{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T20:18:01Z","timestamp":1790626681392,"version":"4.1.0"},"reference-count":39,"publisher":"Elsevier BV","issue":"2","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T00:00:00Z","timestamp":1758067200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People's Republic of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008582","name":"McGill University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008582","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["202408350068"],"award-info":[{"award-number":["202408350068"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Plant Phenomics"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.plaphe.2025.100110","type":"journal-article","created":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T07:04:21Z","timestamp":1758179061000},"page":"100110","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"title":["Edge computing-based computer vision and deep transfer learning for high-throughput assessment of Aspergillus flavus infection in crop seeds"],"prefix":"10.1016","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7184-7124","authenticated-orcid":false,"given":"Libin","family":"Wu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liangliang","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haiyong","family":"Weng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoping","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongfei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yande","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4212-3968","authenticated-orcid":false,"given":"Dapeng","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.plaphe.2025.100110_bib1","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1146\/annurev-phyto-072910-095221","article-title":"Aspergillus flavus","volume":"49","author":"Amaike","year":"2011","journal-title":"Annu. Rev. Phytopathol."},{"key":"10.1016\/j.plaphe.2025.100110_bib2","doi-asserted-by":"crossref","first-page":"2170","DOI":"10.3389\/fmicb.2016.02170","article-title":"Aflatoxins: a global concern for food safety, human health and their management","volume":"7","author":"Kumar","year":"2017","journal-title":"Front. Microbiol."},{"issue":"3","key":"10.1016\/j.plaphe.2025.100110_bib3","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1007\/s00122-024-04575-3","article-title":"Designing future peanut: the power of genomics-assisted breeding","volume":"137","author":"Raza","year":"2024","journal-title":"Theor. Appl. Genet."},{"key":"10.1016\/j.plaphe.2025.100110_bib4","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhazmat.2020.124155","article-title":"Metabolite profiling identified pipecolic acid as an important component of peanut seed resistance against Aspergillus flavus infection","volume":"404","author":"Sharma","year":"2021","journal-title":"J. Hazard Mater."},{"key":"10.1016\/j.plaphe.2025.100110_bib5","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2023.1226637","article-title":"Peanut genomics and biotechnology in breeding applications","volume":"14","author":"Zhuang","year":"2023","journal-title":"Front. Plant Sci."},{"key":"10.1016\/j.plaphe.2025.100110_bib6","article-title":"Antifungal efficacy of paeonol on Aspergillus flavus and its mode of action on cell walls and cell membranes","volume":"149","author":"Li","year":"2021","journal-title":"LWT (Lebensm.-Wiss. & Technol.)"},{"key":"10.1016\/j.plaphe.2025.100110_bib7","article-title":"Anti-fungal activity of lactic acid bacterial isolates against aflatoxigenic fungi inoculated on peanut kernels","volume":"143","author":"Pradhan","year":"2021","journal-title":"LWT (Lebensm.-Wiss. & Technol.)"},{"key":"10.1016\/j.plaphe.2025.100110_bib8","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1016\/j.lwt.2018.09.001","article-title":"Effect of milling, fermentation or roasting on water activity, fungal growth, and aflatoxin contamination of Bambara groundnut (Vigna subterranea (L.) Verdc)","volume":"98","author":"Olagunju","year":"2018","journal-title":"LWT (Lebensm.-Wiss. & Technol.)"},{"issue":"3","key":"10.1016\/j.plaphe.2025.100110_bib9","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1016\/j.jaip.2016.01.008","article-title":"Exposure and health effects of fungi on humans","volume":"4","author":"Baxi","year":"2016","journal-title":"J. Allergy Clin. Immunol. Pract."