Validation of a method employing liquid chromatography to identify and quantify glycomacropeptide of casein in raw milk

BACKGROUND: The information on official testing methods, or regulatory methods in Colombia to test whey in milk is limited; this restriction of information goes against the possibility of mitigating the risk of food fraud. OBJECTIVES: The validation of an HPLC method to determine casein glycomacropeptide (c-GMP), a protein that countries such as Brazil, Spain, and Ecuador have used as an indicator of raw milk adulteration with whey, was carried out. METHODS: A 10mL sample of raw milk is precipitated with 24% TCA using ultrasound, a process followed by filtration. The collected fraction ensured the separation of c-GMP and then injected into the liquid chromatography. RESULTS: A 30 minutes analysis allowed the determination of c-GMP with a retention time of 12.9 ± 0.5 minutes. The performance characteristics method in the validation exercise were: recovery percentage 99.97%, linearity R2> 0.95; % RSD accuracy <5.3%. CONCLUSION, the method exhibits desirable attributes for the intended purpose.

IoT Based Milk Adulteration Analyser

Food safety is a more important issue in rural and urban areas as it affects the health of the citizens. Different studies have shown that adulteration of milk is a problem in many countries. Increased adulteration in milk poses a health risk that can lead to life-threatening diseases. So it is necessary to develop a device that allows detection of such life-threatening adulterants present in milk. This is achieved by detecting adulterants in milk using basic principle of spectrometer combined with automated devices.

Computer Vision Based Detection and Quantification of Extraneous Water in Raw Milk

A rapid method based on digital image analysis and machine learning technique is proposed for the detection of milk adulteration with water. Several machine learning algorithms were compared, and SVM performed best with 89.48 % of total accuracy and 95.10 % precision. An increase in the classification performance was observed in extreme classes. Better quantitative determination of the extraneous water was achieved using SVMR with R2(CV) and R2(P) of 0.65 and 0.71 respectively. The proposed technique can be used to screen raw milk based on the level of added extraneous water without the necessity of any additional reagent.

The Combination of Vibrational Spectroscopy and Chemometrics for Analysis of Milk Products Adulteration

Milk products obtained from cow, goat, buffalo, sheep, and camel as well as fermented forms such as cheese, yogurt, kefir, and butter are in a category of the most nutritious foods due to their high contents of high protein contributing to total daily energy intake. For certain reasons, high price milk products may be adulterated with low-quality ones or with foreign substances such as melamine and formalin which are added into them; therefore, a comprehensive review on analytical methods capable of detecting milk adulteration is needed. The objective of this narrative review is to highlight the use of vibrational spectroscopies (near infrared, mid infrared, and Raman) combined with multivariate analysis for authentication of milk products. Articles, conference reports, and abstracts from several databases including Scopus, PubMed, Web of Science, and Google Scholar were used in this review. By selecting the correct conditions (spectral treatment, normal versus derivative spectra at wavenumbers region, and chemometrics techniques), vibrational spectroscopy is a rapid and powerful analytical technique for detection of milk adulteration. This review can give comprehensive information for selecting vibrational spectroscopic methods combined with chemometrics techniques for screening the adulteration practice of milk products.