With the enhancement of consumers’ food safety awareness, consumers have become more stringent on meat quality. This study constructs an intelligent dynamic prediction model based on knowledge rules and integrates flexible humidity sensors into the non-destructive monitoring of the Internet of Things to provide real-time feedback and dynamic adjustments for the chilled chicken cold chain. The optimized sensing equipment can be attached to the inside of the packaging to deal with various abnormal situations during the cold chain, effectively improving the packaging effect. Through correlation analysis of collected data and knowledge rule extraction of critical factors in the cold chain, the established quality evaluation and prediction model achieved detailed chilled chicken quality level classification and intelligent quality prediction. The obtained results show that the accuracy of the prediction model is higher than 90.5%, and all the regression coefficients are close to 1.00. The relevant personnel (workers and cold chain managers) were invited to participate in the performance analysis and optimization suggestion to improve the applicability of the established prediction model. The optimized model can provide a more efficient theoretical reference for timely decision-making and further e-commerce management.

Omega-3 polyunsaturated fatty acids (n-3 PUFAs) enriched eggs are popular for their enrichment of PUFAs, but their freshness and quality are prone to decline with time, particularly if storage conditions are not well maintained. Home storage is the last but a neglected important tach in eggs supply chain, but few studies are available on the egg storage in the home stage. This study aimed to evaluate the internal quality change of both n-3 PUFAs enriched and conventional eggs by simulating eggs stored at consumers’ home in refrigeration and under room temperature. The egg quality indices (Haugh unit, yolk index, weight, and albumen pH) were adopted and analyzed for both storage conditions. Wireless sensor network (WSN) was used for real-time monitoring of the temperature and humidity during storage. The results showed that temperature, humidity and time of storage all have an influence on the freshness of both n-3 PUFAs enriched and conventional eggs and there is no significant difference happened to n-3 PUFAs enriched eggs and conventional eggs. Refrigeration can decelerate the quality deterioration of both n-3 PUFAs enriched and conventional eggs and consumers should be educated about how to maintain the internal quality of eggs during home storage.

The fractional population diffusion model is crucial for pest prevention. This paper presents an adaptive hierarchical collocation method for solving this model, enhancing the efficiency of algorithms based on Low-Complexity Shannon-Cosine wavelet derived from combinatorial identity theory. This function, an improvement over previous constructs, mitigates the need for iterative computation of parameters and boasts advantages like interpolation, symmetry, and compact support. The method’s extension to other time-fractional partial differential equations (PDEs) is also possible. The algorithm’s complexity analysis illustrates the concise function’s efficiency advantage over the original expression when solving time-fractional PDEs. Comparatively, the method exhibits superior numerical performance to alternative wavelet spectral methods like the Shannon–Gabor wavelet.