Wlodarska, KatarzynaKhmelinskii, IgorSikorska, Ewa2018-12-072018-12-0720182314-49202314-4939http://hdl.handle.net/10400.1/11963Near-infrared (NIR) spectra were recorded for commercial apple juices. Analysis of these spectra using partial least squares (PLS) regression revealed quantitative relations between the spectra and quality- and taste-related properties of juices: soluble solids content (SSC), titratable acidity (TA), and the ratio of soluble solids content to titratable acidity (SSC/TA). Various spectral preprocessing methods were used for model optimization. The optimal spectral variables were chosen using the jack-knife-based method and different variants of the interval PLS (iPLS) method. The models were cross-validated and evaluated based on the determination coefficients (R-2), root-mean-square error of cross-validation (RMSECV), and relative error (RE). The best model for the prediction of SSC (R-2 = 0.881, RMSECV = 0.277 degrees Brix, and RE = 2.37%) was obtained for the first-derivative preprocessed spectra and jack-knife variable selection. The optimal model for TA (R-2 = 0.761, RMSECV = 0.239 g/L, and RE = 4.55%) was obtained for smoothed spectra in the range of 6224-5350 cm(-1). The best model for the SSC/TA (R-2 = 0.843, RMSECV = 0.113, and RE = 5.04%) was obtained for the spectra without preprocessing in the range of 6224-5350 cm(-1). The present results show the potential of the NIR spectroscopy for screening the important quality parameters of apple juices.engSoluble solids contentFt-nir spectroscopyLeast-squares regressionReflectance spectroscopyVariable selectionFourier-TransformFruitModelsFoodBeveragesjournal article10.1155/2018/5191283