چکیده  : 

An attempt to classify dry-cured hams according to the maturation time on the basis of near infrared (NIR)

spectra was studied. The study comprised 128 samples of biceps femoris (BF) muscle from dry-cured hams

matured for 10 (), 12 (), 14 () or 16 months (). Samples were minced and

scanned in the wavelength range from 400 to 2500 nm using spectrometer NIR System model 6500 (Silver

Spring, MD, USA). Spectral data were used for i) splitting of samples into the training and test set using 2D

Kohonen artificial neural networks (ANN) and for ii) construction of classification models using counterpropagation

ANN (CP-ANN). Different models were tested, and the one selected was based on the lowest percentage

of misclassified test samples (external validation). Overall correctness of the classification was 79.7%,

which demonstrates practical relevance of using NIR spectroscopy and ANN for dry-cured ham processing

control.