Nondestructive 3D Image Analysis Pipeline to Extract Rice Grain Traits Using X-Ray Computed Tomography
作者机构：Crop Phenomics Joint Research CenterWuhan 430070China Institute of Genetics and Developmental Biology Chinese Academy of SciencesBeijing 100101China Britton Chance Center for Biomedical PhotonicsWuhan National Laboratory for Optoelectronicsand Key Laboratory of Ministry of Education for Biomedical PhotonicsDepartment of Biomedical EngineeringHuazhong University of Science and TechnologyWuhan 430074China National Key Laboratory of Crop Genetic ImprovementNational Center of Plant Gene ResearchAgricultural Bioinformatics Key Laboratory of Hubei Provinceand College of EngineeringHuazhong Agricultural UniversityWuhan 430070China
出 版 物：《Plant Phenomics》 (植物表型组学（英文）)
年 卷 期：2020年第2卷第1期
页 面：106-117页
核心收录：
学科分类：08[工学] 09[农学] 0501[文学-中国语言文学] 0303[法学-社会学] 0710[理学-生物学] 0502[文学-外国语言文学] 0601[历史学-考古学] 1302[艺术学-音乐与舞蹈学] 1301[艺术学-艺术学理论] 081203[工学-计算机应用技术] 0901[农学-作物学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：This work was supported by grants from the National Key Research and Development Program(2016YFD0100101-18) the National Natural Science Foundation of China(31770397) the Fundamental Research Funds for the Central Universities(2662017PY058),and Hubei Research and Development Innovation Platform Construction Project.We also thank the rice materials provided by Porf.Yunhai Li from Institute of Genetics and Developmental Biology Chinese Academy of Sciences,Beijing,China
摘 要：The traits of rice panicles play important roles in yield assessment,variety classification,rice breeding,and cultivation *** traditional grain phenotyping methods require threshing and thus are time-consuming and labor-intensive;moreover,these methods cannot obtain 3D grain *** this work,based on X-ray computed tomography,we proposed an image analysis method to extract twenty-two 3D grain *** 104 samples were tested,the R^(2) values between the extracted and manual measurements of the grain number and grain length were 0.980 and 0.960,*** also found a high correlation between the total grain volume and *** addition,the extracted 3D grain traits were used to classify the rice varieties,and the support vector machine classifier had a higher recognition accuracy than the stepwise discriminant analysis and random forest *** conclusion,we developed a 3D image analysis pipeline to extract rice grain traits using X-ray computed tomography that can provide more 3D grain information and could benefit future research on rice functional genomics and rice breeding.
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