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Automated System for Identifying Contaminants in Milk and its Products
by
K. Ezhilarasan,
B. Sreevidya,
Bhavya S.A.,
Hamsa K.S.
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 66 |
| Year of Publication: 2025 |
| Authors: K. Ezhilarasan, B. Sreevidya, Bhavya S.A., Hamsa K.S. |
10.5120/ijca2025926112
|
K. Ezhilarasan, B. Sreevidya, Bhavya S.A., Hamsa K.S. . Automated System for Identifying Contaminants in Milk and its Products. International Journal of Computer Applications. 187, 66 ( Dec 2025), 23-27. DOI=10.5120/ijca2025926112
@article{
10.5120/ijca2025926112,
author = {
K. Ezhilarasan,
B. Sreevidya,
Bhavya S.A.,
Hamsa K.S.
},
title = { Automated System for Identifying Contaminants in Milk and its Products },
journal = {
International Journal of Computer Applications
},
issue_date = { Dec 2025 },
volume = { 187 },
number = { 66 },
month = { Dec },
year = { 2025 },
issn = { 0975-8887 },
pages = {
23-27
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume187/number66/automated-system-for-identifying-contaminants-in-milk-and-its-products/
},
doi = { 10.5120/ijca2025926112 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-12-18T17:50:24.500684+05:30
%A K. Ezhilarasan
%A B. Sreevidya
%A Bhavya S.A.
%A Hamsa K.S.
%T Automated System for Identifying Contaminants in Milk and its Products
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 66
%P 23-27
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Milk consumption has increased constantly, with milk being part of the diet of a large proportion of the global population. As a result of this growing demand, the increased competition in the dairy market, and the increasing complexity of the supply chain, the producers in the sector of milk and dairy products resort to technological fraud, which is considered as predominant problem in various countries.[30] Therefore, further research is required to educate the public about fraud or carelessness in milk production. Over time, as counterfeiting methods have become more complex, detection techniques have had to be developed in the same sequence. This paper aims to review the main adulterants, detection techniques, and various methods of detecting defilements in milk.
References
- N. Sowmya, V. Ponnusamy, “Development of spectroscopic sensor system for an IoT application of adulteration identification on milk using machine learning,” IEEE Access, 9, pp. 53979-53995, Apr. 2021.
- Fanelli V; Mascio, I Miazzi M.M.; Savoia, M.A.; De Giovanni, C.; Montemurro, C. Molecular Approaches to Agri-Food Traceability and Authentication: An Updated Review. Foods 2021, 10, 1644.
- Fu, X.; Wu, J.; Xu, H.; Wan, P.; Fu, H.; Mei, Q. Luminescence nanoprobe in the near-infrared-II window for ultrasensitive detection of hypochlorite. Anal. Chem. 2021, 93, 15696–15702.
- Mafra, I.; Honrado, M.; Amaral, J.S. Animal Species Authentication in Dairy Products. Foods 2022, 11, 1124.
- Avula, V.; Sundar, S.P.; Sree Rekha, B.; Kalpana, M. Analytical methods to detect the Adulterants in Milk—An Overview. Asian J. Res. Pharm. Sci. 2022, 12, 272–276.
- Singh, M. Nano sensor Platforms for Detection of Milk Adulterants. Sens. Actuators Rep. 2023, 5, 100159.
- Shalileh, F.; Sabahi, H.; Dadmehr, M.; Hosseini, M. Sensing approaches toward detection of urea adulteration in milk. Microchemist. J. 2023, 193, 108990.
- Bastan, N.; Ahmadi, M.; Madrakian, T.; Afkhami, A.; Khalili, S.; Majidi, Moradi, M. A paired emitter–detector diode-based photometer for the determination of sodium hypochlorite adulteration in milk. Sci. Rep. 2023, 13, 6217.
- Momtaz, M.; Bubli, S.Y.; Khan, M.S. Mechanisms and Health Aspects of Food Adulteration: A Comprehensive Review. Foods 2023, 12, 199
- [10] Yang, Y., Y. Du, V. K. Gupta, F. Ahmad, H. Amiri, J. Pan, M. Aghdashloo, M. Tabatabaei, and A. Rajaei. 2024. Exploring blockchain and artificial intelligence in intelligent packaging to combat food fraud: A comprehensive review. Food Package. Shelf Life 43:101287. https:// doi.org/10.1016/j.fpsl.2024.101287.
- Shrikrishna, N. S., R. Sharma, J. Sahoo, A. Kaushik, and S. Gandhi. 2024. Navigating the landscape of optical biosensors. Chem. Eng. J. 490:151661. https://doi.org/10.1016/j.cej.2024.151661.
