Near-infrared spectroscopy-based analysis to study sensory parameters on pork loins as affected by cooking methods and conditions.

BACKGROUND: The main objectives of this study were to evaluate the use of near infrared spectroscopy (NIRS) to classify pork loins under different methods and cooking conditions, and to predict sensory attributes of this product.

RESULTS: Samples were oven cooked at two temperatures (150 and 180 °C) for different times (45, 60 and 75 min) and confit cooked for different times (120, 180 and 240 min). All cooked loin samples were subjected to a Quantitative Descriptive Analysis by a trained panel. For classification, principal component analysis was performed based on the NIRS database, showing a good discrimination between loins samples subjected to different cooking conditions. Regarding prediction, a data mining technique (multiple linear regression) was applied on a database constructed with data from NIRS and sensory analysis.

CONCLUSION: The correlation coefficient and the mean absolute error obtained suggest that the calculated prediction equations of this study are valid to predict the changes in the sensory attributes depending on the cooking method and conditions used for pork loins. © 2018 Society of Chemical Industry.