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

Optimizing the winemaking process: NIR spectroscopy and e-nose analysis for the online monitoring of fermentation

BACKGROUND

In the winemaking process, the rapid determination of specific quality parameters such as sugar content, pH, acidity, concentrations of phenolic compounds, anthocyanins and volatile organic compounds is crucial for high-quality wine production. Traditional analytical methods allow for precise quantification of these parameters but are time-consuming and expensive. This article explores the potential application of non-destructive analytical technique (NDAT) (near infra-red [NIR] and e-nose), as efficient alternatives for online monitoring of fermentation working on two different winemaking tanks and applying chemometrics to develop predictive models to correlate non-destructive and analytical data.

RESULTS

NIR measurements have been used to build principal components regression models, showing good prediction capability for polyphenols, anthocyanins, glucose and fructose. Both offline and online e-nose applications demonstrate good capability of discriminating different fermentation phases, in agreement with aromatic profile changes observed via gas chromatography-mass spectrometry analysis. Moreover, correlation analysis reveals the potential of quartz microbalances, Taguchi Gas Sensors and H2S sensors in predicting the concentration of compounds of great interest for winemaking (e.g. C6 alcohols, ketones, terpenes and ethyl esters) highlighting the robust connection between sensor data and specific chemical classes.

CONCLUSION

This research aims to showcase the potential employment of NDAT for online monitoring the evolution of must composition during fermentation. The proposed methods could potentially fulfil a longstanding requirement of winemakers, enabling them to closely monitor fermentation allowing the timely making of important technical decisions aimed at achieving oenological objectives in wine production. © 2024 Society of Chemical Industry.

Farm to fork applications: how vibrational spectroscopy can be used along the whole value chain?

Vibrational spectroscopy is a nondestructive analysis technique that depends on the periodic variations in dipole moments and polarizabilities resulting from the molecular vibrations of molecules/atoms. These methods have important advantages over conventional analytical techniques, including (a) their simplicity in terms of implementation and operation, (b) their adaptability to on-line and on-farm applications, (c) making measurement in a few minutes, and (d) the absence of dangerous solvents throughout sample preparation or measurement. Food safety is a concept that requires the assurance that food is free from any physical, chemical, or biological hazards at all stages, from farm to fork. Continuous monitoring should be provided in order to guarantee the safety of the food. Regarding their advantages, vibrational spectroscopic methods, such as Fourier-transform infrared (FTIR), near-infrared (NIR), and Raman spectroscopy, are considered reliable and rapid techniques to track food safety- and food authenticity-related issues throughout the food chain. Furthermore, coupling spectral data with chemometric approaches also enables the discrimination of samples with different kinds of food safety-related hazards. This review deals with the recent application of vibrational spectroscopic techniques to monitor various hazards related to various foods, including crops, fruits, vegetables, milk, dairy products, meat, seafood, and poultry, throughout harvesting, transportation, processing, distribution, and storage.

Digital model of biochemical reactions in lactic acid bacterial fermentation of simple glucose and biowaste substrates

As concerns about the environmental impacts of biowaste disposal increase, lactic acid bacterial fermentation is becoming increasingly popular. Current academic research is aimed at the process optimization by developing digital bioreactors. The primary focus is to develop a digital model mimicking the biochemical reactions. In the light of this, this paper intended to build a digital model of biochemical reactions during the fermentation process of both glucose and biowaste substrates, including white pasta and organic municipal waste. For this purpose, near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were used to collect spectral information during the fermentation process. Next, the samples were analyzed by High Pressure Liquid Chromatography (HPLC) to measure their glucose, fructose, arabinose, xylose, disaccharide, lactic acid, and acetic acid contents. The results showed that learning algorithms trained on MIR spectra accurately estimated the biochemical reactions for both glucose and biowaste substrates. For the glucose substrate, the results showed R-squared of 0.97 and RMSE of 4.69 g/L for glucose, and R-squared of 0.98 and RMSE of 2.74 g/L for lactic acid. In the case of biowaste substrate, estimations included glucose (R-squared = 0.97, RMSE = 4.69 g/L), fructose (R-squared = 0.88, RMSE = 1.47 g/L), arabinose (R-squared = 0.98, RMSE = 0.55 g/L), xylose (R-squared = 0.93, RMSE = 1.11 g/L), disaccharide (R-squared = 0.90, RMSE = 0.55 g/L), total sugar (R-squared = 0.98, RMSE = 3.79 g/L), lactic acid (R-squared = 0.98, RMSE = 2.74 g/L), and acetic acid (R-squared = 0.97, RMSE = 0.36 g/L). Regarding NIR spectral data, the predictive models were accurate when the substrate was glucose, however, they failed to accurately estimate the chemical reactions in the case of biowaste substrate. The findings of this study can be used to fulfill the requirements for a continuous fermentation process with the objective of maximizing lactic acid production.

