Dairy Plant Research Articles

From One Heath to One Sustainability: The Role of Contagious Mastitis Pathogens in Decreasing the Dairy Herd Sustainability.

Economic, social, and environmental sustainability are the results of efforts aiming to improve all aspects of milk production, respecting animal welfare and improving herd health. An epidemiological study was designed to assess the role of contagious pathogens (S. aureus and S. agalactiae) in a cohort of 120 dairy herds located in the southern regions of Italy. Milk quality was assessed using certified methods, and the prevalence of mastitis pathogens in bulk tank milk was determined using quantitative polymerase chain reaction. Welfare scores were assessed using a scoring card that has more than 100 items, including animal-based measurements. Statistical analyses were performed using general lineal model and logistic regression procedures. The results showed that S. aureus had a significant negative effect on the amount of milk nutrients delivered to the dairy plant, and on the level of welfare, whereas the presence of S. agalactiae did not show any significant association. The major risk factors associated with the presence of S. aureus were also identified to help prioritize control programs. These results support the "One Sustainability" approach, implying that an increase in animal productivity is related to the improvement of animal health and welfare and potentially leading to the mitigation of greenhouse gas emissions.

Isolation of biofilm forming microflora from organized dairy plants and assessing their Minimum Inhibitory Concentration (MIC) and Minimum Biofilm Eradication Concentration (MBEC)

Isolation of biofilm forming microflora from organized dairy plants and assessing their Minimum Inhibitory Concentration (MIC) and Minimum Biofilm Eradication Concentration (MBEC)

Inactivation kinetics of dairy phages using photocatalytic paint under diverse environmental conditions and radiation sources

This article investigates the efficacy of a photocatalytic paint for bacteriophages inactivation under various levels of incident radiation flux, relative humidity and radiation sources. Two phages that infect lactic acid bacteria were selected: J-1, infective of Lacticaseibacillus casei ATCC 27139, and M13-G1b, infective of Streptococcus thermophilus G1b. Phage suspensions were deposited on coated and uncoated plates and exposed to radiation typically used for indoor illumination (λ = 360–720 nm). A first-order inactivation kinetics was proposed with respect to the Plaque Forming Units per mL (PFU/mL) that correlates the inactivation constant with the operating conditions. The kinetic constant of this novel model combines a potential function for the incident radiation flux and a logistic function for the relative humidity. The results showed that as these variables increased, phage inactivation turned higher for both uncoated and coated plates. Photonic and quantum efficiencies were also calculated for both phages, when treated with photocatalytic paint under UV-A radiation. The photonic efficiencies were 8.03 × 1012 PFU/Einstein for J-1 and 4.05 × 1012 PFU/Einstein for M13-G1b, while the quantum efficiencies were 1.19 × 1013 PFU/Einstein for J-1 and 6.03 × 1012 PFU/Einstein for M13-G1b. Good agreement was obtained between predictions of the proposed kinetic model and experimental data, with a Root Mean Square Error of 4.43 % for J-1 and 2.98 % for M13-G1b. The developed model would be useful to predict phage inactivation under diverse combinations of operating conditions levels in environments of dairy plants, different from those tested in this work.

A novel approach to energy management in the dairy industry using performance indicators and load profiles: Application to a cheese dairy plant in Tuscany, Italy

The available energy monitoring information in the dairy industry reveals significant gaps regarding the impact of operational factors on performance indicators and the generation of typical days from load profiles. This paper presents a method for predicting performance indicators and load profiles in the dairy industry based on multiple regression and clustering. The method is applied to a cheese dairy plant located in Tuscany, Italy, providing actionable insights for energy efficiency and renewable integration. With regard to performance indicators, predictions using multiple regression achieved accuracies within 8 % for electricity consumption and within 20 % for steam generation, mainly due to limited data availability. The combination of k-means clustering with multiple regression yielded an overall accuracy within approximately 10 % for electricity load profiles, enabling the labelling of clusters based on production and meteorological variables. The analysis of improved production planning and the compatibility of energy demand with solar resources showed potential reductions in the electrical performance indicator by 27 % and self-consumption rates between 14 % and 42 %, respectively. Validation with data from other dairy contexts confirms the accuracy of the method and the considerable potential for improvement, suggesting further implementation towards effective energy management in the dairy industry.

