Microbial communities in dairy processing environment floor-drains are dominated by product-associated bacteria and yeasts

BIOFILM DAIRY FOODS REVIEW: Microbial Community Tracking from Dairy Farm to Factory: Insights on Biofilm Management for Enhanced Food Safety and Quality

This review aimed to assess the scope of the literature on tracking the microbial community of biofilms, focusing on the dairy farm and processing environments. The majority of studies focused on either production, storage, transport or processing of milk, while 5 combined the investigation of both production and processing facilities. Factors influencing short-term changes in dairy microbiota such as the occurrence of mastitis and season were distinguished from factors revealed through long-term studies, such as feed and weather, rather than the milking equipment. Knowledge gaps were identified in relation to the study design, methods, data analysis and interpretation. The application of DNA sequencing technologies is particularly challenging with respect to samples with low microbial load (milk, swabs). There are few studies on the microbial composition of in situ biofilms, which might require new technologies for detection before sampling. Fundamental studies on the structure of biofilms are needed to identify the on-farm practices impacting the cycle of biofilm development in milking systems.

Microbial composition and dynamics in environmental samples from a ready-to-eat food production facility with a long-term colonization of Listeria monocytogenes

Listeria monocytogenes is a foodborne pathogen of significant concern for the food industry due to its remarkable ability to persist through safety control efforts, posing a subsequent health threat to consumers. Understanding the microbial communities coexisting with L. monocytogenes in food processing environments provides insights into its persistence mechanisms. We investigated the microbial communities on non-food contact surfaces in a facility producing ready-to-eat foods, known to harbour a ST121 L. monocytogenes strain over multiple years. A 10-week sampling period was coordinated with the company and public health authorities. Metagenomic analysis revealed a stable microbial composition dominated by Pseudomonas fluorescens. While highly related populations were present in high-care production zones, distinctive taxa characteristic of specific areas were observed (e.g., Sphingomonas aerolata). Although Listeria spp. were not detected in metagenomes, they were detected in cultured samples, suggesting low relative abundance in factory settings. The findings suggest that a stable resident microbiota, with distinct adaptations to different areas within the factory, was selected for by their collective ability to survive control efforts in this environment. Listeria spp. was a member of this microbial community, albeit at low abundance, and may likewise benefit from the mutualism of the overall microbial community.

The choice of 16S rRNA gene sequence analysis impacted characterization of highly variable surface microbiota in dairy processing environments

Accurate knowledge of the microbiota collected from surfaces in food processing environments is important for food quality and safety. This study assessed discrepancies in taxonomic composition and alpha and beta diversity values generated from eight different bioinformatic workflows for the analysis of 16S rRNA gene sequences extracted from the microbiota collected from surfaces in dairy processing environments. We found that the microbiota collected from environmental surfaces varied widely in density (0-9.09 log10 CFU/cm2) and Shannon alpha diversity (0.01-3.40). Consequently, depending on the sequence analysis method used, characterization of low-abundance genera (i.e., below 1% relative abundance) and the number of genera identified (114-173 genera) varied considerably. Some low-abundance genera, including Listeria, varied between the amplicon sequence variant (ASV) and operational taxonomic unit (OTU) methods. Centered log-ratio transformation inflated alpha and beta diversity values compared to rarefaction. Furthermore, the ASV method also inflated alpha and beta diversity values compared to the OTU method (P < 0.05). Therefore, for sparse, uneven, low-density data sets, the OTU method and rarefaction are better for taxonomic and ecological characterization of surface microbiota.IMPORTANCECulture-dependent environmental monitoring programs are used by the food industry to identify foodborne pathogens and spoilage biota on surfaces in food processing environments. The use of culture-independent 16S rRNA amplicon sequencing to characterize this surface microbiota has been proposed as a tool to enhance environmental monitoring. However, there is no consensus on the most suitable bioinformatic analyses to accurately capture the diverse levels and types of bacteria on surfaces in food processing environments. Here, we quantify the impact of different bioinformatic analyses on the results and interpretation of 16S rRNA amplicon sequences collected from three cultured dairy facilities in New York State. This study provides guidance for the selection of appropriate 16S rRNA analysis procedures for studying environmental microbiota in dairy processing environments.

