文献
J-GLOBAL ID:201702285852186900
整理番号:17A0361484
部分最小二乗回帰前変数選択法は中赤外分光学によって予測される乳脂肪酸組成の精度を高める【Powered by NICT】
Variable selection procedures before partial least squares regression enhance the accuracy of milk fatty acid composition predicted by mid-infrared spectroscopy
著者 (4件):
Gottardo P.
(Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Universita 16, 35020 Legnaro (PD), Italy)
,
Penasa M.
(Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Universita 16, 35020 Legnaro (PD), Italy)
,
Lopez-Villalobos N.
(Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Private Bag 11 222, Palmerston North, 4442, New Zealand)
,
De Marchi M.
(Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Universita 16, 35020 Legnaro (PD), Italy)
資料名:
Journal of Dairy Science
(Journal of Dairy Science)
巻:
99
号:
10
ページ:
7782-7790
発行年:
2016年
JST資料番号:
C0282A
ISSN:
0022-0302
CODEN:
JDSCAE
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)