Development of a Ready-to-Drink (RTD) Beverage Formulated with Whey and Beetroot Juice

Whey, a large by-product of cheese manufacturing, is nutritionally valuable, mainly because of its whey proteins. Beetroot juice, purple–red in colour, has numerous benefits for human health; if used as an ingredient in a whey-based RTD beverage, it could mask whey’s less pleasant organoleptic characteristics. This research aimed to develop such a beverage by mixing whey with beetroot juice in a ratio that would yield a nutritionally valuable product with acceptable sensory characteristics. To this end, three RTD beverage formulations, prepared with beetroot juice and whey in different ratios (10:90, 15:85, and 20:80 v/v), were subjected to sensory analysis. The one with a 20:80 v/v ratio of beetroot juice and whey was found to be preferred by consumers, registering the highest overall score (7.8). Next, this formula was prepared with (RTD20:80a) and without citric acid (RTD20:80a) and analysed physiochemically and microbiologically. RTD20:80a was also sensory tested and proved to be the optimum one (with an overall score of 8.1); it showed a content of 1.18 g/100 mL fat, 1.07 g/100 mL protein, 0.56 g/100 mL ash, 9.90 g/100 mL carbohydrate, total soluble solids of 11.69 °Brix, an energy value of 54.44 kcal/100 mL, titratable acidity of 0.77% lactic acid, pH of 3.75, content of 1.16 mg/mL betacyanins, 0.86 mg/mL betaxanthins, and 0.36 mg GAE/mL total phenolics. Based on the microbiological results, RTD20:80a revealed a shelf-life of 14 days. By producing this beverage, a dairy plant could reduce its whey-related losses while increasing its profitability through selling it.

Enhancement of the energy and exergy analysis capabilities of the yoghurt process: a case study of the dairy industry

This study provides a comprehensive analysis of the thermal and exergy characteristics of a dairy plant that produces yoghurt. This study aims to perform a comprehensive analysis of the thermal and exergy aspects of a dairy facility that produces yoghurt. This study also seeks to improve the accuracy of the results by evaluating the reliability of the energy and production data. A comprehensive analysis of energy and exergy is utilized to enhance the yoghurt production process. Moreover, the Grassmann-Sankey diagram is employed to produce a map of energy density. The process’s energy and exergy efficiencies were assessed by taking into account the enhancements and alterations made in addition to the existing implementations. Analysis of the yoghurt production process revealed that the total energy input was 113.9 [kW], the total energy output was 72.05 kW as well and the energy efficiency was 63.3%. The exergy input and output for the yoghurt production process were calculated to be 48.95 [kW] and 29.77 [kW], and the exergy efficiency was determined to be 60.8%. This study is expected to promote the growth of livestock and agriculture in the energy sector, and is forecasted to act as a catalyst for future research. This study, which is the first of its kind in the region and is expected to stimulate further research, reveals that improving energy efficiency and conservation in the production of yoghurt products enhances the factory’s overall energy efficiency.

