Fermentation Monitoring Research Articles

Analysis of volatile compounds of Tremella aurantialba fermentation via electronic nose and HS‐SPME‐GC‐MS

AbstractTo detect the odor changes of the volatile compounds during the Tremella aurantialba (T. aurantialba) fermentation associated with its degree, electronic nose (E‐nose) technique, and headspace solid phase microextraction combined with gas chromatography‐mass spectrometry (HS‐SPME‐GC‐MS) analyses were performed each day. E‐nose and GC‐MS were used to recognize the comprehensive aroma characterization and volatile compounds of T. aurantialba fermentation, respectively. Principal component analysis (PCA) were used to analyze the data detected by E‐nose technique and GC‐MS. Support vector machine (SVM) was established to analyze E‐nose date for predicting the different stage of the T. aurantialba fermentation. The main volatile compounds were identified by GC‐MS analysis as alcohols, esters, aldehydes, ketones, heterocyclic, and aromatic compounds. The results of PCA by E‐nose were more similar with that of GC‐MS. The discrimination rates of the SVM model were 100 and 97.14% in the training and testing sets. It can be concluded that E‐nose technique coupled with SVM classification tool has high potential to monitor the fermentation process. These may sufficiently demonstrate excellent promise for the E‐nose technique and GC‐MS method to be applied in the liquid state industry.Practical applicationsE‐nose combined with GC‐MS could detect the odor changes of the volatile compounds during the T. aurantialba fermentation. Both analytical techniques showed good performances in the classification of the fermentation degree of T. aurantialba. These may provide a theoretical basis for the design of the portable electronic nose, which would achieve the real‐time smell monitoring of liquid state fermentation of T. aurantialba associated with its degree of fermentation. This equipment can be used to determine the state of fermentation instead of workers. The E‐nose technique and HS‐SPME‐GC‐MS method could be applied in the liquid state fermentation industry in the future.

Preventing Overflow Metabolism in Crabtree-Positive Microorganisms through On-Line Monitoring and Control of Fed-Batch Fermentations

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.

Hybrid Electronic Tongue as a Tool for the Monitoring of Wine Fermentation and Storage Process

AbstractHybrid electronic tongue based on potentiometric and voltammetric sensors was applied for the monitoring of wine production process. The sensor array formed by miniaturized ion‐selective electrodes and glassy carbon electrodes provided the analysis of the progress and correctness of wine fermentation and storage process, detection of the presence of disturbing factors and evaluation of the quality of final product. The efficiency of the proposed approach was compared with the monitoring of wine production carried out using standard reference methods. The results indicated that hybrid electronic tongue could be used as simple and reliable analytical tool dedicated to qualitative and quantitative assessment of wine production.

The Use of UV-Vis Spectroscopy in Bioprocess and Fermentation Monitoring

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.

Monitoring of starter culture‐initiated liquid wheat and teff sourdough fermentations by selected ion flow tube‐mass spectrometry

Selected ion flow tube-mass spectrometry (SIFT-MS) is a direct-injection mass spectrometric technique that has been introduced recently into the field of food and flavor analysis. It also shows potential for use in the monitoring of food fermentations. Therefore, this study aimed at the online monitoring of different volatile compounds produced during starter culture-initiated liquid sourdough fermentations by SIFT-MS, for which a new workflow was developed. The online monitoring of the volatile sample compounds acetoin and ethyl acetate, diacetyl, and ethanol was made possible during the production of sourdoughs obtained through fermentation with several interesting strains belonging to the species Lactobacillus crustorum, Lactobacillus fermentum, Lactobacillus hilgardii, Lactobacillus nagelii, Lactobacillus sakei, and Gluconobacter oxydans. Acetoin and ethyl acetate could not be distinguished based solely on SIFT-MS data. Diacetyl production was monitored in the case of Lb. crustorum LMG 23699 as a starter culture strain, thereby making the distinction between those volatiles produced in sourdough without extra ingredients added or after the addition of citrate or malate. Starter culture-initiated liquid sourdough fermentations were monitored successfully. The volatile compound production of the different starter culture strains tested reflected differences in their metabolism and/or competitiveness in a sourdough matrix. © 2018 Society of Chemical Industry.

