A novel high-throughput image based rapid Folin-Ciocalteau assay for assessment of reducing capacity in foods.

The aim of the presented work was to develop and validate a novel high-throughput rapid Folin-Ciocalteau assay for the quantification of reducing capacity of foods based on image scanner (Image-F-C assay). The original rapid F-C assay using a 96-well plate was improved by adding a neutralization step that stabilizes the formed color, enabling image acquisition using a flatbed scanner. Although the scanner has been already used in other analytical applications, no analysis has been reported regarding the effect of the scanner model, the plate orientation or the reaction volume. In the present study, we establish that the mentioned parameters do affect the linearity and precision of image based Folin-Ciocalteau assay, and provide the optimal scanning conditions for the analyzed scanner models. Euclidean distance calculated from R (Red), G (Green) and B (Blue) values was chosen, based on linearity and sensitivity, in order to quantify the reducing capacity. An in-house program using free ImageJ macro language was written to calculate automatically the RGB values of each well. The Image-F-C assay is linear within the range of 0-20 mg L(-1) of gallic acid (R(2)≥0.9939). We compared reducing capacity values from real samples quantified by the image F-C assay and by a microplate reader and an inter-day relative standard error<8% was observed. Bland-Altman and correlation analyzes showed that there were no significant differences between the two methods.