Fermentation Monitoring Research Articles

Fermentation monitoring by Bayesian states estimators. Application to red wines elaboration

Winemakers must understand all chemical aspects involved and make the right decisions to obtain a high quality product. In a winemaking process, the tracking and control of certain variables are keys to achieve a proper fermentation. This paper presents state estimators design based on Gaussian processes, for on-line alcoholic fermentation monitoring in red wines. For this study, 18 fermentations of three different varietals, Cabernet Sauvignon, Malvec and Tannat, were analyzed to train and validate the estimators. Samples were taken from Merced del Estero, a San Juan industrial winery. Then, cell concentration was determined by neubauer chamber count, while ethanol and total sugars concentrations by infrared absorption spectroscopy. Results show a suitable prediction of cell and ethanol content when only substrate measurement is available. Furthermore, the proposed estimator is compared with a competitive approach (neural network) to highlight the suitability of Bayesian theory for this type of application. This paper provides a reliable monitoring tool, with low computational and economic cost to facilitate the work of winemakers.

On-line analysis and in situ pH monitoring of mixed acid fermentation by Escherichia coli using combined FTIR and Raman techniques

We introduce an experimental setup allowing continuous monitoring of bacterial fermentation processes by simultaneous optical density (OD) measurements, long-path FTIR headspace monitoring of CO2, acetaldehyde and ethanol, and liquid Raman spectroscopy of acetate, formate, and phosphate anions, without sampling. We discuss which spectral features are best suited for detection, and how to obtain partial pressures and concentrations by integrations and least squares fitting of spectral features. Noise equivalent detection limits are about 2.6 mM for acetate and 3.6 mM for formate at 5 min integration time, improving to 0.75 mM for acetate and 1.0 mM for formate at 1 h integration. The analytical range extends to at least 1 M with a standard deviation of percentage error of about 8%. The measurement of the anions of the phosphate buffer allows the spectroscopic, in situ determination of the pH of the bacterial suspension via a modified Henderson-Hasselbalch equation in the 6–8 pH range with an accuracy better than 0.1. The 4 m White cell FTIR measurements provide noise equivalent detection limits of 0.21 μbar for acetaldehyde and 0.26 μbar for ethanol in the gas phase, corresponding to 3.2 μM acetaldehyde and 22 μM ethanol in solution, using Henry’s law. The analytical dynamic range exceeds 1 mbar ethanol corresponding to 85 mM in solution. As an application example, the mixed acid fermentation of Escherichia coli is studied. The production of CO2, ethanol, acetaldehyde, acids such as formate and acetate, and the changes in pH are discussed in the context of the mixed acid fermentation pathways. Formate decomposition into CO2 and H2 is found to be governed by a zeroth-order kinetic rate law, showing that adding exogenous formate to a bioreactor with E. coli is expected to have no beneficial effect on the rate of formate decomposition and biohydrogen production.

A New Possibility for Fermentation Monitoring by Electrical Driven Sensing of Ultraviolet Light and Glucose.

Industrial fermentation generates products through microbial growth associated with the consumption of substrates. The efficiency of industrial production of high commercial value microbial products such as ethanol from glucose (GLU) is dependent on bacterial contamination. Controlling the sugar conversion into products as well as the sterility of the fermentation process are objectives to be considered here by studying GLU and ultraviolet light (UV) sensors. In this work, we present two different approaches of SnO2 nanowires grown by the Vapor–Liquid–Solid (VLS) method. In the GLU sensor, we use SnO2 nanowires as active electrodes, while for the UV sensor, a nanowire film was built for detection. The results showed a wide range of GLU sensing and as well as a significant influence of UV in the electrical signal. The effect of a wide range of GLU concentrations on the responsiveness of the sensor through current–voltage based on SnO2 nanowire films under different concentration conditions ranging was verified from 1 to 1000 mmol. UV sensors show a typical amperometric response of SnO2 nanowires under the excitation of UV and GLU in ten cycles of 300 s with 1.0 V observing a stable and reliable amperometric response. GLU and UV sensors proved to have a promising potential for detection and to control the conversion of a substrate into a product by GLU control and decontamination by UV control in industrial fermentation systems.

