Classification of artisanal Andalusian cheeses on physicochemical parameters applying multivariate statistical techniques View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-01

AUTHORS

María Auxiliadora de la Haba Ruiz, Pilar Ruiz Pérez-Cacho, Rafaela Dios Palomares, Hortensia Galán-Soldevilla

ABSTRACT

In order to obtain a Protected Designation of Origin, it is necessary to characterize the food product. The objective of this work was to investigate whether there was a single Andalusian artisanal goat’ milk cheese or several types, depending on the goat breed and/or the cheese-making process (milk heat treatment, rennet type or ripening time). One hundred and eight artisanal goat cheeses, representative of the whole area of Andalusia and widely distributed, have been physicochemically analyzed (pH, TS, fat/TS, and NaCl). Linear regression models were suitable for studying which factors had an independent influence on the physicochemical parameters of these cheeses, the breed and the ripening time being the most influential factors. A K-means cluster analysis with the principal component analysis (PCA) scores was made in order to find profiles which defined these cheeses. The first group was composed of Malagueña fresh cheeses made with pasteurized milk and microbial rennet and which had a higher pH (6.2) and lower values of TS (53.5), fat (26.1), fat/TS (49.2), and NaCl (1.5) than the second cheese group. The second profile was made up of Murciano-Granadina and multi-breed semihard and hard cheeses made with pasteurized or raw milk and animal or vegetable rennet and having lower pH values (5.4) than group 1 and higher TS (62.5), fat (34.4), fat/ TS (54.7), and NaCl (2.0) values than group 1. These results could support the Quesos de Málaga Producer’s Association that is interested in applying for the Málaga fresh cheese quality certification (Protected Designation of Origin). More... »

PAGES

95-106

Journal

TITLE

Dairy Science & Technology

ISSUE

1

VOLUME

96

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13594-015-0242-5

DOI

http://dx.doi.org/10.1007/s13594-015-0242-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020631394


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