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An integrated rice panicle phenotyping method based on X-ray and RGB scanning and deep learning

机译:一种基于X射线和RGB扫描和深度学习的一体稻瘟水稻穗表型方法

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摘要

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.

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  • 来源
    《作物学报(英文版)》 |2021年第1期|42-56|共15页
  • 作者单位

    Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics Key Laboratory of Ministry of Education for Biomedical Photonics Department of Biomedical Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China;

    Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics Key Laboratory of Ministry of Education for Biomedical Photonics Department of Biomedical Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China;

    School of Biomedical Engineering Hainan University Haikou 570228 Hainan China;

    National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Agricultural Bioinformatics Key Laboratory of Hubei Province College of Engineering Huazhong Agricultural University Wuhan 430070 Hubei China;

    National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Agricultural Bioinformatics Key Laboratory of Hubei Province College of Engineering Huazhong Agricultural University Wuhan 430070 Hubei China;

    National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Agricultural Bioinformatics Key Laboratory of Hubei Province College of Engineering Huazhong Agricultural University Wuhan 430070 Hubei China;

    National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Agricultural Bioinformatics Key Laboratory of Hubei Province College of Engineering Huazhong Agricultural University Wuhan 430070 Hubei China;

    National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Agricultural Bioinformatics Key Laboratory of Hubei Province College of Engineering Huazhong Agricultural University Wuhan 430070 Hubei China;

    National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Agricultural Bioinformatics Key Laboratory of Hubei Province College of Engineering Huazhong Agricultural University Wuhan 430070 Hubei China;

    National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Agricultural Bioinformatics Key Laboratory of Hubei Province College of Engineering Huazhong Agricultural University Wuhan 430070 Hubei China;

    National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Agricultural Bioinformatics Key Laboratory of Hubei Province College of Engineering Huazhong Agricultural University Wuhan 430070 Hubei China;

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  • 入库时间 2022-08-19 04:56:58
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