ORGANIZATIONAL AND ECONOMIC MECHANISM FOR DAIRY INDUSTRY ORGANIZATION COMPETITIVENESS ENSURING

The article is devoted to the current problem of increasing the effectiveness of the competitiveness strategy of a dairy industry organization through the formation of a model of an organizational and economic mechanism that allows choosing strategic vectors of development, taking into account the integration impact of various factors. The conducted theoretical analysis of the categories “organizational-economic mechanism” and competitiveness made it possible to define an approach to understanding the content of the interaction of the studied categories as a logical sequence of actions of the organization to achieve the goal, including marketing research of the internal and external environment, identifying development problems, assessing the ways and possibilities of their solution, taking into account the maximum number of influencing factors at various levels. An analysis of statistical data related to the development of the dairy products market at the level of trends in the Russian Federation and the Republic of Tatarstan was carried out. A conclusion is made about the possibility of increasing the volume of dairy production, and the need to build effective inter-industry connections through the formation of an organizational and economic mechanism for increasing the competitiveness of organizations in the dairy industry of the Republic of Tatarstan. Using the example of Kasymovsky Dairy Plant LLC, marketing tools for analyzing competitiveness were tested and calculations were made, some of which are presented in the article (calculation of the need for dairy products in 2026, analysis of nomenclature, sales dynamics and assessment of consumer awareness of dairy consumers). A methodological approach to building an organizational and economic mechanism for achieving a certain level of competitiveness of a dairy industry organization is proposed. The theoretical three-level model of the organizational and economic mechanism for increasing the competitiveness of dairy industry organizations determines the vectors of regulation and criteria for the effectiveness of selected strategies. Within the framework of the methodological approach, a generalized algorithm for the development of the organization and a scheme for forming the process of selling dairy products are proposed.

Application of solar thermal collectors for milk pasteurization to explore the potential of renewable energy in the dairy sector: Challenges and possibilities

Dairy farming has become a key business to fulfill the daily milk needs in populated countries like India. Conversely, pathogenic and spoilage microorganisms in raw milk are killed by applying different heat treatments to increase shelf life, preserve quality, and ensure safety. Among the heat treatment processes used at the dairy plant, pasteurization consumes a significant amount of heat, which increases the energy demand in the dairy sector. Since milk pasteurization occurs between 65°C and 150°C, multiple solar thermal collector alternatives are available for various kinds of pasteurization processes. Employing solar thermal collectors for milk pasteurization allows the dairy sector to use free solar energy. Solar energy in milk heat treatments minimizes fuel and power consumption, reducing carbon emissions and promoting sustainability. However, solar milk pasteurization in dairy sector is limited by the large area requirement, high initial cost, and weather dependency. There have been attempts to use different types of solar thermal collectors to pasteurize the milk in an effort to replace conventional energy usage with solar energy. The parameters of milk heat treatment, primarily pasteurization, have been discussed concerning energy usage. The benefits and limitations of various solar collectors for milk pasteurization and other heating applications in the dairy sector have been addressed. Multiple studies on integrating various solar thermal collectors with different pasteurization systems have been reviewed, summarized, and concluded.

Level of Adoption of Hygiene Practices in Small-Scale Dairy Plants in Serbia.

The main aim of this study was to analyze hygiene practices in small-scale dairy plants (SSDPs) in Serbia. A total of 60 plants were included in the research. A survey questionnaire used for SSDPs was designed to obtain the main information about hygiene practices they perform, as well as the data about the SSDPs, their production portfolio, and improvement plans. For the purpose of this study, a good hygiene practice score (GHPS) was calculated showing that the average score is 75%, spanning from 71.4% to 80.3% depending on the type of dairy plant. This study showed that the biggest challenges for small-scale dairy plants are associated with adequate labeling and external analysis of their dairy products, followed by record keeping and use of appropriate food contact materials. As expected, registered and approved SSDPs had higher GHPS scores and more information on their labels than those still in the approval or registration process. This study confirms the need for supporting this type of dairy producer to improve two main pillars of their business-the infrastructure for where they produce dairy products and awareness/knowledge of food safety legislative requirements. At the same time, approved processors are significantly underutilizing their processing capacity, which implies the need for both policy change consideration and educational initiatives. The policy changes should aim to align regulations with small-scale dairy processing realities.

