The potential for scotch malt whisky flavour diversification by yeast

Scotch Whisky, a product of high importance to Scotland, has gained global approval for its distinctive qualities derived from the traditional production process which is defined in law. However, ongoing research continuously enhances Scotch Whisky production and is fostering a diversification of flavour profiles. To be classified as Scotch Whisky, the final spirit needs to retain the aroma and taste of “Scotch”. While each production step contributes significantly to whisky flavour—from malt preparation and mashing to fermentation, distillation, and maturation—the impact of yeast during fermentation is crucially important. Not only does the yeast convert the sugar to alcohol, it also produces important volatile compounds, for example esters and higher alcohols, that contribute to the final flavour profile of whisky. The yeast chosen for whisky fermentations can significantly influence whisky flavour, so the yeast strain employed is of high importance. This review explores the role of yeast in Scotch Whisky production and its influence on flavour diversification. Furthermore, an extensive examination of non-conventional yeasts employed in brewing and winemaking is undertaken to assess their potential suitability for adoption as Scotch Whisky yeast strains, followed by a review of methods for evaluating new yeast strains

Experimental whisky fermentations:influence of wort pre-treatments

In addition to ethanol yield, the production of flavour congeners during fermentation is a major consideration for Scotch whisky producers. Experimental whisky fermentations can provide useful information to the industry, and this is the focus of this paper. This study investigated the impact of wort pretreatments (boiled, autoclaved, filtered) on fermentation performance and flavour development in Scotch whisky distillates as an alternative to freezing wort for storage. Our study showed that no significant sensorial differences were detected in low wines (first distillates), while the chemical compositions showed clear changes in increased levels of esters and higher alcohols in boiled and autoclaved wort. In contrast, filtered wort comprised overall lower levels of congeners. Regarding alcohol yield, all three pretreatments resulted in decreased yields. In practice, the pretreatment of wort prior to fermentation requires additional process operations, while freezing requires large storage units. The pretreatments adopted in this study significantly influence the composition of the malt wort used for experimental whisky fermentations, and this results in a poorer fermentation performance compared with untreated wort. We recommend the use of fresh or frozen wort as the best options for small-scale fermentation trials

Employing NIR-SWIR hyperspectral imaging to predict the smokiness of Scotch whisky

Scotch Whisky makes a significant contribution to the UK's food and drinks export. The flavour of this high quality spirit is derived naturally from the whisky making process, with smoky aromas being a key character of certain Scotch whiskies. The level of smokiness is determined by the amount of phenolic compounds in the spirit. Phenols are introduced by exposing the barley malt to peat smoke during the kilning process. The current techniques to determine the levels of phenols, such as High Performance Liquid Chromatography (HPLC), are time consuming as they require distillation of the malt prior to analysis. To speed up this process and enable real-time detection before processing, the possibilities of Near-infrared to Short-wave-infrared (NIR-SWIR) Hyperspectral Imaging (HSI) to detect these phenols directly on malted barley are explored. It can be shown that via regression analysis, various levels of phenol concentration used as working levels for whisky production could be estimated to a satisfying degree. To further optimise industrial application, a hyperspectral band selection algorithm is applied that yields good results and reduces computational cost and may open possibilities to employ multispectral rather than hyperspectral cameras in future applications

From fermented wash to new make spirit:assessing the evolution of flavour characteristics of Scotch whisky using lab-scale process simulations

New product development for distilled spirits frequently involves experimental trials at the laboratory scale that attempt to replicate industrial-scale production processes. This process is time-consuming and limits the number of samples that can be analysed. The aim of the present study was to conduct laboratory-scale Scotch malt whisky production experiments to determine if samples taken from earlier in the production process, that is, directly after fermentation (wash stage) or after a single distillation (low wines stage), showed similar analytical differentiation compared to samples of fresh distillates (new make spirits). Napping, a rapid sensory method, was used to assess the impact on flavour characteristics while solid-phase microextraction (SPME) gas chromatography–mass spectrometry (GC–MS) was used to analyse volatile flavour congeners. Hierarchical Multiple Factor Analysis was used to compare the product maps from samples taken at each whisky production stage and revealed a pattern of differences across the samples that could be tracked through the process. Although the flavour descriptors and volatile congeners composition changed at each stage, there were only marginal changes in the differentiation between samples, resulting in the same sample groups being found in all analyses. RV coefficients >0.90 for all analytical comparisons and >0.74 overall showed that all product maps were highly similar to each other and showed the same overall differentiation between samples. These results indicate that the analysis of fermented malt whisky wash may provide sufficient information to proceed to larger-scale industry trials, saving time and allowing a greater number of parameters to be explored

Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning.

Quantifying phenolic compound in peated barley malt and discriminating its origin are essential to maintain the aroma of high-quality Scottish whisky during the manufacturing process. The content of the total phenol varies in peated barley malts, which is critical in measuring the associated peatiness level. Existing methods for measuring such phenols are destructive and/or time consuming. To tackle these issues, we propose in this paper a novel nondestructive system for fast and effective estimating the phenolic concentrations and discriminating their origins with the near-infrared hyperspectral imagery and machine learning. First, novel ways of data acquisition and normalization are developed for robustness. Then, the principal component analysis (PCA) and folded-PCA are fused for extracting the global and local spectral features, followed by the support vector machine (SVM) based origin discrimination and deep neural network based phenolic measurement. In total 27 categories of peated barley malts from eight suppliers are utilized to form thousands of spectral samples for modelling. A classification accuracy up to 99.5% and a squared-correlation-coefficient up to 98.57% are achieved in our experiments, outperforming a few state-of-the-art. These have fully demonstrated the efficacy of our system in automated phenolic measurement and origin discrimination to benefit the quality monitoring in the whisky industry