Dielectric Properties of Yogurt for Online Monitoring of Fermentation Process

Yogurt is one of the most popular dairy products fermented by Lactobacillus bulgaricus and Streptococcus thermophilus. The present study introduced dielectric properties as a new technique for yogurt fermentation monitoring. Dielectric properties of cow milk and yogurt at different time of fermentation were measured from 10 to 3000 MHz at 42 °C using open-ended coaxial-line probe technology by an impedance analyzer. Meanwhile, pH and titratable acidity of yogurt at different fermentation time were measured. Results showed that the dielectric loss factor of yogurt was positively correlated with fermentation time and had an irregular change at the endpoint of fermentation (7 h, pH ≈ 4.6). The polynomial determination coefficients of dielectric loss factor with pH and titratable acidity decreased with increasing frequency and were found highest at 10 MHz (0.927 and 0.963, respectively). The linear coefficients of determination between measured values and calculated values were 0.990 for titratable acidity and 0.965 for pH at 10 MHz, respectively. Accordingly, dielectric loss factor can be a promising indicator for online monitoring of industrial yogurt fermentation process.

Real-time monitoring of hyaluronic acid fermentation by in situ transflectance spectroscopy.

Hyaluronic acid (HA) is a high-value polysaccharide with many biomedical applications. Microbial production of HA is now replacing the traditional extraction method from rooster combs. Production of medical-grade HA with defined characteristics requires controlled process conditions because there are many fermentation process parameters that affect the microbial synthesis of HA. This necessitates the development of online tools for monitoring multiple analytes during microbial fermentation. Here, we describe the application of in situ transflectance spectroscopy for online quantification of seven major fermentation analytes, viz. biomass, glucose, lactate, formate, ethanol, acetate and HA in metabolically engineered Lactococcus lactis fermentations. The near-infrared spectral information acquired from synthetic mixtures and untransformed L. lactis fermentations were used to develop chemometric models. Based on principal component analysis and partial least squares regression methods, analyte-specific models were developed for quantification. These models were then independently validated for fermentation analytes from four different recombinant L. lactis strains. The chemometric model developed for HAbased on recombinant L. lactis fermentation data and pure HA standardscould accurately predict HA concentrations under homolactic conditions. The online estimation of HA was found to be poor under heterolactic conditions due to the overlapping absorbance of acetate produced in these cultures. Alternatively, an independent model based on yield correlation was successfully developed for indirect real-time quantification of HA.

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources.

Studies in the field of microbiology rely on the implementation of a wide range of methodologies. In particular, the development of appropriate methods substantially contributes to providing extensive knowledge of the metabolism of microorganisms growing in chemically defined media containing unique nitrogen and carbon sources. In contrast, the management through metabolism of multiple nutrient sources, despite their broad presence in natural or industrial environments, remains virtually unexplored. This situation is mainly due to the lack of suitable methodologies, which hinders investigations. We report an experimental strategy to quantitatively and comprehensively explore how metabolism operates when a nutrient is provided as a mixture of different molecules, i.e., a complex resource. Here, we describe its application for assessing the partitioning of multiple nitrogen sources through the yeast metabolic network. The workflow combines information obtained during stable isotope tracer experiments using selected 13C- or 15N-labeled substrates. It first consists of parallel and reproducible fermentations in the same medium, which includes a mixture of N-containing molecules; however,a selected nitrogen source is labeled each time. A combination of analytical procedures (HPLC, GC-MS) is implemented to assess the labeling patterns of targeted compounds and to quantify the consumption and recovery of substrates in other metabolites. An integrated analysis of the complete dataset provides an overview of the fate of consumed substrates within cells. This approach requires an accurate protocol for the collection of samples-facilitated by a robot-assisted system for online monitoring of fermentations-and the achievement of numerous time-consuming analyses. Despite these constraints, it allowed understanding, for the first time, the partitioning of multiple nitrogen sources throughout the yeast metabolic network. We elucidated the redistribution of nitrogen from more abundant sources toward other N-compounds and determined the metabolic origins of volatile molecules and proteinogenic amino acids.

Multi-capillary Column Ion Mobility Spectrometry of Volatile Metabolites for Phenotyping of Microorganisms.

Rational strain engineering requires solid testing of phenotypes including productivity and ideally contributes thereby directly to our understanding of the genotype-phenotype relationship. Actually, the test step of the strain engineering cycle becomes the limiting step, as ever advancing tools for generating genetic diversity exist. Here, we briefly define the challenge one faces in quantifying phenotypes and summarize existing analytical techniques that partially overcome this challenge. We argue that the evolution of volatile metabolites can be used as proxy for cellular metabolism. In the simplest case, the product of interest is a volatile (e.g., from bulk alcohols to special fragrances) that is directly quantified over time. But also nonvolatile products (e.g., from bulk long-chain fatty acids to natural products) require major flux rerouting that result potentially in altered volatile production. While alternative techniques for volatile determination exist, rather few can be envisaged for medium to high-throughput analysis required for phenotype testing. Here, we contribute a detailed protocol for an ion mobility spectrometry (IMS) analysis that allows volatile metabolite quantification down to the ppb range. The sensitivity can be exploited for small-scale fermentation monitoring. The insights shared might contribute to a more frequent use of IMS in biotechnology, while the experimental aspects are of general use for researchers interested in volatile monitoring.