Microbiome mapping in dairy industry reveals new species and genes for probiotic and bioprotective activities

The resident microbiome in food industries may impact on food quality and safety. In particular, microbes residing on surfaces in dairy industries may actively participate in cheese fermentation and ripening and contribute to the typical flavor and texture. In this work, we carried out an extensive microbiome mapping in 73 cheese-making industries producing different types of cheeses (fresh, medium and long ripened) and located in 4 European countries. We sequenced and analyzed metagenomes from cheese samples, raw materials and environmental swabs collected from both food contact and non-food contact surfaces, as well as operators’ hands and aprons. Dairy plants were shown to harbor a very complex microbiome, characterized by high prevalence of genes potentially involved in flavor development, probiotic activities, and resistance to gastro-intestinal transit, suggesting that these microbes may potentially be transferred to the human gut microbiome. More than 6100 high-quality Metagenome Assembled Genomes (MAGs) were reconstructed, including MAGs from several Lactic Acid Bacteria species and putative new species. Although microbial pathogens were not prevalent, we found several MAGs harboring genes related to antibiotic resistance, highlighting that dairy industry surfaces represent a potential hotspot for antimicrobial resistance (AR) spreading along the food chain. Finally, we identified facility-specific strains that can represent clear microbial signatures of different cheesemaking facilities, suggesting an interesting potential of microbiome tracking for the traceability of cheese origin.

Occurrence of Enterococci in the Process of Artisanal Cheesemaking and Their Antimicrobial Resistance.

Enterococci are a group of microorganisms that have a controversial position from some scientific points of view. The species of the greatest clinical importance are E. faecalis and E. faecium, which are common agents of nosocomial infections. However, enterococci also have important applications in the dairy industry, as they are used as non-starter lactic acid bacteria (NSLAB) in a variety of cheeses, especially artisanal cheeses. The aim of this study was to determine the presence of representatives from the Enterococcus genus using PCR and MALDI-TOF MS methods on samples of raw milk, processing environment swabs, and cheese from four different artisanal dairy plants in Slovakia. Among the 136 isolates of enterococci, 9 species of genus Enterococci (E. faecalis, E. faecium, E. durans, E. devriesi, E. hirae, E. italicus, E. casseliflavus, E. malodoratus, and E. gallinarum) were identified and were tested for their antimicrobial resistance (AMR) to 8 antibiotics (amoxicillin, penicillin, ampicillin, erythromycin, levofloxacin, vancomycin, rifampicin, and tetracycline); most of them were resistant to rifampicin (35.3%), ampicillin (22.8%), and tetracycline (19.9%). A PCR analysis of vanA (4.41%) and tetM (14.71%) revealed that antimicrobial resistance genes were present in not only phenotypic resistant isolates of enterococci but also susceptible isolates. The investigation of antimicrobial resistance in enterococci during the cheesemaking process can be a source of valuable information for public health in the concept of "One Health".

Application of rosemary oil nano-emulsion as antimicrobial and antioxidant natural alternative in pasteurized cream and Karish cheese

Essential oils possess significant antimicrobial and antioxidant properties and are increasingly used as natural substitutes for food preservation. Therefore, this study investigated the potential application of rosemary essential oil (REO) and REO nano-emulsion in the dairy plant. The antimicrobial effects of REO and REO nano-emulsion were determined by an agar well diffusion assay after chemical profiling by Gas Chromatography-Mass Spectrometry (GC–MS). The REO nano-emulsion was characterized by a Transmission Electron Microscope (TEM). The REO chemical profile revealed the presence of 42 chemical compounds, including 1, 8-cineole (9.72 %), and α-pinene (5.46 %) as major active components. REO nano-emulsion demonstrated significant antimicrobial activity compared to REO (P < 0.05) with a MIC value of 0.0001 mg/ml against Listeria monocytogenes and Aspergillus flavus and 0.001 mg/ml against Pseudomonas aeruginosa and Bacillus cereus. REO nano-emulsion enhanced the oxidative stability of pasteurized fresh cream, revealing a non-significant difference compared with that inoculated with butylated hydroxy anisol (BHA; synthetic antioxidant) (P˃ 0.05). Fortified cream and Karish cheese with REO nano-emulsion were evaluated organoleptically, and the results showed higher grades of overall acceptability when compared to control samples with a statistically significant difference (P < 0.05). Viability studies were estimated using the previously mentioned microorganisms in fortified fresh cream and Karish cheese with REO nano-emulsion. Results of the fortified cream showed a complete reduction of L. monocytogenes, A. flavus, and B. cereus on days 5, 7, and 10, respectively, and a 96.93 % reduction of P. aeruginosa by the end of the storage period. Regarding Karish cheese viability studies, C. albicans, A. flavus, and P. aeruginosa exhibited complete reduction on days 10, 10, and 15 of storage, respectively. In conclusion, REO nano-emulsion was recommended as a natural, safe, and effective antimicrobial and antioxidant additive in the dairy industry.

