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Panicle Ratio Network: streamlining rice panicle measurement by deep learning with ultra-high-definition aerial images in the field.

Journal of experimental botany - 2 Nov 2022

Guo Ziyue, Yang Chenghai, Yang Wangnen, Chen Guoxing, Jiang Zhao, Wang Botao, Zhang Jian

Abstract excerpt

The heading date and effective tiller percentage are important traits in rice, and they directly affect plant architecture and yield. Both traits are related to the ratio of the panicle number to the maximum tiller number, referred to as the panicle ratio (PR). In this study, an automatic PR estimation model (PRNet) based on a deep convolutional neural network was developed. Ultra-high-definition unmanned aerial...

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PMID: 35776094
DOI: 10.1093/jxb/erac294

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