食品与机械2017，Vol.33Issue(3)：51-54,4.DOI:10.13652/j.issn.1003-5788.2017.03.011
基于高光谱技术的柑橘不同部位糖度预测模型研究
Research on the detection model of sugar content in different position of citrus based on the hyperspectral technology
摘要
Abstract
Hyperspectral techniques were used to study the sugar content of different parts of citrus,and the sugar content detection models with hyperspectral information of calyx,stem and equator part were established respectively.The results showed that the model established by calyx was better than that of stem and equator.The detection models of partial least squares regression (PLSR),principal component regression (PCR),and stepwise multivariate linear regression (SMLR) were established respectively,and the results of these three models were close.The PLSR model was found to the best among them,after Norris derivative pretreatment methods were applied,the prediction correlation coefficient (rpre) and the root mean square error of prediction (RMSEP) were 0.950 and 0.636 °Brix.This result inclined that it was feasible to use the hyperspectral technology to detect the sugar content in different parts.The study indicated that the calyx part could be the prior choice for the sugar content detection site in the citrus quality testing,and the conclusion has great significance for the way of citrus place in the actual production.Moreover,the PLSR method was used to establish the model of hyperspectral information and average sugar content in calyx,stem and equator part.The highest prediction rpre and RMSEP of models was in the calyx and only to be 0.913 and 0.621 °Brix,which was not excellent enough.Therefore,it was limited to predict the citrus average sugar content with the hyperspectral information of a certain part.关键词
高光谱技术/柑橘/糖度预测模型/无损检测Key words
hyperspectral technology/citrus/soluble solids content/nondestructive testing引用本文复制引用
介邓飞,杨杰,彭雅欣,连裕翔,张登..基于高光谱技术的柑橘不同部位糖度预测模型研究[J].食品与机械,2017,33(3):51-54,4.基金项目
现代农业(柑橘)产业技术体系建设专项资金项目(编号:CARS-27) （柑橘）
中央高校基本科研业务费资助项目(编号:2662015PY078) （编号:2662015PY078）
国家级大学生创新项目(编号:201610504057) （编号:201610504057）
