An alternative freshness index method for modified atmosphere packaged abalone using an artificial neural network

An alternative freshness index method for abalone (Haliotis asinina) muscle packaged under atmospheric air (Air) and modified atmosphere (MA) of 40% CO2: 30% O2: 30% N2 packaging conditions and stored at 2 ± 1 °C was developed. Biochemical indices covering pH, total volatile basic nitrogen (TVB-N), trimethylamine (TMA) and nucleotide degradation products, as well as instrumental texture and color of the packaged abalones, were determined. Sensory characteristics including odor, color and appearance were evaluated and then summarized into overall freshness scores (freshness index). The biochemical and instrumental analyses were then calibrated with the freshness index, using an artificial neural network algorithm. The neural network was shown to be capable of correlating biochemical and instrumental analyses with the freshness index. A useful prediction was possible, as measured by a low mean square error (MSE = 0.092) and a regression coefficient (R2 = 0.98) between true and predicted data.