QUANTITATIVE BENEDICT TEST FOR REDUCING SUGAR AND MILK ANALYSES

Radina Ivanova, Young Scientist

Microbiology laboratory Multidisciplinary Hospital for Active Treatment “Heart and Brain”, Burgas, Bulgaria

E-mail: radinaivanova1997@abv.bg

Assist. Prof. Zlatina Chengolova, PhD

Department of Biotechnology Burgas State University “Prof Dr Assen Zlatarov”

E-mail: zlatina-chengolova@uniburgas.bg

Abstract

Benedict method for reducing sugers offers rapid semi-quantitative analysis without dangerous materials. The method is mainly used for determining glucose in urine in cases of suspected diabetes or in other samples. It provides information about the concentration of reducing sugars presented in possible ranges of values. This study optimized the method to become quantitative with numerical values for the color of each test sample. The detection was made without any expensive equipment. A free available mobile phone app was used for color parameter determination. The lactose concentrations from 0 to 2.5% were determined in standard solutions and also in milk. Linear trendlines and R² were presentend. The Benedict test was used with other sugars - galactose, glucose amd fructose, that had positive reaction with Benedict reagent, and sucrose and starch that had negative reaction with the reagent. The obtained results are discussed. The proposed method for conversion of semi-quantitative method to quantitative method could be applied for lactose determination on field and also could be adapted for other analytes.

Keywords

quantitative method, reducing sugars, saccharide test, milk lactose determination, Benedict test

REFERENCES

Akter, N., Hakim, A., & Afrin, F. (2021, July). FoodByte: An Android Based Mobile Health Application for Taking Dietary Decisions. In 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE.
Akyüz, E., Başkan, K. S., Tütem, E., & Apak, R. (2021). High performance liquid chromatographic method with post-column detection for quantification of reducing sugars in foods. Journal of Chromatography A, 1660, 462664.
Angyal, S. J. (2001). The Lobry de Bruyn-Alberda van Ekenstein transformation and related reactions. In Glycoscience: epimerisation, isomerisation and rearrangement reactions of carbohydrates (pp. 1-14). Berlin, Heidelberg: Springer Berlin Heidelberg.
Benedict, S. R. (1909). A reagent for the detection of reducing sugars. Journal of Biological Chemistry, 5(5), 485-487.
Benet, W. E., Lewis, G. S., Yang, L. Z., & Hughes, D. P. (2011). The mechanism of the reaction of the Tollens reagent. Journal of chemical Research, 35(12), 675-677.
Chengolova, Z., Shentov, P., Ivanova, R., & Syarova, R. (2024). How to Keep Lactose Avoiders Healthy. Dairy, 5(4), 702-726.
Di Marcantonio, F., Nedelcu, B. R., Padiu, B., & others. (2024). Food-Checker: A mobile- based crowdsourcing application for dual quality of food. Joint Research Centre.
Du, R., Guo, W., Shen, Y., Dai, J., Zhang, H., Fu, M., & Wang, X. (2023). In situ assay of the reducing sugars in hydrophilic natural deep eutectic solvents by a modified DNS method. Journal of Molecular Liquids, 385, 122286.
Ekeberg, D., Morgenlie, S., & Stenstrøm, Y. (2007). Aldose-ketose interconversion in pyridine in the presence of aluminium oxide. Carbohydrate research, 342(14), 1992-1997.
Febriyossa, A. (2024). Carbohydrate Identification Using the Molisch, Benedic and Seliwanoff Chemical Test. BioScist Journal of Biology Scienctist Reasearch, 1(2), 47-52.
Figueira, A. C., & Rocha, J. B. (2014). A proposal for teaching undergraduate chemistry students carbohydrate biochemistry by problem-based learning activities. Biochemistry and Molecular Biology Education, 42(1), 81-87.
Gupta, A., Stead, T. S., & Ganti, L. (2024). Determining a meaningful R-squared value in clinical medicine. Academic Medicine & Surgery.
Hernández-López, A., Sanchez Felix, D. A., Zuñiga Sierra, Z., Garcia Bravo, I., Dinkova, T. D., & Avila-Alejandre, A. X. (2020). Quantification of reducing sugars based on the qualitative technique of Benedict. ACS omega, 5(50), 32403-32410.
Jain, B. P., Pandey, S., & Goswami, S. K. (2024). Protocols in biochemistry and clinical biochemistry (2nd ed.). Academic Press. ISBN 978 0 443 13945 1.
Mahesha, H. B. (2012). Estimation of sugar by Folin Wu method. Yuvaraja’s College, University of Mysore.
Meyers, A., Johnston, N., Rathod, V., Korattikara, A., Gorban, A., Silberman, N., ... & Murphy, K. P. (2015). Im2calories: towards an automated mobile vision food diary. In Proceedings of the IEEE international conference on computer vision (pp. 1233-1241).
Ouellette, R. J., & Rawn, J. D. (2015). Aldehydes and ketones: Nucleophilic addition reactions. In R. J. Ouellette & J. D. Rawn (Eds.), Organic chemistry study guide (pp. 335-360). Elsevier. https://doi.org/10.1016/B978-0-12-801889-7.00019-4
Park, J. W., Cho, Y. H., Park, M. K., & Kim, Y. D. (2024). Consumer Usability Test of Mobile Food Safety Inquiry Platform Based on Image Recognition. Sustainability, 16(21), 9538.
Ratanawimarnwong, N., Suksomphot, V., Sornpipatpong, K., Lengwan, S., Donpudsa, S., Choengchan, N., & Mantim, T. (2022). Microfluidic paper-based analytical device for determination of sucrose in sugarcane juice using Benedict’s reagent. Analytical and Bioanalytical Chemistry, 414(27), 7783-7791.
Rateni, G., Dario, P., & Cavallo, F. (2017). Smartphone-based food diagnostic technologies: A review. Sensors, 17(6), 1453.
Solmaz, M. E., Mutlu, A. Y., Alankus, G., Kılıç, V., Bayram, A., & Horzum, N. (2018). Quantifying colorimetric tests using a smartphone app based on machine learning classifiers. Sensors and Actuators B: Chemical, 255, 1967-1973.
Tiwari, M., Mhatre, S., Vyas, T., Bapna, A., & Raghavan, G. (2023). A validated HPLC- RID Method for quantification and optimization of total sugars: fructose, glucose, sucrose, and lactose in eggless mayonnaise. Separations, 10(3), 199.
Tjandra, Y., Halim, G., Briano, J., & Tjahjono, M. (2025). Smartphone-Based Digital Image Analysis for Qualitative Classification of Food Dyes Using Machine Learning: Effects of Color Space and Lighting Conditions. JKPK (Jurnal Kimia dan Pendidikan Kimia), 10(2), 309- 322.
Yahia, E. M., Carrillo-López, A., & Bello-Pérez, L. A. (2019). Carbohydrates. In E. M. Yahia (Ed.), Postharvest physiology and biochemistry of fruits and vegetables (pp. 175-205). Woodhead Publishing. https://doi.org/10.1016/B978-0-12-813278-4.00009-9