作物学报2012，Vol.38Issue(3)：535-540,6.DOI:10.3724/SP.J.1006.2012.00535
利用花生荚果图像特征识别品种与检验种子
Variety Identification and Seed Test by Peanut Pod Image Characteristics
摘要
Abstract
To verify the feasibility of peanut variety recognition and seed testing by pod image characteristics, we screened 20 peanut varieties mainly released in North peanut regions and collected 50 traits based on pod morphology, colour and texture. We used PCA data optimization, neural networks, support vector machine, and clustering analysis to discuss the varieties identification, origin recognition, DUS characters selecting method and vvarieties clustering process. It has been discovered that the PCA optimization SVM model is better and its identification effect is stable. By this model, the variety recognition rate was above 90% for 20 vvarieties, and the correct origin recognition rate of three origins reached 100%. Additionally, we sorted out some useful traits for seeds DUS test from the 50 features and established the dendrogram of 20 peanut varieties. The results of this study provided some references valuable to the selection of DUS traits, peanuts varieties, origin recognition, and peanut pedigree research.关键词
花生品种识别/主分量分析/人工神经网络/支持向量机/K-均值聚类/DUS测试Key words
Peanuts variety recognition/ Principal component analysis/ Artificial neural network/ Support vector machine/ K-means clustering/ DUS test引用本文复制引用
韩仲志,赵友刚..利用花生荚果图像特征识别品种与检验种子[J].作物学报,2012,38(3):535-540,6.基金项目
本研究由国家农业科技成果转化资金项目(2010GB2C600255),山东省自然科学基金(ZR2009DQ019,ZR2010CM039),山东省科技攻关项目(2009GG10009057)和青岛市科技发展计划项目(11-2-3-20-nsh)资助. （2010GB2C600255）
