Predictive ability of FT-NIRS in the assessment of chemical composition of pork seasoned products.

Conventional chemical analyses of meat cured products are time-consuming, expensive and destructive. Advantages of NIR spectroscopy are its speed, simplicity, low-cost and the possibility to determine a large number of different parameters simultaneously in a large number of samples. The aim of this study is to assess the ability of FT-NIRs to predict chemical composition of seasoned pig products. One hundred and two seasoned products were sampled (43 "Cuore di spalla", 26 Toscano Ham and 33 "Capocollo") and the following chemical components were determined: protein, intramuscular fat, ashes and fatty acid composition. NIR spectra were collected using a Thermo-Fisher Antaris II instrument. Partial least squares (PLS) regression was applied in the calibration and the validation models; the models were fully cross-validated using the "leave-one-out" method. Calibration and cross validation models were developed both for each product separately and grouping all the samples. Calibration correlation coefficients show satisfying values (minimum R2=0.73), while crossvalidation correlation coefficients, despite being generally acceptable, show lower values (minimum R2=0.42). Best R2 was found for fat content (cross-validation R2= 0.95). Results, even if obtained on a reduced sample, show how FT-NIRs could be used in routine analyses of pig seasoned products. [ABSTRACT FROM AUTHOR]