Evaluation of water status of wheat genotypes to aid prediction of yield on sodic soils using UAV-thermal imaging and machine learning

Das, Sumanta and Christopher, Jack and Apan, Armando ORCID: https://orcid.org/0000-0002-5412-8881 and Choudhury, Malini Roy and Chapman, Scott and Menzies, Neal W. and Dang, Yash P. (2021) Evaluation of water status of wheat genotypes to aid prediction of yield on sodic soils using UAV-thermal imaging and machine learning. Agricultural and Forest Meteorology, 307:108477. ISSN 0168-1923


Water stress limits wheat growth and the yield on rain-fed sodic soils. Appropriate selection of traits and novel methods are required to forecast yield and to identify water stress tolerant wheat genotypes on sodic soils. In this study, we proposed a thermal remote sensing and machine learning-based approach to help predict the biomass and grain yields of wheat genotypes grown with variable water stress in sodic soil environments. We employed unmanned aerial vehicle-based thermal imaging to quantify water stress of 18 contrasting wheat genotypes grown on moderately sodic (MS) and highly sodic (HS) soils in north-eastern grains growing regions of Australia and related these to ground-measured plant biomass and grain yields. We evaluated crop water stress indices; standardized canopy temperature index, crop water stress index, stomatal conductance index, vapour pressure deficit, and crop stress index, which were computed from thermal imagery and on-site agro-meteorological parameters close to flowering. We then employed a classification and regression tree (CRT) as a supervised machine learning algorithm to classify crop water stress and predict biomass and grain yields as a function of crop water stress indices. The CRT accurately predicted biomass yield (coefficient of determination (R2) = 0.86; root mean square error (RMSE) = 41.3 g/m2 and R2 = 0.75; RMSE = 47.7 g/m2 for the MS and HS site) and grain yield (R2 = 0.78; RMSE = 16.7 g/m2 and R2 = 0.69; RMSE = 23.2 g/m2 for the MS and HS site, respectively). High sodic soil constraints increased crop water stress more than moderately sodic constraints soil that limits wheat yield ~40%. Wheat genotypes; Bremer, Gregory, Lancer, Mace, and Mitch were more productive than Gladius, Flanker, Scout, Emu Rock, and Janz in sodic soil environments. The study improves our ability to develop decision-making tools to assist farmers and breeders in securing agricultural productivity on sodic soils.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021)
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Sustainable Agricultural Systems (1 Aug 2018 -)
Date Deposited: 12 Jul 2021 23:56
Last Modified: 23 Aug 2022 06:00
Uncontrolled Keywords: thermal remote sensing; crop water stress; classification and regression tree; biomass yield; grain yield; sodic soils
Fields of Research (2008): 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070104 Agricultural Spatial Analysis and Modelling
09 Engineering > 0909 Geomatic Engineering > 090905 Photogrammetry and Remote Sensing
09 Engineering > 0909 Geomatic Engineering > 090999 Geomatic Engineering not elsewhere classified
Fields of Research (2020): 40 ENGINEERING > 4013 Geomatic engineering > 401304 Photogrammetry and remote sensing
40 ENGINEERING > 4013 Geomatic engineering > 401399 Geomatic engineering not elsewhere classified
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300206 Agricultural spatial analysis and modelling
Socio-Economic Objectives (2008): B Economic Development > 82 Plant Production and Plant Primary Products > 8205 Winter Grains and Oilseeds > 820507 Wheat
Socio-Economic Objectives (2020): 26 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 2603 Grains and seeds > 260312 Wheat
Identification Number or DOI: https://doi.org/10.1016/j.agrformet.2021.108477
URI: http://eprints.usq.edu.au/id/eprint/42678

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