Not a load of rubbish: simulated field trials in large-scale containers.

Abstract

Assessment of yield performance under fluctuating environmental conditions is a major aim of crop breeders. Unfortunately, results from controlled-environment evaluations of complex agronomic traits rarely translate to field performance. A major cause is that crops grown over their complete lifecycle in a greenhouse or growth chamber are generally constricted in their root growth, which influences their response to important abiotic constraints like water or nutrient availability. To overcome this poor transferability, we established a plant growth system comprising large refuse containers (120 L 'wheelie bins') that allow detailed phenotyping of small field-crop populations under semi-controlled growth conditions. Diverse winter oilseed rape cultivars were grown at field densities throughout the crop lifecycle, in different experiments over 2 years, to compare seed yields from individual containers to plot yields from multi-environment field trials. We found that we were able to predict yields in the field with high accuracy from container-grown plants. The container system proved suitable for detailed studies of stress response physiology and performance in pre-breeding populations. Investment in automated large-container systems may help breeders improve field transferability of greenhouse experiments, enabling screening of pre-breeding materials for abiotic stress response traits with a positive influence on yield.

Plant phenotyping relevance

大型容器を用いた植物生育・表現型評価システムを構築し、容器栽培の収量から圃場収量を予測できるか検証しており、フェノタイピング手法が研究の中心です。

Code and data availability

The supplied blocks describe large-container drought and nitrogen phenotyping trials in winter oilseed rape with Supporting Information tables/figures, but no public phenotype dataset, image/sensor data, author analysis code, or trained model is deposited or linked. Analysis tools mentioned (Plabstat, SPSS, R/ggplot2),

No evidence-backed public reproduction asset is currently recorded.