Special Issue "Bioprocess and Fermentation Monitoring"

A special issue of Fermentation (ISSN 2311-5637).

Deadline for manuscript submissions: closed (31 July 2018)

Special Issue Editor

Guest Editor
Assoc. Prof. Dr. Daniel Cozzolino

School of Science, RMIT University, Melbourne, Victoria 3000, Australia
E-Mail
Interests: infrared spectroscopy; chemometrics; food chemistry; vibrational spectroscopy; NIR

Special Issue Information

Dear Colleagues,

In recent years, the food industry has had a clear need for simple, rapid, and cost-effective techniques for objectively evaluating the quality and composition of the foods that we produce and consume. Several methods and techniques, such as spectroscopy (e.g., near- and mid-infrared), biosensors, and electronic noses and tongues have been used to monitor and assess the bioprocesses and fermentation of several foods, such as meat, wine, and other agricultural products. This Special Issue invites researchers and industry to submit short communications, reviews or full research papers addressing novel applications related to bioprocessing and monitoring fermentation.

Dr. Daniel Cozzolino
Guest Editor

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 papers will be 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. Fermentation is an international peer-reviewed open access quarterly 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 350 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

  • Bioprocess
  • Monitoring
  • Sensors
  • Chemometrics
  • Instrumental methods

Published Papers (9 papers)

