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A deep learning-integrated micro-CT image analysis pipeline for quantifying rice lodging resistance-related traits.
Wu, Di; Wu, Dan; Feng, Hui; Duan, Lingfeng; Dai, Guoxing; Liu, Xiao; Wang, Kang; Yang, Peng; Chen, Guoxing; Gay, Alan P; Doonan, John H; Niu, Zhiyou; Xiong, Lizhong; Yang, Wanneng.
Afiliación
  • Wu D; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Wu D; School of Information Engineering, Wuhan Technology and Business University, Wuhan 430065, PR China.
  • Feng H; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Duan L; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Dai G; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Liu X; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Wang K; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Yang P; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Chen G; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Gay AP; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Doonan JH; The National Plant Phenomics Centre, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK.
  • Niu Z; The National Plant Phenomics Centre, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK.
  • Xiong L; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
  • Yang W; National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Key Laboratory of Agricultural Bioinformatics and College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China.
Plant Commun ; 2(2): 100165, 2021 03 08.
Article en En | MEDLINE | ID: mdl-33898978
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades de las Plantas / Oryza / Microtomografía por Rayos X / Resistencia a la Enfermedad / Fitomejoramiento / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: Plant Commun Año: 2021 Tipo del documento: Article Pais de publicación: China
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades de las Plantas / Oryza / Microtomografía por Rayos X / Resistencia a la Enfermedad / Fitomejoramiento / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: Plant Commun Año: 2021 Tipo del documento: Article Pais de publicación: China