Developing a multispectral model for detection of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) changes in fish fillet using physarum network and genetic algorithm (PN-GA) method.

Cheng, Jun-Hu; Sun, Da-Wen; Liu, Guixiong; Chen, Yu-Nan

Cheng, Jun-Hu; Sun, Da-Wen; Liu, Guixiong; Chen, Yu-Nan.

Affiliation

Cheng JH; School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China; Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; Engineering and Technological Research Centre of Gua
Sun DW; School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China; Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; Engineering and Technological Research Centre of Gua
Liu G; School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China.
Chen YN; School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China; Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; Engineering and Technological Research Centre of Gua

Food Chem ; 270: 181-188, 2019 Jan 01.

Article in En | MEDLINE | ID: mdl-30174033

Subject(s)

Docosahexaenoic Acids/analysis; Eicosapentaenoic Acid/analysis; Seafood/analysis; Algorithms; Animals; Least-Squares Analysis; Physarum

Key words

DHA; EPA; Hyperspectral imaging; MLR; Physarum network genetic algorithm

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Eicosapentaenoic Acid / Docosahexaenoic Acids / Seafood Type of study: Diagnostic_studies / Prognostic_studies Limits: Animals Language: En Journal: Food Chem Year: 2019 Type: Article

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