Abstract
Olive oil represents an important component of a healthy and balanced dietary. Due to commercial features, characterization of pure olive oil and commercial mixtures represents an important challenge. Reported techniques can successfully quantify components in concentrations lower than 1%, but may present long delays, too many purification steps or use expensive equipment. Image analysis represents an important characterization technique for food science and technology. By coupling image and UV-VIS spectroscopy analysis, models with linear dependence on parameters were developed and could successfully describe the mixture concentration in the range of 0-100% in mass of olive oil content. A validation sample, containing 25% in mass of olive oil, not used for parameter estimation, was also used for testing the proposed procedure, leading to a prediction of 24.8 ± 0.6. Due to image analysis results, 3-parameter-based models considering only R and G components were developed for olive oil content prediction in mixtures with up to 70% in mass of olive oil, the same test sample was used and its concentration was predicted as 24.5 ± 1.2. These results show that image analysis represents a promising technique for on-line/in-line monitoring of blending process of olive soybean oil for commercial mixtures.
Highlights
Olive oil presents growing consumption rates, mainly because its key role played on a balanced and healthy dietary, due to the presence of phenolic antioxidants and their derivatives (FRANKEL, 2011)
It is important to stress that this model includes R, G and ABS670, it indicates that the coupled use of image analysis and UV-VIS spectra improves the composition prediction
It is worth emphasizing that predictions using only image analysis components can be regarded as accurate as the predictions using UV-VIS spectra, allowing the development of a fast low cost sensor
Summary
Olive oil presents growing consumption rates, mainly because its key role played on a balanced and healthy dietary, due to the presence of phenolic antioxidants and their derivatives (FRANKEL, 2011). According to Marchal et al (2011), the lack of proper instrumentation providing fast and reliable information for process control still remains a challenge in olive oil processing, in order to avoid performing the standard laboratory analysis. This manuscript reports the development of a simple and low cost approach to olive and soybean oil mixtures characterization, which can be used for process instrumentation, focusing, for example, on olive oil mixtures monitoring. Image analysis and image analysis coupled with UV-VIS spectra were used for model formulation in order to predict mixture contents by proper parameter estimation
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