文献
J-GLOBAL ID:202102239379152992
整理番号:21A0196098
機械学習法と作物成長モデルを組み合わせた統合アプローチを用いたイネ出穂日の予測【JST・京大機械翻訳】
Predicting Rice Heading Date Using an Integrated Approach Combining a Machine Learning Method and a Crop Growth Model
著者 (5件):
Chen Tai-Shen
(Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo, Japan)
,
Aoike Toru
(Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo, Japan)
,
Yamasaki Masanori
(Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University, Kasai, Hyogo, Japan)
,
Kajiya-Kanegae Hiromi
(Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo, Japan)
,
Iwata Hiroyoshi
(Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo, Japan)
資料名:
Frontiers in Genetics (Web)
(Frontiers in Genetics (Web))
巻:
11
ページ:
599510
発行年:
2020年
JST資料番号:
U7071A
ISSN:
1664-8021
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)