Metabolome segregation of four strains of Saccharomyces cerevisiae, Saccharomyces uvarum and Saccharomyces kudriavzevii conducted under low temperature oenological conditions

The monitoring of fermentation at low temperatures (12-15°C) is a current practice in the winery for retention and enhancement of the flavour volatile content of wines. Among Saccharomyces species, Saccharomyces uvarum and Saccharomyces kudriavzevii have revealed interesting industrial properties, including better adaptation at low temperatures. To gather deeper knowledge of the fermentative metabolism at a low temperature of these species together with S. cerevisiae, we performed a comparative metabolomic analysis using four representative strains. We used batch cultures to obtain an exhaustive and dynamic image of the metabolome of strains passing through the sequential stresses related to the winemaking environment. A great variety of intra- and extracellular metabolites (>500 compounds) were quantified across fermentation using distinct chromatographic methods. Besides a global decrease in the lipid composition of the four strains when they entered into the stationary phase, we reported some strain-specific high magnitude changes. Examples of these differences included divergent patterns of production of short-chain fatty acids and erythritol in the S. uvarum strain. Strains also differed in expression for aromatic amino acid biosynthesis and sulphur metabolism, including the glutathione pathway. These data will allow us to refine and obtain the most value of fermentations with this alternative Saccharomyces species.

Data fusion of UPLC data, NIR spectra and physicochemical parameters with chemometrics as an alternative to evaluating kombucha fermentation

Kombucha consumption has become popular due to health benefits and sensorial properties. Different analytical techniques were associated with unsupervised chemometrics to evaluate kombucha fermentation using a low-level data fusion strategy. Kombucha was prepared from green and black teas (Camellia sinensis). The samples were analyzed by ultra-performance liquid chromatography (UPLC), portable near-infrared spectroscopy (NIR), and physicochemical analyses (ethanol, pH, total reducing sugars, and total titratable acidity). Also, the bioactive phenolic compounds were evaluated in the fermented samples. The merged results were analyzed by principal component analysis (PCA). The PCA was applied to discriminate substrate for kombucha production and the fermentation time. Although the fermentation behavior was similar for both substrates, the kombucha showed quantitative differences in physicochemical parameters. They also showed differences in bioactive compounds for each kombucha. Data fusion strategy was more effective to differentiate the two types of kombucha than single analysis. The portable NIR can be a reliable and robust analysis for fermentation monitoring. Moreover, the results can be used as a base to further studies and mainly to help in which substrate composition is better to be produced on an industrial scale.

Population dynamics of Saccharomyces cerevisiae PE-2 and CAT-1 in CO-culture for the production of ethanol

In the Brazilian industries, the inoculum used throughout the harvest of ethanol production consists of a combination of two or more yeast strains. The combination of yeasts may influence in the metabolic pathways of microorganisms and increase the yields and production rates of some compounds. In biotechnological processes with co-culture, one microorganism can prevail over the other. Therefore, the knowledge about how the population dynamics occurs during fermentation allows modifications in the process in order to obtain higher yields and to achieve greater fermentative efficiency. The aim of this study was to investigate the fermentation with synthetic sugar cane broth in co-culture of Saccharomyces cerevisiae strains CAT-1 and PE-2 followed by molecular fermentation monitoring. The concentration of biomass, ethanol, glycerol, acetic acid and residual sucrose were monitored to verify the influence of different combinations during the fermentation. The mixture of CAT-1 and PE-2 presented the highest ethanol production, with higher performance of fermentative parameters than pure cultures

PTR-ToF-MS for the Online Monitoring of Alcoholic Fermentation in Wine: Assessment of VOCs Variability Associated with Different Combinations of Saccharomyces/Non-Saccharomyces as a Case-Study

The management of the alcoholic fermentation (AF) in wine is crucial to shaping product quality. Numerous variables (e.g., grape varieties, yeast species/strains, technological parameters) can affect the performances of this fermentative bioprocess. The fact that these variables are often interdependent, with a high degree of interaction, leads to a huge ‘oenological space’ associated with AF that scientists and professionals have explored to obtain the desired quality standards in wine and to promote innovation. This challenge explains the high interest in approaches tested to monitor this bioprocess including those using volatile organic compounds (VOCs) as target molecules. Among direct injection mass spectrometry approaches, no study has proposed an untargeted online investigation of the diversity of volatiles associated with the wine headspace. This communication proposed the first application of proton-transfer reaction-mass spectrometry coupled to a time-of-flight mass analyzer (PTR-ToF-MS) to follow the progress of AF and evaluate the impact of the different variables of wine quality. As a case study, the assessment of VOC variability associated with different combinations of Saccharomyces/non-Saccharomyces was selected. The different combinations of microbial resources in wine are among the main factors susceptible to influencing the content of VOCs associated with the wine headspaces. In particular, this investigation explored the effect of multiple combinations of two Saccharomyces strains and two non-Saccharomyces strains (belonging to the species Metschnikowia pulcherrima and Torulaspora delbrueckii) on the content of VOCs in wine, inoculated both in commercial grape juice and fresh grape must. The results demonstrated the possible exploitation of non-invasive PTR-ToF-MS monitoring to explore, using VOCs as biomarkers, (i) the huge number of variables influencing AF in wine, and (ii) applications of single/mixed starter cultures in wine. Reported preliminary findings underlined the presence of different behaviors on grape juice and on must, respectively, and confirmed differences among the single yeast strains ‘volatomes’. It was one of the first studies to include the simultaneous inoculation on two non-Saccharomyces species together with a S. cerevisiae strain in terms of VOC contribution. Among the other outcomes, evidence suggests that the addition of M. pulcherrima to the coupled S. cerevisiae/T. delbrueckii can modify the global release of volatiles as a function of the characteristics of the fermented matrix.

Automated Electrochemical Glucose Biosensor Platform as an Efficient Tool Toward On-Line Fermentation Monitoring: Novel Application Approaches and Insights.

Monitoring and control of fermentation processes remain a crucial challenge for both laboratory and industrial-scale experiments. Reliable identification and quantification of the key process parameters in on-line mode allow operation of the fermentation at optimal reactor efficiency, maximizing productivity while minimizing waste. However, state-of-the-art fermentation on-line monitoring is still limited to a number of standard measurements such as pH, temperature and dissolved oxygen, as well as off-gas analysis as an advanced possibility. Despite the availability of commercial biosensor-based platforms that have been established for continuous monitoring of glucose and various biological variables within healthcare, on-line glucose quantification in fermentation processes has not been implemented yet to a large degree. For the first time, this work presents a complete study of a commercial flow-through-cell with integrated electrochemical glucose biosensors (1st generation) applied in different media, and importantly, at- and on-line during a yeast fed-batch fermentation process. Remarkably, the glucose biosensor–based platform combined with the developed methodology was able to detect glucose concentrations up to 150 mM in the complex fermentation broth, on both cell-free and cell-containing samples, when not compromised by oxygen limitations. This is four to six-fold higher than previously described in the literature presenting the application of biosensors predominately toward cell-free fermentation samples. The automated biosensor platform allowed reliable glucose quantification in a significantly less resource and time (<5 min) consuming manner compared to conventional HPLC analysis with a refractive index (RI) detector performed as reference measurement. Moreover, the presented biosensor platform demonstrated outstanding mechanical stability in direct contact with the fermentation medium and accurate glucose quantification in the presence of various electroactive species. Coupled with the developed methodology it can be readily considered as a simple, robust, accurate and inexpensive tool for real-time glucose monitoring in fermentation processes.

Extended fed-batch fermentation of a C5/C6 optimised yeast strain on wheat straw hydrolysate using an online refractive index sensor to measure the relative fermentation rate

In the production of 2nd generation ethanol, using Saccharomyces cerevisiae, the highest productivity obtained using C5/C6 fermenting yeast is in the co-fermentation phase, in which xylose and glucose are fermented simultaneously. Extending this phase in a fed-batch process increases the yield, rate and additionally reduces needed yeast amount for pitching. Extending this phase, as long as possible, would further enhance yield and economy of the process. To realise the concept a fermentation monitoring technique was developed and applied. Based on online measured refractive index an optimal residual sugar concentration could be maintained in the primary fermentor during the feed phase, requiring little knowledge of the nature of the substrate. The system was able to run stably for at least five fermentor volumes giving an ethanol yield >90% throughout the run. This was achieved with addition of only urea to the wheat straw hydrolysate and with an initial yeast pitch of 0.2 g/L total of finished broth. It has the potential to improve the fermentation technology used in fuel ethanol plants, which could help to meet the growing demand for more sustainable fuels.

Redox potential as a key parameter for monitoring and optimization of xylose fermentation with yeast Spathaspora passalidarum under limited-oxygen conditions.

The determination of optimum values of volumetric oxygen transfer coefficient (kLa) for Spathaspora passalidarum is an important aspect for the optimization of ethanol production from pentoses since oxygen plays a key role on yeast metabolism. By studying the fermentation of a xylose and glucose mixture, the highest ethanol volumetric productivity was achieved at a kLa of 45h-1 (1.12gethanol L-1h-1), reducing the fermentation time to half when compared to other oxygen-limiting conditions that were considered optimum for other native strains, besides increasing xylose consumption rates. The high cell density fermentation showed to be a good strategy to be applied in industrial processes with S. passalidarum, enabling the complete exhaustion of a high initial substrate concentration (90gL-1) in less than 24h, with a final ethanol titer of 28.61 (± 0.42) gL-1. By performing a detailed investigation on oxidation-reduction potential (ORP), it was possible to conclude that the highest ethanol formation rates were registered at oxireduction potential values around - 100mV, becoming an important parameter to be controlled when oxygen-limiting conditions are applied in industrial fermentations. The oxygen availability also affected the activity of enzyme XR and its preference for NADH or NADPH, directly affecting the activity of enzyme XDH and the redox imbalance on the xylose pathway. In addition, respirometric parameters were determined for the yeast S. passalidarum under an aerobic growth condition.

Progress in Electrochemical (Bio)Sensors for Monitoring Wine Production

Electrochemical sensors and biosensors have been proposed as fast and cost effective analytical tools, meeting the robustness and performance requirements for industrial process monitoring. In wine production, electrochemical biosensors have proven useful for monitoring critical parameters related to alcoholic fermentation (AF), malolactic fermentation (MLF), determining the impact of the various technological steps and treatments on wine quality, or assessing the differences due to wine age, grape variety, vineyard or geographical region. This review summarizes the current information on the voltamperometric biosensors developed for monitoring wine production with a focus on sensing concepts tested in industry-like settings and on the main quality parameters such as glucose, alcohol, malic and lactic acids, phenolic compounds and allergens. Recent progress featuring nanomaterial-enabled enhancement of sensor performance and applications based on screen-printed electrodes is emphasized. A case study presents the monitoring of alcoholic fermentation based on commercial biosensors adapted with minimal method development for the detection of glucose and phenolic compounds in wine and included in an automated monitoring system. The current challenges and perspectives for the wider application of electrochemical sensors in monitoring industrial processes such as wine production are discussed.

Monitoring the Progress of Lactic Acid Fermentation in Yogurt Manufacturing Using Terahertz Time-Domain–Attenuated Total-Reflection Spectroscopy

Lactic acid fermentation in yogurt manufacturing can be monitored using terahertz (THz)-attenuated total-reflection (ATR) spectroscopy. Yogurt manufacturing was performed on an ATR prism. The THz absorption coefficient and pH were measured for the entire 1000 min of the fermentation process. The absorption spectra were similar to the spectrum of water at the THz range. Temporal changes in the absorption coefficient at 0.4, 1.0, and 1.6 THz all decreased during the fermentation process, with two inflection points. The absolute value of the change in temporal absorption was greater at high frequencies than at low frequencies. However, the normalized absorption coefficient was larger at 0.4 THz. Because temporal changes in absorption corresponded with temporal changes in pH, the absorption changes appeared to be caused by the decomposition of the milk ingredients during the lactic acid fermentation. THz measurements can therefore be applied to the nondestructive monitoring of lactic acid fermentation in yogurt manufacturing.

ATR-MIR spectroscopy and multivariate analysis in alcoholic fermentation monitoring and lactic acid bacteria spoilage detection

Wine production processes still rely on post-production evaluation and off-site laboratory analyses to ensure the quality of the final product. Here we propose an at-line methodology that combines a portable ATR-MIR spectrometer and multivariate analysis to control the alcoholic fermentation process and to detect wine fermentation problems. In total, 36 microvinifications were conducted, 14 in normal fermentation conditions (NFC) and 22 intentionally contaminated fermentations (ICF) with different lactic acid bacteria (LAB) concentrations. ATR-MIR measurements were collected during alcoholic and malolactic fermentations and relative density, pH, and l-malic acid were analyzed by traditional methods. Partial Least Squares Regression could suitably predict density and pH in fermenting samples (root mean squared errors of prediction of 0.0014 g mL−1 and 0.06 respectively). With regard to ICF, LAB contamination was detected by multivariate discriminant analysis when the difference in l-malic acid concentration between NFC and ICF was in the order of 0.7–0.8 g L−1, before the end of malolactic fermentation. This methodology shows great potential as a fast and simple at-line analysis tool for detecting fermentation problems at an early stage.

Application of green analytical chemistry to a green chemistry process: Magnetic resonance and Raman spectroscopic process monitoring of continuous ethanolic fermentation.

Compact 1 H NMR and Raman spectrometers were used for real-time process monitoring of alcoholic fermentation in a continuous flow reactor. Yeast cells catalyzing the sucrose conversion were immobilized in alginate beads floating in the reactor. The spectrometers proved to be robust and could be easily attached to the reaction apparatus. As environmentally friendly analysis methods, 1 H NMR and Raman spectroscopy were selected to match the resource- and energy-saving process. Analyses took only a few seconds to minutes compared to chromatographic procedures and were, therefore, suitable for real-time control realized as a feedback loop. Both compact spectrometers were successfully implemented online. Raman spectroscopy allowed for faster spectral acquisition and higher quantitative precision, NMR yielded more resolved signals thus higher specificity. By using the software Matlab for automated data loading and processing, relevant parameters such as the ethanol, glycerol, and sugar content could be easily obtained. The subsequent multivariate data analysis using partial linear least-squares regression type 2 enabled the quantitative monitoring of all reactants within a single model in real time.

Inline noninvasive Raman monitoring and feedback control of glucose concentration during ethanol fermentation.

Raman spectroscopy as a process analytical technology tool was implemented for the monitoring and control of ethanol fermentation carried out with Saccharomyces cerevisiae. The need for the optimization of bioprocesses such as ethanol production, to increase product yield, enhanced the development of control strategies. The control system developed by the authors utilized noninvasive Raman measurements to avoid possible sterilization problems. Real-time data analysis was applied using partial least squares regression (PLS) method. With the aid of spectral pretreatment and multivariate data analysis, the monitoring of glucose and ethanol concentration was successful during yeast fermentation with the prediction error of 4.42 g/L for glucose and 2.40 g/L for ethanol. By Raman spectroscopy-based feedback control, the glucose concentration was maintained at 100 g/L by the automatic feeding of concentrated glucose solution. The control of glucose concentration during fed-batch fermentation resulted in increased ethanol production. Ethanol yield of 86% was achieved compared to the batch fermentation when 75% yield was obtained. The results show that the use of Raman spectroscopy for the monitoring and control of yeast fermentation is a promising way to enhance process understanding and achieve consistently high production yield.

Comparison of Raman and Mid-Infrared Spectroscopy for Real-Time Monitoring of Yeast Fermentations: A Proof-of-Concept for Multi-Channel Photometric Sensors

Comparison of Raman and Mid-Infrared Spectroscopy for Real-Time Monitoring of Yeast Fermentations: A Proof-of-Concept for Multi-Channel Photometric Sensors

Comparison of Raman and Mid-Infrared Spectroscopy for Real-Time Monitoring of Yeast Fermentations: A Proof-of-Concept for Multi-Channel Photometric Sensors

