立陶宛
氮气
食品科学
环境科学
化学
渔业
小虾
生物
有机化学
作者
Wei Zhang,Yin‐Yi Han,Yang Shen,Wei Shang,Jianhui Wu,Tianhui Jiao,Jie Wang,Dong Liang,Xiaomei Chen,Quansheng Chen,Qingmin Chen
标识
DOI:10.1016/j.jfca.2024.106026
摘要
The change of volatile organic compounds (VOCs) caused by spoilage bacteria are typical characteristics of seafood decay. This study investigated the freshness of shrimp (Litopenaeus vannamei) using a bi-channel data acquisition based on the colorimetric sensing array (CSA) technique. First, nine color-sensitive dyes were selected to capture VOCs changes during shrimp spoilage. Then, both image and spectral channel data from the CSA were used to predict the total volatile basic nitrogen (TVB-N) content and evaluate its prediction ability, respectively. The original full data from the spectral channel performs better than the image channel. Next, four optimization algorithms are tried to filter spectral feature variables. Finally, the variable combination global analysis-iterative retained information variables (VCPA-IRIV) algorithm combined with a partial least squares (PLS) model was determined for predicting the TVB-N of shrimp, achieving the best precision and robustness performance with the Rp2, RMSEP, and RPD were 0.9734, 1.54, and 6.14, respectively. Therefore, this study provides a new approach to evaluate shrimp freshness rapidly.
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