A High-Throughput Method for Accurate Extraction of Intact Rice Panicle Traits.

Abstract

Rice panicle traits serve as critical indicators of both yield potential and germplasm resource quality. However, traditional manual measurements of these traits, which typically involve threshing, are not only laborious and time-consuming but also prone to introducing measurement errors. This study introduces a high-throughput and nondestructive method, termed extraction of panicle traits (EOPT), along with the software Panicle Analyzer, which is designed to assess unshaped intact rice panicle traits, including the panicle grain number, grain length, grain width, and panicle length. To address the challenge of grain occlusion within an intact panicle, we define a panicle morphology index to quantify the occlusion levels among the rice grains within the panicle. By calibrating the grain number obtained directly from rice panicle images based on the panicle morphology index, we substantially improve the grain number detection accuracy. For measuring grain length and width, the EOPT selects rice grains using an intersection over union threshold of 0.8 and a confidence threshold of 0.7 during the grain detection process. The mean values of these grains were calculated to represent all the panicle grain lengths and widths. In addition, EOPT extracted the main path of the skeleton of the rice panicle using the Astar algorithm to determine panicle lengths. Validation on a dataset of 1,554 panicle images demonstrated the effectiveness of the proposed method, achieving 93.57% accuracy in panicle grain counting with a mean absolute percentage error of 6.62%. High accuracy rates were also recorded for grain length (96.83%) and panicle length (97.13%). Moreover, the utility of EOPT was confirmed across different years and scenes, both indoors and outdoors. A genome-wide association study was conducted, leveraging the phenotypic traits obtained via EOPT and genotypic data. This study identified single-nucleotide polymorphisms associated with grain length, width, number per panicle, and panicle length, further emphasizing the utility and potential of this method in advancing rice breeding.

Plant phenotyping relevance

画像からイネ穂の粒数・粒長・粒幅・穂長を高スループットかつ非破壊で抽出する手法とソフトウェアを開発し、データセットで精度検証しているため、植物表現型取得法が研究の中心である。

Code and data availability

植物フェノタイピング解析を再現する公開資産であることを、入力本文と直接リンクから確認できなかったため保留しました。

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