Image-Based Phenotyping Study of Wheat Growth and Grain Yield Dependence on Environmental Conditions and Nitrogen Usage in a Multi-Year Field Trial

Stanley J. Miklavcic, Joshua Chopin () and Hamid Laga
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Stanley J. Miklavcic: Phenomics and Bioinformatics Research Centre, UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia
Joshua Chopin: Phenomics and Bioinformatics Research Centre, UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia
Hamid Laga: School of Information Technology, Murdoch University, Murdoch, WA 6150, Australia

Sustainability, 2024, vol. 16, issue 9, 1-23

Abstract: As the global population and resource scarcity simultaneously increase, the pressure on plant breeders and growers to maximise the effectiveness of their operations is immense. In this article, we explore the usefulness of image-based data collection and analysis of field experiments consisting of multiple field sites, plant varieties, and treatments. The goal of this approach is to determine whether the noninvasive acquisition and analysis of image data can be used to find relationships between the canopy traits of field experiments and environmental factors. Our results are based on data from three field trials in 2016, 2017, and 2018 in South Australia. Image data were supplemented by environmental data such as rainfall, temperature, and soil composition in order to explain differences in growth and the development of plants across field trials. We have shown that the combination of high-throughput image-based data and independently recorded environmental data can reveal valuable connections between the variables influencing wheat crop growth; meanwhile, further studies involving more field trials under different conditions are required to test hypotheses and draw statistically significant conclusions. This work highlights some of the more responsive traits and their dependencies.

Keywords: wheat; phenotyping; yield; NUE; image analysis; crop; sustainability; nitrogen management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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