ROSMOSE: A web-based decision support tool for the design and optimization of industrial and urban energy systems

Energy efficiency is crucial for the sustainable operation of industrial and urban sectors. However, practicing engineers seldom have access to open-source tools that can readily evaluate and compare scenarios. In this work, a novel web-based tool called ROSMOSE is developed and proposed for analyzing the energy efficiency of industrial and urban systems and comparing potential process integration options. This optimization framework computes and graphically represents the minimum energy requirements, the pinch temperatures, and the Grand and integrated Carnot composite curves of process systems. Results are used to design utility systems that meet energy demands, while minimizing a specified objective function, such as total cost or environmental impacts. The Quarto environment, in which ROSMOSE is built upon, allows the integration of various open-source software and tools, such as database handling software, process modeling suites, and optimization solvers, along with interactive data visualization and reporting tools. This paper discusses the application of ROSMOSE for the energy integration and total site optimization of a dairy process consisting of milk treatment, and cream and cheese production to demonstrate the tool features. Other integration options, such as the use of heat pumps or solar panels, and the production of soft drinks or biogas as value-added byproducts, are also proposed and evaluated. As a result, from 75 % to 90 % in fuel savings and up to 80 % CO2 emissions reduction in the dairy plant are identified by optimizing the utility systems integration. Moreover, complete electrification via heat pumps eliminates any fossil fuel needs and it results in 85 % energy savings and up to 96 % CO2 emissions reduction. The activation of renewable electricity sources, such as solar power, made plausible this fully electrified scenario. Finally, optimized waste management strategies led to in-house fuel production and net export of biogas to the grid, but they also reduce cheese yield by prioritizing the biogas production from whey upgrading process. In this way, decision-makers have access to a clear performance comparison for a list of system configurations to draw informed trade-offs. A similar approach could be adopted to aid decision-making for the design and operation of other industrial and urban energy systems using ROSMOSE.

Dairy factory milk product processing and sustainable of the shelf-life extension with artificial intelligence: a model study

This study models milk product processing and sustainable of the shelf-life extension in a dairy factory using artificial intelligence. The Cappadocia dairy factory was used to study chemical processes and computational system modeling and simulation. Levenberg–Marquardt algorithm was used to create an artificial neural network model from real-time data. An AI-based method utilizing a Multilayer Perceptron (MLP) Artificial Neural Network (ANN) model was employed to precisely analyze productivity data in dairy factories. There are 9 product types and production quantities used as input parameters, and 90 datasets of actual dairy products used as output values. The model was trained using the Levenberg–Marquardt algorithm on 62 datasets for training, 14 for validation, and 14 for testing. The accuracy of the model is affected by the optimal data segmentation. The model showed how AI algorithms can improve processes and industrial production by increasing dairy production efficiency from 20 to 40%. Model efficiency values were compared to observed values to determine prediction accuracy. Model mean squared error was 4.02E-06, and coefficient of determination was 0.99984. Model efficiency predictions and observed values differed by −0.04% on average. This study investigated using artificial intelligence to optimize salvage processes and systems to increase energy efficiency and reduce environmental impact. The results show that a neural network model trained with real data can predict dairy plant productivity.

