Prediction model of Populus simonii seedlings based on growth characteristics in China

摘要：

　　In this paper,we originally apply the BP neural network to predict the plant height of Populus simonii seedlings.Firstly,we explore correlation among the section length variables of Populus simonii seedlings in four growth periods by using principal component analysis and hierarchical clustering method,which obtain 5 principal components.In addition,we utilize Fuzzy C-Means Clustering(FCM)to classify the Populus simonii seedlings,and are obviously classified into two subpopulations.Furthermore,we utilize BP neural network to establish seedlings height growth model and aboveground biomass prediction model,respectively.Through numerical experiments,prediction accuracy of the seedling height growth models in four periods reaches about 84.89%.Meanwhile,the prediction accuracies of stem and leaf fresh weight and stem and leaf dry weight are 91.15%and 83.79%,respectively.This paper provides an effective method for studying phenotypic characteristics and predicting the height of Populus simonii seedlings,which supplies a reference for genome-wide association analysis.

作者: Huishuo Ge Xiaoyu Zhang

作者单位: College of Science,Beijing Forestry University,No.35,Qinghua East Road,Beijing 100083,P.R.China

会议类型: 国际会议

会议名称: 2018 International Symposium on Water System Operations(ISWRSO 2018)(2018年水资源系统及调度国际研讨会)

会议地点: 北京

会议语种:英文

页码: 1-8

在线出版日期: 2018-10-12（万方平台首次上网日期，不代表论文的发表时间）