As one of the most widely grown crops in the world,rice is not only a staple food but also a source of calorie intake for more than half of the world's population,occupying an important position in China's agr...As one of the most widely grown crops in the world,rice is not only a staple food but also a source of calorie intake for more than half of the world's population,occupying an important position in China's agricultural production.Thus,determining the inner potential connections between the genetic mechanisms and phenotypes of rice using dynamic analyses with high-throughput,nondestructive,and accurate methods based on high-throughput crop phenotyping facilities associated with rice genetics and breeding research is of vital importance.In this work,we developed a strategy for acquiring and analyzing 58 image-based traits(i-traits)during the whole growth period of rice.Up to 84.8%of the phenotypic variance of the rice yield could be explained by these i-traits.A total of 285 putative quantitative trait loci(QTLs)were detected for the i-traits,and principal components analysis was applied on the basis of the i-traits in the temporal and organ dimensions,in combination with a genome-wide association study that also isolated QTLs.Moreover,the differences among the different population structures and breeding regions of rice with regard to its phenotypic traits demonstrated good environmental adaptability,and the crop growth and development model also showed high inosculation in terms of the breeding-region latitude.In summary,the strategy developed here for the acquisition and analysis of image-based rice phenomes can provide a new approach and a different thinking direction for the extraction and analysis of crop phenotypes across the whole growth period and can thus be useful for future genetic improvements in rice.展开更多
The traits of rice panicles play important roles in yield assessment,variety classification,rice breeding,and cultivation management.Most traditional grain phenotyping methods require threshing and thus are time-consu...The traits of rice panicles play important roles in yield assessment,variety classification,rice breeding,and cultivation management.Most traditional grain phenotyping methods require threshing and thus are time-consuming and labor-intensive;moreover,these methods cannot obtain 3D grain traits.In this work,based on X-ray computed tomography,we proposed an image analysis method to extract twenty-two 3D grain traits.After 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,respectively.We also found a high correlation between the total grain volume and weight.In 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 classifiers.In 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.展开更多
基金supported by the National Key Research and Development Plan(2022YFD2002304)Strategic Priority Research Program of the Chinese Academy of Sciences(grant no.XDA24040201)+3 种基金National Natural Science Foundation of China(U21A20205)Key Projects of Natural Science Foundation of Hubei Province(2021CFA059)Major Science and Technology Project of Hubei Province(2021AFB002)Fundamental Research Funds for the Central Universities(2021ZKPY006 and 2662022JC006).
文摘As one of the most widely grown crops in the world,rice is not only a staple food but also a source of calorie intake for more than half of the world's population,occupying an important position in China's agricultural production.Thus,determining the inner potential connections between the genetic mechanisms and phenotypes of rice using dynamic analyses with high-throughput,nondestructive,and accurate methods based on high-throughput crop phenotyping facilities associated with rice genetics and breeding research is of vital importance.In this work,we developed a strategy for acquiring and analyzing 58 image-based traits(i-traits)during the whole growth period of rice.Up to 84.8%of the phenotypic variance of the rice yield could be explained by these i-traits.A total of 285 putative quantitative trait loci(QTLs)were detected for the i-traits,and principal components analysis was applied on the basis of the i-traits in the temporal and organ dimensions,in combination with a genome-wide association study that also isolated QTLs.Moreover,the differences among the different population structures and breeding regions of rice with regard to its phenotypic traits demonstrated good environmental adaptability,and the crop growth and development model also showed high inosculation in terms of the breeding-region latitude.In summary,the strategy developed here for the acquisition and analysis of image-based rice phenomes can provide a new approach and a different thinking direction for the extraction and analysis of crop phenotypes across the whole growth period and can thus be useful for future genetic improvements in rice.
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.
文摘The traits of rice panicles play important roles in yield assessment,variety classification,rice breeding,and cultivation management.Most traditional grain phenotyping methods require threshing and thus are time-consuming and labor-intensive;moreover,these methods cannot obtain 3D grain traits.In this work,based on X-ray computed tomography,we proposed an image analysis method to extract twenty-two 3D grain traits.After 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,respectively.We also found a high correlation between the total grain volume and weight.In 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 classifiers.In 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.
