with digital cameras and evaluated it by characterizing 142 winter wheat genotypes for drought tolerance under field conditions. The same genotypes were additionally characterized for seedling stage traits by imaging under controlled growth conditions. The analysis revealed that under field conditions, plant biomass, relative growth rates, and Normalized Difference Vegetation Index (NDVI) from different growth stages estimated by imaging were significantly correlated to drought tolerance. Under controlled growth conditions, root count at the seedling stage evaluated by imaging was significantly correlated to adult plant drought tolerance observed in the field. Random forest models were trained by integrating measurements from field and controlled conditions and revealed that plant biomass and relative growth rates at key plant growth stages are important predictors of drought tolerance. Thus, based on the results, it can be concluded that the consumer-grade cameras can be key components of affordable automated phenotyping systems to accelerate pre-breeding for drought tolerance. View Full-Text
Keywords: wheat; drought; machine learning; affordable phenotyping wheat; drought; machine learning; affordable phenotyping
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MDPI and ACS Style

Kumar, D.; Kushwaha, S.; Delvento, C.; Liatukas, Ž.; Vivekanand, V.; Svensson, J.T.; Henriksson, T.; Brazauskas, G.; Chawade, A. Affordable Phenotyping of Winter Wheat under Field and Controlled Conditions for Drought Tolerance. Agronomy 2020, 10, 882.

AMA Style

Kumar D, Kushwaha S, Delvento C, Liatukas Ž, Vivekanand V, Svensson JT, Henriksson T, Brazauskas G, Chawade A. Affordable Phenotyping of Winter Wheat under Field and Controlled Conditions for Drought Tolerance. Agronomy. 2020; 10(6):882.

Chicago/Turabian Style

Kumar, Dhananjay; Kushwaha, Sandeep; Delvento, Chiara; Liatukas, Žilvinas; Vivekanand, Vivekanand; Svensson, Jan T.; Henriksson, Tina; Brazauskas, Gintaras; Chawade, Aakash. 2020. "Affordable Phenotyping of Winter Wheat under Field and Controlled Conditions for Drought Tolerance" Agronomy 10, no. 6: 882.

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