The relationship between optical properties and soluble solid contents of Gong pear for non-destructive internal quality inspection

被引:1
|
作者
Liu, Yande [1 ,2 ]
Huo, Yuxu [1 ,2 ]
Liao, Jun [1 ,2 ]
Lu, Yang [1 ,2 ]
Yang, Shimin [1 ,2 ]
机构
[1] East China Jiaotong Univ, Sch Mechatron & Vehicle Engn, Nanchang 330013, Jiangxi, Peoples R China
[2] East China Jiaotong Univ, Inst Intelligent Mech & Elect Equipment, Nanchang 330013, Peoples R China
基金
中国国家自然科学基金;
关键词
Scattering coefficient; Absorption coefficient; Soluble solids content; Different regions of Gong pear; SCATTERING PROPERTIES; FIRMNESS; ABSORPTION;
D O I
10.1007/s11694-024-02370-8
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
To investigate the relationship between optical properties and soluble solids content (SSC) in different regions of Gong pear. The optical properties of the upper, middle and lower parts of Gong pear were measured by the single integrating sphere system in the range of 500-1100 nm. The differences of absorption coefficient (mu a\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{a}$$\end{document}) spectra and reduced scattering coefficient (mu s '\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{s}<^>{\prime}$$\end{document}) spectra in three regions of Gong pear were analyzed. The differences of mu a\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{a}$$\end{document} and mu s '\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{s}<^>{\prime}$$\end{document} at 670,710, 750, 800 and 980 nm were analyzed. Gong Pear SSC was positively correlated with mu a\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{a}$$\end{document} and mu s '\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{s}<^>{\prime}$$\end{document} in the range of 500-1050 nm.The local model of Gong pear SSC was established based on the mu a\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{a}$$\end{document} spectra and mu s '\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{s}<^>{\prime}$$\end{document} spectra in the upper, middle and lower regions respectively. And the partial least square regression (PLSR) model and support vector regression (SVR) model were established based on the mean mu a\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{a}$$\end{document} spectra, mean mu s '\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{s}<^>{\prime}$$\end{document} spectra and mean mu a\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{a}$$\end{document}+mu s '\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{s}<^>{\prime}$$\end{document} spectra after standard normal variables (SNV) pretreatment. The results showed that the optical properties of the upper, middle and lower sections of Gong pear were less different. Among all established SSC prediction models, the model based on the mean mu a\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{a}$$\end{document} spectra had the best prediction effect. Its correction coefficient of determination (Rc2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${R}_{c}<^>{2}$$\end{document}) and prediction coefficient of determination (RP2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${R}_{P}<^>{2}$$\end{document}) were 0.894 and 0.837, and its correction root mean square error (RMSEC) and prediction root mean square error (RMSEP) were 0.305 and 0.429, respectively. The results showed that soluble solids content mainly affected the absorption characteristics of Gong pear, and the internal quality of Gong pear could be predicted better based on the absorption coefficient.
引用
收藏
页码:2916 / 2925
页数:10
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