BP neural network to predict shelf life of channel catfish fillets based on near infrared transmittance (NIT) spectroscopy
文献类型： 外文期刊
作者： Mao, Shucan 1 ; Zhou, Junpeng 1 ; Hao, Meng 1 ; Ding, Anzi 1 ; Li, Xin 1 ; Wu, Wenjin 1 ; Qiao, Yu 1 ; Wang, Lan 1 ; Xiong, Guangquan 1 ; Shi, Liu 1 ;
作者机构： 1.Hubei Acad Agr Sci, Inst Agroprod Proc & Nucl Agr Technol, Key Lab Agr Prod Cold Chain Logist, Minist Agr & Rural Affairs, Wuhan 430064, Peoples R China
2.Hubei Minzu Univ, Coll Biol Sci & Technol, Enshi 445000, Peoples R China
3.Hubei Univ Technol, Bioengn & Food Coll, Dept Biomed & Biopharmacol, Wuhan 430068, Peoples R China
关键词： Prediction model; BP neural network; Channel catfish fillets; Freshness; Transmission near infrared
期刊名称：FOOD PACKAGING AND SHELF LIFE （ 影响因子：8.0； 五年影响因子：8.1 ）
ISSN： 2214-2894
年卷期： 2023 年 35 卷
页码：
收录情况： SCI
摘要： The objective of this research was to establish shelf-life prediction model of channel catfish fillets by Back-propagation (BP) neural network technology based on near infrared transmittance (NIT). First, freshness pre-diction model of channel catfish fillets was established based on the chemical analysis data (total volatile basic nitrogen (TVB-N), K value, thiobarbituric acid reactive substance (TBARS) and trimethylamine (TMA)) and NIT spectra (850-1050 nm). The linear correlation coefficient (R2: 0.667-0.887) showed a good performance of the freshness model prediction. Then, BP neural network was applied to establish the shelf-life prediction model of catfish fillets under temperature fluctuation (-6 to-18 degrees C). The end effective accumulated temperature of frozen catfish fillets was 10,278.4 h degrees C. The prediction model showed a great stability (above 93 %) and accuracy (above 90 %) as the structure of BP neural network was 4-7-1. Therefore, this study provided a practical basis and technical supports for the establishment of shelf-life prediction model of freshwater fillets by BP neural network based on NIT spectroscopy.
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