Development of a risk assessment model to predict the occurrence of late blowing defect in Gouda cheese and evaluate potential intervention strategies

Microbial food spoilage: impact, causative agents and control strategies

Microbial food spoilage is a major contributor to food waste and, hence, to the negative environmental sustainability impacts of food production and processing. Globally, it is estimated that 15-20% of food is wasted, with waste, by definition, occurring after primary production and harvesting (for example, in households and food service establishments). Although the causative agents of food spoilage are diverse, many microorganisms are major contributors across different types of foods. For example, the genus Pseudomonas causes spoilage in various raw and ready-to-eat foods. Aerobic sporeformers (for example, members of the genera Bacillus, Paenibacillus and Alicyclobacillus) cause spoilage across various foods and beverages, whereas anaerobic sporeformers (for example, Clostridiales) cause spoilage in a range of products that present low-oxygen environments. Fungi are also important spoilage microorganisms, including in products that are not susceptible to bacterial spoilage due to their low water activity or low pH. Strategies that can reduce spoilage include improved control of spoilage microorganisms in raw material and environmental sources as well as application of microbicidal or microbiostatic strategies (for example, to products and packaging). Emerging tools (for example, systems models and improved genomic tools) represent an opportunity for rational design of systems, processes and products that minimize microbial food spoilage.

Strain-specific Growth Parameters are Important to Accurately Model Bacterial Growth on Baby Spinach in Simulation Models

Digital tools to predict produce shelf life have the potential to reduce food waste and improve consumer satisfaction. To address this need, we (i) performed an observational study on the microbial quality of baby spinach, (ii) completed growth experiments of bacteria that are representative of the baby spinach microbiota, and (iii) developed an initial simulation model of bacterial growth on baby spinach. Our observational data showed that the predominant genera found on baby spinach were Pseudomonas, Pantoea and Exiguobacterium. Rifampicin-resistant mutants (rifR mutants) of representative bacterial subtypes were subsequently generated to obtain strain-specific growth parameters on baby spinach. These experiments showed that: (i) it is difficult to select rifR mutants that do not have fitness costs affecting growth (9 of 15 rifR mutants showed substantial differences in growth, compared to their corresponding wild-type strain) and (ii) based on estimates from primary growth models, the mean (geometric) maximum population of rifR mutants on baby spinach (7.6 log10 CFU/g, at 6°C) appears lower than that of the spinach microbiota (9.6 log10 CFU/g, at 6°C), even if rifR mutants did not have substantial growth-related fitness costs. Thus, a simulation model, parameterized with the data obtained here as well as literature data on home refrigeration temperatures, underestimated bacterial growth on baby spinach. The root mean square error of the simulation's output, compared against data from the observational study, was 1.11 log10 CFU/g. Sensitivity analysis was used to identify key parameters (e.g., strain maximum population) that impact the simulation model's output, allowing for prioritization of future data collection to improve the simulation model. Overall, this study provides a roadmap for the development of models to predict bacterial growth on leafy vegetables with strain-specific parameters and suggests that additional data are required to improve these models.

Decarboxylase activity of the non-starter lactic acid bacterium Loigolactobacillus rennini gives crack defects in Gouda cheese through the production of γ-aminobutyric acid

Ten Gouda cheese wheels with an age of 31 weeks from six different batch productions were affected by a crack defect and displayed an unpleasant off-flavor. To unravel the causes of these defects, the concentrations of free amino acids, other organic acids, volatile organic compounds, and biogenic amines were quantified in zones around the cracks and in zones without cracks, and compared with those of similar Gouda cheeses without crack defect. The Gouda cheeses with cracks had a significantly different metabolome. The production of the non-proteinogenic amino acid γ-aminobutyric acid (GABA) could be unraveled as the key mechanism leading to crack formation, although the production of the biogenic amines cadaverine and putrescine contributed as well. High-throughput amplicon sequencing of the full-length 16S rRNA gene based on whole-community DNA revealed the presence of Loigolactobacillus rennini and Tetragenococcus halophilus as most abundant non-starter lactic acid bacteria in the zones with cracks. Shotgun metagenomic sequencing allowed to obtain a metagenome-assembled genome of both Loil. rennini and T. halophilus. However, only Loil. rennini contained genes necessary for the production of GABA, cadaverine, and putrescine. Metagenetics further revealed the brine and the rennet used during cheese manufacturing as the most plausible inoculation sources of both Loil. rennini and T. halophilus.IMPORTANCECrack defects in Gouda cheeses are still poorly understood, although they can lead to major economic losses in cheese companies. In this study, the bacterial cause of a crack defect in Gouda cheeses was identified, and the pathways involved in the crack formation were unraveled. Moreover, possible contamination sources were identified. The brine bath might be a major source of bacteria with the potential to deteriorate cheese quality, which suggests that cheese producers should regularly investigate the quality and microbial composition of their brines. This study illustrated how a multiphasic approach can understand and mitigate problems in a cheese company.

