{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T05:51:03Z","timestamp":1791179463471,"version":"4.1.0"},"reference-count":49,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:00:00Z","timestamp":1785888000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:00:00Z","timestamp":1785888000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Microscopy Res &amp;amp; Technique"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Authentication of high\u2010value honey, particularly from the biodiverse Anzer Valley, relies on melissopalynology to verify botanical origin. However, traditional manual analysis is time\u2010consuming and subject to observer bias. This study developed an automated system for the simultaneous detection and classification of 53 pollen grains belonging to ecologically and apiculturally important taxa distributed in Anzer Valley using advanced deep learning architectures. A novel dataset was constructed from approximately 2095 light microscopy images of the pollen grains, enhanced to 19,860 images via geometric and photometric data augmentation to improve model robustness. Two state\u2010of\u2010the\u2010art object detection models, YOLOv11 and YOLOv12, were trained and compared. The YOLOv11 architecture outperformed YOLOv12, demonstrating superior stability and precision with a mean Average Precision (mAP@0.5) of 93.2% and an F1\u2010score of 0.896. The model showed exceptional generalization on unseen data (recall 90.6%), successfully handling the visual complexity of raw microscopic samples. Misclassifications were minimal, primarily occurring among pollen grains belonging to morphologically similar taxa of Geraniaceae and Fabaceae. These findings demonstrate that YOLOv11 provides a reliable, high\u2010throughput framework for automated pollen analysis. By significantly reducing processing time while maintaining high accuracy, this system offers a scalable tool for the identification of pollen grains, overcoming the bottlenecks of manual microscopy. Beyond its technical contribution, this approach may support more objective, standardized, and scalable regulatory practices for honey authentication and geographical origin verification.<\/jats:p>","DOI":"10.1002\/jemt.70165","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T04:52:58Z","timestamp":1785991978000},"page":"1306-1326","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Automated Detection and Classification of Pollen Grains Using\n                    <scp>YOLO<\/scp>\n                    \u2010Based Deep Learning Models"],"prefix":"10.1002","volume":"89","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-8666-7793","authenticated-orcid":false,"given":"Zeynep","family":"T\u00fcrker","sequence":"first","affiliation":[{"name":"Department of Biology, Faculty of Science Karadeniz Technical University  Trabzon T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6204-5535","authenticated-orcid":false,"given":"Onur","family":"Mutlu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Science Karadeniz Technical University  Trabzon T\u00fcrkiye"},{"name":"Retina R&amp;D Software and Engineering Services Ltd. Trabzon Teknokent  Trabzon T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"U\u011fur","family":"\u015eevik","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Science Karadeniz Technical University  Trabzon T\u00fcrkiye"},{"name":"Retina R&amp;D Software and Engineering Services Ltd. Trabzon Teknokent  Trabzon T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kamil","family":"Co\u015fkun\u00e7elebi","sequence":"additional","affiliation":[{"name":"Department of Biology, Faculty of Science Karadeniz Technical University  Trabzon T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,5]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.LWT.2025.118125"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.7717\/peerj\u2010cs.1463"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.ECOINF.2020.101165"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/NPH.19186;WGROUP:STRING:PUBLICATION"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.1111\/MEC.14840"},{"key":"e_1_2_12_7_1","doi-asserted-by":"publisher","DOI":"10.1139\/gen\u20102015\u20100200"},{"key":"e_1_2_12_8_1","doi-asserted-by":"publisher","DOI":"10.1108\/BFJ\u201004\u20102025\u20100497"},{"key":"e_1_2_12_9_1","unstructured":"Chudyk C. H.Castaneda R.L\u00e9ger et\u00a0al.2015.