Factors Affecting the Chemical and Microbiological Profiles Together with the Technological Properties of Milk and Dairy Products

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Dairy".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 5258

Special Issue Editors


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Guest Editor
Department of Animal Science, Food and Nutrition (DIANA), Università Cattolica del Sacro Cuore, Piacenza and Cremona Campus, Piacenza, Italy
Interests: foodomics; feedomics; food chemistry; cheese; milk; food quality and traceability
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Guest Editor
Agris Agricultural Research Agency of Sardinia, Località Bonassai, 07040 Olmedo, Italy
Interests: dairy sheep nutrition; plant secondary metabolites; milk quality; ruminant lipid metabolism; environmental sustainability of dairy production

Special Issue Information

Dear Colleagues,

The dairy industries, particularly those involving milk-to-cheese processing, have always been a reservoir of technology, microbiological and chemical phenomena. Understanding the different chemical and microbiological profiles is a crucial aspect of obtaining a high-quality final product. In particular, it becomes crucial to understand how milk quality, applied technology, dairy practices, and farm practices affect the final product. Accordingly, new investigations based on OMICS technologies (such as metabolomics and metagenomics) coupled with classical target microbiology and chemical methods, can improve our understanding of those phenomena occurring during milk processing and considering the raw material used.

In this Special Issue, we invite you to submit contributions (including original research and current review articles) on milk and dairy chemistry, milk and dairy microbiology using high-throughput techniques (metabolomics and metagenomics), and target techniques on specific metabolites or microorganisms from different stages of the transformation process or helpful in explaining positive or defective phenomena in milk and dairy. The works afferent to this Special Issue could include:

Correlations between chemistry, microbiology, and sensory analysis of milk and cheese; evaluation of milk characteristics, feeding choices, process variables, defects, and additional phenomena occurring in milk and dairy products.

Dr. Gabriele Rocchetti
Dr. Andrea Cabiddu
Guest Editors

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Keywords

  • milk composition 
  • milk and cheese quality 
  • foodomics 
  • metabolomics 
  • metagenomics 
  • processing conditions 
  • lactic acid bacteria 
  • sensory profile 
  • bovine and non-bovine milk 
  • novel technologies

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Published Papers (2 papers)

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Research

13 pages, 1350 KiB  
Article
Impact of Pasture-Based Diets on the Untargeted Metabolomics Profile of Sarda Sheep Milk
by Gabriele Rocchetti, Pier Paolo Becchi, Lorenzo Salis, Luigi Lucini and Andrea Cabiddu
Foods 2023, 12(1), 143; https://doi.org/10.3390/foods12010143 - 27 Dec 2022
Cited by 5 | Viewed by 2286
Abstract
In this work, untargeted metabolomics was used to shed light on the impact of different pasture-based diets on the chemical profile of Sarda sheep milk. The study considered 11 dairy sheep farms located in Sardinia, and milk samples were collected in 4 different [...] Read more.
In this work, untargeted metabolomics was used to shed light on the impact of different pasture-based diets on the chemical profile of Sarda sheep milk. The study considered 11 dairy sheep farms located in Sardinia, and milk samples were collected in 4 different periods, namely January, March, May, and July 2019, when all sheep had 58, 98, 138, and 178 days in milk, respectively. The animal diet composition was based on the intake of grazed herbage in natural pasture, hay, and concentrate. Overall, the combination of two comprehensive databases on food, namely the Milk Composition Database and Phenol-Explorer, allowed the putative identification of 406 metabolites, with a significant (p < 0.01) enrichment of several metabolite classes, namely amino acids and peptides, monosaccharides, fatty acids, phenylacetic acids, benzoic acids, cinnamic acids, and flavonoids. The multivariate statistical approach based on supervised orthogonal projections to latent structures (OPLS-DA) allowed us to predict the chemical profile of sheep milk samples as a function of the high vs no fresh herbage intake, while the prediction model was not significant when considering both hay and concentrate intake. Among the discriminant markers of the herbage intake, we found five phenolic metabolites (such as hippuric and coumaric acids), together with lutein and cresol (belonging to carotenoids and their metabolites). Additionally, a high discriminant power was outlined for lipid derivatives followed by sugars, amino acids, and peptides. Finally, a pathway analysis revealed that the herbage intake affected mainly five biochemical pathways in milk, namely galactose metabolism, phenylalanine metabolism, alpha-linolenic acid metabolism, linoleic acid metabolism, and aromatic amino acids involved in protein synthesis (namely tyrosine, phenylalanine, and tryptophan). Full article
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16 pages, 1971 KiB  
Article
Quantitative Detection of Viable but Nonculturable Cronobacter sakazakii Using Photosensitive Nucleic Acid Dye PMA Combined with Isothermal Amplification LAMP in Raw Milk
by Lianxia Hu, Shufei Zhang, Yuling Xue, Yaoguang Zhang, Wei Zhang and Shijie Wang
Foods 2022, 11(17), 2653; https://doi.org/10.3390/foods11172653 - 1 Sep 2022
Cited by 7 | Viewed by 2184
Abstract
An accurate method that rapidly detects the number of viable but nonculturable (VBNC) Cronobacter sakazakii was developed by combining propidium bromide with quantitative LAMP (PMA-QLAMP). The gyrB gene was the target for primers design. The optimal PMA treatment conditions were determined to eliminate [...] Read more.
An accurate method that rapidly detects the number of viable but nonculturable (VBNC) Cronobacter sakazakii was developed by combining propidium bromide with quantitative LAMP (PMA-QLAMP). The gyrB gene was the target for primers design. The optimal PMA treatment conditions were determined to eliminate the DNA amplification of 108 CFU/mL of dead C. sakazakii without affecting any viable C. sakazakii DNA amplification. Compared with the DNA of 24 strains of common non-C. sakazakii strains found in raw milk and dairy products, the DNA of only six C. sakazakii strains from different sources was amplified using PMA-QLAMP. The ability of PMA-QLAMP to quantitatively detect non-dead C. sakazakii in a 10% powdered infant formula (PIF) solution was limited to 4.3 × 102 CFU/mL and above concentrations. Pasteurizing 106 CFU/mL viable C. sakazakii yielded the maximum ratio of the VBNC C. sakazakii. PMA-QLAMP-based detection indicated that, although approximately 13% of 60 samples were positive for viable C. sakazakii, the C. sakazakii titers in these positive samples were low, and none entered the VBNC state under pasteurization. PMA-QLAMP showed potential as a specific and reliable method for detecting VBNC-C. sakazakii in pasteurized raw milk, thereby providing an early warning system that indicates potential contamination of PIF. Full article
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