Two-year investigation of spore-formers through the production chain at two cheese plants in Norway

Spore-forming bacteria are the most complex group of microbes to eliminate from the dairy production line due to their ability to withstand heat treatment usually used in dairy processing. These ubiquitous microorganisms have ample opportunity for multiple points of entry into the milk chain, creating issues for food quality and safety. Certain spore-formers, namely bacilli and clostridia, are more problematic to the dairy industry due to their possible pathogenicity, growth, and production of metabolites and spoilage enzymes. This research investigated the spore-forming population from raw milk reception at two Norwegian dairy plants through the cheesemaking stages until ripening. Samples were collected over two years and examined by amplicon sequencing in a culture independent manner and after an anaerobic spore-former enrichment step. In addition, a total of 608 isolates from the enriched samples were identified at the genus or species level using MALDI-TOF analysis. Most spore-forming isolates belong to the genera Bacillus or Clostridium, with the latter dominating the enriched MPN tubes of raw milk and bactofugate. Results showed a great variation among the clostridia and bacilli detected in the enriched MPN tubes. However, B. licheniformis and C. tyrobutyricum were identified in all sample types from both plants throughout the 2-year study. In conclusion, our results shed light on the fate of different spore-formers at different processing stages in the cheese production chain, which could facilitate targeted actions to reduce quality problems.

Technical and financial feasibility of a chemicals recovery and energy and water production from a dairy wastewater treatment plant

Due to the high volume of wastewater produced from dairy factories, it is necessary to integrate a water recovery process with the treatment plant. Today, bipolar membrane electrodialysis units (BMEUs) are increasingly developed for wastewater treatment and reutilizing. This article aims to develop and evaluate (technical and cost analyses) a combined BMEU/batch reverse osmosis unit (BROU) process for the recovery of chemicals and water from the dairy wastewater plant. The combined BROU/BMEU process is able to simultaneously produce water and strong base-acid, and reduce power consumption due to the injection of concentrated feed flow into the BMEU. A comprehensive comparative analysis on the performances of two combined and stand-alone BMEU configurations are developed. The proposed combined technology for dairy factory wastewater treatment is designed on a new structure and configuration that can address superior cost analysis compared to similar technologies. Further, the optimal values of permeate flux and current density as two vital and influencing parameters on the performance of the studied dairy wastewater treatment process were calculated and discussed. From the outcomes, the total cost of production in the combined configuration has been reduced by approximately 26% compared to the stand-alone configuration. Increasing the feed concentration rate using the batch reverse osmosis process for the dairy wastewater treatment process can be an ideal solution from an economic point of view. Moreover, point (current density, feed concentration rate, total unit cost) = 328.9,7,14.37\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left(328.9, 7, 14.37\\right)$$\\end{document} can be considered as an optimal point for the economic performance of the studied wastewater treatment process.

A medium‐throughput approach for improved taxonomic identification of lipids preserved in ancient pottery

AbstractOrganic residue analysis (ORA) is a valuable tool for the study of ancient diets, but conventional methods remain limited in terms of taxonomic identification or to resolve mixtures. Here, we propose a method to further explore a class of compounds—triacylglycerols (TAGs)—using high‐resolution mass spectrometry to overcome these limitations in an attempt to better characterise culinary practices. Over 70 medieval Sicilian pots and a wide range of authentic fresh products were studied by matrix‐assisted laser desorption/ionisation–mass spectrometry (MALDI‐MS and MALDI‐MS/MS). MALDI‐MS analysis can distinguish fresh foodstuffs but provides little additional information regarding the contents of archaeological pottery compared to conventional ORA methods. In contrast, product ion analyses were able to deconvolute a range of animal carcass fat mixtures. In addition, detailed analysis of the composition of saturated T44 and unsaturated T50–T54 TAGs was able to provide greater taxonomic resolution regarding dairy products and plant oils.

Complete genome sequence of Lacticaseibacillus paracasei A02.

Lacticaseibacillus paracasei, a facultative anaerobic gram-positive bacterium, is commonly found in the gut of humans and animals, as well as in dairy products and plant ferments. Here, we report the complete genome sequence of L. paracasei A02, whose total genome length is 3,038,472 bp, with a GC content of 46.41%.

