期刊
FOOD CHEMISTRY
卷 244, 期 -, 页码 184-189出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2017.09.148
关键词
PSE (pale, soft and exudative); DFD (dark, firm and dry); L*; pH; Water-holding capacity; PLSR; PCA
资金
- China National Science and Technology Support Program [2012BAK08B04]
In this study visible/near-infrared spectroscopy (Vis/NIRS) was evaluated to rapidly classify intact chicken breast fillets. Five principal components (PC) were extracted from reference quality traits (L*, pH, drip loss, expressible fluid, and salt-induced water gain). A quality grades classification method by PC1 score was proposed. With this method, 150 chicken fillets were properly classified into three quality grades, i.e., DFD (dark, firm and dry), normal, and PSE (pale, soft and exudative). Furthermore, P(C)1 score could be predicted using partial least squares regression (PLSR) model based on Vis/NIRS (R(2)p= 0.78, RPD= 1.9), without the measurement of any quality traits. Thresholds of PC1 classification method were applied to classify the predicted PC1 score values of each fillet into three quality grades. The classification accuracy of calibration and prediction set were 85% and 80%, respectively. Results revealed that PC1 score classification method is feasible, and with Vis/ NIRS, this method could be rapidly implemented.
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