Development and deployment of a supply-chain digital tool to predict fluid-milk spoilage due to psychrotolerant sporeformers

Psychrotolerant sporeformers pose a challenge to maintaining fluid milk quality. Dynamic temperature changes along the supply chain can favor the germination and growth of these bacteria and lead to fluid milk spoilage. In this study, we aim to expand on our previous work on predicting milk spoilage due to psychrotolerant sporeformers. The key model innovations include (1) the ability to account for changing temperatures along the supply chain, and (2) a deployed user-friendly interface to allow easy access to the model. Using the frequencies and concentrations of 8 Bacillales subtypes specific to fluid milk collected in New York, the model simulated sporeformer growth in half-gallons of high-temperature, short-time (HTST) pasteurized fluid milk transported from processing facility to retail store and then to consumer. The Monte Carlo simulations predicted that 44.3% of half-gallons of milk were spoiled (defined as having a bacterial concentration >20,000 cfu/mL, a conservative estimate that represents the Pasteurized Milk Ordinance regulatory limit) after 21 d of refrigerated storage at consumer's home. Model validations showed that the model was the most accurate in predicting the mean sporeformer concentration at low temperatures (i.e., at 3°C and 4°C; compared with higher temperatures at 6°C and 10°C) within the first 21 d of consumer storage, with a root mean square error of 0.29 and 0.34 log10 cfu/mL, respectively. Global sensitivity analyses indicated that home storage temperature, facility-to-retail transportation temperature, and initial spore concentration were the 3 most influential factors for predicting milk spoilage on d 21 of shelf life. What-if scenarios indicated that microfiltration was predicted to be the most effective strategy to reduce spoilage. The implementation of this strategy (assumed to reduce initial spore concentration by 2.2 log10 cfu/mL) was predicted to reduce the percentage of spoiled milk by 17.0 percentage points on d 21 of storage and could delay the date by which 50% of half-gallons of milk were spoiled, from d 25 to 35. Overall, the model is readily deployed as a digital tool for assessing fluid milk spoilage along the supply chain and evaluating the effectiveness of intervention strategies, including those that target storage temperatures at different supply chain stages.

Hyperspectral imaging through vacuum packaging for monitoring cheese biochemical transformation caused by Clostridium metabolism

This study developed a novel method for monitoring cheese contamination with Clostridium spores non-invasively using hyperspectral imaging (HSI). The ability of HSI to quantify Clostridium metabolites was investigated with control cheese and cheese manufactured with milk contaminated with Clostridium tyrobutyricum, Clostridium butyricum and Clostridium sporogenes. Microbial count, HSI and SPME-GC-MS data were obtained over 10 weeks of storage. The developed method using HSI successfully quantified butyric acid (R² = 0.91, RPD = 3.38) a major compound of Clostridium metabolism in cheese. This study creates a new venue to monitor the spatial and temporal development of late blowing defect (LBD) in cheese using fast and non-invasive measurement.

Invited review: Redefining raw milk quality-Evaluation of raw milk microbiological parameters to ensure high-quality processed dairy products

Raw milk typically has little bacterial contamination as it leaves the udder of the animal; however, through a variety of pathways, it can become contaminated with bacteria originating from environmental sources, the cow herself, and contact with contaminated equipment. Although the types of bacteria found in raw milk are very diverse, select groups are particularly important from the perspective of finished product quality. In particular, psychrophilic and psychrotolerant bacteria that grow quickly at low temperatures (e.g., species in the genus Pseudomonas and the family Enterobacteriaceae) and produce heat-stable enzymes, and sporeforming bacteria that survive processing hurdles in spore form, are the 2 primary groups of bacteria related to effects on processed dairy products. Understanding factors leading to the presence of these important bacterial groups in raw milk is key to reducing their influence on processed dairy product quality. Here we examine the raw milk microbiological parameters used in the contemporary dairy industry for their utility in identifying raw milk supplies that will perform well in processed dairy products. We further recommend the use of a single microbiological indicator of raw milk quality, namely the total bacteria count, and call for the development of a whole-farm approach to raw milk quality that will use data-driven, risk-based tools integrated across the continuum from production to processing and shelf-life to ensure continuous improvement in dairy product quality.

Ropiness in Bread-A Re-Emerging Spoilage Phenomenon

As bread is a very important staple food, its spoilage threatens global food security. Ropy bread spoilage manifests in sticky and stringy degradation of the crumb, slime formation, discoloration, and an odor reminiscent of rotting fruit. Increasing consumer demand for preservative-free products and global warming may increase the occurrence of ropy spoilage. Bacillus amyloliquefaciens, B. subtilis, B. licheniformis, the B. cereus group, B. pumilus, B. sonorensis, Cytobacillus firmus, Niallia circulans, Paenibacillus polymyxa, and Priestia megaterium were reported to cause ropiness in bread. Process hygiene does not prevent ropy spoilage, as contamination of flour with these Bacillus species is unavoidable due to their occurrence as a part of the endophytic commensal microbiota of wheat and the formation of heat-stable endospores that are not inactivated during processing, baking, or storage. To date, the underlying mechanisms behind ropy bread spoilage remain unclear, high-throughput screening tools to identify rope-forming bacteria are missing, and only a limited number of strategies to reduce rope spoilage were described. This review provides a current overview on (i) routes of entry of Bacillus endospores into bread, (ii) bacterial species implicated in rope spoilage, (iii) factors influencing rope development, and (iv) methods used to assess bacterial rope-forming potential. Finally, we pinpoint key gaps in knowledge and related challenges, as well as future research questions.