Caseinomacropeptide (CMP) index is a method used to detect adulteration of milk by addition of cheese whey, since CMP is a glycopeptide characteristic produced during cheesemaking, and soluble in the whey phase. The objective of this work was to evaluate the caseinomacropeptide index of UHT milk stored under different temperatures. Six batches of recently processed UHT milk were collected and stored under three temperatures (21°C, 6°C, and -12°C) and analyzed by HPLC in the day of the milk collection (day 0) and at 30, 60, 90, and 120 days of storage. The experiment was run as a randomized block design with a 3x5 factorial arrangement, and the Student-Newman-Keuls (SNK) method was used as the posthoc test (p = 0.05). There was a progressive increase of the CMP index during the storage period of 120 days, and this indicates the possibility of false positive results if the CMP index is used as an adulteration test for long term stored UHT milk. The validity of the CMP index as an adulteration indicator is only possible soon after packaging, and sample freezing is the only alternative when immediate analysis is not possible. The method was found to be precise, with robust CV of 1.9% even with high CMP levels.Keywords: UHT whole milk, caseinomacropeptide, HPLC 0, 30, 60, 90 RESUMO O objetivo deste trabalho foi avaliar a influência da temperatura e do tempo de armazenamento de amostras de leite UAT, em relação ao índice de caseinomacropeptídeo, por cromatografia líquida de alta eficiência, e a precisão do método de detecção. Seis lotes foram coletados e armazenados em três temperaturas (21°C, 6°C e -12°C ± 1°C) e analisadas durante o armazenamento nos dias
Muitas crianças têm a alimentação escolar como principal refeição durante o dia, porém muitas escolas brasileiras não possuem um programa de higienização que visa estabelecer o procedimento operacional pela qual as instituições evitarão as contaminações diretas e cruzadas e bem como preservarão a saúde dos alunos. Portanto, este trabalho teve como objetivo a avaliação microbiológica da água e das condições higiênico-sanitárias de bebedouros, torneiras e manipuladores de alimentos em escola municipal. As amostras foram coletadas em três repetições e analisadas em triplicata. Os resultados foram avaliados com o auxílio do software SPSS 21.0®. Realizou-se a pesquisa de coliformes totais e termotolerantes na água e micro-organismos mesófilos nas superfícies. A água das caixas d’água apresentou resultados satisfatórios e está de acordo com a legislação. A qualidade higiênico-sanitária das superfícies e dos manipuladores foram insatisfatórias. Esse cenário pode ser melhorado por meio de treinamentos contínuos e maior sensibilização e engajamento de toda a equipe escolar. Palavras-chaves: Água. Microbiologia. Higiene. Alimentos. Escola.
Cheese whey level and caseinomacropeptide (CMP) index of fermented milk beverages added with four levels of cheese whey (0, 10, 20, and 40%) and stored at 8-10 o C for 0, 7, 14 and 21 days were determined by high performance liquid chromatography-gel filtration (HPLC-GF). Additionally, the interference of the starter culture and the storage time on the detection of cheese whey and CMP were investigated. Refrigerated storage up to 21 days did not affect (P>0.05) cheese whey and CMP amounts in milk (0% of cheese whey) and in fermented milk beverages added with 10 and 20% of cheese whey (P>0.05). However, cheese whey and CMP amounts were higher than expected (P<0.05) in fermented milk beverages added with 40% of cheese whey and stored for 21 days.
This research was performed to ascertain the most suitable Artificial Neural Network (ANN) model to quantify the degree of fraud in powdered milk through the addition of powdered whey via regular standard physicochemical analyses. In this study, an evaluation was done on 103 samples with different quantities of added whey powder to whole milk powder. Using Fourier Transform Infrared Spectroscopy the fat, cryoscopy, total solids, defatted dry extract, lactose, protein and casein were analyzed. The hyperbolic tangent transformation function was used with 45 topologies, and the Holdback and K-fold validation methods were tested. In the Holdback method, 75% of the database was employed for training, while 25% was used for validation. In the K-fold method, the database was categorized into five equal sized subsets, which alternated between training and validation. Of the two methods, the K-fold method was proven to have superior efficiency. Next, analysis was done on three models of multilayer perceptron networks with feedforward architecture. In Model 1, the input layer contained all the physicochemical analyses conducted, in model 2 the casein analysis was excluded, and in model 3 the routine analyses performed for dairy products was done (fat, defatted dry extract, cryoscopy and total solids). From Model 3 an ANN was derived which could satisfactorily predict fraud calculated from using the routine and standard analyses for dairy products, containing 64 nodes in the hidden layer, with R2 of 0.9935 and RMSE of 0.5779 for training, and R2 of 0.9964 and RMSE of 0.4358 for validation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.