Literature DB >> 17386814

Effect of temperature variation on the visible and near infrared spectra of wine and the consequences on the partial least square calibrations developed to measure chemical composition.

D Cozzolino1, L Liu, W U Cynkar, R G Dambergs, L Janik, C B Colby, M Gishen.   

Abstract

Many studies have reported the use of near infrared (NIR) spectroscopy to characterize wines or to predict wine chemical composition. However, little is known about the effect of variation in temperature on the NIR spectrum of wine and the subsequent effect on the performance of calibrations used to measure chemical composition. Several parameters influence the spectra of organic molecules in the NIR region, with temperature being one of the most important factors affecting the vibration intensity and frequency of molecular bonds. Wine is a complex mixture of chemical components (e.g. water, sugars, organic acids, and ethanol), and a simple ethanol and water model solution cannot be used to study the possible effects of temperature variations in the NIR spectrum of wine. Ten red and 10 white wines were scanned in triplicate at six different temperatures (25 degrees C, 30 degrees C, 35 degrees C, 40 degrees C, 45 degrees C and 50 degrees C) in the visible (vis) and NIR regions (400-2500 nm) in a monochromator instrument in transmission mode (1 mm path length). Principal component analysis (PCA) and partial least squares (PLS) regression models were developed using full cross validation (leave-one-out). These models were used to interpret the spectra and to develop calibrations for alcohol, sugars (glucose+fructose) and pH at different temperatures. The results showed that differences in the spectra around 970 nm and 1400 nm, related to O-H bonding were observed for both varieties. Additionally an effect of temperature on the vis region of red wine spectra was observed. The standard error of cross validation (SECV) achieved for the PLS calibration models tended to inverse as the temperature increased. The practical implication of this study it is recommended that the temperature of scanning for wine analysis using a 1 mm path length cuvette should be between 30 degrees C and 35 degrees C.

Entities:  

Year:  2007        PMID: 17386814     DOI: 10.1016/j.aca.2007.01.079

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  6 in total

1.  Characterization of connective tissues using near-infrared spectroscopy and imaging.

Authors:  Isaac O Afara; Rubina Shaikh; Ervin Nippolainen; William Querido; Jari Torniainen; Jaakko K Sarin; Shital Kandel; Nancy Pleshko; Juha Töyräs
Journal:  Nat Protoc       Date:  2021-01-18       Impact factor: 13.491

2.  Grading of Chinese Cantonese Sausage Using Hyperspectral Imaging Combined with Chemometric Methods.

Authors:  Aiping Gong; Susu Zhu; Yong He; Chu Zhang
Journal:  Sensors (Basel)       Date:  2017-07-25       Impact factor: 3.576

3.  Nondestructive monitoring storage quality of apples at different temperatures by near-infrared transmittance spectroscopy.

Authors:  Zhiming Guo; Mingming Wang; Ali Shujat; Jingzhu Wu; Hesham R El-Seedi; Jiyong Shi; Qin Ouyang; Quansheng Chen; Xiaobo Zou
Journal:  Food Sci Nutr       Date:  2020-05-27       Impact factor: 2.863

4.  Near-infrared spectroscopy and machine learning-based technique to predict quality-related parameters in instant tea.

Authors:  Xiaoli Bai; Lei Zhang; Chaoyan Kang; Bingyan Quan; Yu Zheng; Xianglong Zhang; Jia Song; Ting Xia; Min Wang
Journal:  Sci Rep       Date:  2022-03-09       Impact factor: 4.379

5.  Temperature Sensing of Deep Abdominal Region in Mice by Using Over-1000 nm Near-Infrared Luminescence of Rare-Earth-Doped NaYF4 Nanothermometer.

Authors:  Shota Sekiyama; Masakazu Umezawa; Shuhei Kuraoka; Takuji Ube; Masao Kamimura; Kohei Soga
Journal:  Sci Rep       Date:  2018-11-19       Impact factor: 4.379

6.  Using Raman Spectroscopy as a Fast Tool to Classify and Analyze Bulgarian Wines-A Feasibility Study.

Authors:  Vera Deneva; Ivan Bakardzhiyski; Krasimir Bambalov; Daniela Antonova; Diana Tsobanova; Valentin Bambalov; Daniel Cozzolino; Liudmil Antonov
Journal:  Molecules       Date:  2019-12-31       Impact factor: 4.411

  6 in total

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