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 RR 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.