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J-GLOBAL ID：202102218965052762   整理番号：21A0522443

適切な播種と移植日を決定するためのイネモデルシステム【JST・京大機械翻訳】

A Rice Model System for Determining Suitable Sowing and Transplanting Dates

著者 (41件)： Wu Yueting (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Wu Yueting (MOE Engineering and Research Center for Smart Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Wu Yueting (Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China) ,  Wu Yueting (Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Wu Yueting (Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China) ,  Qiu Xiaolei (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Qiu Xiaolei (MOE Engineering and Research Center for Smart Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Qiu Xiaolei (Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China) ,  Qiu Xiaolei (Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Qiu Xiaolei (Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhang Ke (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhang Ke (MOE Engineering and Research Center for Smart Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhang Ke (Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhang Ke (Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhang Ke (Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China) ,  Chen Zhiliang (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Chen Zhiliang (MOE Engineering and Research Center for Smart Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Chen Zhiliang (Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China) ,  Chen Zhiliang (Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Chen Zhiliang (Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China) ,  Pang Alexis (School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Building 184, Royal Parade, Parkville, Victoria 3010, Australia) ,  Tian Yongchao (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Tian Yongchao (MOE Engineering and Research Center for Smart Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Tian Yongchao (Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China) ,  Tian Yongchao (Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Tian Yongchao (Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China) ,  Cao Weixing (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Cao Weixing (MOE Engineering and Research Center for Smart Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Cao Weixing (Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China) ,  Cao Weixing (Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Cao Weixing (Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China) ,  Liu Xiaojun (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Liu Xiaojun (MOE Engineering and Research Center for Smart Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Liu Xiaojun (Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China) ,  Liu Xiaojun (Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Liu Xiaojun (Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhu Yan (National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhu Yan (MOE Engineering and Research Center for Smart Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhu Yan (Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhu Yan (Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China) ,  Zhu Yan (Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China)
資料名： Agronomy (Web)  (Agronomy (Web))
巻： 10  号： 4  ページ： 604  発行年： 2020年 
JST資料番号： U7129A  ISSN： 2073-4395  資料種別： 逐次刊行物 (A)
記事区分： 原著論文  発行国： スイス (CHE)  言語： 英語 (EN)

抄録/ポイント： 播種と移植日付は,イネ生産のための重要な栽培因子である。したがって,本研究は,異なる農業-生態学的地帯における多様な品種と植栽方法のための播種と移植日付を決定することができるイネモデルシステムの開発に焦点を当てた。異なるモデルパラメータを,この研究における相互作用効果に基づいてイネモデル系に統合した。結果は,イネモデルシステムによって設計した播種と移植日が,高収量慣行のための地方農業専門家が推奨する植栽日付に近づき,根平均二乗誤差(RMSE)が5.3から14.74日であったことを示した。モデル系は,比較的低いRMSE,高い線形相関係数(R2),およびモデル効率(EF)で,ほとんどのシナリオの下で適切な播種と移植日付を正確にシミュレートした。モデルシステム推奨を用いて,低肥沃土壌における手動移植下のイネ収量は最大(5.5%)増加したが,高肥沃土壌における直接播種では収量増加は中程度(0.8%)であった。新しく開発されたイネモデル系は,高収率と効果的な作物生産を達成するための適切な播種と移植日付を設計するための技術的アプローチとして機能できる。Copyright 2021 The Author(s) All rights reserved. Translated from English into Japanese by JST.【JST・京大機械翻訳】

シソーラス用語： 農業 ,  相関係数 ,  *栽培 ,  線形性 ,  品種 ,  生態学
準シソーラス用語： 平均二乗誤差 ,  モデルパラメータ ,  作物生産 ,  播種日 ,  肥沃 , 【Automatic Indexing@JST】

著者キーワード (5件)： 米 ,  播種日 ,  移植日 ,  モデルシステム ,  設計

分類 (1件)： 稲作  (FC03020C)

引用文献 (64件)：

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• Gregory, P.; George, T.S. Feeding nine billion: The challenge to sustainable crop production. J. Exp. Bot. 2011, 62, 5233-5239.
• Yuan, S.; Peng, S.; Li, T. Evaluation and application of the ORYZA rice model under different crop managements with high-yielding rice cultivars in central China. Field Crop. Res. 2017, 212, 115-125.
• Deng, A.; Chen, C.; Jinfei, F.; Chen, J.; Zhang, W. Cropping system innovation for coping with climatic warming in China. Crop. J. 2017, 5, 136-150.
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タイトルに関連する用語 (2件)： 播種 ,  移植