Linear and nonlinear multivariate regressions for determination sugar content of intact Gannan navel orange by Vis-NIR diffuse reflectance spectroscopy

Linear and nonlinear multivariate regressions were implemented to estimate sugar content of intact Gannan navel orange based on Vis-NIR diffuse reflectance spectroscopy in the wavelength range of 450-1750 nm. Four pre-processing methods, including average smoothing, multiplicative scatter correction (MSC), first and second derivatives, were applied to improve the predictive ability of the models. The models were developed by MLR, PCR, PLS, Poly-PLS and Spline-PLS with MSC pretreatment. Except MLR, the predictive results were insignificant among PCR, PLS, Poly-PLS and Spline-PLS by analysis of variance test at 5% level. The Spline-PLS model was superior to others with R of 0.87, RMSEP of 0.47^@?Brix and SDR=2.34. The results illustrated Spline-PLS could be applied to deal with nonlinear problem, and Vis-NIR spectroscopy in combination with it, could determine sugar content of intact Gannan navel orange precisely.

[1]  M. M. Ferreira,et al.  Simultaneously calibrating solids, sugars and acidity of tomato products using PLS2 and NIR spectroscopy. , 2007, Analytica chimica acta.

[2]  Yibin Ying,et al.  FOURIER TRANSFORM NEAR-INFRARED DETERMINATION OF TOTAL SOLUBLE SOLIDS AND AVAILABLE ACID IN INTACT PEACHES , 2005 .

[3]  Yibin Ying,et al.  Experiments on predicting sugar content in apples by FT-NIR Technique ☆ , 2007 .

[4]  Roman M. Balabin,et al.  Comparison of linear and nonlinear calibration models based on near infrared (NIR) spectroscopy data for gasoline properties prediction , 2007 .

[5]  R. Lu.  PREDICTING FIRMNESS AND SUGAR CONTENT OF SWEET CHERRIES USING NEAR–INFRARED DIFFUSE REFLECTANCE SPECTROSCOPY , 2001 .

[6]  S. Wold,et al.  Nonlinear PLS modeling , 1989 .

[7]  Bart Nicolai,et al.  Kernel PLS regression on wavelet transformed NIR spectra for prediction of sugar content of apple , 2007 .

[8]  S. Kawano,et al.  Firmness, dry-matter and soluble-solids assessment of postharvest kiwifruit by NIR spectroscopy , 1998 .

[9]  Giovanni Attolico,et al.  Non-destructive grading of peaches by near-infrared spectrometry , 2004 .

[10]  Z. Schmilovitch,et al.  Determination of mango physiological indices by near-infrared spectrometry , 2000 .

[11]  A. Peirs,et al.  Effect of biological variability on the robustness of NIR models for soluble solids content of apples , 2003 .

[12]  Yibin Ying,et al.  RAPID DETERMINATION OF MATURITY IN APPLE USING OUTLIER DETECTION AND CALIBRATION MODEL OPTIMIZATION , 2006 .

[13]  J. Roger,et al.  Application of LS-SVM to non-linear phenomena in NIR spectroscopy: development of a robust and portable sensor for acidity prediction in grapes , 2004 .

[14]  In-Beum Lee,et al.  A novel multivariate regression approach based on kernel partial least squares with orthogonal signal correction , 2005 .

[15]  J. Abbott,et al.  NEAR-INFRARED DIFFUSE REFLECTANCE FOR QUANTITATIVE AND QUALITATIVE MEASUREMENT OF SOLUBLE SOLIDS AND FIRMNESS OF DELICIOUS AND GALA APPLES , 2003 .

[16]  S. Wold.  Nonlinear partial least squares modelling II. Spline inner relation , 1992 .

[17]  V. Mcglone,et al.  Vis/NIR estimation at harvest of pre- and post-storage quality indices for 'Royal Gala' apple , 2002 .

[18]  Renfu Lu,et al.  A NEAR–INFRARED SENSING TECHNIQUE FOR MEASURING INTERNAL QUALITY OF APPLE FRUIT , 2002 .