热带作物学报2018，Vol.39Issue(1)：182-188,7.DOI:10.3969/j.issn.1000-2561.2018.01.028
基于近红外光谱技术建立沉香含油量预测模型
Prediction Models of Oil Content of Agarwood Based on Near Infrared Spectroscopy
摘要
Abstract
The spectral data of 64 agarwood samples between the spectrum of 950 nm to 1650 nm were collected using DA7200 NIRS analyzer to estabilish a prediction model of near infrared spectroscopy of agarwood oil content.A regression model was established using the partial least squares (PLS) method,and selecting the best pretreatment method and the optimal number of principal components to set up a model of the near infrared spectra of the oil content.Results showed that the smoothing (S-G) method was best for spectral preprocessing,and when the best optimum principal component number was 7 can achieve the optimal mode.The related coefficient of calibration (RC) and root mean square error of calibration (RMSEC) was 0.9809,0.9589;the related coefficient of validation (RV) and root mean square error of validation (RMSEV) was 0.6974,1.0290.The prediction value has a significant correlation with the measured value,and the prediction accuracy of the model is high,which can meet the requirement of rapid prediction of agarwood quality.关键词
近红外/沉香/含油量/预测模型Key words
near infrared spectroscopy/Aquilaria sinensis/oil content/prediction models分类
农业科技引用本文复制引用
林艳,何紫迪,毛积鹏,蒋开彬,刘天颐,黄少伟..基于近红外光谱技术建立沉香含油量预测模型[J].热带作物学报,2018,39(1):182-188,7.基金项目
国家林业公益性行业科研专项“黎蒴等华南重要乡土树种良种选育”(No.201204303). （No.201204303）
