Near-infrared Spectroscopy in the Brewing Industry

Fast and Reliable On-Site Quality Assessment of Essential Raw Brewing Materials Using MicroNIR and Chemometrics

The interest in the quality control of the raw materials, intermediates, and final products, as well as production methods, of beer has increased significantly in recent decades due to the needs and expectations of consumers. Increasing in the industrialization and globalization of beer supply chains led to a need for novel analytical tools suitable for the rapid and reliable characterization of the materials involved. In this study, an ultracompact instrument operating in the NIR region of the spectrum, microNIR, was tested for the chemical investigation of barley malts. The essential raw materials for brewing require careful control since they deeply affect the characteristic flavor and taste of the final products. Therefore, a robust prediction model able to classify base and specialty barley malts was developed starting from NIR measurements. Soft Independent Class Analogy (SIMCA) was selected as the chemometric technique for the optimization of two prediction models, and ground and sieved materials were investigated using spectroscopy. The microNIR/chemometric approach proposed in this study permitted the correct prediction of the malt samples included in the external validation set, providing false positive and false negative rates no higher than 3.41% and 0.25%, respectively, and confirming the feasibility of the novel analytical platform.

An Overview of the Application of Multivariate Analysis to the Evaluation of Beer Sensory Quality and Shelf-Life Stability

Achieving beer quality and stability remains the main challenge for the brewing industry. Despite all the technologies available, to obtain a high-quality product, it is important to know and control every step of the beer production process. Since the process has an impact on the quality and stability of the final product, it is important to create mechanisms that help manage and monitor the beer production and aging processes. Multivariate statistical techniques (chemometrics) can be a very useful tool for this purpose, as they facilitate the extraction and interpretation of information from brewing datasets by managing the connections between different types of data with multiple variables. In addition, chemometrics could help to better understand the process and the quality of the product during its shelf life. This review discusses the basis of beer quality and stability and focuses on how chemometrics can be used to monitor and manage the beer quality parameters during the beer production and aging processes.

Gluten Assessment in Beers: Comparison by Different Commercial ELISA Kits and Evaluation of NIR Analysis as a Complementary Technique

Traditionally, beers are made with gluten-containing cereals. It is crucial to have rapid analytical methodologies that allow gluten content control of the beers for celiac consumers. We assess the content of gluten in 65 conventional and 41 gluten-free labeled beers commercialized in Europe and compare the results in a subgroup of 71 beers with three ELISA kits. This research allows gathering information on the potential complementary utility of NIR analysis applied to gluten analysis of gluten-free beers in terms of time saving. Results obtained with the ELISA technique identified competitive R5 to be the most sensitive in detecting the prolamins, by eliciting a higher number of beers containing gluten above 20 mg/kg. The gluten content in conventional beers tested increased with the presence of wheat as raw material and with the use of ale-type yeasts. By using competitive R5, 3 out of the 41 gluten-free labeled beers appeared to contain gluten above 20 mg/kg, and conversely, 15 out of 65 of the conventional beers showed a gluten content below this threshold. According to our approaches, NIR did not achieve a suitable correlation with ELISA results, neither for gluten quantification nor for discrimination, and therefore, it cannot be proposed as a complementary technique.

Insights into chemical and sensorial aspects to understand and manage beer aging using chemometrics

Beer chemical instability remains, at present, the main challenge in maintaining beer quality. Although not fully understood, after decades of research, significant progress has been made in identifying "aging compounds," their origin, and formation pathways. However, as the nature of aging relies on beer manufacturing aspects such as raw materials, process variables, and storage conditions, the chemical profile differs among beers. Current research points to the impact of nonoxidative reactions on beer quality. The effect of Maillard and Maillard intermediates on the final beer quality has become the focus of beer aging research, as prevention of oxidation can only sustain beer quality to some extent. On the other hand, few studies have focused on tracing a profile of whose compound is sensory relevant to specific types of beer. In this matter, the incorporation of "chemometrics," a class of multivariate statistic procedures, has helped brewing scientists achieve specific correlations between the sensory profile and chemical data. The use of chemometrics as exploratory data analysis, discrimination techniques, and multivariate calibration techniques has made the qualitatively and quantitatively translation of sensory perception of aging into manageable chemical and analytical parameters. However, despite their vast potential, these techniques are rarely employed in beer aging studies. This review discusses the chemical and sensorial bases of beer aging. It focuses on how chemometrics can be used to their full potential, with future perspectives and research to be incorporated in the field, enabling a deeper and more specific understanding of the beer aging picture.

The Brewing Industry and the Opportunities for Real-Time Quality Analysis Using Infrared Spectroscopy

Brewing is an ancient process which started in the middle east over 10,000 years ago. The style of beer varies across the globe but modern brewing is very much the same regardless of the style. While there are thousands of compounds in beer, current methods of analysis rely mostly on the content of only several important processing parameters such as gravity, bitterness, or alcohol. Near infrared and mid infrared spectroscopy offer opportunities to predict dozens to hundreds of compounds simultaneously at different stages of the brewing process. Importantly, this is an opportunity to move deeper into quality through measuring wort and beer composition, rather than just content. This includes measuring individual sugars and amino acids prior to fermentation, rather than total °Plato or free amino acids content. Portable devices and in-line probes, coupled with more complex algorithms can provide real time measurements, allowing brewers more control of the process, resulting in more consistent quality, reduced production costs and greater confidence for the future.

Fourier Transform Near-Infrared Spectroscopy and Chemometrics To Predict Zygosacchromyces rouxii in Apple and Kiwi Fruit Juices

This study investigated the capability of near-infrared spectroscopy (NIRS) to predict the concentration of Zygosaccharomyces rouxii in apple and kiwi fruit juices. The yeast was inoculated in fresh kiwi fruit juice ( n = 68), reconstituted kiwi juice ( n = 85), and reconstituted apple juice ( n = 64), followed by NIR spectra collection and plate counting. A principal component analysis indicated direct orthogonal signal correction preprocessing was suitable to separate spectral samples. Parameter optimization algorithms increased the performance of support vector machine regression models developed in a single variety juice system and a multiple variety juice system. Single variety juice models achieved accurate prediction of Z. rouxii concentrations, with the limit of quantification at 3 to 15 CFU/mL ( R² = 0.997 to 0.999), and the method was also feasible for Hanseniaspora uvarum and Candida tropicalis. The best multiple variety juice model obtained had a limit of quantification of 237 CFU/mL ( R² = 0.961) for Z. rouxii. A Bland-Altman analysis indicated good agreement between the support vector machine regression model and the plate counting method. It suggests that NIRS can be a high-throughput method for prediction of Z. rouxii counts in kiwi fruit and apple juices.

Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials

Principles, interpretation and applications of near-infrared (NIR) spectroscopy and NIR hyperspectral imaging are reviewed.