食品与机械2016，Vol.32Issue(11)：122-125,211,5.DOI:10.13652/j.issn.1003-5788.2016.11.027
基于高光谱技术的马铃薯外部品质检测
Detection of potato external qual ity based on hyperspectral technology
摘要
Abstract
In order to detect the external quality of potato quickly,the hyperspectral imaging technology was used.Potato with germination and other three kinds of common defects were studied.The partial least-squares discriminant model were built after different pretreat-ment methods for spectral data processing.The results showed that pretreatment method of SNV was the best.1 3 and 9 feature bands were selected after using successive projections algorithm (SPA)and weighted weight method (WWM)for spectral data preprocessed. The support vector machine (SVM)discriminant model were estab-lished for both SPA and WWM.Our results also showed that the two methods to predict the set of discriminant accuracy reached 100%. WWM-SVM discriminant model of calibration set of cross validation rate was 99.5%,higher than that of the SPA-SVM discriminant model.The study demonstrated the feasibility of using hyperspectral imaging technology combined with WWM-SVM and SPA-SVM for potato external quality grading.关键词
高光谱成像技术/马铃薯/连续投影算法/加权权重法/支持向量机Key words
hyperspectral imaging technology/potato/successive projection algorithm/weighted weight method/support vector ma-chine引用本文复制引用
邓建猛,王红军,黎邹邹,黎源鸿..基于高光谱技术的马铃薯外部品质检测[J].食品与机械,2016,32(11):122-125,211,5.基金项目
广东省科技计划项目(编号:2016A010102013) （编号:2016A010102013）
