Immunofluorescence in Determining Veterinary Drugs in Dairy Products
Year: 2025
Type: article
Abstract: The current methods for detecting residual antibiotics and veterinary drugs in dairy products require more accuracy and a wider target range. Immunofluorescence demonstrates high potential, but its efficiency depends on the physical and chemical properties of the dairy product, e.g., mass fraction of solids, protein, and fat, pH, etc. This research featured the immune response of an immunofluorescence bioanalyzer to the physicochemical parameters of milk permeate, milk retentate, buttermilk, and cream in order to establish the limits of determination of residual antibiotics. The experiment involved whole standardized milk, raw whole milk, skim milk, whole milk powder, skim milk powder, cream, milk permeate, milk retentate, buttermilk, and their composite systems. All samples were tested for residual veterinary drugs and physicochemical profile (five replications). The data obtained were processed in Unisensor S. A., Wolfram Mathematica, and Microsoft Excel (Solver and Data Analysis add-ins). A simultaneous consideration of the specified parameters minimized the probability of false negative and false positive results in detecting residual veterinary drugs. The approach increased the analytical accuracy and reproducibility. The research yielded a universal algorithm for adapting immunofluorescence analysis to various types of dairy products. This algorithm provided accurate determination of residual amounts of antibiotics in raw milk, buttermilk, permeate, retentate, cream, and processed dairy products, which indicated its practical significance in dairy quality control. If implemented on commercial scale, the new method will improve the current dairy safety standards, strengthen consumers’ trust in the domestic dairy industry, and improve their health.
Authors: Anna Krinitsyna, Andrey Petrov
Language: English
Subfield: Animal Science and Zoology
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4414924612