Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4565307 | LWT - Food Science and Technology | 2007 | 6 Pages |
Abstract
The aim of this study was to classify whole-leg cooked hams, made without polyphosphates, by linear discriminant analysis. Principal component analysis (PCA) was used for the selection of significant variables. Thirty-two variables were evaluated on 26 cooked hams prepared using different levels of brine injection and legs from pork bred in different countries (France or Denmark). Previously published data related to 20 hams were also used for classification. A chemometric model, based on ten variables, was obtained by using PCA. The variables were pH, moisture, protein, fat, NaCl, superficial wateriness, L* and a*/b* of biceps femoris muscle, modulus and elasticity index of semitendinosus muscle. Discriminant functions calculated using PCA-selected variables enable correct classification of the cooked hams according to the origin of the meat used and, when this is the same, according to the percentage of brine injected.
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Authors
Ernestina Casiraghi, Cristina Alamprese, Carlo Pompei,