Assessment of Variability Sources in Grape Ripening Parameters by Using FTIR and Multivariate Modelling

The variability in grape ripening is associated with the fact that each grape berry undergoes its own biochemical processes. Traditional viticulture manages this by averaging the physicochemical values of hundreds of grapes to make decisions. However, to obtain accurate results it is necessary to evaluate the different sources of variability, so exhaustive sampling is essential. In this article, the factors "grape maturity over time" and "position of the grape" (both in the grapevine and in the bunch/cluster) were considered and studied by analyzing the grapes with a portable ATR-FTIR instrument and evaluating the spectra obtained with ANOVA-simultaneous component analysis (ASCA). Ripeness over time was the main factor affecting the characteristics of the grapes. Position in the vine and in the bunch (in that order) were also significantly important, and their effect on the grapes evolves over time. In addition, it was also possible to predict basic oenological parameters (TSS and pH with errors of 0.3 °Brix and 0.7, respectively). Finally, a quality control chart was built based on the spectra obtained in the optimal state of ripening, which could be used to decide which grapes are suitable for harvest.

Physicochemical and biological ageing processes of (micro)plastics in the environment: a multi-tiered study on polyethylene

Pollution by plastic and microplastic impacts the environment globally. Knowledge on the ageing mechanisms of plastics in natural settings is needed to understand their environmental fate and their reactivity in the ecosystems. Accordingly, the study of ageing processes is gaining focus in the context of the environmental sciences. However, laboratory-based experimental research has typically assessed individual ageing processes, limiting environmental applicability. In this study, we propose a multi-tiered approach to study the environmental ageing of polyethylene plastic fragments focusing on the combined assessment of physical and biological processes in sequence. The ageing protocol included ultraviolet irradiation in air and in a range of water solutions, followed by a biofouling test. Changes in surface characteristics were assessed by Fourier transform infrared spectroscopy, scanning electron microscopy, and water contact angle. UV radiation both in air and water caused a significant increase in the density of oxidized groups (i.e., hydroxyl and carbonyl) on the plastic surface, whereby water solution chemistry influenced the process both by modulating surface oxidation and morphology. Biofouling, too, was a strong determinant of surface alterations, regardless of the prior irradiation treatments. All biofouled samples present (i) specific infrared bands of new surface functional groups (e.g., amides and polysaccharides), (ii) a further increase in hydroxyl and carbonyl groups, (iii) the diffuse presence of algal biofilm on the plastic surface, and (iv) a significant decrease in surface hydrophobicity. This suggests that biological-driven alterations are not affected by the level of physicochemical ageing and may represent, in real settings, the main driver of alteration of both weathered and pristine plastics. This work highlights the potentially pivotal role of biofouling as the main process of plastic ageing, providing useful technical insights for future experimental works. These results also confirm that a multi-tiered laboratory approach permits a realistic simulation of plastic environmental ageing in controlled conditions.

Fourier transform infrared spectroscopy in monitoring the wine production

The complexity of the wine matrix makes monitoring of the winemaking process from the grapes to the final product crucial for the wine industry. In this context, analytical methodologies that can combine good accuracy, robustness, high sample throughput, “green character”, and by preference real-time analysis, are on-demand to create high-quality vitivinicultural products. In the last years, Fourier-transform Infrared Spectroscopy (FTIR) combined with chemometric analysis has been evaluated in several studies as an effective analytical tool for the wine sector. Some applications of FTIR spectroscopy have been already accepted by the wine industry, mainly for the prediction of basic oenological parameters, using portable and non-portable instruments, but still many others are waiting to be thoroughly developed. This literature review aims to provide a critical synopsis of the most important studies assessing grape and wine quality and authenticity, and to identify possible gaps for further research, meeting the needs of the modern wine industry and the expectations of most demanding consumers. The FTIR studies were grouped according to the main sampling material used - 1) leaves, stems, and berries; 2) grape must and wine applications - along with a summary of the basic limitations and future perspectives of this analytical technique.

