农业机械学报2012，Vol.43Issue(3)：108-112,5.DOI:10.6041/j.issn.1000-1298.2012.03.021
鲜枣可溶性固形物可见/近红外光谱检测建模方法比较
Comparison of Modeling Methods of Fresh Jujube Soluble Solids Measurement by NIR Spectroscopy
摘要
Abstract
Totally 180 samples coining from one orchard were divided into calibration set with 150 samples and prediction set with 30 samples. Field Spec3 spectrometer was used for collecting spectra data of 180 fresh jujube samples separately. Then successive projection algorithm and stepwise regression analysis combined with spectral theory were used to process the spectral data after MSC pretreatment. Characteristic wavelengths of 150 samples in calibration set were selected by using SPA and SRA, and the partial least square (PLS) and LS - SVM methods were used to establish models of the fresh jujube soluble solids with the whole spectrum and characteristic wavelengths selected by using SPA and SRA. At last, the models of MSC - PLS model, MSC - LS - SVM model, the MSC - SPA - PLS model, the MSC -SPA - LS - SVM model, the MSC - SRA - PLS model and the MSC - SRA - LS - SVM model were used to predict the soluble solids of 30 samples in the prediction set. The results showed that the correlation coefficient and the root mean square error of prediction of MSC - PLS model for full band are 0. 887 4 and 1. 088 9 and that is the best. The correlation coefficient and the root mean square error of prediction of MSC - SPA - PLS model and MSC - SRA - PLS model are 0. 7990, 1.407 8 and 0. 8224, 1. 385 1, and they are less precise than the MSC - PLS model. The correlation coefficient and the root mean square error of prediction of MSC - SPA - LS - SVM model are 0. 7% 3 and 1. 145 8, and that is more precise than the MSC - LS - SVM model. The precision of MSC - SRA - LS - SVM model is very low and is not suitable.关键词
鲜枣/可溶性固形物/可见/近红外光谱/无损检测Key words
Fresh jujube/Soluble solids/NIR spectroscopy/Nondestructive detection分类
农业科技引用本文复制引用
张淑娟,张海红,赵艳茹,赵华民..鲜枣可溶性固形物可见/近红外光谱检测建模方法比较[J].农业机械学报,2012,43(3):108-112,5.基金项目
高等学校博士学科点专项科研基金资助项目(20101403110003) （20101403110003）
