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

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.

Plant phenotyping relevance

圃場試験での非侵襲的な画像取得・解析を中心に、コムギのキャノピー形質を環境要因と関連付けて評価しており、画像ベース表現型計測の実質的な適用研究である。

Code and data availability

The paper's image-based phenotyping dataset (canopy coverage, vigour, height, yield/quality data from 2016–2018 wheat trials) is not publicly deposited; the Data Availability Statement requires contacting the corresponding author. The Supplementary Data File S1 only contains additional variety-pair figures, not the raw

No evidence-backed public reproduction asset is currently recorded.