中国农业科技导报2025，Vol.27Issue(5)：103-112,10.DOI:10.13304/j.nykjdb.2023.0915
黄花菜花蕾的精准识别与分级方法
Accurate Identification and Grading Method for Daylily Flower Buds
摘要
Abstract
Aiming at the problems of complex backgrounds,small individual size and inconsistent grading standards after harvesting of daylily buds in field environment,a recognition and post-harvest grading method for daylily buds was proposed.A database was established based on 1 716 images of daylily buds under various complex conditions such as different lighting,occlusion,and blurriness.The Biformer self-attention mechanism was introduced into the backbone network of the YOLOv5s model to train the dataset,and comparative tests were conducted against various other target detection algorithms.After recognition,a daylily bud grading algorithm was used to obtain the contours of the daylily buds through image processing technology,and geometric calculation techniques were used to measure the length and diameter of the daylily buds for grading.Experimental results showed that theimproved YOLOv5s algorithm significantly increased recognition precisionthe precision,recall rate,and mean average precision(mAP)of improved YOLOv5s algorithm of 94.80%,91.40%,and 96.60%,respectively,in the open field recognition of daylily.The accuracy of the daylily grading algorithm reached to 97.00%,meeting the requirements for daylily grading in production practice and providing reliable support for the intelligent development of the daylily industry.关键词
黄花菜识别/Biformer注意力机制/改进YOLOv5s/大田环境/品质分级Key words
daylily recognition/biformer attention mechanism/improved YOLOv5s/open field environment/quality grading分类
农业科技引用本文复制引用
袁嘉良,连润楠,张吴平..黄花菜花蕾的精准识别与分级方法[J].中国农业科技导报,2025,27(5):103-112,10.基金项目
国家重点研发计划项目(2021YFDI1600301-4). （2021YFDI1600301-4）