Investigation of Staphylococcus Spp and Coliform Bacteria Contamination Sources after Cleaning-in-Place in Production Lines of Dairy Factories in Türkiye

Microorganisms detected on dairy factory surfaces after disinfection can cause product contamination, leading to economic losses and health hazards for consumers. In this study, the presence of Staphylococcus spp. and Coliform in a total of 450 samples taken from food-contact and non-contact surfaces (stainless steel, plastic, cloth, and tiles surfaces), raw milk and final product (white cheese, kashar cheese, butter, yogurt, and cream) samples in five dairy factories was investigated by conventional techniques. The isolates obtained were identified by matrix-assisted laser desorption/ionization-time of flight mass spectrometry. In this study, a total of 54 Staphylococci (16.7% S. aureus and 81.5% coagulase-negative Staphylococci [CNS]) and 44 coliform isolates were identified at the species level. The most common CNS isolated by samples was S. epidermidis followed by S. saprophyticus, S. capitis, S. succinus S. carnosus. S. xylosus, S. sciuri, S. equorum, S. warneri, and S. hominis. Eighteen of the coliform isolates (41%) were identified as E. coli; 13 (29.5%) as E. cloacae; 3 (6.9%) as E. kobei, C. freundii, and K. oxytoca; 2 (4.5%) as K. pneumoniae; 1 (2.3%) as E. ludwigii and C. farmeri. The contamination rate of non-food contact surfaces (71.3%) was found to be higher than food contact surfaces (10.4%), and contaminated surfaces were found to be effective in product contamination. Study results show that some bacterial species obtained from raw milk, surfaces, and final products are factory specific and surface-associated bacteria are prominent in the product microbial profile.

Raw milk cheeses from Beira Baixa, Portugal-A contributive study for the microbiological hygiene and safety assessment

Due to specific bacterial microbiota, raw milk cheeses have appreciated sensory properties. However, they may pose a threat to consumer safety due to potential pathogens presence. This study evaluated the microbiological contamination of 98 raw milk cheeses from Beira Baixa, Portugal. Presence and enumeration of Coagulase Positive Staphylococci (CPS), Listeria monocytogenes, Salmonella spp., pathogenic Escherichia coli, and indicator microorganisms (non-pathogenic E. coli and Listeria spp.) was attained. E. coli antimicrobial resistance (AMR) was also evaluated. PCR and/or Whole genome sequencing (WGS) was used to characterize E. coli, Salmonella spp. and L. monocytogenes isolates. Sixteen cheeses (16.3%) were classified as Satisfactory, 59 (60.2%) as Borderline and 23 (23.5%) as Unsatisfactory/Potential Injurious to Health. L. monocytogenes, CPS > 104 cfu g-1, Extraintestinal pathogenic E. coli (ExPEC) and Salmonella spp. were detected in 4.1%, 6.1%, 3.1% and 1.0% of the samples, respectively. Listeria innocua (4.1%) and E. coli > 104 cfu g-1 (16.3%) were also detected. AMR E. coli was detected in 23/98 (23.5%) of the cheese samples, of which two were multidrug resistant. WGS identified genotypes already associated to human disease and Listeria spp. cluster analysis indicated that cheese contamination might be related with noncompliance with Good Hygiene Practices during cheese production.

