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Adaptation of the Folin-Ciocalteu and Fast Blue BB spectrophotometric methods to digital image analysis for the determination of total phenolic content: Reduction of reaction time, interferences and sample analysis.
- Source :
-
LWT - Food Science & Technology . Feb2024, Vol. 193, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
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Abstract
- The Folin-Ciocalteu (FC) method is the most common method used for total phenolic content (TPC) determination, but in recent years, a more specific method that does not detect non-phenolic reducing compounds has been developed, the Fast Blue BB (FBBB) assay. In this study, the reference spectrophotometric methods have been adapted to a rising, simple, fast and low-cost technique (Digital Image Analysis, (DIA)) based assay while studying if the reaction time of both methods could be reduced and applied for the determination of TPC in food samples. Moreover, the interaction of ascorbic acid (AA) and fructose (F), with both reagents, has been observed. Two linear methods were obtained by DIA with R2 values of 0.997 and 0.995, low detection limits (LOD), a precision and accuracy below 10%, and no statistically significant differences (p > 0.05) with the spectrophotometer. The reaction times were 60 and 30 min for FC and FBBB, respectively. The FC method required lower concentrations of AA and F to observe interactions in contrast to the FBBB, which did not exhibit any interactions with F. DIA has successfully been applied with both methods on a variety of drink samples, with results ranging from 10 to 600 mg GAE/g sample. • The Fast Blue BB assay is better than Folin-Ciocalteu for polyphenol determination. • A combination of assays is useful for a better perspective on antioxidant capacity. • Digital Image Analysis (DIA), an alternative technique to UV–Vis spectrophotometry. • DIA shows major advantages regarding operation time and waste production. • Green and black tea, along with grape juice, have the highest phenolic content. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00236438
- Volume :
- 193
- Database :
- Academic Search Index
- Journal :
- LWT - Food Science & Technology
- Publication Type :
- Academic Journal
- Accession number :
- 175258649
- Full Text :
- https://doi.org/10.1016/j.lwt.2024.115756