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Estimation of Serpa cheese ripening time using multiple linear regression (MLR) considering rheological, physical and chemical data

Published online by Cambridge University Press:  12 May 2008

Nuno Alvarenga*
Affiliation:
Instituto Politécnico de Beja – Escola Superior Agrária, Rua Pedro Soares, Apartado 6158, 7801-908 Beja, Portugal
Paula Silva
Affiliation:
Instituto Politécnico de Beja – Escola Superior Agrária, Rua Pedro Soares, Apartado 6158, 7801-908 Beja, Portugal
José Rodriguez Garcia
Affiliation:
Technical University of Lisbon, Instituto Superior de Agronomia, DAIAT, Tapada de Ajuda, 1349-017 Lisboa, Portugal
Isabel Sousa
Affiliation:
Technical University of Lisbon, Instituto Superior de Agronomia, DAIAT, Tapada de Ajuda, 1349-017 Lisboa, Portugal
*
*For correspondence; e-mail: bartolomeu.alvarenga@esab.ipbeja.pt

Abstract

Raw ewes' milk semi-soft cheeses (RESS-cheeses) are important products in Portugal and in several European regions. Creamy texture is an essential attribute of these cheeses, which results from structural properties that are not always well characterized. Here, the structural changes occurring during the ripening period of a traditional RESS-cheese, known as Serpa cheese, were analysed through small amplitude oscillatory shear (SAOS). Rheological data was complemented with other physical and chemical parameters, that were monitored during ripening, in order to estimate Serpa cheese ripening time using multiple linear regression (MLR). Mechanical spectra indicated a relatively strong structure, comparable to a gel, with a low dependence on frequency at the beginning of ripening and a weak structure, comparable to a concentrated suspension, with a crossing point (G″=G′) at the left of the graphic and with both moduli highly dependent on frequency, at the end of ripening. Good correlations (P<0·05) were obtained between structural (hardness and storage modulus) and proteolysis indicators. Using a combination of chemical, colour and rheological parameters we were able to obtain a multiple linear regression (MLR) which allows the estimation of Serpa cheese ripening time with an estimation error of 1·7 d (adjusted R2=0·98, P<0·0001).

Type
Research Article
Copyright
Copyright © Proprietors of Journal of Dairy Research 2008

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