Airborne signals of Pseudomonas fluorescens modulate swimming motility and biofilm formation of Listeria monocytogenes in a contactless coculture system

Bacterial volatile compounds (BVCs) facilitate interspecies communication in socio-microbiology across physical barriers, thereby influencing interactions between diverse species. The impact of BVCs emitted from Pseudomonas on the biofilm formation characteristics of Listeria monocytogenes within the same ecological niche has been scarcely investigated under practical conditions of food processing. The objective of this study was to explore the motility and biofilm formation characteristics of L. monocytogenes under the impact of Pseudomonas BVCs. It was revealed that BVCs of P. fluorescens, P. lundensis, and P. fragi significantly promoted swimming motility of L. monocytogenes (P < 0.05). As evidenced by crystal violet staining, the L. monocytogenes biofilms reached a maximum OD570 value of approximately 3.78 at 4 d, which was 0.65 units markedly higher than that of the control group (P < 0.05). Despite a decrease in adherent cells of L. monocytogenes biofilms among the BVCs groups, there was a remarkable increase in the abundance of extracellular polysaccharides and proteins with 3.58 and 4.90 μg/cm2, respectively (P < 0.05), contributing to more compact matrix architectures, which suggested that the BVCs of P. fluorescens enhanced L. monocytogenes biofilm formation through promoting the secretion of extracellular polymers. Moreover, the prominent up-regulated expression of virulence genes further revealed the positive regulation of L. monocytogenes under the influence of BVCs. Additionally, the presence of BVCs significantly elevated the pH and TVB-N levels in both the swimming medium and biofilm broth, thereby exhibiting a strong positive correlation with increased motility and biofilm formation of L. monocytogenes. It highlighted the crucial signaling regulatory role of BVCs in bacterial interactions, while also emphasizing the potential food safety risk associated with the hitchhiking behavior of L. monocytogenes, thereby shedding light on advancements in control strategies for food processing.

Context matters: environmental microbiota from ice cream processing facilities affected the inhibitory performance of two lactic acid bacteria strains against Listeria monocytogenes

IMPORTANCE

Antilisterial LAB strains have been proposed as biological control agents for application in food processing environments. However, the effect of resident food processing environment microbiota on the performance on antilisterial LAB strains is poorly understood. Our study shows that the presence of microbiota collected from ice cream processing facilities' environmental surfaces can affect the attachment and inhibitory effect of LAB strains against L. monocytogenes. Further studies are therefore needed to assess whether individual microbial taxa affect antilisterial properties of LAB strains and to characterize the underlying mechanisms.

Assessment of the Microbiological Safety and Hygiene of Raw and Thermally Treated Milk Cheeses Marketed in Central Italy between 2013 and 2020

A profile of the microbial safety and hygiene of cheese in central Italy was defined based on an analysis of 1373 cheeses sampled under the Italian National Control Plan for Food Safety spanning the years 2013 to 2020 and tested according to Commission Regulation (EC) No. 2073/2005 (as amended). A total of 97.4% of cheese samples were assessed as being satisfactory for food safety criteria and 80.5% for process hygiene criteria. Staphylococcal enterotoxin was found in 2/414 samples, while Salmonella spp. and Listeria monocytogenes were detected in 15 samples out of 373 and 437, respectively. Escherichia coli and coagulase-positive staphylococci counts were found unsatisfactory in 12/61 and 17/88 cheese samples, respectively. The impact of milking species, milk thermal treatment, and cheese hardness category was considered. A statistically significant association (p < 0.05) was found between milk thermal treatment and the prevalence of coagulase-positive staphylococci and Listeria monocytogenes and between hardness and unsatisfactory levels of Escherichia coli. The data depict a contained public health risk associated with these products and confirm, at the same time, the importance of strict compliance with good hygiene practices during milk and cheese production. These results can assist in bolstering risk analysis and providing insights for food safety decision making.