},{"key":"10.1016\/j.plaphe.2025.100110_bib10","doi-asserted-by":"crossref","DOI":"10.1016\/j.aiia.2024.06.004","article-title":"Computer vision in smart agriculture and precision farming: techniques and applications","author":"Ghazal","year":"2024","journal-title":"Artificial Intelligence in Agriculture"},{"key":"10.1016\/j.plaphe.2025.100110_bib11","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.compag.2018.08.001","article-title":"Computer vision and artificial intelligence in precision agriculture for grain crops: a systematic review","volume":"153","author":"Patr\u00edcio","year":"2018","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"10.1016\/j.plaphe.2025.100110_bib12","doi-asserted-by":"crossref","first-page":"1485","DOI":"10.1038\/s41467-022-29171-1","article-title":"Programmable black phosphorus image sensor for broadband optoelectronic edge computing","volume":"13","author":"Lee","year":"2022","journal-title":"Nat. Commun."},{"issue":"1","key":"10.1016\/j.plaphe.2025.100110_bib13","doi-asserted-by":"crossref","DOI":"10.1038\/s41928-018-0194-x","article-title":"How we created edge computing","volume":"2","author":"Satyanarayanan","year":"2019","journal-title":"Nature Electronics"},{"key":"10.1016\/j.plaphe.2025.100110_bib14","article-title":"Prediction of health monitoring with deep learning using edge computing","volume":"25","author":"Gupta","year":"2023","journal-title":"Measurement: Sensors"},{"key":"10.1016\/j.plaphe.2025.100110_bib15","doi-asserted-by":"crossref","DOI":"10.1016\/j.jnca.2020.102781","article-title":"A survey on computation offloading modeling for edge computing","volume":"169","author":"Lin","year":"2020","journal-title":"J. Netw. Comput. Appl."},{"issue":"11","key":"10.1016\/j.plaphe.2025.100110_bib16","doi-asserted-by":"crossref","first-page":"682","DOI":"10.3390\/drones7110682","article-title":"Implementation of an edge-computing vision System on reduced-board computers embedded in UAVs for intelligent traffic management","volume":"7","author":"Rosende","year":"2023","journal-title":"Drones"},{"key":"10.1016\/j.plaphe.2025.100110_bib17","doi-asserted-by":"crossref","first-page":"41852","DOI":"10.1109\/ACCESS.2024.3376570","article-title":"Performance analysis of container technologies for computer vision applications on edge devices","volume":"12","author":"Alqaisi","year":"2024","journal-title":"IEEE Access"},{"issue":"11","key":"10.1016\/j.plaphe.2025.100110_bib18","article-title":"Implementation of an edge-computing vision System on reduced-board computers embedded in UAVs for intelligent traffic management","volume":"7","author":"Rosende","year":"2023","journal-title":"Drones"},{"issue":"5","key":"10.1016\/j.plaphe.2025.100110_bib19","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1109\/JIOT.2016.2579198","article-title":"Edge computing: Vision and challenges","volume":"3","author":"Shi","year":"2016","journal-title":"IEEE Internet Things J."},{"issue":"15","key":"10.1016\/j.plaphe.2025.100110_bib20","doi-asserted-by":"crossref","first-page":"5866","DOI":"10.3390\/s22155866","article-title":"Smart Strawberry farming using edge computing and IoT","volume":"22","author":"Cruz","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.plaphe.2025.100110_bib21","doi-asserted-by":"crossref","first-page":"11615","DOI":"10.1109\/ACCESS.2019.2963159","article-title":"mVideo: Edge computing based Mobile video processing systems","volume":"8","author":"Sun","year":"2020","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.plaphe.2025.100110_bib22","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1109\/JIOT.2021.3098051","article-title":"Machine-Learning-Assisted security and privacy provisioning for Edge Computing: a Survey","volume":"9","author":"Singh","year":"2022","journal-title":"IEEE Internet Things J."},{"issue":"1","key":"10.1016\/j.plaphe.2025.100110_bib23","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1186\/s13634-021-00734-6","article-title":"A robot vision navigation method using deep learning in edge computing environment","volume":"2021","author":"Li","year":"2021","journal-title":"EURASIP J. Appl. Signal Process."},{"issue":"1","key":"10.1016\/j.plaphe.2025.100110_bib24","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.dcan.2022.04.032","article-title":"Edge robotics: are we ready? An experimental evaluation of current vision and future directions","volume":"9","author":"Groshev","year":"2023","journal-title":"Digital Commun.Netw."},{"issue":"8","key":"10.1016\/j.plaphe.2025.100110_bib25","doi-asserted-by":"crossref","first-page":"1697","DOI":"10.1109\/JPROC.2019.2915983","article-title":"Edge computing for autonomous driving: opportunities and challenges","volume":"107","author":"Liu","year":"2019","journal-title":"Proc. IEEE"},{"issue":"2","key":"10.1016\/j.plaphe.2025.100110_bib26","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1007\/s13735-022-00227-8","article-title":"Anomaly detection using edge computing in video surveillance system","volume":"11","author":"Patrikar","year":"2022","journal-title":"Int.J. Multimed. Information Retr."