Izvorni znanstveni članak
https://doi.org/10.46419/cvj.57.5.6
Prediction of Frozen Chicken Meat Storage Time through Artificial Neural Network Analysis of Colour Parameters
Mounia Megaache
; Laboratory of Health, Animal Production and Environment, Department of Veterinary Sciences, Institute of Veterinary and Agricultural Sciences, University of Batna 1, Batna, Algeria
*
Hafsa Akkari
; Department of Veterinary Sciences, Institute of Veterinary and Agricultural Sciences, University of Batna 1, Batna, Algeria
* Dopisni autor.
Sažetak
Poultry meat colour deteriorates during prolonged frozen storage, affecting consumer perception and product value. This study investigated changes in colour parameters (L*, a*, b*) of frozen chicken breast meat, and developed an artificial neural network to predict storage time non-destructively. Ten chicken breast samples were analysed at different freezing storage times (0, 3, 6, 9, and 12 weeks) at -18°C, with colour measurements performed directly on each sample. Lightness (L*) increased from 51.82 ± 1.1 to 58.21 ± 1.0 units, redness (a*) decreased from 3.25 ± 0.2 to 2.12 ± 0.2 units, and yellowness (b*) increased from 8.12 ± 0.5 to 9.91 ± 0.6 units, resulting in a total colour difference of ΔE = 6.87, and all changes were statistically significant. The multilayer perceptron artificial neural network showed good agreement between predicted and actual storage times (R² ≈ 0.98), demonstrating the potential of colour-based modelling as a rapid, non-destructive tool for monitoring frozen chicken meat quality.
Ključne riječi
colourimetry; MLP neural network; frozen poultry; storage prediction; non-destructive analysis
Hrčak ID:
347603
URI
Datum izdavanja:
15.9.2026.
Posjeta: 0 *