Quality control in the meat industry by multivariate statistics. The case of raw ham

R Virgili; G Parolari

doi:10.1016/0309-1740(91)90025-L

Quality control in the meat industry by multivariate statistics. The case of raw ham

Meat Sci. 1991;29(1):83-96. doi: 10.1016/0309-1740(91)90025-L.

Authors

R Virgili¹, G Parolari

Affiliation

¹ Stazione Sperimentale Industria Conserve Alimentari, V. le F. Tanara, 31/A, Parma, Italy.

PMID: 22060974
DOI: 10.1016/0309-1740(91)90025-L

Abstract

Two multivariate statistical techniques were tested on sensory and instrumental data from raw ham technology. (1) Cluster analysis, applied to parameters ranging from the beginning of processing to the end of resting, originated three groups which provided an explanation of the observed trends in the occurrence of microbial defects. (2) Partial-least-squares (PLS) regression, used to relate three sensory descriptors to five instrumental variables, provided a fully instrumental method for the assessment of quality of aged ham. Application of both techniques for prediction and description purposes is discussed.