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High-resolution crop yield and water productivity dataset generated using random forest and remote sensing.
Cheng, Minghan; Jiao, Xiyun; Shi, Lei; Penuelas, Josep; Kumar, Lalit; Nie, Chenwei; Wu, Tianao; Liu, Kaihua; Wu, Wenbin; Jin, Xiuliang.
Affiliation
  • Cheng M; Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College, Yangzhou University, 225009, Yangzhou, P.R. China.
  • Jiao X; Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, 225009, Yangzhou, P.R. China.
  • Shi L; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, P.R. China.
  • Penuelas J; College of Agricultural Science and Engineering, Hohai University, Nanjing, Jiangsu Province, 210098, P.R. China.
  • Kumar L; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, P.R. China.
  • Nie C; CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, 08193, Barcelona, Catalonia, Spain.
  • Wu T; CREAF, Cerdanyola del Vallès, 08193, Barcelona, Catalonia, Spain.
  • Liu K; EastCoast Geospatial Consultants, Armidale, NSW, 2350, Australia.
  • Wu W; Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College, Yangzhou University, 225009, Yangzhou, P.R. China.
  • Jin X; College of Agricultural Science and Engineering, Hohai University, Nanjing, Jiangsu Province, 210098, P.R. China.
Sci Data ; 9(1): 641, 2022 10 21.
Article in En | MEDLINE | ID: mdl-36271097
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Water Resources / Crops, Agricultural Type of study: Clinical_trials / Prognostic_studies Country/Region as subject: Asia Language: En Journal: Sci Data Year: 2022 Document type: Article
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Water Resources / Crops, Agricultural Type of study: Clinical_trials / Prognostic_studies Country/Region as subject: Asia Language: En Journal: Sci Data Year: 2022 Document type: Article