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https://hdl.handle.net/20.500.14279/19334
Title: | Characterizing Halloumi cheese's bacterial communities through metagenomic analysis | Authors: | Kamilari, Eleni Anagnostopoulos, Dimitrios A. Papademas, Photis Kamilaris, Andreas Tsaltas, Dimitrios |
Major Field of Science: | Agricultural Sciences | Field Category: | Animal and Dairy Science | Keywords: | 16S rDNA sequencing;Bacterial communities;Halloumi;Lactic acid bacteria (LAB);Metagenomics;Microbiome | Issue Date: | May-2020 | Source: | LWT-Food Science and Technology, 2020, vol. 126, articl. no. 109298 | Volume: | 126 | Journal: | LWT-Food Science and Technology | Abstract: | Halloumi is a semi-hard cheese produced in Cyprus for centuries and its popularity has significantly risen over the past years. High-throughput sequencing (HTS) was applied in the present research to characterize traditional Cyprus Halloumi bacterial diversity. Eighteen samples made by different milk mixtures and produced in different areas of the country were analyzed, to reveal that Halloumi's microbiome was mainly comprised by lactic acid bacteria (LAB), including Lactobacillus, Leuconostoc, and Pediococcus, as well as halophilic bacteria, such as Marinilactibacillus and Halomonas. Additionally, spore forming bacteria and spoilage bacteria, were also detected. Halloumi produced with the “traditional” method, had significantly richer bacterial diversity compared to Halloumi produced with the “industrial” method. Variations detected among the bacterial communities highlight the contribution of the initial microbiome that existed in milk and survived pasteurization, as well as factors associated with Halloumi manufacturing conditions, in the final microbiota composition shaping. Identification and characterization of Halloumi microbiome provides an additional, useful tool to characterize its typicity and probably safeguard it from fraud products that may appear in the market. Also, it may assist producers to further improve its quality and guarantee consumers' safety. | URI: | https://hdl.handle.net/20.500.14279/19334 | ISSN: | 00236438 | DOI: | 10.1016/j.lwt.2020.109298 | Rights: | © Elsevier Attribution-NonCommercial-NoDerivatives 4.0 International |
Type: | Article | Affiliation : | Cyprus University of Technology University of Twente |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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