Chemical and sensory profiling of Shiraz wines co-fermented with commercial non-Saccharomycesinocula

Background and Aims The choice of yeast strain(s) to conduct the fermentation can greatly affect wine chemical and sensory profile. Even though the use of non-Saccharomyces co-inocula to build complexity and diversify styles is increasingly in vogue, a limited number of such products are available to date, and more research is required to guide their use in the wine industry. This study evaluates the potential of commercial yeast inocula to modulate the quality of Shiraz wines at two maturity levels. Methods and Results Vinification outcomes of eight yeast treatments were compared in earlier (24°Brix) and later (29°Brix) harvested Shiraz fruit. Yeast treatments included five non-Saccharomyces products with sequentially inoculated Saccharomyces cerevisiae, a commercial blend of non-Saccharomyces and S. cerevisiae strains, and a S. cerevisiae inoculum. Fermentation monitoring, and comprehensive analytical profiling in terms of basic chemistry, volatile composition, phenolic measurements and descriptive sensory analysis, allowed for the comparison of the resulting wines. Both harvest date and yeast inoculation treatments had a significant impact on a range of compositional and, in turn, sensory parameters of the wines. Conclusions Certain non-Saccharomyces sequential inoculation treatments led to increased appeal of earlier harvest wines compared to the S. cerevisiae Control. These treatments, however, were related to an increased risk of arrested fermentation in higher ripeness conditions. Significance of the Study This study contributes to a better understanding of yeast inoculum-derived modulation of Shiraz wine quality parameters at different maturity levels.

Design and implementation of an ultrasonic sensor for rapid monitoring of industrial malolactic fermentation of wines

ABSTRACTUltrasound is an emerging technology that can be applied to monitor food processes. However, ultrasonic techniques are usually limited to research activities within a laboratory environment and they are not extensively used in industrial processes. The aim of this paper is to describe a novel ultrasonic sensor designed to monitor physical–chemical changes that occur in wines stored in industrial tanks. Essentially, the sensor consists of an ultrasonic transducer in contact with a buffer rod, mounted inside a stainless steel tube section. This structure allows the ultrasonic sensor to be directly installed in stainless steel tanks of an industrial plant. The operating principle of this design is based on the measurement of ultrasonic velocity of propagation. To test its proper operation, the sensor has been used to measure changes of concentration in aqueous samples and to monitor the progress of a malolactic fermentation of red wines in various commercial wineries. Results show the feasibility of using this sensor for monitoring malolactic fermentations in red wines placed in industrial tanks.

Yeast fermentation of sugarcane for ethanol production: Can it be monitored by using in situ microscopy?

ABSTRACT This paper addresses some key issues related to the automation of fermentation process analysis in the context of industrial-scale ethanol production from sugarcane substrates. As the current methods for the determination of cell density and viability are time consuming and laborious, high resolution in situ microscopy (0.5µm) is proposed as a promising alternative. Laboratory-scale experiments presented here show that this imaging technique allows automatic, on-line, and real-time monitoring of yeast cells suspended in sugarcane molasses used in the ethanol industry. In particular, the feasibility of cell concentration measurements of Saccharomyces cerevisiae SA-1 in industrial sugarcane molasses is demonstrated. Automated concentration measurements exhibit a linear correlation with manual reference values using a Neubauer chamber from 3×106 cells/mL up to a saturation level at approximately 2×108 cells/mL. Furthermore, it was demonstrated that the microscopic resolution of this technique, combined with its large statistics, allows a morphological assessment of the size, shape and some internal structures of the yeast cells. On average, the accuracy of the algorithm´s yeast cells classification was 0.80. The results obtained suggest that the ISM is a suitable tool to perform in-line sugarcane fermentation monitoring.

Prediction of black tea fermentation quality indices using NIRS and nonlinear tools.

Catechin content, the ratio of tea polyphenols and free amino acids (TP/FAA), as well as the ratio of theaflavins and thearubigins (TFs/TRs) are important biochemical indicators to evaluate fermentation quality. To achieve rapid determination of such biochemical indicators, synergy interval partial least square and extreme learning machine combined with an adaptive boosting algorithm, Si-ELM-AdaBoost algorithm, were used to establish quantitative analysis models between near infrared spectroscopy (NIRS) and catechin content and between TFs/TRs and TP/FAA, respectively. The results showed that prediction performance of the Si-ELM-AdaBoost mixed algorithm is superior than that of other models. The prediction results with root-mean-square error of prediction ranged from 0.006 to 0.563, the ratio performance deviation values exceeded 2.5, and predictive correlation coefficient values exceeded 0.9 in the prediction model of each biochemical indicator. NIRS combined with Si-ELM-AdaBoost mixed algorithm could be utilized for online monitoring of black tea fermentation. Meanwhile, the AdaBoost algorithm effectively improved the accuracy of the ELM model and could better approach the nonlinear continuous function.

Flow-through sensor based on piezoelectric MEMS resonator for the in-line monitoring of wine fermentation

The traditional procedure followed by winemakers for monitoring grape must fermentation is not automated, has not enough accuracy or has only been tested in discrete must samples. In order to contribute to the automation and improvement of the wine fermentation process, we have designed an AlN-based piezoelectric microresonator, serving as a density sensor, resonantly excited in the 4th-order roof tile-shaped vibration mode. Furthermore, conditioning circuits were designed to convert the one-port impedance of the resonator into a resonant two-port transfer function. This allowed us to design a Phase Locked Loop-based oscillator circuit, implemented with a commercial lock-in amplifier with an oscillation frequency determined by the resonance mode. We measured the fermentation kinetics by simultaneously tracking the resonance frequency and the quality factor of the microresonator. The device was first calibrated with an artificial model solution of grape must and then applied for the in-line monitoring of real grape must fermentation. Our results demonstrate the high potential of MEMS resonators to detect the decrease in sugar and the increase in ethanol concentrations during the grape must fermentation with a resolution of 1mg/ml and 20μPas as upper limits for the density and viscosity, respectively.

The application of near-infrared spectroscopy in beer fermentation for online monitoring of critical process parameters and their integration into a novel feedforward control strategy

Traditional methods used in the analysis of fermentation media suffer from a number of limitations. The search for more rapid and efficient methods has led to the development and application of near-infrared spectroscopy. Near-infrared spectroscopy has been applied successfully in a variety of industrial processes: agricultural, food, chemical and pharmaceutical, generally in the areas of raw material quality control but also including intermediate and finished product testing. The present research explores its potential for online fermentation monitoring of total cell count (TCC), specific gravity (SG), free amino nitrogen (FAN) and percentage alcohol by volume (% v v−1) in a 300 L pilot-scale validation batch. Models that were generated from three calibration batches for each of these constituents exhibited overall favourable standard error of cross validation (SECV) and fit of predicted vs actual cross validated results (SECV, R2): SG (0.00072, 0.995), ethanol (0.17% v v−1, 0.990), FAN (16.5 mg L−1, 0.886) and TCC (1.24 × 106 cells mL−1, 0.640). The data that was most relevant to cell metabolism was determined to be sugar consumption rate, ethanol production rate, yield of ethanol and fermentation lag time. These ‘critical performance parameters’ were incorporated into a novel feed-forward control strategy where yeast pitching rate was modified based on values of the critical performance parameters from the previous batch. Use of this feed-forward strategy demonstrated how brewers can utilize near-infrared monitoring for quality assurance through early detection of shifts in fermentation performance. Copyright © 2017 The Institute of Brewing & Distilling

Potential of Piezoelectric MEMS Resonators for Grape Must Fermentation Monitoring.

In this study grape must fermentation is monitored using a self-actuating/self-sensing piezoelectric micro-electromechanical system (MEMS) resonator. The sensor element is excited in an advanced roof tile-shaped vibration mode, which ensures high Q-factors in liquids (i.e., Q ~100 in isopropanol), precise resonance frequency analysis, and a fast measurement procedure. Two sets of artificial model solutions are prepared, representing an ordinary and a stuck/sluggish wine fermentation process. The precision and reusability of the sensor are shown using repetitive measurements (10 times), resulting in standard deviations of the measured resonance frequencies of ~0.1%, Q-factor of ~11%, and an electrical conductance peak height of ~12%, respectively. With the applied evaluation procedure, moderate standard deviations of ~1.1% with respect to density values are achieved. Based on these results, the presented sensor concept is capable to distinguish between ordinary and stuck wine fermentation, where the evolution of the wine density associated with the decrease in sugar and the increase in ethanol concentrations during fermentation processes causes a steady increase in the resonance frequency for an ordinary fermentation. Finally, the first test measurements in real grape must are presented, showing a similar trend in the resonance frequency compared to the results of an artificial solutions, thus proving that the presented sensor concept is a reliable and reusable platform for grape must fermentation monitoring.

