Article
Application of linear and machine learning models to genomic prediction of fatty acid composition in Japanese Black cattle.
Animal science journal = Nihon chikusan Gakkaiho - 1 Jan 2000
Nishio Motohide, Inoue Keiichi, Arakawa Aisaku, Ichinoseki Kasumi, Kobayashi Eiji, Okamura Toshihiro, Fukuzawa Yo, Ogawa Shinichiro, Taniguchi Masaaki, Oe Mika, Takeda Masayuki, Kamata Takehiro, Konno Masaru, Takagi Michihiro, Sekiya Mario, Matsuzawa Tamotsu, Inoue Yoshinobu, Watanabe Akihiro, Kobayashi Hiroshi, Shibata Eri, Ohtani Akihumi, Yazaki Ryu, Nakashima Ryotaro, Ishii Kazuo
Abstract excerpt
We collected 3180 records of oleic acid (C18:1) and monounsaturated fatty acid (MUFA) measured using gas chromatography (GC) and 6960 records of C18:1 and MUFA measured using near-infrared spectroscopy (NIRS) in intermuscular fat samples of Japanese Black cattle. We compared genomic prediction performance for four linear models (genomic best linear unbiased prediction [GBLUP], kinship-adjusted multiple loci...
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