{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,30]],"date-time":"2026-08-30T13:09:48Z","timestamp":1788095388405,"version":"build-2803163510"},"reference-count":35,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T00:00:00Z","timestamp":1774051200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The increasing diffusion of plant-based milk alternatives poses new challenges at the intersection of food safety and consumer experience, particularly regarding allergen cross-contamination and beverage performance during preparation. Traditional quality control strategies are typically confined to upstream production stages and are unable to address individualized risks and sensory variability at the point of consumption. In this study, we propose an embedded volatilomic sensing approach that combines metal oxide semiconductor (MOX) sensor arrays with lightweight artificial intelligence algorithms to enable real-time, on-device decision-making. The volatilome of four commercially available plant-based milk beverages (oat, almond, soy, and coconut) was characterized using GC\u2013MS\/SPME as a reference method, while a MOX-based electronic nose provided rapid, non-destructive sensing of volatile fingerprints. Linear Discriminant Analysis demonstrated clear discrimination among beverage types based on their volatile signatures, supporting the use of MOX sensor arrays as functional descriptors of compositional identity and process-related variability. Beyond beverage classification, the proposed framework is designed to support future implementation of (i) screening for anomalous volatilomic patterns potentially compatible with accidental cow\u2019s milk carryover in shared preparation settings and (ii) adaptive tuning of preparation parameters (e.g., foaming-related settings) in smart beverage systems. The results highlight the role of embedded volatilomic intelligence as a unifying layer between personalized risk-aware screening and sensory-oriented process control, paving the way for intelligent food-processing appliances capable of autonomous, real-time adaptation at the point of consumption.<\/jats:p>","DOI":"10.3390\/s26061976","type":"journal-article","created":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T08:47:42Z","timestamp":1774255662000},"page":"1976","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Embedded MOX-Based Volatilomic Sensing for Real-Time Classification of Plant-Based Milk Beverages"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2358-2410","authenticated-orcid":false,"given":"Elisabetta","family":"Poeta","sequence":"first","affiliation":[{"name":"Department of Life Sciences, University of Modena and Reggio Emilia, Via J.F. Kennedy, 17\/i, 42124 Reggio Emilia, RE, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5991-9391","authenticated-orcid":false,"given":"Veronica","family":"Sberveglieri","sequence":"additional","affiliation":[{"name":"Institute of Bioscience and Bioresources (CNR-IBBR), National Research Council URT Reggio Emilia, Via J.F. Kennedy, 17\/i, 42124 Reggio Emilia, RE, Italy"},{"name":"Nano Sensor System s.r.l. (NASYS), Via Alfonso Catalani, 9, 42124 Reggio Emilia, RE, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4621-0658","authenticated-orcid":false,"given":"Estefan\u00eda","family":"N\u00fa\u00f1ez-Carmona","sequence":"additional","affiliation":[{"name":"Institute of Bioscience and Bioresources (CNR-IBBR), National Research Council URT Reggio Emilia, Via J.F. Kennedy, 17\/i, 42124 Reggio Emilia, RE, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111272","DOI":"10.1016\/j.bios.2019.04.040","article-title":"Rapid methods and sensors for milk quality monitoring and spoilage detection","volume":"140","author":"Poghossian","year":"2019","journal-title":"Biosens. Bioelectron."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Poeta, E., N\u00fa\u00f1ez-Carmona, E., and Sberveglieri, V. (2025). A Review: Applications of MOX Sensors from Air Quality Monitoring to Biomedical Diagnosis and Agro-Food Quality Control. J. Sens. 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