山西农业大学学报（自然科学版）2019，Vol.39Issue(5)：106-112,7.DOI:10.13842／j.cnki.issn1671-8151.201812001
基于可见/近红外光谱对不同产地晋虞1 号桃 SSC 含量的检测研究
Detection of soluble solids content (SSC) in Jinyu No .1 Peach by VIS／NIR spectroscopy
摘要
Abstract
[Objectives] T he soluble solids content (SSC) of Jinyu No .1 peach in Shanxi Province was determined by vis-ible ／near infrared(Vis／NIR)spectroscopy in order to establish a simple and effective model with good adaptability , w hich could provide a model reference for the development and utilization of the on-line detection equipment in the fu-ture .[M ethods] Vis／NIR diffuse reflectance spectra of Jinyu No .1 peach from three different production areas were ob-tained ,and different pre-treatment methods were selected to eliminate the influence of objective factors on the original spectrum .T he most effective pre-treatment method was determined as Savitzky-Golaysmoothing combined with multi-variate scattering correction (M SC)method .T he samples were divided at 3∶1 scale by Kennard-Stone algorithm ,among w hich 270 samples were used as a calibration set to establish PLS model and 90 samples were used as a prediction set to assess the performance of the model .In order to simplify the computation and to improve the prediction of the model , Monte Carlo information-free variable elimination (MC-U VE) combined with continuous projection algorithm (SPA ) were used to filter the effective feature wavelengths .T he SSC prediction ability of developed models from a single or mixed production areas were compared between each other based on the partial least square (PLS )algorithm .[Result ] Compared to the models developed with samples from a single or two mixed production areas ,the one developed with the mixed calibration sets from three production areas produced the best prediction ability with the correlation coeffi- cient of prediction(Rp)of 0.949 and the root mean square error (RM SEP)of prediction at 0.652°Brix .[Conclusion]T he results suggested that the model based on mixed samples from three production areas possessed a higher tolerance ,and could improve the SSC prediction accuracy and reduce the influence of the different producing areas on SSC values w hen using visible／near infrared spectroscopy .It provided a theoretical basis for SSC nondestructive testing model to deter-mine the inner quality of Jinyu No .1 peach in Shanxi Province .关键词
晋虞1号桃/可见／近红外光谱/产地/可溶性固形物Key words
Jinyu No .1 peach/Vis／NIR spectroscopy/Origin/Soluble solids content分类
农业科技引用本文复制引用
Zhao Xuting,Zhang Shujuan,Sun Haixia,Xing Shuhai,Li Chengji,Chen Caihong,Gao Tingyao..基于可见/近红外光谱对不同产地晋虞1 号桃 SSC 含量的检测研究[J].山西农业大学学报（自然科学版）,2019,39(5):106-112,7.基金项目
国家自然科学基金(31271973) （31271973）
晋中市科技重点研发计划(Y172007-4) （Y172007-4）
