偏最小二乘回归
拉曼光谱
分析化学(期刊)
傅里叶变换红外光谱
食物腐败
决定系数
化学
化学计量学
数学
环境化学
色谱法
统计
物理
生物
光学
遗传学
细菌
作者
Qingsen Liu,Pengcheng Dong,Lemonia-Christina Fengou,George‐John E. Nychas,Stephanie M. Fowler,Yanwei Mao,Xin Luo,Yimin Zhang
出处
期刊:Meat Science
[Elsevier BV]
日期:2023-03-20
卷期号:200: 109168-109168
被引量:45
标识
DOI:10.1016/j.meatsci.2023.109168
摘要
The objective of this study was to assess the potential to predict the microbial beef spoilage indicators by Raman and Fourier transform infrared (FT-IR) spectroscopies. Vacuum skin packaged (VSP) beef steaks were stored at 0 °C, 4 °C, 8 °C and under a dynamic temperature condition (0 °C ∼ 4 °C ∼ 8 °C, for 36 d). Total viable count (TVC) and total volatile basic nitrogen (TVB-N) were obtained during the storage period along with spectroscopic data. The Raman and FTIR spectra were baseline corrected, pre-processed using Savitzky-Golay smoothing and normalized. Subsequently partial least squares regression (PLSR) models of TVC and TVB-N were developed and evaluated. The root mean squared error (RMSE) ranged from 0.81 to1.59 (log CFU/g or mg/100 g) and the determination coefficient (R2) from 0.54 to 0.75. The performance of PLSR model based on data fusion (combination of Raman and FT-IR data) is better than that based on Raman spectra and similar to that of FT-IR. Overall, Raman spectroscopy, FT-IR spectroscopy, and a combination of both exhibited a potential for the prediction of the beef spoilage.
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