},{"key":"10.1016\/j.plaphe.2025.100110_bib27","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.124587","article-title":"Advancing tracking-by-detection with MultiMap: towards occlusion-resilient online multiclass strawberry counting","volume":"255","author":"Zhou","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.plaphe.2025.100110_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.aca.2023.341687","article-title":"Computer vision-assisted smartphone microscope imaging digital immunosensor based on click chemistry-mediated microsphere counting technology for the detection of aflatoxin B1 in peanuts","volume":"1278","author":"Ren","year":"2023","journal-title":"Anal. Chim. Acta"},{"issue":"2","key":"10.1016\/j.plaphe.2025.100110_bib29","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/s12161-023-02548-8","article-title":"Identification of Peanut kernels infected with multiple Aspergillus flavus fungi using line-scan raman hyperspectral imaging","volume":"17","author":"Yang","year":"2024","journal-title":"Food Anal. Methods"},{"key":"10.1016\/j.plaphe.2025.100110_bib30","doi-asserted-by":"crossref","DOI":"10.1016\/j.foodchem.2022.132442","article-title":"Identification of informative spectral ranges for predicting major chemical constituents in corn using NIR spectroscopy","volume":"383","author":"Fatemi","year":"2022","journal-title":"Food Chem."},{"key":"10.1016\/j.plaphe.2025.100110_bib31","doi-asserted-by":"crossref","DOI":"10.1016\/j.microc.2019.104057","article-title":"Non-destructive screening method for detecting the presence of insects in sorghum grains using near infrared spectroscopy and discriminant analysis","volume":"149","author":"Santos","year":"2019","journal-title":"Microchem. J."},{"key":"10.1016\/j.plaphe.2025.100110_bib32","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.biosystemseng.2015.07.010","article-title":"Detection of fungal infection in almond kernels using near-infrared reflectance spectroscopy","volume":"137","author":"Liang","year":"2015","journal-title":"Biosyst. Eng."},{"issue":"12","key":"10.1016\/j.plaphe.2025.100110_bib33","doi-asserted-by":"crossref","first-page":"1421","DOI":"10.1094\/Phyto-84-1421","article-title":"Components of rust resistance in peanut genotypes","volume":"84","author":"Mehan","year":"1994","journal-title":"Phytopathology"},{"key":"10.1016\/j.plaphe.2025.100110_bib34","doi-asserted-by":"crossref","first-page":"2239","DOI":"10.1007\/s00122-020-03594-0","article-title":"High-density SNP map facilitates fine mapping of QTLs and candidate genes discovery for Aspergillus flavus resistance in peanut (Arachis hypogaea)","volume":"133","author":"Khan","year":"2020","journal-title":"Theor. Appl. Genet."},{"issue":"5","key":"10.1016\/j.plaphe.2025.100110_bib35","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1038\/s41588-019-0402-2","article-title":"The genome of cultivated peanut provides insight into legume karyotypes, polyploid evolution and crop domestication","volume":"51","author":"Zhuang","year":"2019","journal-title":"Nat. Genet."},{"key":"10.1016\/j.plaphe.2025.100110_bib36","article-title":"YOLOv11: an overview of the key architectural enhancements","author":"Khanam","year":"2024","journal-title":"arXiv"},{"key":"10.1016\/j.plaphe.2025.100110_bib37","article-title":"CSPNet: a new backbone that can enhance learning capability of CNN","author":"Wang","year":"2019","journal-title":"arXiv"},{"issue":"4","key":"10.1016\/j.plaphe.2025.100110_bib38","doi-asserted-by":"crossref","first-page":"1680","DOI":"10.3390\/make5040083","article-title":"A comprehensive review of yolo architectures in computer vision: from yolov1 to yolov8 and yolo-nas","volume":"5","author":"Terven","year":"2023","journal-title":"Machine learning knowledge extraction"},{"key":"10.1016\/j.plaphe.2025.100110_bib39","series-title":"Computer Vision - ECCV 2018","first-page":"3","article-title":"CBAM: convolutional block attention module","author":"Woo","year":"2018"}],"container-title":["Plant Phenomics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2643651525001165?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2643651525001165?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T08:26:30Z","timestamp":1782289590000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2643651525001165"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":39,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["S2643651525001165"],"URL":"https:\/\/doi.org\/10.1016\/j.plaphe.2025.100110","relation":{},"ISSN":["2643-6515"],"issn-type":[{"value":"2643-6515","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Edge computing-based computer vision and deep transfer learning for high-throughput assessment of Aspergillus flavus infection in crop seeds","name":"articletitle","label":"Article Title"},{"value":"Plant Phenomics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.plaphe.2025.100110","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier B.V. on behalf of Nanjing Agricultural University.","name":"copyright","label":"Copyright"}],"article-number":"100110"}}