Lactic acid bacteria (LAB) found in milk can be responsible for organoleptic defects in cheese. To identify sources of LAB that could potentially develop during cheese making, we evaluated their prevalence and abundance in milk according to the type of forage used in dairy cow feeding. Forages and bulk tank milk were sampled 3 times on 24 farms using either hay alone (control), or grass or legume silage supplemented with corn silage or not. Both types of silage were either non-inoculated or inoculated with commercial preparations containing at least a Lactobacillus buchneri strain along with Lactobacillus casei, Lactobacillus plantarum, Enterococcus faecium, or Pediococcus pentosaceus. Our results indicate that LAB viable counts in milk samples (2.56 log cfu/mL) did not differ according to the type of forage used. A total of 1,239 LAB were isolated and identified by partial 16S rRNA gene sequencing. Although inoculation increased lactobacilli abundance in grass silage by 35%, we did not observe an effect on the LAB profile of milk. Indeed, we found no significant difference in milk LAB prevalence and abundance according to the type of forage (P > 0.05). Moreover, isolates belonging to the L. buchneri group were rarely found in bulk tank milk (3 out of 481 isolates). Random amplified polymorphic DNA typing of 406 LAB isolates revealed the plausible transfer of some strains from silage to milk (~6%). Thus, forage is only a minor contributor to LAB contamination of milk.

The temporal instability of raw milk microbiota drastically affects the reliability of microbiome studies. However, little is known about the microbial integrity in preserved samples. Raw cow milk samples were preserved with azidiol or bronopol and stored at 4 °C, or with dimethyl sulfoxide (DMSO) or a mixture of azidiol and DMSO and stored at −20 °C for up to 30 days. Aliquots of 5-, 10-, and 30-day post-storage were treated with propidium monoazide (PMA), then analyzed by sequencing the 16S rRNA gene V3-V4 and V6-V8 regions. The V6-V8 gave a higher richness and lower diversity than the V3-V4 region. After 5-day storage at 4 °C, the microbiota of unpreserved samples was characterized by a drastic decrease in diversity, and a significant shift in community structure. The treatment with azidiol and DMSO conferred the best community stabilization in preserved raw milk. Interestingly, the azidiol treatment performed as well for up to 10 days, thus appearing as a suitable alternative. However, neither azidiol nor bronopol could minimize fungal proliferation as revealed by PMA-qPCR assays. This study demonstrates the preservative ability of a mixture of azidiol and DMSO and provides deeper insights into the microbial changes occurring during the cold storage of preserved raw milk.

Environmental and herd-associated factors such as geographical location, climatic conditions, forage types, bedding, soil, animal genetics, herd size, housing, lactation stage, and udder health are exploited by farmers to dictate specific management strategies that ensure dairy operation profitability and enhance the sustainability of milk production. Along with milking routines, milking systems, and storage conditions, these farming practices greatly influence the microbiota of raw milk, as evidenced by several recent studies. During the past few years, the increased interest in high-throughput sequencing technologies combined with culture-dependent methods to investigate dairy microbial ecology has improved our understanding of raw milk community dynamics throughout storage and processing. However, knowledge is still lacking on the niche-specific communities in the farm environment, and on the factors that determine bacteria transfer to the raw milk. This review summarizes findings from the past 2 decades regarding the effects of farm management practices on the diversity of bacterial species that determine the microbiological quality of raw cow milk.

The microbiota of silage is a key determinant of its quality. Although commercial inoculants are often used to improve silage quality, studies to analyze their impact on the microbiota of preserved forage at farm-scale facilities are scarce. We assessed the diversity of viable bacterial communities of hay (unfermented dry forage) and grass or legume (GL) and corn (C) silage to deepen our knowledge of how inoculant addition drives microbial occurrence patterns on dairy farms. Forage samples were collected from 24 dairy farms over two sampling periods. Samples were analyzed by high-throughput sequencing and quantitative PCR after being treated with propidium monoazide to account for viable cells. We found consistent significant differences between hay and silage community structures across sampling periods. Silage was generally dominated by lactic acid bacteria (LAB), while Pantoea and Sphingomonas were the main co-dominant genera in hay. The GL silage dominated by Pediococcus, Weissella, and Bacillus was phylogenetically different from C silage enriched in Acetobacter. The use of inoculants including Lentilactobacillus buchneri either alone or in combination with Lactiplantibacillus plantarum, Lacticaseibacillus casei, Pediococcus pentosaceus, or Enterococcus faecium did not systematically prevent the occurrence of undesirable bacteria, especially when corn-based, probably because of factors that can mitigate the effect of inoculation on the microbiota. The core Lactobacillales constituted the dominant LAB in silage with up to 96% relative abundance, indicating either the ubiquity of inoculants or the high competitiveness of epiphytes. Silage chemical profiles varied inconsistently with sampling periods and the use of inoculants. Multivariate multi-table analyses allowed the identification of bacterial clusters mainly driven by moisture and magnesium content in hay, while pH, lactic, and fatty acids were the main drivers for silage. Bacterial network analyses showed considerable variations in the topological roles with the use of inoculants. These results may help evaluate the effectiveness of forage management practices implemented on dairy farms and, therefore, are useful for fine-tuning the search for new additives. Such knowledge can be used by forage makers to adjust processing routines to improve the hygienic quality, nutritional potential, and aerobic stability of preserved forage.