Vucane Sanita, Cinkmanis Ingmars, Juhnevica-Radenkova Karina, Sabovics Martins
Food Institute, Faculty of Agriculture and Food Technology, Latvia University of Life Sciences and Technologies, LV-3004 Jelgava, Latvia.
Processing and Biochemistry Department, Institute of Horticulture, LV-3701 Dobele, Latvia.
Foods. 2024 May 29;13(11):1700. doi: 10.3390/foods13111700.
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 and limit of quantification (LOQ) of 3.801 mg L further confirmed the reliability and comparability of the method. With these findings, it was expected that the method would be widely adopted in the future.
本研究满足了对一种更易于使用且高效的植物油酚类含量分析方法的需求。该研究旨在开发一种能够被研究人员和行业专业人士广泛采用的方法，最终彻底改变植物油酚类含量的分析方式。本研究开发了一种在RGB颜色模型中使用智能手机图像分析来测定植物油中总酚含量（TPC）的方法。该方法采用没食子酸校准溶液，并展示了RGB颜色出色的测定系数。选择红色（R）作为分析基础，该方法在统计学上与标准紫外/可见分光光度法等效。在大麻油和橄榄油中测定出最高的TPC，而在米糠油、葡萄籽油和澳洲坚果油中TPC最低。本研究得出结论，主要使用RGB颜色模型的红色（R）分量的智能手机图像分析，是测定植物油中TPC的传统分光光度法的一种优越替代方法。这种创新方法可为研究人员和行业专业人士提供一种经济高效、安全且高效的工具，从而彻底改变酚类含量分析。估计的检测限（LOD）为1.254 mg/L，定量限（LOQ）为3.801 mg/L，进一步证实了该方法的可靠性和可比性。基于这些发现，预计该方法未来将被广泛采用。