Environmental persistence of Listeria monocytogenes and its implications in dairy processing plants

Listeriosis, an invasive illness with a fatality rate between 20% and 30%, is caused by the ubiquitous bacterium Listeria monocytogenes. Human listeriosis has long been associated with foods. This is because the ubiquitous nature of the bacteria renders it a common food contaminant, posing a significant risk to the food processing sector. Although several sophisticated stress coping mechanisms have been identified as significant contributing factors toward the pathogen's persistence, a complete understanding of the mechanisms underlying persistence across various strains remains limited. Moreover, aside from genetic aspects that promote the ability to cope with stress, various environmental factors that exist in food manufacturing plants could also contribute to the persistence of the pathogen. The objective of this review is to provide insight into the challenges faced by the dairy industry because of the pathogens' environmental persistence. Additionally, it also aims to emphasize the diverse adaptation and response mechanisms utilized by L. monocytogenes in food manufacturing plants to evade environmental stressors. The persistence of L. monocytogenes in the food processing environment poses a serious threat to food safety and public health. The emergence of areas with high levels of L. monocytogenes contamination could facilitate Listeria transmission through aerosols, potentially leading to the recontamination of food, particularly from floors and drains, when sanitation is implemented alongside product manufacturing. Hence, to produce safe dairy products and reduce the frequency of outbreaks of listeriosis, it is crucial to understand the factors that contribute to the persistence of this pathogen and to implement efficient control strategies.

Microbial Succession in the Cheese Ripening Process-Competition of the Starter Cultures and the Microbiota of the Cheese Plant Environment

A large variety of cheeses can be produced using different manufacturing processes and various starter or adjunct cultures. In this study, we have described the succession of the microbial population during the commercial production and subsequent ripening of smear-ripened cheese using 16S rRNA gene sequencing. The composition of the microbiota during the first 6 days of production was constant and consisted mainly of LAB (lactic acid bacteria) originating from the starter culture. From day 7, the proportion of LAB decreased as other bacteria from the production environment appeared. From the 14th day of production, the relative proportion of LAB decreased further, and at the end of ripening, bacteria from the environment wholly dominated. These adventitious microbiota included Psychrobacter, Pseudoalteromonas haloplanktis/hodoensis, Vibrio toranzoniae, and Vibrio litoralis (Proteobacteria phylum), as well as Vagococcus and Marinilactibacillus (Firmicutes phylum), Psychrilyobacter (Fusobacteria phylum), and Malaciobacter marinus (Campylobacterota phylum), all of which appeared to be characteristic taxa associated with the cheese rind. Subsequent analysis showed that the production and ripening of smear-ripened cheese could be divided into three stages, and that the microbiota compositions of samples from the first week of production, the second week of production, and supermarket shelf life all differed.

A Meta-Analysis of Bacterial Communities in Food Processing Facilities: Driving Forces for Assembly of Core and Accessory Microbiomes across Different Food Commodities

Microbial spoilage is a major cause of food waste. Microbial spoilage is dependent on the contamination of food from the raw materials or from microbial communities residing in food processing facilities, often as bacterial biofilms. However, limited research has been conducted on the persistence of non-pathogenic spoilage communities in food processing facilities, or whether the bacterial communities differ among food commodities and vary with nutrient availability. To address these gaps, this review re-analyzed data from 39 studies from various food facilities processing cheese (n = 8), fresh meat (n = 16), seafood (n = 7), fresh produce (n = 5) and ready-to-eat products (RTE; n = 3). A core surface-associated microbiome was identified across all food commodities, including Pseudomonas, Acinetobacter, Staphylococcus, Psychrobacter, Stenotrophomonas, Serratia and Microbacterium. Commodity-specific communities were additionally present in all food commodities except RTE foods. The nutrient level on food environment surfaces overall tended to impact the composition of the bacterial community, especially when comparing high-nutrient food contact surfaces to floors with an unknown nutrient level. In addition, the compositions of bacterial communities in biofilms residing in high-nutrient surfaces were significantly different from those of low-nutrient surfaces. Collectively, these findings contribute to a better understanding of the microbial ecology of food processing environments, the development of targeted antimicrobial interventions and ultimately the reduction of food waste and food insecurity and the promotion of food sustainability.

