Foods (Oct 2022)

Microbial Properties of Raw Milk throughout the Year and Their Relationships to Quality Parameters

  • Huizhi Yuan,
  • Sufang Han,
  • Shufei Zhang,
  • Yuling Xue,
  • Yaoguang Zhang,
  • Han Lu,
  • Shijie Wang

DOI
https://doi.org/10.3390/foods11193077
Journal volume & issue
Vol. 11, no. 19
p. 3077

Abstract

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Raw milk microbiota is complex and influenced by many factors that facilitate the introduction of undesirable microorganisms. Milk microbiota is closely related to the safety and quality of dairy products, and it is therefore critical to characterize the variation in the microbial composition of raw milk. In this cross-sectional study, the variation in raw milk microbiota throughout the year (n = 142) from three farms in China was analyzed using 16S rRNA amplicon sequencing, including α and β diversity, microbial composition, and the relationship between microbiota and milk quality parameters. This aimed to characterize the contamination risk of raw milk throughout the year and the changes in quality parameters caused by contamination. Collection month had a significant effect on microbial composition; microbial diversity was higher in raw milk collected in May and June, while milk collected in October and December had the lowest microbial diversity. Microbiota composition differed significantly between milk collected in January–June, July–August, and September–December (p Pseudomonas, Acinetobacter, Streptococcus and Lactobacillus were the most common genera. Redundancy analysis (RDA) found strong correlations between microbial distribution and titratable acidity (TA), fat, and protein. Many genera were significantly correlated with TA, for example Acinetobacter (R = 0.426), Enhydrobacter (R = 0.309), Chryseobacterium (R = 0.352), Lactobacillus (R = −0.326), norank_o__DTU014 (R = −0.697), norank_f__SC-I-84 (R = −0.678), and Subgroup_10 (R = −0.721). Additionally, norank_f__ Muribaculaceae was moderately negatively correlated with fat (R = −0.476) and protein (R = −0.513). These findings provide new information on the ecology of raw milk microbiota at the farm level and contribute to the understanding of the variation in raw milk microbiota in China.

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