A digital image-based method for determining of total acidity in red wines using acid-base titration without...

Area of Science:

• Analytical Chemistry
• Food Science
• Digital Imaging Technology

Background:

• Traditional methods for determining total acidity in red wine often require external indicators or sample pre-treatment.
• Anthocyanins, natural pigments in red wine, change color with pH, offering a potential visual endpoint for titration.
• Accurate acidity measurement is crucial for wine quality control and consistency.

Purpose of the Study:

• To develop and validate a novel digital image-based method for quantifying total acidity in red wines.
• To eliminate the need for external indicators and sample pre-treatment in acid-base titrations.
• To compare the precision and accuracy of the proposed digital imaging method against the official reference method.

Main Methods:

• Utilizing digital image analysis to capture color changes of emergent radiation during acid-base titration.
• Employing anthocyanin color shifts, which are pH-dependent, to identify the titration endpoint.
• Building titration curves using Red Green Blue (RGB) values and localizing endpoints via second derivative analysis.
• Comparing results with the official potentiometric titration method using NaOH standard solution.

Main Results:

• The digital image-based method successfully determined total acidity in ten red wine samples without pre-treatment or external indicators.
• Titration endpoints were accurately localized by analyzing RGB color variations in digital images.
• Results obtained using the proposed method showed no statistically significant difference compared to the official potentiometric method (p < 0.05).
• The digital imaging method demonstrated higher precision than the conventional official method due to its trivariate (RGB) measurement nature.

Conclusions:

• The proposed digital image-based titration method is a feasible, accurate, and precise alternative for determining total acidity in red wines.
• This technique offers advantages by simplifying the process, eliminating external indicators, and avoiding sample pre-treatment.
• The method's reliance on RGB color data from digital images enhances measurement precision, making it a valuable tool for wine analysis.