The composition of environmental microbiota in three tree fruit packing facilities changed over seasons and contained taxa indicative of L. monocytogenes contamination

BACKGROUND

Listeria monocytogenes can survive in cold and wet environments, such as tree fruit packing facilities and it has been implicated in outbreaks and recalls of tree fruit products. However, little is known about microbiota that co-occurs with L. monocytogenes and its stability over seasons in tree fruit packing environments. In this 2-year longitudinal study, we aimed to characterize spatial and seasonal changes in microbiota composition and identify taxa indicative of L. monocytogenes contamination in wet processing areas of three tree fruit packing facilities (F1, F2, F3).

METHODS

A total of 189 samples were collected during two apple packing seasons from floors under the washing, drying, and waxing areas. The presence of L. monocytogenes was determined using a standard culturing method, and environmental microbiota was characterized using amplicon sequencing. PERMANOVA was used to compare microbiota composition among facilities over two seasons, and abundance-occupancy analysis was used to identify shared and temporal core microbiota. Differential abundance analysis and random forest were applied to detect taxa indicative of L. monocytogenes contamination. Lastly, three L. monocytogenes-positive samples were sequenced using shotgun metagenomics with Nanopore MinION, as a proof-of-concept for direct detection of L. monocytogenes' DNA in environmental samples.

RESULTS

The occurrence of L. monocytogenes significantly increased from 28% in year 1 to 46% in year 2 in F1, and from 41% in year 1 to 92% in year 2 in F3, while all samples collected from F2 were L. monocytogenes-positive in both years. Samples collected from three facilities had a significantly different microbiota composition in both years, but the composition of each facility changed over years. A subset of bacterial taxa including Pseudomonas, Stenotrophomonas, and Microbacterium, and fungal taxa, including Yarrowia, Kurtzmaniella, Cystobasidium, Paraphoma, and Cutaneotrichosporon, were identified as potential indicators of L. monocytogenes within the monitored environments. Lastly, the DNA of L. monocytogenes was detected through direct Nanopore sequencing of metagenomic DNA extracted from environmental samples.

CONCLUSIONS

This study demonstrated that a cross-sectional sampling strategy may not accurately reflect the representative microbiota of food processing facilities. Our findings also suggest that specific microorganisms are indicative of L. monocytogenes, warranting further investigation of their role in the survival and persistence of L. monocytogenes. Video Abstract.

Source Tracker Modeling Based on 16S rDNA Sequencing and Analysis of Microbial Contamination Sources for Pasteurized Milk

Milk is rich in fat, protein, minerals, vitamins, peptides, immunologically active substances, and other nutrients, and it plays an important role in satisfying human nutrition and health. However, dairy product safety incidents caused by microbial contamination have occurred. We found that the total bacterial numbers in the pasteurized product were low and far below the limit requirements of the food safety standards of the European Union, the United States, and China. At the genus level, the primary microbial groups found in milk samples were Acinetobacter, Macrococcus, Pseudomonas, and Lactococcus, while in the equipment rinse water and air samples there was contamination by Stenotrophomonas and Acinetobacter. The Source Tracker model analysis indicated that the microorganisms in the final milk products were significantly related to the contamination in product tanks and raw milk. Therefore, it is the hope that this work can provide guidance to pinpoint contamination problems using the proper quality control sampling at specific stages in the pasteurization process.

Study of the microbial diversity of a panel of Belgian artisanal cheeses associated with challenge studies for Listeria monocytogenes

