{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T11:06:51Z","timestamp":1790593611582,"version":"4.1.0"},"reference-count":158,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T00:00:00Z","timestamp":1790553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Plant Sci."],"abstract":"<jats:p>Tomato quality assessment involves multiple external and internal attributes. Conventional reference methods remain important for accurate characterization but are often destructive, time-consuming, or unsuitable for repeated and online measurements. This review critically examines recent advances in nondestructive sensing technologies for tomato quality evaluation and organizes them according to sensing mechanism. Electromagnetic and optical techniques are assessed for their ability to characterize surface, compositional, spectral, and physiological information, while mechanical and tactile sensing approaches are discussed in relation to firmnes. Electrical and emerging sensors further extend quality assessment toward bioelectrical properties, volatile profiles, and other physicochemical changes. Particular attention is given to information fusion and multimodal sensing, with emphasis on the distinction between homogeneous spectral fusion and heterogeneous integration of physically complementary modalities. Future research should therefore prioritize complementary sensor selection, independent cross-condition validation, calibration transfer, interpretable modeling, system miniaturization, and standardized implementation in sorting, storage, and postharvest monitoring. In general, the transition from isolated laboratory models to transferable and operational quality-monitoring systems remains a central challenge for nondestructive tomato sensing.<\/jats:p>","DOI":"10.3389\/fpls.2026.1931669","type":"journal-article","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T10:53:45Z","timestamp":1790592825000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Recent advancements on innovative technologies and applications for non-destructive monitoring of tomato quality"],"prefix":"10.3389","volume":"17","author":[{"given":"Yirui","family":"Huang","sequence":"first","affiliation":[{"name":"College of Information Engineering, Hebei Province Key Laboratory of Intelligent Sensing and Data Processing for Geoenvironment, Hebei Key Laboratory of Optoelectronic Information and Geo-detection Technology, Intelligent Sensor Network Engineering Research Center of Hebei Province","place":["Shijiazhuang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiahao","family":"Gu","sequence":"additional","affiliation":[{"name":"Medical Business Department, Frist Affiliated Hospital of Hebei Medical University","place":["Shijiazhuang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingyu","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Hebei Province Key Laboratory of Intelligent Sensing and Data Processing for Geoenvironment, Hebei Key Laboratory of Optoelectronic Information and Geo-detection Technology, Intelligent Sensor Network Engineering Research Center of Hebei Province","place":["Shijiazhuang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weifeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Hebei Province Key Laboratory of Intelligent Sensing and Data Processing for Geoenvironment, Hebei Key Laboratory of Optoelectronic Information and Geo-detection Technology, Intelligent Sensor Network Engineering Research Center of Hebei Province","place":["Shijiazhuang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Future Information Technology, Shijiazhuang University","place":["Shijiazhuang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhanmin","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Hebei Province Key Laboratory of Intelligent Sensing and Data Processing for Geoenvironment, Hebei Key Laboratory of Optoelectronic Information and Geo-detection Technology, Intelligent Sensor Network Engineering Research Center of Hebei Province","place":["Shijiazhuang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Hebei Province Key Laboratory of Intelligent Sensing and Data Processing for Geoenvironment, Hebei Key Laboratory of Optoelectronic Information and Geo-detection Technology, Intelligent Sensor Network Engineering Research Center of Hebei Province","place":["Shijiazhuang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,28]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2025.110354","article-title":"A systematic review of explainable artificial intelligence for spectroscopic agricultural quality assessment","volume":"235","author":"Ahmed","year":"2025","journal-title":"Comput. 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