With the increasing demand for high-quality, healthy, and nutritious food, hairtails have good potential for development in both domestic and international markets. In particular, Zhoushan hairtail is known as one of the best-tasting hairtail in the world for its unique composition and flavor. However, as a perishable food, the quality and safety of hairtails are susceptible to temperature and storage time. Therefore, the management of storage conditions and the prediction of quality changes in hairtails have become particularly important. In this study, Zhoushan hairtail is selected as an experimental subject, and its quality is assessed by collecting the physicochemical characteristics of hairtail at four different temperatures (−7 °C, −13 °C, −18 °C, and −23 °C) over time. Combined with the K-Means++ algorithm, we have constructed a hierarchy of hairtail quality and predicted its quality using the ETSFormer model. Through the validation of the self-constructed data set, our model has achieved good results in predicting the low, medium, and high quality of hairtails, with F1 values of 92.44%, 95.10%, and 98.01%, respectively. The model provides a theoretical basis for the scientific storage and quality regulation of Zhoushan hairtail.
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