Monitoring multicomponent quality traits in tomato juice using portable mid-infrared (MIR) spectroscopy and multivariate analysis. (August 2016)

• Record Type: Journal Article
• Authors: Ayvaz, Huseyin; Sierra-Cadavid, Andrea; Aykas, Didem P.; Mulqueeney, Brett; Sullivan, Scott; Rodriguez-Saona, Luis E.
• Is Part Of: Food control. Volume 66(2016:Aug.)
• Page Start: 79
• Page End: 86
• Publication Date: 2016-08
• Subjects: Tomato -- FT-IR -- Portable spectrometer -- PLSR -- Quality -- Rheological properties; cSt centistokes -- FT-IR Fourier transform mid-infrared spectroscopy -- HPLC high performance liquid chromatography -- JB juice Bostwick -- PLSR partial least squares regression -- PBB predicted paste Bostwick -- SECV standard error of cross validation -- SEP standard error of prediction -- rCV correlation coefficient of cross validation -- rpred correlation coefficient of prediction for the validation set; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2016.01.031
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: In this study, a novel portable infrared spectrometer was evaluated for rapid and simultaneous determination of glucose, fructose, total reducing sugars, soluble solids (°Brix), serum viscosity, Bostwick consistency, predicted paste Bostwick value and pH. A total of 350 hot-break juices from two consecutive years (2013 and 2014) including 66 different varieties grown in 6 counties of California, USA, were used in this study. Duplicate spectra for each tomato juice were collected using the transmission accessory of the portable infrared spectrometer at 50 μm fixed path length. Samples were randomly divided into calibration (n = 280) and external validation (n = 70) sets and partial least squares (PLS) regression was used to develop calibration models to predict all the variables (quality traits) in the validation samples based on the tomato juice spectral data (rpred > 0.82). Overall, our validated chemometric models allowed rapidly (∼2 min) predicting all the quality traits in tomato juice samples with no sample preparation. Highlights: A novel portable FT-IR spectrometer was used in this study. Total of 350 hot-break juices from 2013 to 2014 were utilized. PLS models were developed and validated for tomato juice quality parameters. Models rapidly predict quality traits in tomato juice with no sample preparation.