Optimisation of PLS Calibrations for Filtered and Untreated Samples towards In-Line Monitoring of Phenolic Extraction during Red-Wine Fermentations

Infrared spectroscopy provides an efficient, robust, and multivariate means to measure phenolic levels during red-wine fermentations. However, its use is currently limited to off-line sampling. In this study, partial least squares (PLS) regression was used to investigate the possibility of using spectral data from minimally pre-treated or untreated samples for the optimisation of prediction calibrations towards an in-line monitoring set-up. The evaluation of the model performance was conducted using a variety of metrics. Limits of detection and quantification of the PLS calibrations were used to assess the ability of the models to predict lower levels of phenolics from the start of fermentation. The calibrations were shown to be useful for the quantification of phenolic compounds and phenolic parameters with minimal or no sample pre-treatment during red-wine fermentation. Upon evaluation of performance, the calibrations built for attenuated-transmission Fourier-transform mid-infrared (ATR-FT-MIR) and diffuse-reflectance Fourier-transform near-infrared (DR-FT-NIR) were shown to be the most suitable spectroscopy techniques for eventual application in an automated and in-line system with values for limits of detection and quantification being suitable for the entire duration of fermentation.

Biospectroscopy and chemometrics as an analytical tool for comparing the antibacterial mechanism of silver nanoparticles with popular antibiotics against Escherichia coli

Despite the fact that silver nanoparticles (AgNPs) have been widely studied in medical and correlated fields, details on their mechanisms are yet to be fully understood. Herein we present the first study on the combination of infrared spectroscopy and chemometrics as an analytical tool to investigate the mechanism of action of AgNPs against Escherichia coli by comparison with popular and commercially available antibiotics. The rationale behind this study is that the selected antibiotics act on bacteria in specific and distinct manners (DNA, cell membrane, mitochondria, etc.). Hence, via multivariate analysis we were able to compare the spectra of bacteria treated with the antibiotics and AgNPs to determine the main target of the latter. Spectral comparison, exploratory analysis, clustering and classification based on infrared spectra were carried out for E. coli samples in the absence and presence (treated) of four widely known antibiotics (ampicillin, ciprofloxacin, gentamicin and sulfadiazine) as well as RA-AgNPs and ERA-AgNPs. Chemometrics models indicated an interesting similarity between infrared spectra from E. coli treated with sulfadiazine and AgNPs, in which vibrational modes associated to phosphate groups were found to be the most representative. This result suggests that both AgNPs and sulfadiazine affects DNA structural features and availability, but not necessarily through the same mechanism. This biospectroscopy-based approach opens an interesting possibility for the understanding over the mechanism of antibacterial activity of AgNPs.

Prediction of wine sensory properties using mid-infrared spectra of Cabernet Sauvignon and Chardonnay grape berries and wines

The study determined optimal parameters to four preprocessing techniques for mid-infrared (MIR) spectra of wines and grape berry homogenates and tested MIR's ability to model sensory properties of research Cabernet Sauvignon and Chardonnay wines. Savitsky-Golay (SG) derivative, smoothing points, and polynomial order, and extended multiplicative signal correction (EMSC) polynomial were investigated as preprocessing techniques at 2, 2, 5, and 3 levels, respectively, all in combination. Preprocessed data were analysed with partial least squares regression (PLS) to model the wine sensory data and the regression coefficients of PLS calibration models (R²) were further analysed with multivariate analysis of variance (MANOVA). SG transformations were significant factors from the MANOVA that influenced R², while EMSC did not. Overall, PLSR models that predicted wine sensory characteristics gave a poor to moderate R². Consistently predicting wine sensory attributes within a variety and across vintages is challenging, regardless of using grape or wine spectra as predictors.