ArticleFoods (Basel, Switzerland)2024
Revolutionizing Phenolic Content Determination in Vegetable Oils: A Cutting-Edge Approach Using Smartphone-Based Image Analysis.
Article in Foods (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- DiColorimetry: A smartphone application for colorimetric analysis of phenolics and antioxidant activity in vegetable oils.MethodsX · 2026Article
- Physicochemical Characterization, Fatty Acid Profile, and In Vitro Antioxidant Capacity of Tumbo (Foods (Basel, Switzerland) · 2026Article
- Integrated Phytochemical, Anthocyanin, Organic Acid and Colour Profiling of Plant-Derived Syrups as Potential Natural Food Ingredients.Foods (Basel, Switzerland) · 2026Article
- Colorimetric paper-based test strip for detection of methylparaben in nonconforming health care products.RSC advances · 2026Article
- Smartphones as Catalysts for Synergistic Nutrition: A New Era in Bioactive Detection, Personalization, and Food System Intelligence.Food science & nutrition · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
This study addressed the need for a more accessible and efficient method of analyzing phenolic content in vegetable oils. The research aimed to develop a method that could be widely adopted by both researchers and industry professionals, ultimately revolutionizing the way phenolic content in vegetable oils is analyzed. This study developed a method of determining the total phenolic content (TPC) in vegetable oils using smartphone image analysis in the RGB color model. The method employed a gallic acid calibration solution and demonstrated exceptional determination coefficients for the RGB colors. The R-red color was selected as the basis for the analyses, and the method was statistically equivalent to standard UV/Vis spectrophotometry. The highest TPC was determined in hemp and olive oils, while the lowest was found in rice bran, grapeseed, and macadamia nut oils. This study concluded that smartphone image analysis, mainly using the R component of the RGB color model, was a superior alternative to traditional spectrophotometric methods for determining the TPC in vegetable oils. This innovative approach could revolutionize phenolic content analysis by providing researchers and industry professionals with a cost-effective, safe, and efficient tool. The estimated limit of detection (LOD) of 1.254 mg L
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Registered trials
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