Rapid analysis of sugars in fruit juices by FT-NIR spectroscopy

A simple analytical procedure using FT-NIR and multivariate techniques for the rapid determination of individual sugars in fruit juices was evaluated. Different NIR detection devices and sample preparation methods were tested by using model solutions to determine their analytical performance. Aqueou...

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Bibliographic Details
Published in:Carbohydrate research 2001-11, Vol.336 (1), p.63-74
Main Authors: Rodriguez-Saona, Luis E., Fry, Fredrick S., McLaughlin, Michael A., Calvey, Elizabeth M.
Format: Article
Language:English
Subjects:
Beverages - analysis
Beverages - standards
Calibration
Carbohydrates - analysis
Fructose - analysis
Fruit
Fruit juices
FT-NIR spectroscopy
Glucose - analysis
Multivariate analysis
Reference Standards
Reproducibility of Results
Spectroscopy, Fourier Transform Infrared - instrumentation
Spectroscopy, Fourier Transform Infrared - methods
Sucrose - analysis
Sugars
Time Factors
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Summary:A simple analytical procedure using FT-NIR and multivariate techniques for the rapid determination of individual sugars in fruit juices was evaluated. Different NIR detection devices and sample preparation methods were tested by using model solutions to determine their analytical performance. Aqueous solutions of sugar mixtures (glucose, fructose, and sucrose; 0–8% w/v) were used to develop a calibration model. Direct measurements were made by transflection using a reflectance accessory, by transmittance using a 0.5-mm cell, and by reflectance using a fiberglass paper filter. FT-NIR spectral data were transformed to the second derivative. Partial least-squares regression (PLSR) was used to create calibration models that were cross-validated (leave-one-out approach). The prediction ability of the models was evaluated on fruit juices and compared with HPLC and standard enzymatic techniques. The PLSR loading spectra showed characteristic absorption bands for the different sugars. Models generated from transmittance spectra gave the best performance with standard error of prediction (SEP)
ISSN:0008-6215
1873-426X
DOI:10.1016/S0008-6215(01)00244-0