{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T04:22:22Z","timestamp":1787458942894,"version":"build-2736575974"},"reference-count":42,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62541312"],"award-info":[{"award-number":["62541312"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"award":["62541312"],"award-info":[{"award-number":["62541312"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006407","name":"Natural Science Foundation of Henan Province","doi-asserted-by":"crossref","award":["252300421868"],"award-info":[{"award-number":["252300421868"]}],"id":[{"id":"10.13039\/501100006407","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100013066","name":"Key Scientific Research Project of Colleges and Universities in Henan Province","doi-asserted-by":"crossref","award":["25A520019"],"award-info":[{"award-number":["25A520019"]}],"id":[{"id":"10.13039\/501100013066","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Foods"],"abstract":"<jats:p>Wheat flour transportation involves extended transit periods, which present considerable challenges for safety risk oversight. Therefore, it is essential to develop an efficient anomaly detection method to support risk assessment during this stage. However, existing anomaly detection methods often neglect the coupling effects across different time scales and the spatial clustering of hazard factors. To address this limitation, we propose a multi-scale spatial\u2013temporal graph model-based unsupervised anomaly detection framework (MSTUAD), which can simultaneously capture the spatial\u2013temporal correlations between importance and hazard factors across multiple time scales. Specifically, feature maps are first constructed for each hazard factor within a given time window to represent coupling effects. Secondly, a multi-scale spatial\u2013temporal graph model is designed to extract spatial\u2013temporal characteristics from these feature maps. Finally, a reconstruction model based on a variational autoencoder learns latent representations of spatial\u2013temporal features of hazard factors, thereby capturing the intrinsic characteristics of normal wheat flour. Experimental validation on the wheat flour transportation hazard factor dataset and three public industrial datasets demonstrates that MSTUAD significantly outperforms state-of-the-art anomaly detection methods, achieving an average F1-score greater than 84.55%. This approach provides valuable decision support and technical guidance for relevant regulatory authorities.<\/jats:p>","DOI":"10.3390\/foods15162934","type":"journal-article","created":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T08:14:01Z","timestamp":1787300041000},"page":"2934","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-Scale Spatial\u2013Temporal Graph Model for Unsupervised Anomaly Detection in the Wheat Flour Transportation Process"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4086-4132","authenticated-orcid":false,"given":"Wanbao","family":"Sheng","sequence":"first","affiliation":[{"name":"College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huawei","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenqiang","family":"Pi","sequence":"additional","affiliation":[{"name":"Henan Zhongyu Port and Shipping Construction Engineering Co., Ltd., Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2347-2225","authenticated-orcid":false,"given":"Zhen","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Like","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"104725","DOI":"10.1016\/j.tifs.2024.104725","article-title":"Mitigating toxic metals contamination in foods: Bridging knowledge gaps for addressing food safety","volume":"153","author":"Srivastava","year":"2024","journal-title":"Trends. 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