Your browser doesn't support javascript.
loading
Optimization of accelerated solvent extraction of ellagitannins in black raspberry seeds using artificial neural network coupled with genetic algorithm.
Lee, Ga Eun; Kim, Ryun Hee; Lim, Taehwan; Kim, Jaecheol; Kim, Suna; Kim, Hyoung-Geun; Hwang, Keum Taek.
Afiliación
  • Lee GE; Department of Food and Nutrition, and Research Institute of Human Ecology, Seoul National University, Seoul 08826, Republic of Korea; BK21 FOUR Education and Research Team for Sustainable Food & Nutrition, Seoul National University, Seoul 08826, Republic of Korea.
  • Kim RH; Department of Food and Nutrition, and Research Institute of Human Ecology, Seoul National University, Seoul 08826, Republic of Korea; BK21 FOUR Education and Research Team for Sustainable Food & Nutrition, Seoul National University, Seoul 08826, Republic of Korea.
  • Lim T; Department of Biomedical Engineering, Tufts University, 4 Colby St., Medford 02155, MA, USA.
  • Kim J; Department of Food and Nutrition, and Research Institute of Human Ecology, Seoul National University, Seoul 08826, Republic of Korea; BK21 FOUR Education and Research Team for Sustainable Food & Nutrition, Seoul National University, Seoul 08826, Republic of Korea.
  • Kim S; Division of Human Ecology, College of Natural Science, Korea National Open University, Seoul 03078, Republic of Korea.
  • Kim HG; Graduate School of Biotechnology and Department of Oriental Medicinal Biotechnology, Kyung Hee University, Yongin 17104, Republic of Korea.
  • Hwang KT; Department of Food and Nutrition, and Research Institute of Human Ecology, Seoul National University, Seoul 08826, Republic of Korea; BK21 FOUR Education and Research Team for Sustainable Food & Nutrition, Seoul National University, Seoul 08826, Republic of Korea. Electronic address: keum@snu.ac
Food Chem ; 396: 133712, 2022 Dec 01.
Article en En | MEDLINE | ID: mdl-35863176
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Nigella sativa / Rubus Tipo de estudio: Prognostic_studies Idioma: En Revista: Food Chem Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Nigella sativa / Rubus Tipo de estudio: Prognostic_studies Idioma: En Revista: Food Chem Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido