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Innovative Biopreservation and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Fermented Foods

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A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Microbiology".

Deadline for manuscript submissions: closed (15 December 2020) | Viewed by 20813

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Special Issue Editors

Prof. Dr. Ursula Andrea Gonzales-Barron

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Guest Editor

CIMO Mountain Research Center, School of Agriculture, Polytechnic Institute of Bragança, Santa Apolónia Campus, 5300-253 Bragança, Portugal
Interests: predictive microbiology; quantitative risk assessment; meta-analysis; statistical quality control; Bayesian applications; experimental designs; shelf-life determination
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Vasco Cadavez

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Guest Editor

CIMO Mountain Research Center, School of Agriculture, Polytechnic Institute of Bragança, Santa Apolónia Campus, 5300-253 Bragança, Portugal
Interests: quality of meat and meat products; dynamic modelling; process optimization; linear and non-linear modelling; predictive microbiology; meta-regression; web applications; databases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biopreservatives such as functional starter cultures and plant-based antimicrobials have been widely proposed, tested, and validated as hurdles to increase microbiological quality and safety of fermented products. LAB strains selected for producing specific bacteriocins and/or for their acidogenic capacity have been used as functional starter cultures, while natural extracts have been added directly to fermented foods or even incorporated into packaging materials or coated films. Plant-based extracts have been demonstrated to also be effective in delaying degradation and nutritional quality loss, and enhancing organoleptic attributes. Nonetheless, such advances and innovations should be coupled with predictive models, probabilistic models or quantitative risk assessment models that could enable a quantitative appraisal of the impact of such hurdle technologies on either quality loss dynamics or microbial dynamics for food preservation. The Special Issue “Innovative Biopreservation and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Fermented Foods” seeks to reunite novel work on systematic reviews/meta-analysis of biopreservation agents; challenge studies involving the application of biopreservative agents in fermented foods; elucidation of microbial interactions in food fermentations through genomic approaches; quantitative assessment of new, effective biopreservatives for improving quality, controlling microbiological hazards, extending shelf-life, and reducing product deterioration and food waste; and predictive microbiology, probabilistic or process risk models that assist in the decision of the most appropriate processing strategies to be implemented to ensure quality and safety of fermented foods. This Special Issue welcomes scientific research aiming to strengthen the sustainable production of artisanal fermented foods of traditional recipes in less privileged regions of the world.

Prof. Dr. Ursula Gonzales-Barron
Prof. Vasco Cadavez
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Functional starter cultures
Microbial interaction
Antimicrobials
Challenge studies
Cheese
Meat products
Predictive microbiology
Shelf-life
Quantitative risk assessment

Published Papers (5 papers)

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Research

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14 pages, 1017 KiB

Open AccessArticle

Omnibus Modeling of Listeria monocytogenes Growth Rates at Low Temperatures

by Vincenzo Pennone, Ursula Gonzales-Barron, Kevin Hunt, Vasco Cadavez, Olivia McAuliffe and Francis Butler

Foods 2021, 10(5), 1099; https://doi.org/10.3390/foods10051099 - 15 May 2021

Cited by 4 | Viewed by 2656

Abstract

Listeria monocytogenes is a pathogen of considerable public health importance with a high case fatality. L. monocytogenes can grow at refrigeration temperatures and is of particular concern for ready-to-eat foods that require refrigeration. There is substantial interest in conducting and modeling shelf-life studies on L. monocytogenes, especially relating to storage temperature. Growth model parameters are generally estimated from constant-temperature growth experiments. Traditionally, first-order and second-order modeling (or primary and secondary) of growth data has been done sequentially. However, omnibus modeling, using a mixed-effects nonlinear regression approach, can model a full dataset covering all experimental conditions in one step. This study compared omnibus modeling to conventional sequential first-order/second-order modeling of growth data for five strains of L. monocytogenes. The omnibus model coupled a Huang primary model for growth with secondary models for growth rate and lag phase duration. First-order modeling indicated there were small significant differences in growth rate depending on the strain at all temperatures. Omnibus modeling indicated smaller differences. Overall, there was broad agreement between the estimates of growth rate obtained by the first-order and omnibus modeling. Through an appropriate choice of fixed and random effects incorporated in the omnibus model, potential errors in a dataset from one environmental condition can be identified and explored. Full article

(This article belongs to the Special Issue Innovative Biopreservation and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Fermented Foods)

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20 pages, 1828 KiB

Open AccessArticle

Chemical Profile and Bioactivities of Extracts from Edible Plants Readily Available in Portugal

by Beatriz Nunes Silva, Vasco Cadavez, Pedro Ferreira-Santos, Maria José Alves, Isabel C. F. R. Ferreira, Lillian Barros, José António Teixeira and Ursula Gonzales-Barron