Raman and mid-infrared (MIR) spectroscopy are useful tools for the specific detection of molecules, since both methods are based on the excitation of fundamental vibration modes. In this study, Raman and MIR spectroscopy were applied simultaneously during aerobic yeast fermentations of Saccharomyces cerevisiae. Based on the recorded Raman intensities and MIR absorption spectra, respectively, temporal concentration courses of glucose, ethanol, and biomass were determined. The chemometric methods used to evaluate the analyte concentrations were partial least squares (PLS) regression and multiple linear regression (MLR). In view of potential photometric sensors, MLR models based on two (2D) and four (4D) analyte-specific optical channels were developed. All chemometric models were tested to predict glucose concentrations between 0 and 30 g L−1, ethanol concentrations between 0 and 10 g L−1, and biomass concentrations up to 15 g L−1 in real time during diauxic growth. Root-mean-squared errors of prediction (RMSEP) of 0.68 g L−1, 0.48 g L−1, and 0.37 g L−1 for glucose, ethanol, and biomass were achieved using the MIR setup combined with a PLS model. In the case of Raman spectroscopy, the corresponding RMSEP values were 0.92 g L−1, 0.39 g L−1, and 0.29 g L−1. Nevertheless, the simple 4D MLR models could reach the performance of the more complex PLS evaluation. Consequently, the replacement of spectrometer setups by four-channel sensors were discussed. Moreover, the advantages and disadvantages of Raman and MIR setups are demonstrated with regard to process implementation.

Perfusion Microfermentor Integrated into a Fiber Optic Quasi-Elastic Light Scattering Sensor for Fast Screening of Microbial Growth Parameters.

This research presents a microfermentor integrated into an optical fiber sensor based on quasi-elastic light scattering (QELS) to monitor and swiftly identify cellular growth kinetic parameters. The system uses a 1310 nm laser light that is guided through single-mode silica optical fibers to the interior of perfusion chambers, which are separated by polycarbonate membranes (470 nm pores) from microchannels, where a culture medium flows in a constant concentration. The system contains four layers, a superior and an inferior layer made of glass, and two intermediate poly(dimethylsiloxane) layers that contain the microchannels and the perfusion chambers, forming a reversible microfluidic device that requires only the sealing of the fibers to the inferior glass cover. The QELS autocorrelation decay rates of the optical signals were correlated to the cells counting in a microscope, and the application of this microsystem to the monitoring of alcoholic fermentation of Saccharomyces cerevisiae resulted in the kinetic parameters of KM = 4.1 g/L and μm = 0.49 h−1. These results agree with both the data reported in the literature and with the control batch test, showing that it is a reliable and efficient biological monitoring system.

Isothermal calorimetry for monitoring of grape juice fermentation with yeasts immobilized on nylon-6 nanofibrous membranes

Isothermal microcalorimetry is often used to monitor microbiological activity and growth in various types of biological samples. Usually, it is useful to convert the isothermal microcalorimetry data into biologically meaningful data such as growth rate, lag phase or maximum growth. In this work, isothermal calorimetry was applied for monitoring of grape juice fermentation by Saccharomyces cerevisiae immobilized in nylon-6 nanofibrous membranes (NFM) prepared by electrospinning in comparison with freely dispersed yeasts. The resulting heat flow can be fitted using various approaches applying graphical, exponential, Gompertz, modified logistic and Michaelis–Menten models. Advantages and drawbacks of each approach for monitoring of the immobilized yeasts have been discussed in relation to the S. cerevisiae yeasts. Analysis of the fitting parameters showed that immobilized yeasts had the highest growth rate and maximum growth in comparison with freely dispersed yeasts. Parallel measurements of sugar and oxygen consumption rates for immobilized and free yeasts cells confirmed the calorimetric data. The results of this work demonstrate practical approach to analysis and modeling of calorimetric data in food analysis and advantages of application of NFM as solid support for yeast immobilization.

Electrochemical Glucose Quantification as a Strategy for Ethanolic Fermentation Monitoring

The possibility of using an electrochemical biosensor, using screen-printed electrodes modified with a carbonaceous material and a commercial kit for the determination of glucose, to monitor an ethanolic fermentation was analyzed. The determination is based on the electrochemical oxidation reaction of NADH that occurs at a potential where the components of the kit do not generate a current signal, even in the presence of the fermentation medium. The electrochemical system was used to analyze the variation of glucose concentration during a laboratory-scale fermentation. The results were contrasted with the variation of standard characterization parameters such as pH, total soluble solids (TSS), the viability of the yeast, and concentration of ethanol produced. Of these values, the total soluble solids should be related to the concentration of glucose obtained by the electrochemical sensor, however, this last measure is more specific for sugar since the TSS refers to all soluble solids. The obtained results allow us to verify the usefulness of the electrochemical method for real-time monitoring of a fermentation.