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 (r) 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.
Highlights
Visible-near infrared (Vis-NIR) spectroscopy is a rapid, accurate and nondestructive technique, which is widely used in the analysis of internal quality of fruits
By calculation and comparison of calibration models and the results in Shao and Zhuang,[22] the simplest db[1] waveletlter and 5 scale decomposition was adopted in the study
Variable selection methods including Moving window partial least squares (MW-PLS) and Monte Carlo uninformative variables elimination (MC-uninformative variables elimination (UVE)) were proposed for simplifying calibration models for online quantitative analysis of solids content (SSC) by Vis-NIR
Summary
Visible-near infrared (Vis-NIR) spectroscopy is a rapid, accurate and nondestructive technique, which is widely used in the analysis of internal quality of fruits. Faster and more accurate analysis of the soluble solids content (SSC) in fruits is very important to meet consumer demand. The very simple technology, which is based on re°ectance. This is an Open Access article published by World Scientic Publishing Company. Pan model measurement, has been available for online fruit grading since 1989. It has been well established for internal quality evaluation of fruits.[1,2]
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