Estimation of ripening time of Pategras cheese using physicochemical parameters and multivariate techniques

RAMONDA, M. B.; PEROTTI, M.C.; BERNAL, S.; ZALAZAR, C

AUSTRALIAN JOURNAL OF DAIRY TECHNOLOGY

Año: 2008 vol. 63 p. 21 - 24

0004-9433

Abstract In this paper, Principal Component Regression (PCR) and Partial Least Squares Regression (PLS) were used to estimate the ripening time of Pategrás cheese, based on physicochemical parameters. Cheeses were produced at pilot scale, according to the standard process for this type and manufactured in different seasons over a period of 2 years and 6 months. These cheeses were separated in two sets: 20 cheeses as calibration set and the remaining 10 as validation set. The gross composition parameters were within the normal ranges for this type of cheese. All cheeses shown a satisfactory and typical sensory quality that has been demonstrated by sensory examination. The pH did not undergo any significant changes, on the contrary %pH4.6-SN/TN, %TCA-SN/TN and %PTA-SN/TN underwent significant increases over the studied ripening period. As a consequence, these last three parameters were chosen as the predictors variables. Similar results were obtained from PCR and PLS regressions. Two regression methods yielded good correlations (R > 0,97) and low RMSEPCV values that suggest a good predictive capacity. PLS model was applied to the validation data and a high value of R (0,98) and a low error of prediction (RMSEP of about 5 days) were obtained.CV values that suggest a good predictive capacity. PLS model was applied to the validation data and a high value of R (0,98) and a low error of prediction (RMSEP of about 5 days) were obtained.