偏最小二乘回归
校准
多元统计
化学
肉牛
均方预测误差
分析化学(期刊)
数学
动物科学
色谱法
统计
生物
作者
Qingmin Chen,Yunfei Xie,Hang Yu,Yahui Guo,Weirong Yao
出处
期刊:Food Chemistry
[Elsevier]
日期:2023-01-19
卷期号:413: 135513-135513
被引量:16
标识
DOI:10.1016/j.foodchem.2023.135513
摘要
Freeze-thaw accelerated the colour deterioration of beef with the increase of colour b* and the decrease of colour a* values (P < 0.05). The maximum exudate loss reached 22 % after the seventh freeze-thaw. A strong correlation between the transversal relaxation time T21 and thawing loss may mean that T21 water contributed to the exudate loss during freeze-thaw. Afterwards, competitive adaptive reweighted sampling-partial least square (CARS-PLS) has the best prediction in thawing loss of frozen/thawed beef with correlation coefficients of prediction (Rp) of 0.971, and root mean square error of prediction (RMSEP) of 1.436. Besides, Uninformative variable elimination-partial least squares (UVE-PLS) showed good prediction effects on colour values (Rp = 0.932 - 0.994) and water content (Rp = 0.928, RMSEP = 0.582) of frozen/thawed beef. Therefore, this work demonstrated that Raman spectroscopy coupled with multivariate calibration has a good ability for non-destructive prediction in colour and water-related properties of frozen/thawed beef.
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