<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>One of the most important indicators of quality of vegetable oils is colour, which can be detected with colorimetric measurements. The determination of colour is traditionally done using colorimeters, spectrometers, tintometers, and other analytical equipment. As an alternative to replace the classical analytical methods, smartphone-based colorimetry using digital image analysis can be used. For colorimetric detection of colour in vegetable oils, a Huawei P30 lite smartphone and android application “Colour Picker” with an image matching algorithm RGB model was used. The image of sample and standard solutions was captured in a polyvinyl chloride box with light-emitting diode (LED) lamps. The aim of the study was to detect the colour of vegetable oils with smartphone-based image analysis. The detected colour of eleven vegetable oils (sea buckthorn, sunflower, rice, macadamia nut, hemp, corn, grape, linseed, rapeseed, olive, and milk thistle oils) was compared with standard solutions of iodine with a concentration range from 0 to 100 mg·100 ml<sup>−1</sup>. The results show that smartphone-based colorimetry can be used for detection of the colour of vegetable oils and it is possible to compare the colour with standard solutions of iodine. The colour of vegetable oils was expressed as the colour number obtained from an iodine standard solution prepared in deionised water.</p>
</abstract>

One of the most important indicators of quality of vegetable oils is colour, which can be detected with colorimetric measurements. The determination of colour is traditionally done using colorimeters, spectrometers, tintometers, and other analytical equipment. As an alternative to replace the classical analytical methods, smartphone-based colorimetry using digital image analysis can be used. For colorimetric detection of colour in vegetable oils, a Huawei P30 lite smartphone and android application “Colour Picker” with an image matching algorithm RGB model was used. The image of sample and standard solutions was captured in a polyvinyl chloride box with light-emitting diode (LED) lamps. The aim of the study was to detect the colour of vegetable oils with smartphone-based image analysis. The detected colour of eleven vegetable oils (sea buckthorn, sunflower, rice, macadamia nut, hemp, corn, grape, linseed, rapeseed, olive, and milk thistle oils) was compared with standard solutions of iodine with a concentration range from 0 to 100 mg·100 ml−1. The results show that smartphone-based colorimetry can be used for detection of the colour of vegetable oils and it is possible to compare the colour with standard solutions of iodine. The colour of vegetable oils was expressed as the colour number obtained from an iodine standard solution prepared in deionised water.

Colorimetric Measurements of Vegetable Oils by Smartphone-Based Image Analysis

Latvia University of Life Sciences and Technologies

Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Colorimetric Measurements of Vegetable Oils by Smartphone-Based Image Analysis"}

One of the most important indicators of quality of vegetable oils is colour, which can be detected with colorimetric measurements. The determination of colour...

Colorimetric Measurements of Vegetable Oils by Smartphone-Based Image Analysis

Published Online: Mar 03, 2022

Page range: 110 - 115

Received: Mar 22, 2021

Accepted: Nov 22, 2021

DOI: https://doi.org/10.2478/prolas-2022-0017

Keywords
colour, digital image colorimetry, Android, Huawei, vegetable fats

© 2022 Sanita Vucāne et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Colorimetric Measurements of Vegetable Oils by Smartphone-Based Image Analysis

Published Online: Mar 03, 2022

Page range: 110 - 115

Received: Mar 22, 2021

Accepted: Nov 22, 2021

DOI: https://doi.org/10.2478/prolas-2022-0017

Keywordscolour, digital image colorimetry, Android, Huawei, vegetable fats

© 2022 Sanita Vucāne et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
colour, digital image colorimetry, Android, Huawei, vegetable fats