{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:50:55Z","timestamp":1786978255120,"version":"build-2736575974"},"reference-count":39,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T00:00:00Z","timestamp":1711065600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["PDCPN 2015\u2010241"],"award-info":[{"award-number":["PDCPN 2015\u2010241"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61473179"],"award-info":[{"award-number":["61473179"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["scijournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Sci Food Agric"],"published-print":{"date-parts":[[2024,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>BACKGROUND<\/jats:title>\n                    <jats:p>Astragalus is a widely used traditional Chinese medicine material that is easily confused due to its quality, price and other factors derived from different origins. This article describes a novel method for the rapid tracing and detection of Astragalus via the joint application of an electronic tongue (ET) and an electronic eye (EE) combined with a lightweight convoluted neural network (CNN)\u2013transformer model. First, ET and EE systems were employed to measure the taste fingerprints and appearance images, respectively, of different Astragalus samples. Three spectral transform methods \u2013 the Markov transition field, short\u2010time Fourier transform and recurrence plot \u2013 were utilized to convert the ET signals into 2D spectrograms. Then, the obtained ET spectrograms were fused with the EE image to obtain multimodal information. A lightweight hybrid model, termed GETNet, was designed to achieve pattern recognition for the Astragalus fusion information. The proposed model employed an improved transformer module and an improved Ghost bottleneck as its backbone network, complementarily utilizing the benefits of CNN and transformer architectures for local and global feature representation. Furthermore, the Ghost bottleneck was further optimized using a channel attention technique, which boosted the model's feature extraction effectiveness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>The experiments indicate that the proposed data fusion strategy based on ET and EE devices has better recognition accuracy than that attained with independent sensing devices.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>The proposed method achieved high precision (99.1%) and recall (99.1%) values, providing a novel approach for rapidly identifying the origin of Astragalus, and it holds great promise for applications involving other types of Chinese herbal medicines. \u00a9 2024 Society of Chemical Industry.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jsfa.13450","type":"journal-article","created":{"date-parts":[[2024,3,9]],"date-time":"2024-03-09T05:55:19Z","timestamp":1709963719000},"page":"5930-5943","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Electronic eye and electronic tongue data fusion combined with a\n                    <scp>GETNet<\/scp>\n                    model for the traceability and detection of Astragalus"],"prefix":"10.1002","volume":"104","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2840-382X","authenticated-orcid":false,"given":"Xinning","family":"Jin","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology Shandong University of Technology  Zibo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiqiang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Shandong University of Technology  Zibo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingyu","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Shandong University of Technology  Zibo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuanzheng","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Shandong University of Technology  Zibo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuerui","family":"Bai","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology Shandong University of Technology  Zibo China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yubin","family":"Lan","sequence":"additional","affiliation":[{"name":"School of Agricultural Engineering and Food Science Shandong University of Technology  Zibo China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,3,22]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.saa.2018.07.033"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.phymed.2019.153155"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.foodcont.2023.110052"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aca.2021.339028"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.20964\/2018.12.45"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/molecules23123362"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.3892\/etm.2016.3733"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.foodchem.2023.138148"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-53210-5"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/pca.3208"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.microc.2023.109190"},{"key":"e_1_2_9_13_1","volume-title":"Data Handling in Science and Technology","author":"Biancolillo A","year":"2019"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.talanta.2018.11.046"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.foodchem.2019.03.080"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.3390\/s19010217"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.measen.2023.100835"},{"key":"e_1_2_9_18_1","unstructured":"HowardAGet al. 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