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BACKGROUND: The steam processing characteristics of chicken are a key factor in the simplicity and versatility of steamed chicken dishes. The aim of this study was to investigate in depth the changes in tenderness and water retention of marinated chicken at different slow steaming endpoint temperatures, and to further explore the effect of the evolution of protein conformations on the water status. RESULTS: The results showed that chicken samples' shear force peaked at 80 °C and decreased rapidly at 90 °C. As the steaming endpoint temperature increased between 50 and 90 °C, T21, T22, moisture content and centrifugal loss decreased, but P21, P22 and myofibril water‐holding capacity showed regular changes. The electrophoretic bands and protein conformation changes showed that protein in marinated chicken underwent different degrees of denaturation, degradation and aggregation. And at 70 °C, with an increase of hydrophobic groups and crosslinking of disulfide bonds as well as an increase in the number of denatured sarcoplasmic proteins, the intermolecular network was enhanced, thus affecting the water retention. CONCLUSION: Water status of chicken meat heated at different steaming temperatures is closely related to the evolution of protein conformations. The present study serves as a robust theoretical foundation for enhancing the quality of steamed chicken products at an industrial scale. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Background: Ultraviolet (UV) irradiation has been widely employed to disinfect food, however, the efficacy of UV irradiation in degrading polycyclic aromatic hydrocarbons (PAHs) in smoked sausages has not been explored. In this article, the UV degradation ability of PAHs in smoked sausages was investigated with different UV irradiation conditions, including different irradiation powers, durations and wavelengths. The effects of UV radiation on the quality of sausages were also evaluated, and potential degradation mechanisms were elucidated. Results: The results showed that the irradiation duration was the primary determinant of PAHs degradation, achieving 84.4% and 84.2% degradation rates at 16 W and 32 W power for 30 min, respectively. Among the three UV wavelengths assessed, 254 nm demonstrated a significantly higher degradation rate for benzo[a]pyrene (BaP), PAH4 and PAHs compared to 365 nm and 310 nm. To further explore the degradation mechanism, UV irradiation was combined with water, 0.1 mol/L hydrogen peroxide (H2O2) and 0.1 mol/L ascorbic acid (vitamin C) coatings. The 0.1 mol/L H2O2 coating exhibited the most pronounced degradation effect, suggesting that the highly reactive oxygen hydroxyl radicals (·OH) generated by UV irradiation played a critical role in initiating redox reactions. Conclusion: This systematic investigation paves the way for developing novel strategies to eliminate PAHs or other organic contaminants from smoked sausages. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Abstract: BACKGROUND: Benzo[a]pyrene (BaP), a potent mutagen and carcinogen, is reported to be present in processed meat products and, in particular, in smoked meat. However, few methods exist for predictive determination of the BaP content of smoked meats such as sausage. In this study, an artificial neural network (ANN) model based on the back‐propagation (BP) algorithm was used to predict the BaP content of smoked sausage. RESULTS: The results showed that the BP network based on the Levenberg–Marquardt algorithm was the best suited for creating a nonlinear map between the input and output parameters. The optimal network structure was 3‐7‐1 and the learning rate was 0.6. This BP‐ANN model allowed for accurate predictions, with the correlation coefficients (R) for the experimentally determined training, validation, test and global data sets being 0.94, 0.96, 0.95 and 0.95 respectively. The validation performance was 0.013, suggesting that the proposed BP‐ANN may be used to predictively detect the BaP content of smoked meat products. CONCLUSION: An effective predictive model was constructed for estimation of the BaP content of smoked sausage using ANN modeling techniques, which shows potential to predict the BaP content in smoked sausage. © 2017 Society of Chemical Industry [ABSTRACT FROM AUTHOR]