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Although the monitoring system has been widely used, the actual monitoring task still needs more manpower to complete. This paper takes yolov5l model and deep sort algorithm as the basic framework to identify and track the staff in kitchen environment. We apply a relation construction with detected items and people, then label the relation corresponding to behaviors violate the regulations of kitchen, such as the staff did not wear mask or hat. We train our model and the experimental results show that the model can correctly identify the inappropriate behaviors of staff. The model achieves the time-constrained accuracy of 95.32% in identifying whether the staff wear a hat or not, and the time-constrained accuracy of 96.32% in identifying whether the staff wear mask correctly. The result shows that the proposed model could fulfil monitoring task in this kitchen environment.

Millet Huangjiu is a national alcoholic beverage in China. The quality of Chinese millet Huangjiu is significantly influenced by the protein components in the raw materials of millet. Therefore, in this study, the impact of different protein components on the quality of millet Huangjiu was investigated by adding exogenous proteins glutelin and albumin either individually or in combination. The study commenced with the determination of the oenological parameters of different millet Huangjiu samples, followed by the assessment of free amino acids and organic acids. In addition, the volatile profiles of millet Huangjiu were characterized by employing HS-SPME-GC/MS. Finally, a sensory evaluation was conducted to evaluate the overall aroma profiles of millet Huangjiu. The results showed that adding glutelin significantly increased the contents of total soluble solids, amino acid nitrogen, and ethanol in millet Huangjiu by 32.2%, 41.5%, and 17.7%, respectively. Furthermore, the fortification of the fermentation substrate with glutelin protein was found to significantly enhance the umami (aspartic and glutamic acids) and sweet-tasting (alanine and proline) amino acids in the final product. Gas chromatography-quadrupole mass spectrometry coupled with multivariate statistical analysis revealed distinct impacts of protein composition on the volatile organic compound (VOC) profiles of millet Huangjiu. Excessive glutelin led to an over-accumulation of alcohol aroma, while the addition of albumin protein proved to be a viable approach for enhancing the ester and fruity fragrances. Sensory analysis suggested that the proper amount of protein fortification using a Glu + Alb combination could enhance the sensory attributes of millet Huangjiu while maintaining its unique flavor characteristics. These findings suggest that reasonable adjustment of the glutelin and albumin contents in millet could effectively regulate the chemical composition and improve the sensory quality of millet Huangjiu.

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The storage environment can significantly impact paddy quality, which is vital to human health. Changes in storage can cause growth of fungi that affects grain quality. This study analyzed grain storage monitoring data from over 20 regions and found that five factors are essential in predicting quality changes during storage. The study combined these factors with the FEDformer (Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting) model and k-medoids algorithm to construct a paddy quality change prediction model and a grading evaluation model, which showed the highest accuracy and lowest error in predicting quality changes during paddy storage. The results emphasize the need for monitoring and controlling the storage environment to preserve grain quality and ensure food safety.