Multi-factor fusion models for soluble solid content detection in pear (Pyrus bretschneideri 'Ya') using Vis/NIR online half-transmittance technique
文献类型： 外文期刊
作者： Xia, Yu 1 ; Fan, Shuxiang 1 ; Tian, Xi 1 ; Huang, Wenqian 1 ; Li, Jiangbo 1 ;
作者机构： 1.Beijing Res Ctr Intelligent Equipment Agr, 11 Shuguang Huayuan Rd M, Beijing 100097, Peoples R China
2.Northwest A&F Univ, Coll Mech & Elect Engn, Yangling 712100, Shaanxi, Peoples R China
关键词： Pear; Soluble solids content; Online detection; Parameter fusion; Quality assessment
期刊名称：INFRARED PHYSICS & TECHNOLOGY （ 影响因子：2.638； 五年影响因子：2.581 ）
ISSN： 1350-4495
年卷期： 2020 年 110 卷
页码：
收录情况： SCI
摘要： Development of the online and nondestructive technologies for inspecting and grading the quality of fruit in the postharvest period can improve industry competitiveness and profitability. The effect of fruit temperature, diameter and weight on online evaluation system of soluble solids content (SSC) of 'Ya' pears using visible/near infrared (Vis/NIR) spectroscopy was studied. To establish calibration models, partial least square (PLS) regression and least squares-support vector machine (LS-SVM) were employed in 630-900 nm and two fruit orientations (stem-calyx axis vertical with stem upward (T1), stem-calyx axis horizontal with stem towards belt moving direction (T2)), respectively. After pretreatments of Savitzky-Golay smoothing (SGS), multiplicative scattering correction (MSC), standard normal variate (SNV), and competitive adaptive reweighted sampling (CARS) for effective wavelength (EWs) selection, models were optimized and compared to evaluate calibration strategies. 36 EWs using PLS (r(p) = 0.89, RMSEP = 0.56) with the consideration of diameter (T1) and 34 EWs using LS-SVM (r(p) = 0.90, RMSEP = 0.57) with the consideration of temperature and diameter (T2) were finally selected, respectively. The fusion information of temperature and diameter showed beneficial effect and the best prediction results based on the designed online Vis/NIR half-transmittance system after MSC and 7-SGS for SSC evaluation of pears using LS-SVM, which would be effective to simplify models and promote computing efficiency and further make this proposed nondestructive detection technique have the practical application.
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