Traditional cheeses which are normally produced from raw milk are very popular due to their intense and unique taste and aroma. However, high microbial contamination of raw milk due to manual milking and secondary contamination may lead to many diseases in humans in Iran. Lighvan is a traditional starter-free locally made Iranian cheese that is made from raw ewe's milk. Since the use of raw milk in the preparation of cheese produces serious health problems, due to the limited ripening period of this type of cheese, this study aimed to evaluate the feasibility of preparing Lighvan cheese from pasteurized milk. For this purpose, different characteristics of cheese prepared with pasteurized milk were compared with raw milk cheese. The results showed a reduction in the microbial population over the ripening time in both types of cheeses. However, coliforms and were seen in raw milk cheeses until the last day of ripening. Regarding chemical analyses, the water-soluble nitrogen fraction and lipolysis products increased during ripening. Moreover, the raw milk cheeses indicated a higher lipolysis index than the pasteurized ones. According to the obtained results from the sensory evaluation, the raw milk cheese indicated higher acceptability compared with the pasteurized milk cheese. However, since the presence of . makes the cheese inedible, it seems that the pasteurization of milk is mandatory for the production of this type of cheese.
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http://dx.doi.org/10.1002/fsn3.2511 | DOI Listing |
BMC Res Notes
December 2024
Department of Microbiology and Parasitology, Faculty of Science, University of Buea, Box 63, Buea, Cameroon.
Objectives: Methicillin-resistant Staphylococcus aureus (MRSA) is a zoonotic pathogen that poses a serious threat to veterinary and public health worldwide. We investigated mastitis milk samples for contamination with MRSA and also characterized the MRSA isolates by investigating antimicrobial resistance and virulence factors.
Result: We confirmed MRSA in 69 of 201 (34.
Vet Sci
November 2024
Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University, Chattogram 4225, Bangladesh.
Antimicrobial resistance (AMR) is a growing global concern and poses a significant threat to public health. The emergence of multidrug-resistant organisms, including , also presents a risk of transmission to humans through the food chain, including milk. This study aimed to investigate the prevalence of in raw milk in the Chattogram metropolitan area (CMA) of Bangladesh and their phenotypic and genotypic antimicrobial resistance patterns.
View Article and Find Full Text PDFBiosensors (Basel)
December 2024
Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, Universitat de València, Camino de Vera s/n, E46022 Valencia, Spain.
(1) Background: In drug discovery and pharmaceutical quality control, a challenge is to assess protein extracts used for allergy therapy and in vivo diagnosis, such as prick tests. Indeed, there are significant differences between the features of marketed products due to variations in raw materials, purification processes, and formulation techniques. (2) Methods: A protein array technology has been developed to provide comprehensive information on protein-biomarker interactions on a large scale to support the pharmaceutical industry and clinical research.
View Article and Find Full Text PDFJ Food Prot
December 2024
Université Paris-Saclay, Micalis Institute, INRAE, AgroParisTech, 78352 Jouy en Josas, France. Electronic address:
Staphylococcus aureus is a pathogenic microorganism often found in animal-derived foods and is known for its ability to readily develop resistance to antibiotic treatments. This study was designed to determine prevalence of S. aureus strains in raw milk and meat in Italy and to evaluate their antibiotic resistance profiles and biofilm production.
View Article and Find Full Text PDFWei Sheng Yan Jiu
November 2024
National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Objective: To improve the accuracy of food intelligent recognition and weight estimation technology, establish a large-scale food image dataset.
Methods: Building large-scale food image and ingredient datasets based on web crawler technology, professional manual collection, and regular user uploads.
Results: A big dataset was constructed containing over 1.
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