The Effect of Path Length on the Measurement Accuracies of Wine Chemical Parameters by UV, Visible, and Near-Infrared Spectroscopy

被引:4
作者
Molla, Nevse [1 ]
Bakardzhiyski, Ivan [2 ]
Manolova, Yana [1 ]
Bambalov, Valentin [3 ]
Cozzolino, Daniel [4 ]
Antonov, Liudmil [1 ]
机构
[1] Bulgarian Acad Sci, Ctr Phytochem, Inst Organ Chem, Acad G Bonchev Str,Bldg 9, BU-1113 Sofia, Bulgaria
[2] Univ Food Technol Plovdiv, Dept Technol Wine & Beer, 26 Maritza Blvd, Plovdiv 4002, Bulgaria
[3] Agr Univ Plovdiv, Dept Viticulture, 12 Mendeleev Blvd, Plovdiv 4000, Bulgaria
[4] Cent Queensland Univ, Sch Med & Appl Sci, CQIRP, Bruce Highway, North Rockhampton, Qld 4701, Australia
关键词
Path length; Near infrared; UV; Visible; Wine; Phenolic compounds; GEOGRAPHICAL ORIGIN; BULGARIAN; AUTHENTICITY; GRAPES;
D O I
10.1007/s12161-016-0735-8
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
The use of spectral measurements using either UV, visible (VIS), or near-infrared (NIR) spectroscopy to characterize wines or to predict wine chemical composition has been extensively reported. However, little is known about the effect of path length on the UV, VIS, and 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 path length and temperature being one of the most important factors affecting the intensity of the absorptions. In this study, the effect of path length on the standard error of UV, VIS, and NIR calibration models to predict phenolic compounds was evaluated. Nineteen red and 13 white wines were analyzed in the UV, VIS, and NIR regions (200-2500 nm) in transmission mode using two effective path lengths 0.1 and 1 mm. 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 phenolic compounds. These results indicated that path length has an effect on the standard error of cross validation (SECV) absolute values obtained for the PLS calibration models used to predict phenolic compounds in both red and white wines. However, no statistically significant differences were observed (p > 0.05). The practical implication of this study was that the path length of scanning for wines has an effect on the calibration accuracies; however, they are non-statistically different. Main differences were observed in the PCA score plot. Overall, well-defined protocols need to be defined for routine use of these methods in research and by the industry.
引用
收藏
页码:1156 / 1163
页数:8
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