Journal of Innovative Optical Health Sciences, 2014, 7 (6): 1350065, Published Online: Jan. 10, 2019  

Online quantitative analysis of soluble solids contentin navel oranges using visible-near infrared spectroscopy and variable selection methods

Author Affiliations
Institute of Optics-Mechanics-Electronics Technology and Application (OMETA), School of Mechanical and Electronical Engineering East China Jiaotong University Nanchang 330013, P. R. China
Abstract
Variable selection is applied widely for visible-near infrared (Vis-NIR) spectroscopy analysis of internal quality in fruits. Different spectral variable selection methods were compared for online quantitative analysis of soluble solids content (SSC) in navel oranges. Moving window partial least squares (MW-PLS), Monte Carlo uninformative variables elimination (MC-UVE) and wavelet transform (WT) combined with the MC-UVE method were used to select the spectral variables and develop the calibration models of online analysis of SSC in navel oranges. The performances of these methods were compared for modeling the Vis-NIR data sets of navel orange samples. Results show that the WT-MC-UVE methods gave better calibration models with the higher correlation coefficient erT of 0.89 and lower root mean square error of prediction (RMSEP) of 0.54 at 5 fruits per second. It concluded that Vis-NIR spectroscopy coupled with WT-MC-UVE may be a fast and effective tool for online quantitative analysis of SSC in navel oranges.

Ya-nde Liu, Yanrui Zhou, Yuanyuan Pan. Online quantitative analysis of soluble solids contentin navel oranges using visible-near infrared spectroscopy and variable selection methods[J]. Journal of Innovative Optical Health Sciences, 2014, 7(6): 1350065.

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