Research Article Evaluation of Quality Parameters of Apple Juices Using Near-Infrared Spectroscopy and Chemometrics Katarzyna Wlodarska , 1 Igor Khmelinskii , 2 and Ewa Sikorska 1 1 Faculty of Commodity Science, Pozna´ n University of Economics and Business, al. Niepodleglo´ sci 10, 61-875 Pozna´ n, Poland 2 Universidade do Algarve, FCT, DQB and CEOT, Campus de Gambelas, 8005-139 Faro, Portugal Correspondence should be addressed to Ewa Sikorska; ewa.sikorska@ue.poznan.pl Received 8 March 2018; Revised 12 May 2018; Accepted 26 May 2018; Published 28 June 2018 Academic Editor: Jose S. Camara Copyright © 2018 Katarzyna Włodarska et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Near-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. e optimal spectral variables were chosen using the jack-knife-based method and different variants of the interval PLS (iPLS) method. e 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). e best model for the prediction of SSC (R 2 � 0.881, RMSECV � 0.277 ° Brix, and RE � 2.37%) was obtained for the first-derivative preprocessed spectra and jack-knife variable selection. e 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 . e 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 . e present results show the potential of the NIR spectroscopy for screening the important quality parameters of apple juices. 1. Introduction Over the past years, the application of the near-infrared (NIR) spectroscopy coupled with chemometrics has gained wide acceptance in different fields, including food and ag- ricultural products [1–6]. NIR spectroscopy is based on the absorption of elec- tromagnetic radiation in the range of 12,500–4000cm -1 [2, 7]. e NIR spectra consist of broad overlapping bands arising from overtones and combination tones of the fun- damental vibrations involving C-H, O-H, and N-H chemical bonds. ese bonds are the primary structural components of organic molecules; thus, NIR is very useful for mea- surements of biological and organic systems, including foods. Due to the wealth of chemical information provided by the NIR spectra, they allow simultaneous determination of several constituents and/or of diverse sample properties [4, 7]. One of the main advantages of the NIR technique is its nondestructive character and simple and rapid measure- ments. Different measurement modes enable direct analysis of both liquid and solid samples without any preparation. Due to its advantages, the NIR technique coupled with chemometrics provides a rapid, effective, and cost-saving alternative to the conventional methods in routine, high- throughput analysis of foods. NIR has been used to assess both the properties and concentrations of the food com- ponents, being also a well-established tool for process monitoring. Using NIR for quality control requires chemometric methods to extract useful information out of complex spectra of the products studied [8]. Practical applications usually require development of multivariate calibration, which define the relationships between the measured spectra and the content of the compound or property of interest, obtained by the respective reference methods. Multivariate Hindawi Journal of Spectroscopy Volume 2018, Article ID 5191283, 8 pages https://doi.org/10.1155/2018/5191283