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Comparison and Optimization of Models for Determination of Sugar Content in Pear by Portable Vis-NIR Spectroscopy Coupled with Wavelength Selection Algorithm

文献类型： 外文期刊

作者： Li, Jiangbo 1 ; Wang, Qingyan 1 ; Xu, Lu 1 ; Tian, Xi 1 ; Xia, Yu 1 ; Fan, Shuxiang 1 ;

作者机构： 1.Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

2.Shihezi Univ, Coll Mech & Elect Engn, Shihezi 832003, Peoples R China

关键词： Portable detection; Comparison and optimization of models; Sugar content; Pear; Wavelength selection

期刊名称：FOOD ANALYTICAL METHODS （ 影响因子：3.366； 五年影响因子：3.07 ）

ISSN： 1936-9751

年卷期： 2019 年 12 卷 1 期

页码：

收录情况： SCI

摘要： The portable device could help to obtain a complete follow-up of fruit quality in orchards and during post-harvest. Thus, it is an important step to develop portable and non-destructive technology for current and future research in fruit. In this study, the ability of portable visible-near infrared (Vis-NIR) spectroscopy to non-invasively determine sugar content in pear was studied. Partial least square regression (PLSR) was applied to establish calibration models based on the spectral signatures of three regions (550-1050, 650-950, 750-1050nm) and four types of data sets (Set-I, Set-II, Set-III, and Set-IV), respectively, and the performance of models was compared to determine the optimal spectral calibration strategy. The spectral region of 650-950nm was proved to be much better compared with other two spectral regions. Competitive adaptive reweighted sampling (CARS) algorithm was used to reduce redundancy and collinearity of the original spectral data based on the optimal spectral region for selecting the most important wavelengths. The CARS-PLSR was identified as the most effective method to calibrate the prediction models for sugar content determination, resulting in good coefficient of determination for prediction (RP2) of 0.85-0.92 and root mean square error of prediction (RMSEP) of 0.27-0.20 for four types of data sets, respectively. The overall results show that the portable Vis-NIR spectroscopy is a promising tool for the non-destructive on-site evaluation of sugar content in pear, as well as affording the additional advantage of low cost.

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