基于多元统计分析的小麦籽粒分类方法研究

Research on Wheat Grain Classification Based on Multivariate Statistical Analysis

小麦籽粒是培育优良品种的基础,提高小麦籽粒识别准确率可有效提高育种效率,提高粮食产量。因此,提出了一种基于多元统计分析的小麦籽粒分类方法,以提高小麦籽粒识别准确率。该方法以3种不同品种小麦的籽粒数为数据集,分别利用主成分分析法(Principal Component Analysis,PCA)和谱系聚类法对数据集进行降维、分类,实现对3种不同品种小麦籽粒的分类。

Wheat grain is the basis of breeding excellent varieties.Improving the accuracy of wheat grain identification can effectively improve the breeding efficiency and increase grain yield.Therefore,this paper proposed a wheat grain classification method based on multivariate statistical analysis to improve the accuracy of wheat grain recognition.In this method,the grain number of three different varieties of wheat was used as the data set,and the Principal Component Analysis(PCA)method and pedigree clustering method were used to reduce the dimension and classify the data set,which realized the classification of wheat grain.