近红外光谱
偏最小二乘回归
校准
分析化学(期刊)
化学
数学
色谱法
统计
生物
神经科学
作者
Qin Ouyang,Lihua Liu,Muhammad Zareef,Li Wang
标识
DOI:10.1016/j.lwt.2022.113304
摘要
In this study, a portable visible and near-infrared (Vis-NIR) spectroscopy system was developed to quickly assess the cooking loss rate in pork, with findings comparing spectra from frozen and thawed pork. Firstly, the Vis-NIR spectral data of samples were collected under freezing and thawing conditions. After selecting characteristic variables using four different variable selection algorithms, partial least square (PLS) was used to predict cooking loss rate. The competitive adaptive reweighted sampling PLS (CARS-PLS) models were noted with higher prediction results, based on correlation coefficients of calibration (Rc) = 0.8362 and prediction (Rp) = 0.8154 for frozen pork samples spectra, while Rc and Rp for thawed pork samples spectra were noted as 0.8748 and 0.8421, respectively. The results of the comparison showed that the prediction effects of frozen and thawed pork spectra were similar. The current method has an excellent prospect to predict frozen pork quality without thawing.
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