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Evaluation of Beef Freshness Using Visible-near Infrared Reflectance Spectra
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 Title & Authors
Evaluation of Beef Freshness Using Visible-near Infrared Reflectance Spectra
Choi, Chang-Hyun; Kim, Jong-Hun; Kim, Yong-Joo;
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The objective of this study was to develop models to predict freshness factors (total viable counts (TVC), pH, volatile basic nitrogen (VBN), trimethylamine (TMA), and thiobarbituric acid (TBA) values) and the storage period in beef using a visible and near-infrared (NIR) spectroscopic technique. A total of 216 beef spectra were collected during the storage period from 0 to 14 d at a storage. A spectrophotometer was used to measure reflectance spectra from beef samples, and beef freshness spectra were divided into a calibration set and a validation set. Multi-linear regression (MLR) models using the stepwise method were developed to predict the factors. The MLR results showed that beef freshness had a good correlation between the predicted and measured factors using the selected wavelength. The correlation of determination (), standard error of prediction (SEP), and ratio of standard deviation to SEP (RPD) of the prediction set for TVC was 0.74, 0.64, and 2.75 Log CFU/, respectively. The , SEP, and RPD values for pH were 0.43, 0.10, and 1.10; those for VBN were 0.73, 1.45, and 2.00 mg%; those for TMA were 0.70, 0.19, and 2.58 mg%; those for TBA values were 0.73, 0.13, and 2.77 mg MA/kg; and those for storage period were 0.77, 1.94, and 2.53 d, respectively. The results indicate that visible and NIR spectroscopy can predict beef freshness during storage.
beef freshness;visible-near infrared reflectance spectra;multi linear regression;stepwise;
 Cited by
한우의 이화학적, 관능적 특성을 통한 신선도와 맛의 품질 인자 설정,문지혜;성미선;김종훈;김병삼;김윤숙;

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