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Explorative study of apple juice fluorescence in relation to antioxidant properties

Overview of attention for article published in Food Chemistry, May 2016
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Title
Explorative study of apple juice fluorescence in relation to antioxidant properties
Published in
Food Chemistry, May 2016
DOI 10.1016/j.foodchem.2016.05.007
Pubmed ID
Authors

Katarzyna Włodarska, Katarzyna Pawlak-Lemańska, Igor Khmelinskii, Ewa Sikorska

Abstract

Total fluorescence spectra (excitation-emission matrices, EEM) were recorded for a series of commercial apple juices, including clear and cloudy juices produced from concentrate, cloudy juices that were not from concentrate, and freshly squeezed juices. An exploratory study of the spectra with parallel factor analysis (PARAFAC) revealed three groups of fluorophores with different emission properties, and these properties were characterized by excitation/emission maxima at 270/315nm, (310, 370)/455nm, and 430/(550, 680)nm, respectively. A regression analysis of the total fluorescence spectra arranged into three-way arrays using N-way partial least squares regression methods (NPLS1 and NPLS2) and an analysis of the unfolded spectra by partial least squares methods (PLS1 and PLS2) revealed quantitative relations between the fluorescence and antioxidant properties of juices. The best models for the total phenolic contents and total antioxidant capacities were obtained by applying the NPLS1 method to the EEM. The model parameters were as follows: R(2)CV=0.802, RPD=2.3 for the total phenolic content and R(2)CV=0.808 and RPD=2.3 for the total antioxidant capacity. These results show the potential use of fluorescence spectroscopy for screening apple juices for their antioxidant properties.

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Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 17%
Student > Ph. D. Student 10 16%
Researcher 8 13%
Student > Bachelor 6 9%
Professor 5 8%
Other 11 17%
Unknown 13 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 20%
Chemistry 11 17%
Biochemistry, Genetics and Molecular Biology 4 6%
Chemical Engineering 4 6%
Nursing and Health Professions 3 5%
Other 10 16%
Unknown 19 30%