{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T09:21:56Z","timestamp":1787822516047,"version":"build-2784847793"},"reference-count":22,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100009102","name":"Science and Technology Research Project of Jiangxi Provincial Department of Education","doi-asserted-by":"publisher","award":["GJJ2502301"],"award-info":[{"award-number":["GJJ2502301"]}],"id":[{"id":"10.13039\/501100009102","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Construction Plan for Scientific Research Innovation Team of Detection Technology and Intelligent Control, Jingdezhen University"},{"id":[{"id":"https:\/\/ror.org\/012czx379","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Accurate tea bud detection in natural plantation environments is challenged by variable illumination, foliage occlusion, target\u2013background similarity, and dense target distribution. This study proposes YOLO11-ECA, a lightweight detector derived from YOLO11n, to improve the detection performance while reducing the computational demands. The P3\/8 prediction branch and its associated high-resolution feature fusion path are removed, while the P4\/16 and P5\/32 detection scales are retained. Standard adaptive efficient channel attention (ECA) modules are then integrated into the retained feature paths for lightweight channel recalibration. On the validation set, YOLO11-ECA achieved 79.8% precision, 85.1% recall, an 89.2% mAP@0.5, a 52.8% mAP@0.5:0.95, and an F1 score of 82.0%. Relative to YOLO11n, these metrics increased by 1.9, 2.6, 3.1, 0.4, and 2.0 percentage points, respectively, while the parameters and GFLOPs decreased by 7.4% and 28.8%. Scale-specific evaluation showed that P3 removal reduced the APS from 36.0% to 32.4%, whereas adding ECA to the dual-scale architecture increased the APS to 37.0%. On an independent test set, YOLO11-ECA achieved 82.2% precision, an 84.8% mAP@0.5, and an F1 score of 81.0%. The model also reached 86.28 FPS with end-to-end latency of 11.59\u00b10.75 ms under a unified GPU evaluation protocol. These results indicate a favorable balance between tea bud detection performance and computational efficiency.<\/jats:p>","DOI":"10.3390\/s26175398","type":"journal-article","created":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T15:04:32Z","timestamp":1787756672000},"page":"5398","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["YOLO11-ECA: A Lightweight Tea Bud Detection Method for Complex Tea Plantation Environments"],"prefix":"10.3390","volume":"26","author":[{"given":"Zhaodong","family":"Wang","sequence":"first","affiliation":[{"name":"School of Mechanical and Electronic Engineering, Jingdezhen Ceramic University, Jingdezhen 333403, China"},{"name":"Research and Innovation Group of Detection Technology and Intelligent Control, School of Mechanical and Electronic Engineering, Jingdezhen University, Jingdezhen 333400, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinqiang","family":"Liao","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electronic Engineering, Jingdezhen Ceramic University, Jingdezhen 333403, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electronic Engineering, Jingdezhen Ceramic University, Jingdezhen 333403, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"You","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electronic Engineering, Jingdezhen Ceramic University, Jingdezhen 333403, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2183-0324","authenticated-orcid":false,"given":"Wenzhi","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Information Processing, Ghent University, B-9000 Ghent, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Li","sequence":"additional","affiliation":[{"name":"Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,26]]},"reference":[{"key":"ref_1","first-page":"377","article-title":"Researches on Tender Tea Shoots Identification under Natural Conditions","volume":"32","author":"Wei","year":"2012","journal-title":"J. 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