ANN modeling of dose-dependent efficacy of ergothioneine-loaded chitosan nanoparticles against discoloration and lipid oxidation in refrigerated yellowfin tuna cubes

Abstract

The present study evaluates the efficacy of ergothioneine-loaded chitosan nanoparticles (ECNP) in enhancing color and lipid oxidative stability in refrigerated yellowfin tuna cubes based on key indicators, including redness index (RI), metmyoglobin (metMb), total lipid hydroperoxides (HPO), and thiobarbituric acid reactive substances (TBARS). The findings revealed that ECNP effectively delayed discoloration and lipid oxidation, with its efficacy directly linked to the applied dose. Two-way ANOVA confirmed that both ECNP dose and storage time had a significant impact on discoloration and lipid oxidation (p < 0.001), with their interaction indicated that ECNP efficacy depends on both factors. Furthermore, artificial neural network (ANN) models were developed to predict ECNP’s effectiveness. The predictions confirmed that ECNP’s efficacy varies with dosage and storage duration. The ANNs determined that an ECNP dose of 367 mg/kg could maintain the quality of tuna cubes classified as grade A for up to 2.55 days, while a dose of 253 mg/kg could maintain the quality of tuna cubes classified as grade B for 5 days. These results underscore the potential of ECNP as a bio-based preservative, offering a sustainable and viable alternative to synthetic additives for seafood preservation. Additionally, ANN proved to be a valuable tool for rapidly determining the optimal ECNP dose for specific preservation goals. This approach improves cost-effectiveness and enhances practical applicability.