- D. Kourti, M. Angelopoulou, K. Misiakos, E. Makarona, A. Economou, P. Petrou, and S. Kakabakos, “Detection of adulteration of milk from other species with cow milk through an immersible photonic immunosensor,” Eng. Proc., vol. 35, p. 582, 2023.
- A. Sarkar and A. Dutta, “The Milk Producers’ Organization and Indian dairy sector—a strategic alignment,” Veterinarska stanica, vol. 53, no. 3, pp. 329–342, 2022.
- P. P. Lal, A. A. Prakash, A. A. Chand, K. A. Prasad, U. Mehta, M. H. Assaf, F. S. Mani, and K. A. Mamun,” IoT integrated fuzzy classification analysis for detecting adulterants in cow milk,” Sensing and Bio-Sensing Res., vol. 36, 2022.
- S. Goswami and A. Dangi,” Arduino based milk quality monitoring system,” Int. J. Agric. Environ. Biotechnology., 2021.
- A. Tapadar, F. A. Khanday, S. Sen, and A. Adhikary, “Fractional calculus in electronic circuits: a review,” in Fractional Order Systems, vol. 1, Academic Press, 2022, pp. 441–482.
- S. A. Mehdizadeh and M. Noshad,” Smartphone application assisted optoelectronic nose for monitoring milk freshness,” J. Food Eng., vol. 368, p. 111915,2024, Doi: 10.1016/j.jfoodeng.2023.111915.
- Y. K. Anagaw et al.,” Food adulteration: Causes, risks, and detection techniques,” SAGE Open Med., vol. 12, p. 20503121241250184,2024, Doi:10.1177/20503121241250184.
- M. Aqeel, A. Sohaib, M. Iqbal, H. U. Rehman, and F. Rustam, “Hyperspectral identification of oil adulteration using machine learning techniques,” Curr. Res. Food Sci., vol. 8, p.100773,2024, Doi: 10.1016/j.crfs.2024.100773.
- S. Dortez, A. G. Crevillen, A. Escarpa, and S. Cinti,” Electroanalytical paper-based device for reliable detection and quantification of sugars in milk,” Sens. Actuators B Chem., vol. 398, p. 134704, 2024, Doi: 10.1016/j.snb.2023.134704.
- J. S. Farah et al.,” Differential scanning calorimetry coupled with machine learning technique: An effective approach to determine the milk authenticity,” Food Control, vol. 121, p.107585,2021,
- A. Roy, T. Rana, and A. Shee,” Prevention and control of milk contamination, adulterants, antimicrobial residues, and agrochemicals,” in The Microbiology, Pathogenesis and Zoonosis of Milk Borne Diseases, Elsevier, 2024, pp. 135–151, Doi: 10.1016/B978-0-443-13805-8.00012-0.
- U. Salmaz, A. N. Siddiquee, and T. Islam,” A novel inexpensive capacitive sensor for instant milk adulteration detection,” IEEE Trans. Instrum. Meas., vol. 73, p. 7501708, 2024, doi: 10.1109/TIM.2024.3353277.
- F. Sayyad, K. Gandhi, R. Sharma, T. M. Amrutha, P. B. Gautam, and C. G. Harshitha,” Development and validation of paper-based strip method for the detection of formalin in milk,” J. Food Sci. Technol., vol. 61, pp. 2367–2376, 2024, doi: 10.1007/s13197-024-06003-2.
- [25] G. Kaur, R. Bhari, and K. Kumar,” Nano biosensors and their role in detection of adulterants and contaminants in food products,” Crit. Rev. Biotechnol., vol. 44, pp. 547–561, 2024, doi: 10.1080/07388551.2023.2175196.
- A. Khan, M. T. Munir, W. Yu, and B. Young,” Wavelength selection for rapid identification of different particle size fractions of milk powder using hyperspectral imaging,” Sensors (Basel), vol. 20, p. 4645, 2020, doi: 10.3390/s20164645.
- S. Patari and P. S. Mahapatra,” Imbibition of liquids through a paper substrate in a controlled environment,” Langmuir, vol. 38, pp. 4736–4746, 2022.
- X. Han, K. Liu, S. Zhang, P. Peng, C. Fu, L. Qiao, and Z. Ma, “CSRR metamaterial microwave sensor for measuring dielectric constants of solids and liquids,” IEEE Sensors Journal, vol. 24, no. 9, pp. 14167–14176, 2024.
- S. Kapse, P. Kedia, A. Kumar, S. Kausley, P. Pal, and B. Rai, “A noninvasive method for detection of freshness of packaged milk,” Journal of Food Engineering, vol. 346, p. 111424, 2023.
- M Priya, S Namratha, M Bhuvaneshwari, Asha kagawad, K Ezhilarasan “Detection of Defilement in milk and its products”, https://doi.org/10.1016/j.gltp.2021.08.015.
Index Terms
Computer Science
Information Sciences
Keywords