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Image-based phenotyping of seed architectural traits and prediction of seed weight using machine learning models in soybean.
Duc, Nguyen Trung; Ramlal, Ayyagari; Rajendran, Ambika; Raju, Dhandapani; Lal, S K; Kumar, Sudhir; Sahoo, Rabi Narayan; Chinnusamy, Viswanathan.
Affiliation
  • Duc NT; Division of Plant Physiology, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi, India.
  • Ramlal A; Vietnam National University of Agriculture, Hanoi, Vietnam.
  • Rajendran A; Division of Genetics, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi, India.
  • Raju D; School of Biological Sciences, Universiti Sains Malaysia (USM), Georgetown, Penang, Malaysia.
  • Lal SK; Division of Genetics, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi, India.
  • Kumar S; Division of Plant Physiology, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi, India.
  • Sahoo RN; Division of Genetics, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi, India.
  • Chinnusamy V; Division of Plant Physiology, Indian Council of Agricultural Research-Indian Agricultural Research Institute (ICAR-IARI), New Delhi, India.
Front Plant Sci ; 14: 1206357, 2023.
Article in En | MEDLINE | ID: mdl-37771485
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Plant Sci Year: 2023 Document type: Article Affiliation country: India Country of publication: Switzerland
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Plant Sci Year: 2023 Document type: Article Affiliation country: India Country of publication: Switzerland