\u201cDevelopment of an Automatic Pollen Classification System Using Shape Texture and Aperture Features.\u201d1458 65\u201374 https:\/\/doi.org\/10.34894\/VQ1DJA."},{"key":"e_1_2_12_10_1","unstructured":"Daood A. I.2018.\u201cPollen Grains Recognition Based on Computer Vision Methods.\u201dTheses and dissertations.https:\/\/repository.fit.edu\/etd\/764."},{"key":"e_1_2_12_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/NPH.16882"},{"key":"e_1_2_12_12_1","doi-asserted-by":"publisher","DOI":"10.1080\/11035895209453507"},{"key":"e_1_2_12_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263\u2010009\u20100275\u20104"},{"key":"e_1_2_12_14_1","doi-asserted-by":"publisher","DOI":"10.1111\/NPH.19857"},{"key":"e_1_2_12_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-68793-9_36"},{"key":"e_1_2_12_16_1","unstructured":"G\u00fcner A. M.Vural andK.Sorkun.1987.\u201cRize Floras\u0131 Vejetasyonu ve Y\u00f6re Ballar\u0131n\u0131n Polen Analizi.\u201d"},{"key":"e_1_2_12_17_1","doi-asserted-by":"publisher","DOI":"10.1111\/NPH.12848"},{"key":"e_1_2_12_18_1","doi-asserted-by":"crossref","unstructured":"Jegham N. C. Y.Koh M.Abdelatti andA.Hendawi.2024.\u201cYOLO Evolution: A Comprehensive Benchmark and Architectural Review of YOLOv12 YOLO11 and Their Previous Versions.\u201dhttps:\/\/arxiv.org\/pdf\/2411.00201.","DOI":"10.2139\/ssrn.5175639"},{"key":"e_1_2_12_19_1","unstructured":"Jocher G. J.Qiu andA.Chaurasia.2024.\u201cUltralytics YOLO11 [Computer Software].\u201dUltralytics.https:\/\/github.com\/ultralytics\/ultralytics."},{"key":"e_1_2_12_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.JAFR.2025.101665"},{"key":"e_1_2_12_21_1","doi-asserted-by":"publisher","DOI":"10.1021\/ACSAGSCITECH.4C00220"},{"key":"e_1_2_12_22_1","doi-asserted-by":"publisher","DOI":"10.1080\/09500340.2013.868173"},{"key":"e_1_2_12_23_1","doi-asserted-by":"publisher","DOI":"10.1111\/PLB.12251"},{"key":"e_1_2_12_24_1","unstructured":"Khanam R. andM.Hussain.2024.\u201cYOLOv11: An Overview of the Key Architectural Enhancements.\u201dhttps:\/\/arxiv.org\/pdf\/2410.17725."},{"key":"e_1_2_12_25_1","doi-asserted-by":"publisher","DOI":"10.5220\/0013102700003911"},{"key":"e_1_2_12_26_1","doi-asserted-by":"publisher","DOI":"10.1111\/1755\u20100998.12288"},{"key":"e_1_2_12_27_1","doi-asserted-by":"publisher","DOI":"10.1038\/S41598\u2010017\u201017333\u2010X"},{"key":"e_1_2_12_28_1","doi-asserted-by":"publisher","DOI":"10.3390\/S22072690"},{"key":"e_1_2_12_29_1","doi-asserted-by":"publisher","DOI":"10.3390\/S21103526\/S1"},{"key":"e_1_2_12_30_1","doi-asserted-by":"publisher","DOI":"10.3390\/STRESSES2040035"},{"key":"e_1_2_12_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2013.6475049"},{"key":"e_1_2_12_32_1","doi-asserted-by":"publisher","DOI":"10.1111\/2041\u2010210X.13575;CTYPE:STRING:JOURNAL"},{"key":"e_1_2_12_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.FOODCONT.2023.109630"},{"key":"e_1_2_12_34_1","doi-asserted-by":"publisher","DOI":"10.1111\/2041\u2010210X.13917"},{"key":"e_1_2_12_35_1","unstructured":"Rize \u0130l Tar\u0131m ve Orman M\u00fcd\u00fcrl\u00fc\u011f\u00fc.2021.\u201cAnzer Bal\u0131.\u201d(Patent 676). T\u00fcrk Patent.https:\/\/ci.turkpatent.gov.tr\/Files\/GeographicalSigns\/d032bdaf\u2010ec73\u20104769\u2010a8e3\u2010cac9a0cfcacc.pdf."},{"key":"e_1_2_12_36_1","doi-asserted-by":"publisher","DOI":"10.3389\/FDATA.2025.1507036\/BIBTEX"},{"key":"e_1_2_12_37_1","doi-asserted-by":"publisher","DOI":"10.1371\/JOURNAL.PONE.0201807"},{"key":"e_1_2_12_38_1","doi-asserted-by":"publisher","DOI":"10.1371\/JOURNAL.PONE.0229751"},{"key":"e_1_2_12_39_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40537\u2010019\u20100197\u20100"},{"key":"e_1_2_12_40_1","doi-asserted-by":"publisher","DOI":"10.1093\/EE\/NVW159"},{"key":"e_1_2_12_41_1","first-page":"75","article-title":"Pollen Analysis of Rize\u2010Anzer (Turkish) Honey","volume":"30","author":"Sorkun K.","year":"1995","journal-title":"Apiacta\/an International Technical Magazine of Apicultural and Economic Information"},{"key":"e_1_2_12_42_1","volume-title":"Of\u2010\u0130kizdere\u2010Anzer Vadisi Floras\u0131","author":"Terzio\u011flu S.","year":"1994"},{"key":"e_1_2_12_43_1","doi-asserted-by":"crossref","unstructured":"Tian Y. 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