Performance of hybrid electronic tongue and HPLC coupled with chemometric analysis for the monitoring of yeast biotransformation

Monitoring of process parameters is of great importance in the field of bioprocess control. In this work two analytical systems: hybrid electronic tongue combining potentiometric and voltammetric detection (hET) and HPLC coupled with Partial Least Squares (PLS) analysis (HPLC-PLS) have been evaluated and compared as novel, rapid techniques for biotransformation monitoring. They were applied for the analysis of yeast culture media during batch fermentation carried out for 2-phenylethanol production. Work-flow of numerical analysis of sample fingerprints provided by these both techniques was presented. The ability of hET-PLS and HPLC-PLS to predict main process parameters, such as optical density, time of culture, glucose and 2-phenylethanol concentration was studied. Both non-selective analytical systems revealed to be suitable tools for yeast fermentation monitoring, while slightly better results were obtained by hET-PLS.

Monitoring black tea fermentation using a colorimetric sensor array-based artificial olfaction system

The fermentation process plays an important role in black tea's quality control and determination. This article presented a portable artificial olfaction system for real-time monitoring of black tea. Herein, a colorimetric sensor array, which was fabricated by printing 12 chemical dyes, including 9 porphyrins/metalloporphyrins and 3 pH indicators on a C2 reverse silica-get flat plate, was utilized to develop the artificial olfaction system for data acquisition. With specific colorific fingerprint of volatile compounds from black tea, fermentation time can be achieved with efficient chemometrics. Additionally, a novel classification algorithm, which combined K-Nearest Neighbor and adaptive boosting, namely KNN-AdaBoost, was proposed with a comparison of two classical classification algorithms (e.g., KNN and BP-ANN). Results demonstrated that the optimum KNN-AdaBoost model was superior to others with discrimination rate of 100% in both the training and prediction set. The overall results sufficiently reveal that the colorimetric sensor has promising applications in real-time fermentation monitoring. Practical applications The fermentation process plays an important role in black tea's quality control and determination. However, traditional analytical chemical methods (i.e., mass spectrometry, liquid chromatography gas, and gas chromatography-mass spectrometry) can monitor the fermentation process and have some drawbacks, such as complicated operation, high costs of implementation, and lengthy analysis time. This research notably proposed a portable artificial olfaction system for real-time monitoring black tea; and examined the feasibility, accuracy and effectiveness of this sensor. The overall results obtained from this study sufficiently reveals that the colorimetric sensor has promising applications in real-time fermentation monitoring.

Evaluation of a newly developed mid-infrared sensor for real-time monitoring of yeast fermentations

A mid-infrared (MIR) sensor using the attenuated total reflection (ATR) technique has been developed for real-time monitoring in biotechnology. The MIR-ATR sensor consists of an IR emitter as light source, a zinc selenide ATR prism as boundary to the process, and four thermopile detectors, each equipped with an optical bandpass filter. The suitability of the sensor for practical application was tested during aerobic batch-fermentations of Saccharomyces cerevisiae by simultaneous monitoring of glucose and ethanol. The performance of the sensor was compared to a commercial Fourier transform mid-infrared (FT-MIR) spectrometer by on-line measurements in a bypass loop. Sensor and spectrometer were calibrated by multiple linear regression (MLR) in order to link the measured absorbance in the transmission ranges of the four optical sensor channels to the analyte concentrations. For reference analysis, high-performance liquid chromatography (HPLC) was applied. Process monitoring using the sensor yielded in standard errors of prediction (SEP) of 6.15g/L and 1.36g/L for glucose and ethanol. In the case of the FT-MIR spectrometer the corresponding SEP values were 4.34g/L and 0.61g/L, respectively. The advantages of optical multi-channel mid-infrared sensors in comparison to FT-MIR spectrometer setups are the compactness, easy process implementation and lower price.

La cytométrie appliquée aux mircoorganismes du vin

Flow cytometry (FCM) is a powerful technique allowing detection and enumeration of microbial populations in food and during food process. Thanks to the fluorescent dyes used and specific probes, FCM provides information about cell physiological state and allows enumeration of a microorganism in a mixed culture. Thus, this technique is increasingly used to quantify pathogen, spoilage microorganisms and microorganisms of interest. Since one decade, FCM applications to the wine field increase greatly to determine population and physiological state of microorganisms performing alcoholic and malolactic fermentations. We will describe FCM principles and the available techniques allowing quantification of wine microorganisms by FCM using fluorescent dyes. Different examples of FCM analysis regarding monitoring of alcoholic fermentation, malolactic fermentation (total population, viable population, physiological state), specific detection and quantification of spoilage microorganisms like Brettanomyces will be presented.