Prevolnik, Maja and Andronikov, Darko and Zlender, Bozidar and Font-i-Furnols, Maria and Novic, Marjana and Skorjanc, Dejan and Candek-Potokar, Marjeta (2013) Classification of dry-cured hams according to the maturation time using near infrared spectra and artificial neural networks. Meat Science, 96 (1). pp. 14-20. ISSN S0309-1740(13)00290-8
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Classification of Dry-Cured Hams according to the Maturation Time using Near Infrared Spectra and Artificial Neural Networks.pdf Download (436kB) | Preview |
Abstract
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 (n=32), 12 (n=32), 14 (n=32) or 16 months (n=32). 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 counter-propagation 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.
Key words: dry-cured ham, classification, near infrared spectroscopy, artificial neural networks
| Item Type: | Article |
|---|---|
| Subjects: | Agricultural Sciences > Animal and dairy science |
| Divisions: | Faculty of Agriculture |
| Depositing User: | Darko Andronikov |
| Date Deposited: | 17 Sep 2013 08:53 |
| Last Modified: | 17 Sep 2013 08:53 |
| URI: | https://eprints.ugd.edu.mk/id/eprint/6884 |
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