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Research

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Open AccessArticle
Effects of the Starch Molecular Structures in Barley Malts and Rice Adjuncts on Brewing Performance
Fermentation 2018, 4(4), 103; https://doi.org/10.3390/fermentation4040103
Received: 11 November 2018 / Revised: 30 November 2018 / Accepted: 13 December 2018 / Published: 16 December 2018
Cited by 1 | PDF Full-text (1746 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Background: Achieving optimal fermentation is challenging when the variation within malt starch structure and enzyme activities are not part of the standard malting specifications. This study explores how the variation of starch and starch amylolytic enzymes in both malts and rice adjuncts affect [...] Read more.
Background: Achieving optimal fermentation is challenging when the variation within malt starch structure and enzyme activities are not part of the standard malting specifications. This study explores how the variation of starch and starch amylolytic enzymes in both malts and rice adjuncts affect the mashing and the subsequent yeast fermentation in the laboratory-scale production of beer. Results: The addition of rice adjuncts significantly increased the maltose content whilst reducing the glucose content during mashing. The maltotriose content, released during mashing, was significantly negatively correlated with the total amylose content (r = −0.64, p < 0.05), and significantly negatively correlated with the number of amylopectin longer chains (degree of polymerization 37–100) (r = −0.75, p < 0.01). During fermentation, while the content of maltotriose significantly and positively correlated with both the rate and amount of ethanol production (r = 0.70, p < 0.05; r = 0.70, p < 0.05, respectively), the content of soluble nitrogen in the wort was significantly and positively correlated with both the rate and the amount of ethanol production (r = 0.63, p< 0.05; r = 0.62, p < 0.05, respectively). The amount of amylopectin with longer chains was; however, significantly negatively correlated with the ethanol production (r = −0.06, p < 0.05). Small variations among the ethanol concentration and the rate of ethanol production during fermentation were found with the addition of different rice varieties. Conclusions: The effects of the rice adjuncts on the performance of fermentation depends on the properties of the malt, including the protein modification and malt enzyme activities. This study provides data to improve standard malt specifications in order for brewers to acquire more efficient fermentation, and includes useful molecular structural characterisation. Full article
(This article belongs to the Special Issue Bioprocess and Fermentation Monitoring)
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Open AccessArticle
Wineinformatics: Regression on the Grade and Price of Wines through Their Sensory Attributes
Fermentation 2018, 4(4), 84; https://doi.org/10.3390/fermentation4040084
Received: 4 September 2018 / Revised: 22 September 2018 / Accepted: 24 September 2018 / Published: 29 September 2018
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Abstract
Wineinformatics is a field that uses machine-learning and data-mining techniques to glean useful information from wine. In this work, attributes extracted from a large dataset of over 100,000 wine reviews are used to make predictions on two variables: quality based on a “100-point [...] Read more.
Wineinformatics is a field that uses machine-learning and data-mining techniques to glean useful information from wine. In this work, attributes extracted from a large dataset of over 100,000 wine reviews are used to make predictions on two variables: quality based on a “100-point scale”, and price per 750 mL bottle. These predictions were built using support vector regression. Several evaluation metrics were used for model evaluation. In addition, these regression models were compared to classification accuracies achieved in a prior work. When regression was used for classification, the results were somewhat poor; however, this was expected since the main purpose of the regression was not to classify the wines. Therefore, this paper also compares the advantages and disadvantages of both classification and regression. Regression models can successfully predict within a few points of the correct grade of a wine. On average, the model was only 1.6 points away from the actual grade and off by about $13 per bottle of wine. To the best of our knowledge, this is the first work to use a large-scale dataset of wine reviews to perform regression predictions on grade and price. Full article
(This article belongs to the Special Issue Bioprocess and Fermentation Monitoring)
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Open AccessArticle
Wineinformatics: A Quantitative Analysis of Wine Reviewers
Fermentation 2018, 4(4), 82; https://doi.org/10.3390/fermentation4040082
Received: 31 July 2018 / Revised: 14 September 2018 / Accepted: 17 September 2018 / Published: 25 September 2018
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Abstract
Data Science is a successful study that incorporates varying techniques and theories from distinct fields including Mathematics, Computer Science, Economics, Business and domain knowledge. Among all components in data science, domain knowledge is the key to create high quality data products by data [...] Read more.
Data Science is a successful study that incorporates varying techniques and theories from distinct fields including Mathematics, Computer Science, Economics, Business and domain knowledge. Among all components in data science, domain knowledge is the key to create high quality data products by data scientists. Wineinformatics is a new data science application that uses wine as the domain knowledge and incorporates data science and wine related datasets, including physicochemical laboratory data and wine reviews. This paper produces a brand-new dataset that contains more than 100,000 wine reviews made available by the Computational Wine Wheel. This dataset is then used to quantitatively evaluate the consistency of the Wine Spectator and all of its major reviewers through both white-box and black-box classification algorithms. Wine Spectator reviewers receive more than 87% accuracy when evaluated with the SVM method. This result supports Wine Spectator’s prestigious standing in the wine industry. Full article
