
https://www.food.actapol.net/volume11/issue3/7_3_2012.pdf
Background. The aim of the study was to elaborate a method of modelling and forecasting rheological features which could be applied to raw minced meat at the stage of mixture preparation with a given ingredient composition.
Conclusion. High percentage of the total variance explained in PCA analysis (73.5%) indicated that the percentage composition of raw minced meat can be successfully used in the prediction of its rheological features. Statistical analysis of the results revealed, that artificial neural network model is able to predict rheological parameters and thus a complete texture profile of raw minced meat.
MLA | Balejko, Jerzy A., et al. "Artificial neural network as the tool in prediction rheological features of raw minced meat." Acta Sci.Pol. Technol. Aliment. 11.3 (2012): 273-281. |
APA | Balejko J.A., Nowak Z., Balejko E. (2012). Artificial neural network as the tool in prediction rheological features of raw minced meat. Acta Sci.Pol. Technol. Aliment. 11 (3), 273-281 |
ISO 690 | BALEJKO, Jerzy A., NOWAK, Zbigniew, BALEJKO, Edyta. Artificial neural network as the tool in prediction rheological features of raw minced meat. Acta Sci.Pol. Technol. Aliment., 2012, 11.3: 273-281. |