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CHINESE JOURNAL OF OIL CROP SCIENCES ›› 2020, Vol. 42 ›› Issue (1): 61-.doi: 10.19802/j.issn.1007-9084.2020028

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 Automatic acquisition of accurate phenotype from stems of soybean based on semantic segmentation and its application in selection of imported line materials

  

  1.  1. College of Arts and Science, Northeast Agricultural University, Harbin 150030, China;  2. College of Engineering, Northeast Agricultural University, Harbin 150030, China;  3. College of Agriculture, Northeast Agricultural Universi⁃ ty, Harbin 150030, China;  4. Jilin Academy of Agricultural Sciences,Changchun 130000,China;  5. College of Electri⁃ cal and Information Engineering, Northeast Agricultural University, Harbin 150030, China
  • Online:2020-02-28 Published:2020-03-05

Abstract:  The construction of soybean imported line population and selection of materials are important in soy⁃ bean breeding. The selection of imported line materials for a specific phenotype can not only improve the efficiency of breeding, but also speed up the process of locating target trait genes. In this study, the semantic segmentation technique in machine detection was used to automatically extract the main stem-related phenotypes from the import⁃ ed lines (190 individuals) constructed for both parents, Suinong 14 (recurrent parent) and wild soybean ZYD00006 (donor parent). On this basis, this study systematically clustered the tested materials for the main stem-related phe⁃ notypes, and the results clearly showed the aggregation of the tested materials (near-equal materials) based on the main stem-phenotypes. It became an important basis for the selection of materials for the main stem-phenotypes. At the same time, the results could greatly accelerate the locating procedure of the main stem related phenotype genes. 

Key words: color:#000000, font-family:", sans serif", ,tahoma,verdana,helvetica, font-size:12px, font-style:normal, font-weight:normal, line-height:1.5, text-decoration:none, ">yield soybean;introgression lines;semantic segmentation;automatic withdrawal

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