(This article belongs to the Special Issue Bioprocess and Fermentation Monitoring)
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Open AccessArticle
Preventing Overflow Metabolism in Crabtree-Positive Microorganisms through On-Line Monitoring and Control of Fed-Batch Fermentations
Fermentation 2018, 4(3), 79; https://doi.org/10.3390/fermentation4030079
Received: 30 August 2018 / Revised: 14 September 2018 / Accepted: 15 September 2018 / Published: 18 September 2018
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Abstract
At specific growth rates above a particular critical value, Crabtree-positive microorganisms exceed their respiratory capacity and enter diauxic growth metabolism. Excess substrate is converted reductively to an overflow metabolite, resulting in decreased biomass yield and productivity. To prevent this scenario, the cells can [...] Read more.
At specific growth rates above a particular critical value, Crabtree-positive microorganisms exceed their respiratory capacity and enter diauxic growth metabolism. Excess substrate is converted reductively to an overflow metabolite, resulting in decreased biomass yield and productivity. To prevent this scenario, the cells can be cultivated in a fed-batch mode at a growth rate maintained below the critical value, µcrit. This approach entails two major challenges: accurately estimating the current specific growth rate and controlling it successfully over the course of the fermentation. In this work, the specific growth rate of S. cerevisiae and E. coli was estimated from enhanced on-line biomass concentration measurements obtained with dielectric spectroscopy and turbidity. A feedforward-feedback control scheme was implemented to maintain the specific growth rate at a setpoint below µcrit, while on-line FTIR measurements provided the early detection of the overflow metabolites. The proposed approach is in line with the principles of Bioprocess Analytical Technology (BioPAT), and provides a means to increase the productivity of Crabtree-positive microorganisms. Full article
(This article belongs to the Special Issue Bioprocess and Fermentation Monitoring)
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Open AccessCommunication
Computing the Composition of Ethanol-Water Mixtures Based on Experimental Density and Temperature Measurements
Fermentation 2018, 4(3), 72; https://doi.org/10.3390/fermentation4030072
Received: 24 July 2018 / Revised: 15 August 2018 / Accepted: 24 August 2018 / Published: 27 August 2018
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Abstract
Two correlations were developed to calculate the composition of binary ethanol-water solutions from experimental temperature and density inputs. The first correlation is based on a Redlich-Kister (R-K) expansion and computes mixture composition within an average accuracy of ±0.45 wt.%. The R-K model is [...] Read more.
Two correlations were developed to calculate the composition of binary ethanol-water solutions from experimental temperature and density inputs. The first correlation is based on a Redlich-Kister (R-K) expansion and computes mixture composition within an average accuracy of ±0.45 wt.%. The R-K model is a non-linear function of composition and therefore requires the use of an iterative solving tool. A polynomial correlation was additionally developed which utilizes a direct solving method, and computes ethanol composition over a range of 0–100 wt.% [283.15–313.15 K] with an accuracy better than ±0.37 wt.%. The polynomial model is particularly advantageous as it can be tailored to specific composition ranges for increased accuracy. Both correlations are intended to provide a method for monitoring ethanol concentration within a chemical process in real time without off-line sample analysis, allowing for precise in-situ system control and optimization. Full article
(This article belongs to the Special Issue Bioprocess and Fermentation Monitoring)
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Open AccessArticle
Gas Fermentation Enhancement for Chemolithotrophic Growth of Cupriavidus necator on Carbon Dioxide
Fermentation 2018, 4(3), 63; https://doi.org/10.3390/fermentation4030063
Received: 7 July 2018 / Revised: 3 August 2018 / Accepted: 7 August 2018 / Published: 9 August 2018
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Abstract
Cupriavidus necator, a facultative hydrogen-oxidizing bacterium, was grown on carbon dioxide, hydrogen, and oxygen for value-added products. High cell density and productivity were the goal of gas fermentation, but limited by gas substrates because of their low solubility in the aqueous medium [...] Read more.
Cupriavidus necator, a facultative hydrogen-oxidizing bacterium, was grown on carbon dioxide, hydrogen, and oxygen for value-added products. High cell density and productivity were the goal of gas fermentation, but limited by gas substrates because of their low solubility in the aqueous medium solution. Enhancement of gas fermentation was investigated by (i) adding n-hexadecane as a gas vector to increase the volumetric mass transfer coefficient (kLa) and gas solubility, (ii) growing C. necator under a raised gas pressure, and (iii) using cell mass hydrolysates as the nutrients of chemolithotrophic growth. In contrast to previous studies, little positive but negative effects of the gas vector were observed on gas mass transfer and cell growth. The gas fermentation could be significantly enhanced under a raised pressure, resulting in a higher growth rate (0.12 h−1), cell density (18 g L−1), and gas uptake rate (200 mmole L−1 h−1) than a fermentation under atmospheric pressure. The gain, however, was not proportional to the pressure increase as predicted by Henry’s law. The hydrolysates of cell mass were found a good source of nutrients and the organic nitrogen was equivalent to or better than ammonium nitrogen for chemolithotrophic growth of C. necator on carbon dioxide. Full article
(This article belongs to the Special Issue Bioprocess and Fermentation Monitoring)
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Open AccessFeature PaperArticle
Performances of Different Metabolic Lactobacillus Groups During the Fermentation of Pizza Doughs Processed from Semolina
Fermentation 2018, 4(3), 61; https://doi.org/10.3390/fermentation4030061
Received: 22 June 2018 / Revised: 30 July 2018 / Accepted: 31 July 2018 / Published: 3 August 2018
Cited by 1 | PDF Full-text (2028 KB) | HTML Full-text | XML Full-text
Abstract
The main hypothesis of this work is that facultative and obligate heterofermentative Lactobacillus species can differently impact the final characteristics of pizza. The objective was to evaluate separately the behavior of the facultative heterofermentative species (FHS), such as Lactobacillus sanfranciscensis, Lactobacillu brevis [...] Read more.
The main hypothesis of this work is that facultative and obligate heterofermentative Lactobacillus species can differently impact the final characteristics of pizza. The objective was to evaluate separately the behavior of the facultative heterofermentative species (FHS), such as Lactobacillus sanfranciscensis, Lactobacillu brevis, and Lactobacillus rossiae, and to obligate the heterofermentative species (OHS), including Lactobacillus plantarum, Lactobacillus graminis, and Lactobacillus curvatus, in the sourdoughs to be used for pizza production. The production of the experimental pizzas was carried out with semolina (Triticum turgidum L. ssp. durum). The acidification process, followed by pH, total titratable acidity (TTA), and lactic acid bacteria (LAB) development indicated for all of the experimental trials kinetics is comparable to those of the controls. The fermentation quotient of the FHS trial was particularly higher than that of the other trials, including the control production performed with a sourdough inoculum used in an artisanal bakery. The dominance of the added strains indicated the clear persistence of L. sanfranciscensis PON 100336, L. brevis 200571, and L. plantarum PON 100148 in the obligate–facultative heterofermentative species (OFHS) trial. The pizzas were baked without seasoning in order to investigate weight loss, color, morphology, and a generation of volatile organic compounds (VOCs). The data showed the differences among trials regarding the inocula. Eight classes of VOCs were detected in the pizza samples with aldehydes, esters, alcohols, and acids as major compounds. The sensory attributes were significantly different for the judges and the pizzas. The multivariate statistical approach found marked differences among the trials. The results indicated that the application of mixed cultures of the facultative heterofermentative species of Lactobacillus determined high quality pizzas. Full article
(This article belongs to the Special Issue Bioprocess and Fermentation Monitoring)
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Open AccessArticle
Enhancement of the Efficiency of Bioethanol Production by Saccharomyces cerevisiae via Gradually Batch-Wise and Fed-Batch Increasing the Glucose Concentration
Fermentation 2018, 4(2), 45; https://doi.org/10.3390/fermentation4020045
Received: 24 May 2018 / Revised: 8 June 2018 / Accepted: 11 June 2018 / Published: 13 June 2018
Cited by 4 | PDF Full-text (1149 KB) | HTML Full-text | XML Full-text
Abstract
High initial glucose concentrations may inhibit glucose utilization and decrease ethanol fermentation efficiency. To minimize substrate inhibition, the effects of feeding yeast with different glucose concentrations on the ethanol production by batch and fed-batch cultures in a 5-L fermentor were investigated. When a [...] Read more.
High initial glucose concentrations may inhibit glucose utilization and decrease ethanol fermentation efficiency. To minimize substrate inhibition, the effects of feeding yeast with different glucose concentrations on the ethanol production by batch and fed-batch cultures in a 5-L fermentor were investigated. When a batch culture system with Saccharomyces cerevisiae was used for ethanol fermentation with glucose concentrations ranging 10–260 g/L, as a result, 0.2–7.0 g/L biomass and 5.1–115.0 g/L ethanol were obtained. However, substrate inhibition was observed with the initial glucose concentrations greater than 200 g/L in the fermentative media. When a fed-batch culture system (an initial glucose concentration of 180 g/L and total glucose concentration of 260 g/L) was performed, the maximum ethanol concentrations and ethanol yield were significantly higher than those of the batch cultures. The cell biomass, maximum ethanol concentration, and ethanol yields for the fed-batch fermentation cultures were 8.3 g/L, 130.1 g/L and 51% (100% of the theoretical value), respectively. The results indicated that high ethanol concentration and ethanol yield could be achieved by the fed-batch cultures with total glucose concentrations up to 260 g/L. Full article
(This article belongs to the Special Issue Bioprocess and Fermentation Monitoring)
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Review

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Open AccessReview
The Use of UV-Vis Spectroscopy in Bioprocess and Fermentation Monitoring
Fermentation 2018, 4(1), 18; https://doi.org/10.3390/fermentation4010018
Received: 11 February 2018 / Revised: 1 March 2018 / Accepted: 7 March 2018 / Published: 13 March 2018
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Abstract
Real-time analytical tools to monitor bioprocess and fermentation in biological and food applications are becoming increasingly important. Traditional laboratory-based analyses need to be adapted to comply with new safety and environmental guidelines and reduce costs. Many methods for bioprocess fermentation monitoring are spectroscopy-based [...] Read more.
Real-time analytical tools to monitor bioprocess and fermentation in biological and food applications are becoming increasingly important. Traditional laboratory-based analyses need to be adapted to comply with new safety and environmental guidelines and reduce costs. Many methods for bioprocess fermentation monitoring are spectroscopy-based and include visible (Vis), infrared (IR) and Raman. This paper describes the main principles and recent developments in UV-Vis spectroscopy to monitor bioprocess and fermentation in different food production applications. Full article
(This article belongs to the Special Issue Bioprocess and Fermentation Monitoring)
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