High throughput sequencing could become a powerful tool in food safety. This study was the first to investigate artisanal cheeses from Belgium (31 batches) using metagenetics, in relation to Listeria monocytogenes growth data acquired during a previous project. Five cheese types were considered, namely unripened acid-curd cheeses, smear- and mold-ripened soft cheeses, and Gouda-type and Saint-Paulin-type cheeses. Each batch was analyzed in triplicate the first and the last days of storage at 8 °C. Globally, 2697 OTUs belonging to 277 genera and to 15 phyla were identified. Lactococcus was dominant in all types, but Streptococcus was co-dominant in smear-ripened soft cheeses and Saint-Paulin-type cheeses. The dominant population was not always associated with added starter cultures. Bacterial richness and diversity were significantly higher in both types of soft cheeses than in other categories, including particular genera like Prevotella, Faecalibacterium and Hafnia-Obesumbacterium in mold-ripened cheeses and Brevibacterium, Brachybacterium, Microbacterium, Bacteroides, Corynebacterium, Marinilactibacillus, Fusobacterium, Halomonas and Psychrobacter in smear-ripened soft cheeses. A strong correlation was observed between no growth of L. monocytogenes in a smear-ripened cheese and the presence of an unknown Fusobacterium (relative abundance around 10%). This in silico correlation should be confirmed by further experiments in vitro and in situ.

Comparative analysis of the microbial community and nutritional quality of sufu

Sufu is a type of fermented food with abundant nutrients and delicious taste. It is made from the fermentation of tofu by various microorganisms. In this study, three types of sufu were prepared through natural fermentation: (NF), single-strain fermentation (SF), and mixed-strain fermentation (MF). Microbial species, amino acids, and fatty acids were identified to investigate dynamic changes in nutritional quality and microbial flora in sufu. The results showed that the number of microbial species in NF sufu was the highest (n = 284), whereas that in SF sufu was the lowest (n = 194). Overall, 153 microbial species were found in all three types of sufu. Relative abundance analysis also revealed that Tetragonococcus, Bacillus, Acinetobacter, and Staphylococcus were the main bacteria in sufu. However, there was a large number of harmful bacteria such as Enterococcaceae in NF sufu. The levels of various nutrients were low in SF sufu, whereas the contents of protein and soy isoflavones were higher in NF and MF sufu. Seventeen kinds of amino acids were detected, comprising seven essential amino acids and ten other amino acids. The contents of essential amino acids and essential fatty acids were higher in MF sufu than the other two types, resulting in its high nutritional value. The sufu produced through the three fermentation methods differed significantly (p < .05) in terms of microbial flora and nutritional quality.

From Cheese-Making to Consumption: Exploring the Microbial Safety of Cheeses through Predictive Microbiology Models

Cheeses are traditional products widely consumed throughout the world that have been frequently implicated in foodborne outbreaks. Predictive microbiology models are relevant tools to estimate microbial behavior in these products. The objective of this study was to conduct a review on the available modeling approaches developed in cheeses, and to identify the main microbial targets of concern and the factors affecting microbial behavior in these products. Listeria monocytogenes has been identified as the main hazard evaluated in modelling studies. The pH, a_w, lactic acid concentration and temperature have been the main factors contemplated as independent variables in models. Other aspects such as the use of raw or pasteurized milk, starter cultures, and factors inherent to the contaminating pathogen have also been evaluated. In general, depending on the production process, storage conditions, and physicochemical characteristics, microorganisms can grow or die-off in cheeses. The classical two-step modeling has been the most common approach performed to develop predictive models. Other modeling approaches, including microbial interaction, growth boundary, response surface methodology, and neural networks, have also been performed. Validated models have been integrated into user-friendly software tools to be used to obtain estimates of microbial behavior in a quick and easy manner. Future studies should investigate the fate of other target bacterial pathogens, such as spore-forming bacteria, and the dynamic character of the production process of cheeses, among other aspects. The information compiled in this study helps to deepen the knowledge on the predictive microbiology field in the context of cheese production and storage.

Yeast biofilm in food realms: occurrence and control

In natural environments, microorganisms form microbial aggregates called biofilms able to adhere to a multitude of different surfaces. Yeasts make no exception to this rule, being able to form biofilms in a plethora of environmental niches. In food realms, yeast biofilms may cause major problems due to their alterative activities. In addition, yeast biofilms are tenacious structures difficult to eradicate or treat with the current arsenal of antifungal agents. Thus, much effort is being made to develop novel approaches to prevent and disrupt yeast biofilms, for example through the use of natural antimicrobials or small molecules with both inhibiting and dispersing properties. The aim of this review is to provide a synopsis of the most recent literature on yeast biofilms regarding: (i) biofilm formation mechanisms; (ii) occurrence in food and in food-related environments; and (iii) inhibition and dispersal using natural compounds, in particular.

