A scalable phenotyping approach for female floral organ development and senescence in the absence of pollination in wheat

Abstract

In the absence of pollination, female reproductive organs senesce, leading to an irrevocable loss in the reproductive potential of the flower, which directly affects seed set. In self-pollinating crops like wheat (Triticum aestivum), the post-anthesis viability of unpollinated carpels has been overlooked, despite its importance for hybrid seed production systems. To advance our knowledge of carpel development in the absence of pollination, we created a high-throughput phenotyping approach to quantify stigma and ovary morphology. We demonstrate the suitability of the approach, which uses light-microscopy imaging and machine learning, for the analysis of floral organ traits in field-grown plants using fresh and fixed samples. We show that the unpollinated carpel undergoes a well-defined initial growth phase, followed by a peak phase in which stigma area reaches its maximum and the radial expansion of the ovary slows, and a final deterioration phase. These developmental dynamics were consistent across years and could be used to classify male-sterile cultivars. This phenotyping approach provides a new tool for examining carpel development, which we hope will advance research into female fertility of wheat.

Plant phenotyping relevance

コムギの柱頭・子房形態を定量化する高スループット画像・機械学習手法の開発と適用が研究の中心であり、植物表現型取得法として明確に該当する。

Code and data availability

The paper's authors publicly deposited both the analysis code (CNN training/implementation scripts and R scripts) on GitHub and the carpel image/training/validation datasets on Earlham OpenData, directly reproducing this paper's wheat carpel phenotyping measurements and analysis.