Foods 2021, 10(3), 673; https://doi.org/10.3390/foods10030673 - 22 Mar 2021

Cited by 18 | Viewed by 4029 | Correction

Abstract

Plant extracts have been proposed as alternative biocides and antioxidants to be included in a variety of food products. In this work, to assess the potential of French lavender, lemon balm, basil, tarragon, sage, and spearmint to be used as food additives, the chemical profiles and bioactivities of such plant extracts were studied. Furthermore, to evaluate the influence of extraction methods and solvents on the chemical characteristics and bioactivities of the plant extracts, two extraction methods (solid-liquid and Soxhlet extraction) and two solvents (water and ethanol 70% (v/v)) were tested for each plant. Groupwise summary statistics were calculated by plant, extraction method, and solvent, and linear models were built to assess the main effects of those terms and their interactions on the chemical characteristics and bioactivities of the extracts. The results revealed that all factors—type of plant, extraction method and solvent—have influence on the chemical profile and antioxidant activity of the resultant extracts. Interactions between factors were also observed. Hydroethanolic Soxhlet extracts presented the least potential as biopreservatives due to their low phenolic content and reduced antioxidant capacity. Oppositely, aqueous Soxhlet extracts and hydroethanolic solid-liquid extracts showed high contents in phenolic compounds and high antioxidant activities. In particular, the hydroethanolic solid-liquid extracts of lemon balm, spearmint, and sage presented the highest phenolic and flavonoid contents, accompanied by a high antioxidant activity, and they revealed antimicrobial activity against four pathogens (S. enterica ser. Typhimurium, E. coli, L. monocytogenes and S. aureus). These results demonstrate the potential of these natural resources to be incorporated as bioactive preservatives in foods or their packaging. Full article

(This article belongs to the Special Issue Innovative Biopreservation and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Fermented Foods)

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12 pages, 2011 KiB

Open AccessArticle

Effect of Ohmic Heating on Sensory, Physicochemical, and Microbiological Properties of “Aguamiel” of Agave salmiana

by Luis Rascón, Mario Cruz, Rosa M. Rodríguez-Jasso, Alberto A. Neira-Vielma, Sonia N. Ramírez-Barrón and Ruth Belmares

Foods 2020, 9(12), 1834; https://doi.org/10.3390/foods9121834 - 10 Dec 2020

Cited by 5 | Viewed by 2271

Abstract

The use of ohmic heating (OH) processing technologies in beverages might provide a higher quality value to the final product; consumers tended to prefer more natural products with minimum preservative substances. The aim of this work was to evaluate the effect of OH over the presence of microorganisms in “aguamiel” as well as to study the effects on physicochemical analysis like total sugars, soluble solids, electric conductivity pH, and color. The results showed that the conductivity of “aguamiel” was 0.374 s/m, this as temperature increased, conductivity rose as well. During OH a bubbling was observed when reaching 70 °C due to the generation of electrochemical reactions during the OH process. OH had a significant effect in the reduction of E. coli, yeast, and lactobacillus compared to conventional pasteurization, reaching optimal conditions for its total inactivation. Regarding its physicochemical properties, both treatments, conventional pasteurization and OH, did not show negative changes in aguamiel, demonstrating that OH technology can be a feasible option as a pasteurization technique. In conclusion it is important to notice that negative changes were not found in quality, color and sugars of “aguamiel”. Therefore, ohmic heating can be an option to replace traditional methods used for pasteurization. Full article

(This article belongs to the Special Issue Innovative Biopreservation and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Fermented Foods)

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15 pages, 1374 KiB

Open AccessArticle

Effects of Essential Oils on Escherichia coli Inactivation in Cheese as Described by Meta-Regression Modelling

by Beatriz Nunes Silva, Vasco Cadavez, José António Teixeira and Ursula Gonzales-Barron

Foods 2020, 9(6), 716; https://doi.org/10.3390/foods9060716 - 02 Jun 2020

Cited by 8 | Viewed by 3383

Abstract

The growing intention to replace chemical food preservatives with plant-based antimicrobials that pose lower risks to human health has produced numerous studies describing the bactericidal properties of biopreservatives such as essential oils (EOs) in a variety of products, including cheese. This study aimed to perform a meta-analysis of literature data that could summarize the inactivation of Escherichia coli in cheese achieved by added EOs; and compare its inhibitory effectiveness by application method, antimicrobial concentration, and specific antimicrobials. After a systematic review, 362 observations on log reduction data and study characteristics were extracted from 16 studies. The meta-regression model suggested that pathogenic E. coli is more resistant to EO action than the non-pathogenic type (p < 0.0001), although in both cases the higher the EO dose, the greater the mean log reduction achieved (p < 0.0001). It also showed that, among the factual application methods, EOs’ incorporation in films render a steadier inactivation (p < 0.0001) than when directly applied to milk or smeared on cheese surface. Lemon balm, sage, shallot, and anise EOs showed the best inhibitory outcomes against the pathogen. The model also revealed the inadequacy of inoculating antimicrobials in cheese purposely grated for performing challenge studies, as this non-realistic application overestimates (p < 0.0001) the inhibitory effects of EOs. Full article

(This article belongs to the Special Issue Innovative Biopreservation and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Fermented Foods)

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Review

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22 pages, 399 KiB

Open AccessReview

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

by Arícia Possas, Olga María Bonilla-Luque and Antonio Valero

Foods 2021, 10(2), 355; https://doi.org/10.3390/foods10020355 - 07 Feb 2021

Cited by 38 | Viewed by 7518

Abstract

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. Full article

(This article belongs to the Special Issue Innovative Biopreservation and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Fermented Foods)

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