Accurate Estimation of Ethanol Content in Fruit Juices using CIELab Color Space and Chemometrics via Smartphone-based Digital Image Colorimetry

Authors

Chairul Ichsan, Department of Chemistry, Faculty of Science and Technology, Universitas Islam Negeri Raden Fatah Palembang, Palembang 30252, IndonesiaFollow
Yasir Amrulloh, Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Andalas, Padang 25163, Indonesia
Desti Erviana, Laboratory of Chemistry, Integrated Laboratory of Universitas Islam Negeri Raden Fatah, Universitas Islam Negeri Raden Fatah Palembang, Palembang 30252, Indonesia

Abstract

This study aims to investigate the optimal color space and chemometric technique for digital image colorimetry to determine ethanol content (% v/v) in apple, orange, and grape juices, using potassium dichromate (K₂Cr₂O₇) under acidic conditions. The accuracy of colorimetric–chemometric integration across various color spaces (RGB, HSV, CIELab, CMYK, CIELuv, CIEXYZ, and CIELch) was benchmarked against UV–Vis spectrophotometry using metrics such as coefficient of determination (R²), mean absolute percentage error (MAPE), and root–mean–squared error (RMSE). Various chemometric techniques (PLS, PCR, MLR, multivariable–SVR, and multivariable NN regression) were evaluated. Results demonstrate that combining the CIELab color space with PLS or MLR yields the most accurate ethanol determination. Both techniques achieved average MAPE and %RMSE values below 10% (7.026% and 7.78% for PLS; 7.34% and 7.94% for MLR) and a competitive limit of detection of 0.02% (v/v) at best, and 0.087% (v/v) on average, indicating excellent model predictability and accuracy.

Recommended Citation

Ichsan, Chairul; Amrulloh, Yasir; and Erviana, Desti (2024) "Accurate Estimation of Ethanol Content in Fruit Juices using CIELab Color Space and Chemometrics via Smartphone-based Digital Image Colorimetry," Makara Journal of Science: Vol. 28: Iss. 1, Article 9.
DOI: 10.7454/mss.v28i1.2250
Available at: https://scholarhub.ui.ac.id/science/vol28/iss1/9