Measurement of quality parameters of sugar beet juices using near-infrared spectroscopy and chemometrics. (April 2020)

• Record Type: Journal Article
• Authors: Bahrami, Mohammad Erfan; Honarvar, Masoud; Ansari, Keivan; Jamshidi, Bahareh
• Is Part Of: Journal of food engineering. Volume 271(2020)
• Publication Date: 2020-04
• Subjects: Near-infrared spectroscopy -- Sugar beet juices -- Brix -- Partial least squares regression; SBJ Sugar beet juice; Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Analyse -- Périodiques; Aliments -- Recherche -- Périodiques; 664.005
• DOI: 10.1016/j.jfoodeng.2019.109775
• Languages: English
• ISSNs: 0260-8774

Abstract

Abstract: Near-infrared transmittance spectroscopy combined with multivariate chemometric was investigated in the present work to predict the Polarization (Pol), soluble solids content (°brix), sucrose concentration and pH value of raw, thin and thick sugar beet juices (SBJs). All samples were scanned to obtained spectral information in the wavelength range of 860–1800 nm. The impacts of various pre-processing and spectra treatment methods, such as standard normal variate transformation (SNV), Moving Average (MA) and area normalization (AN) were also investigated. Partial least squares (PLS) regression was introduced to develop the calibration model relating quality parameter values to spectral data. Accordingly, the results show that the PLS models were acceptable for predicting the pol (R 2 = 0.969), °brix (R 2 = 0.984), sucrose (R 2 = 0.921) and slightly pH value (R 2 = 0.671) in SBJ samples. Results suggest that the near-infrared spectroscopy coupled with the PLS regression method can become a useable and fast tool for evaluation of quality parameters in SBJs. Highlights: Quality parameters of sugar beet juices have been measured using NIR spectroscopy. The PLS regression predicts pol, brix and sucrose with high accuracy. SNV, AN and MA pre-processing methods have been tested to improve the models. NIR spectroscopy can be proposed as a rapid technique for beet juices analysis.