Intelligent assessment of the histamine level in mackerel (Scomber australasicus) using near-infrared spectroscopy coupled with a hybrid variable selection strategy

• Published in: Food science & technology Vol. 145; p. 111524
• Main Authors: Pauline, Ong, Chang, Hsin-Tze, Tsai, I-Lin, Lin, Che-Hsuan, Chen, Suming, Chuang, Yung-Kun
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2021
• Subjects: algorithms; Artificial neural networks; Backward interval partial least squares; data collection; Flower pollination algorithm; freshness; histamine; mackerel; near-infrared spectroscopy; Partial least squares; poisoning; prediction; risk; Scomber australasicus; Selectivity ratio; wavelet; Backward interval partial least squares; Partial least squares; Selectivity ratio; Artificial neural networks; Flower pollination algorithm

Determination of the histamine level in fish is essential not only because it is an indicator of fish freshness but also because this prevents the risk of histamine intoxication in consumers. This study used the strategy of near-infrared (NIR) spectroscopy coupled with a hybrid variable selection fo...