Automatic and Accurate Calculation of Rice Seed Setting Rate Based on Image Segmentation and Deep Learning.

ABSTRACT: The rice seed setting rate (RSSR) is an important component in calculating rice yields and a key phenotype for its genetic analysis. Automatic calculations of RSSR through computer vision technology have great significance for rice yield predictions. The basic premise for calculating RSSR is having an accurate and high throughput identification of rice grains. In this study, we propose a method based on image segmentation and deep learning to automatically identify rice grains and calculate RSSR. By collecting information on the rice panicle, our proposed image automatic segmentation method can detect the full grain and empty grain, after which the RSSR can be calculated by our proposed rice seed setting rate optimization algorithm (RSSROA). Finally, the proposed method was used to predict

SUBMITTER: Guo Y 

PROVIDER: S-EPMC8712771 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature