{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T01:03:11Z","timestamp":1784682191447,"version":"3.55.0"},"reference-count":29,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100013147","name":"Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region","doi-asserted-by":"publisher","award":["NJZY22351"],"award-info":[{"award-number":["NJZY22351"]}],"id":[{"id":"10.13039\/501100013147","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32201914"],"award-info":[{"award-number":["32201914"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["scijournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pest Management Science"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>BACKGROUND<\/jats:title>\n                    <jats:p>Differentiating between potato common scab, powdery scab, and the physiological disorder of enlarged corky lenticels is challenging due to their similar visual symptoms. To address this, we propose YOLOv8\u2010ST, an enhanced deep learning model that incorporates the Swin Transformer and Triplet Attention modules to effectively distinguish between these visually similar tuber blemishes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>YOLOv8\u2010ST is an enhanced YOLOv8 model with the integration of Triplet Attention and the Swin Transformer, which achieved significant accuracy improvements. Compared to the baseline of YOLOv3, YOLOv5, YOLOv6, and YOLOv8, YOLOv8\u2010ST achieved the highest precision (0.903), recall (0.831), F1\u2010score (0.866), mAP@0.5 (0.931), and mAP@0.5:0.95 (0.616), with strong performance in detecting common scab and powdery scab (both &gt;0.9 at mAP@0.5 or precision). Detection outputs showed higher confidence (e.g., 0.94 for scab), fewer false positives, and no missed lesions, outperforming models prone to misclassification or overlap.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>The YOLOv8\u2010ST model enables fast, accurate, and reliable detection of common scab, powdery scab, and enlarged lenticels on potato tubers. This field\u2010deployable solution supports early disease diagnosis and timely intervention, thus reducing crop losses. The model is available through the mobile app Plant Guardian, enabling growers to identify potato skin blemishes directly in the field, thereby advancing both practical disease management and agricultural AI applications. \u00a9 2025 Society of Chemical Industry.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ps.70424","type":"journal-article","created":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T06:34:58Z","timestamp":1765002898000},"page":"3029-3040","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Rapid detection of common scab, powdery scab, and enlarged lenticels in potato tubers using deep learning"],"prefix":"10.1002","volume":"82","author":[{"given":"Jiale","family":"Lv","sequence":"first","affiliation":[{"name":"Inner Mongolia Potato Engineering and Technology Research Center Inner Mongolia University  Hohhot China"},{"name":"The Inner Mongolia Autonomous Region Institute of Product Quality Inspection  Hohhot China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6715-3998","authenticated-orcid":false,"given":"Teng","family":"Liu","sequence":"additional","affiliation":[{"name":"Peking University Institute of Advanced Agricultural Sciences  Weifang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Wu","sequence":"additional","affiliation":[{"name":"Inner Mongolia Potato Engineering and Technology Research Center Inner Mongolia University  Hohhot China"},{"name":"Key Laboratory of Herbage &amp; Endemic Crop Biology. Ministry of Education Inner Mongolia University  Hohhot China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenpeng","family":"Zhu","sequence":"additional","affiliation":[{"name":"Peking University Institute of Advanced Agricultural Sciences  Weifang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialin","family":"Yu","sequence":"additional","affiliation":[{"name":"Peking University Institute of Advanced Agricultural Sciences  Weifang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruofang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Inner Mongolia Potato Engineering and Technology Research Center Inner Mongolia University  Hohhot China"},{"name":"Key Laboratory of Herbage &amp; Endemic Crop Biology. Ministry of Education Inner Mongolia University  Hohhot China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8783-5814","authenticated-orcid":false,"given":"Utpal","family":"Handique","sequence":"additional","affiliation":[{"name":"Inner Mongolia Potato Engineering and Technology Research Center Inner Mongolia University  Hohhot China"},{"name":"Key Laboratory of Herbage &amp; Endemic Crop Biology. Ministry of Education Inner Mongolia University  Hohhot China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,12,5]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11540-022-09588-3"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1094\/PDIS-01-24-0168-SC"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1094\/PDIS-06-21-1242-PDN"},{"key":"e_1_2_8_5_1","first-page":"2800","article-title":"Status of major diseases and insect pests of potato and pesticide usage in China","volume":"52","author":"Xu J","year":"2019","journal-title":"Sci Agric Sin"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12230-017-9575-3"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12230-008-9019-1"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12230-023-09923-5"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.3390\/agriengineering3020020"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13007-021-00722-9"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-15221-3"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13111936"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpls.2022.868745"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/ps.7102"},{"key":"e_1_2_8_15_1","doi-asserted-by":"crossref","unstructured":"IqbalMAandTalukderKH Detection of potato disease using image segmentation and machine learning. In2020 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET): Chennai India pp. 43\u201347(2020).","DOI":"10.1109\/WiSPNET48689.2020.9198563"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/6114061"},{"key":"e_1_2_8_17_1","article-title":"Automated abnormal potato plant detection system using deep learning models and portable video cameras","volume":"104","author":"Oishi Y","year":"2021","journal-title":"Int J Appl Earth Obs Geoinf"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12870-025-06679-4"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1094\/PHYTO-08-18-0288-R"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-51074-4"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1099\/00207713-16-3-313"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008782309333"},{"key":"e_1_2_8_23_1","unstructured":"TzutalinLI https:\/\/github.com\/tzutalin\/labelImg [accessed 2025]."},{"key":"e_1_2_8_24_1","unstructured":"LiC LiL JiangH WengK GengY LiLet al. 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