Deciphering microbial communities of three Savoyard raw milk cheeses along ripening and regarding the cheese process

Different Savoyard cheeses are granted with PDO (Protected Designation or Origin) and PGI (Protected Geographical Indication) which guarantees consumers compliance with strict specifications. The use of raw milk is known to be crucial for specific flavor development. To unravel the factors influencing microbial ecosystems across cheese making steps, according to the seasonality (winter and summer) and the mode of production (farmhouse and dairy factory ones), gene targeting on bacteria and fungus was used to have a full picture of 3 cheese making technologies, from the raw milk to the end of the ripening. Our results revealed that Savoyard raw milks are a plenteous source of biodiversity together with the brines used during the process, that may support the development of specific features for each cheese. It was shown that rinds and curds have very contrasted ecosystem diversity, composition, and evolution. Ripening stage was selective for some bacterial species, whereas fungus were mainly ubiquitous in dairy samples. All ripening stages are impacted by the type of cheese technologies, with a higher impact on bacterial communities, except for fungal rind communities, for which the technology is the more discriminant. The specific microorganism's abundance for each technology allow to see a real bar-code, with more or less differences regarding bacterial or fungal communities. Bacterial structuration is shaped mainly by matrices, differently regarding technologies while the influence of technology is higher for fungi. Production types showed 10 differential bacterial species, farmhouses showed more ripening taxa, while dairy factory products showing more lactic acid bacteria. Meanwhile, seasonality looks to be a minor element for the comprehension of both microbial ecosystems, but the uniqueness of each dairy plant is a key explicative feature, more for bacteria than for fungus communities.

Dynamic microbial and metabolic changes during Apulian Caciocavallo cheesemaking and ripening produced according to a standardized protocol

The microbiota of a cheese play a critical role in influencing its sensory and physicochemical properties. In this study, traditional Apulian Caciocavallo cheeses coming from 4 different dairies in the same area and produced following standardized procedures were examined, as well as the different bulk milks and natural whey starter (NWS) cultures used. Moreover, considering the cheese wheels as the blocks of Caciocavallo cheeses as whole, these were characterized at different layers (i.e., core, under-rind, and rind) of the block using a multi-omics approach. In addition to physical-chemical characterization, culturomics, quantitative PCR, metagenomics, and metabolomics analysis were carried out after salting and throughout the ripening time (2 mo) to investigate major shifts in the succession of the microbiota and flavor development. Culture-dependent and 16S rRNA metataxonomics results clearly clustered samples based on microbiota biodiversity related to the production dairy plant as a result of the use of different NWS or the intrinsic conditions of each production site. At the beginning of the ripening, cheeses were dominated by Lactobacillus, and in 2 dairies (Art and SdC), Streptococcus genera were associated with the NWS. The analysis allowed us to show that although the diversity of identified genera did not change significantly between the rind, under-rind, and core fractions of the same samples, there was an evolution in the relative abundance and absolute quantification, modifying and differentiating profiles during ripening. The real-time PCR, also known as quantitative or qPCR, mainly differentiated the temporal adaptation of those species originating from bulk milks and those provided by NWS. The primary starters detected in NWS and cheeses contributed to the high relative concentration of 1-butanol, 2-butanol, 2-heptanol, 2-butanone, acetoin, delta-dodecalactone, hexanoic acid ethyl ester, octanoic acid ethyl ester, and volatile free fatty acids during ripening, whereas cheeses displaying low abundances of Streptococcus and Lactococcus (dairy Del) had a lower total concentration of acetoin compared with Art and SdC. However, the subdominant strains and nonstarter lactic acid bacteria present in cheeses are responsible for the production of secondary metabolites belonging to the chemical classes of ketones, alcohols, and organic acids, reaffirming the importance and relevance of autochthonous strains of each dairy plant although only considering a delimited production area.