Strain variability in biofilm formation: A food safety and quality perspective

The inherent differences in microbial behavior among identically treated strains of the same microbial species, referred to as "strain variability", are regarded as an important source of variability in microbiological studies. Biofilms are defined as the structured multicellular communities with complex architecture that enable microorganisms to grow adhered to abiotic or living surfaces and constitute a fundamental aspect of microbial ecology. The research studies assessing the strain variability in biofilm formation are relatively few compared to the ones evaluating other aspects of microbial behavior such as virulence, growth and stress resistance. Among the available research data on intra-species variability in biofilm formation, compiled and discussed in the present review, most of them refer to foodborne pathogens as compared to spoilage microorganisms. Molecular and physiological aspects of biofilm formation potentially related to strain-specific responses, as well as information on the characterization and quantitative description of this type of biological variability are presented and discussed. Despite the considerable amount of available information on the strain variability in biofilm formation, there are certain data gaps and still-existing challenges that future research should cover and address. Current and future advances in systems biology and omics technologies are expected to aid significantly in the explanation of phenotypic strain variability, including biofilm formation variability, allowing for its integration in microbiological risk assessment.

Microbial Ecology Evaluation of an Iberian Pig Processing Plant through Implementing SCH Sensors and the Influence of the Resident Microbiota on Listeria monocytogenes

There is a whole community of microorganisms capable of surviving the cleaning and disinfection processes in the food industry. These persistent microorganisms can enhance or inhibit biofilm formation and the proliferation of foodborne pathogens. Cleaning and disinfection protocols will never reduce the contamination load to 0; however, it is crucial to know which resident species are present and the risk they represent to pathogens, such as Listeria monocytogenes, as they can be further used as a complementary control strategy. The aim of this study was to evaluate the resident surface microbiota in an Iberian pig processing plant after carrying out the cleaning and disinfection processes. To do so, surface sensors were implemented, sampled, and evaluated by culture plate count. Further, isolated microorganisms were identified through biochemical tests. The results show that the surfaces are dominated by Bacillus spp., Pseudomonas spp., different enterobacteria, Mannheimia haemolytica, Rhizobium radiobacter, Staphylococcus spp., Aeromonas spp., lactic acid bacteria, and yeasts and molds. Moreover, their probable relationship with the presence of L. monocytogenes in three areas of the plant is also explained. Further studies of the resident microbiota and their interaction with pathogens such as L. monocytogenes are required. New control strategies that promote the most advantageous profile of microorganisms in the resident microbiota could be a possible alternative for pathogen control in the food industry. To this end, the understanding of the resident microbiota on the surfaces of the food industry and its relation with pathogen presence is crucial.

Diversity and Control of Spoilage Fungi in Dairy Products: An Update

Fungi are common contaminants of dairy products, which provide a favorable niche for their growth. They are responsible for visible or non-visible defects, such as off-odor and -flavor, and lead to significant food waste and losses as well as important economic losses. Control of fungal spoilage is a major concern for industrials and scientists that are looking for efficient solutions to prevent and/or limit fungal spoilage in dairy products. Several traditional methods also called traditional hurdle technologies are implemented and combined to prevent and control such contaminations. Prevention methods include good manufacturing and hygiene practices, air filtration, and decontamination systems, while control methods include inactivation treatments, temperature control, and modified atmosphere packaging. However, despite technology advances in existing preservation methods, fungal spoilage is still an issue for dairy manufacturers and in recent years, new (bio) preservation technologies are being developed such as the use of bioprotective cultures. This review summarizes our current knowledge on the diversity of spoilage fungi in dairy products and the traditional and (potentially) new hurdle technologies to control their occurrence in dairy foods.