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An integrated rice panicle phenotyping method based on X-ray and RGB scanning and deep learning 被引量:1
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作者 Lejun Yu Jiawei Shi +7 位作者 Chenglong Huang Lingfeng Duan Di Wu Debao Fu Changyin Wu Lizhong Xiong Wanneng Yang Qian Liu 《The Crop Journal》 SCIE CSCD 2021年第1期42-56,共15页
Rice panicle phenotyping is required in rice breeding for high yield and grain quality.To fully evaluate spikelet and kernel traits without threshing and hulling,using X-ray and RGB scanning,we developed an integrated... Rice panicle phenotyping is required in rice breeding for high yield and grain quality.To fully evaluate spikelet and kernel traits without threshing and hulling,using X-ray and RGB scanning,we developed an integrated rice panicle phenotyping system and a corresponding image analysis pipeline.We compared five methods of counting spikelets and found that Faster R-CNN achieved high accuracy(R~2 of 0.99)and speed.Faster R-CNN was also applied to indica and japonica classification and achieved 91%accuracy.The proposed integrated panicle phenotyping method offers benefit for rice functional genetics and breeding. 展开更多
关键词 Rice(O.satiua) panicle traits RGB imaging X-ray scanning Faster R-CNN
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