Ascorbic Acid Oxidase in Barley and Malt and Its Possible Role During Mashing

Bamforth,

doi:10.1094/asbcj-2014-0120-01

Cited by 2 publications

(2 citation statements)

References 21 publications

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“…In the initial fractional factorial screen, it was the linear aeration term for NC that was closest to statistical significance (p = 0.0561) and aeration has been shown to affect the concentrations of non-carbohydrate species in a mash like polyphenols and thiol-containing species [10]. The magnitude of this effect was on the order of that of pH, but the sign of the term coefficient was positive, which was reversed relative to expectation based on the previous research (i.e., that increased exposure to oxygen would lead to precipitation of polyphenols and thiol-containing species, thereby lowering the relative proportion of NC) [10,13]. The lack of any significant interaction was definitive though, as the temperature-aeration interaction (aliased with the pH-grist ratio interaction) was insignificant for all responses in the fractional factorial screen and the pH-grist ratio term was similarly insignificant for all responses in the central composite design.…”

Section: Discussionmentioning

confidence: 75%

“…Oxygen exposure during mashing has also been shown to cause oxidative lipid degradation, which can lead to the production of undesirable flavor compounds like trans-2-nonenal, and to increase the formation of staling aldehydes (Strecker aldehydes; benzaldehyde, 2-methybutanal, 3-methylbutanal, methional, and phenylacetaldehyde) as compared to mashes conducted under nitrogen atmosphere [11,12]. Aeration has not, however, previously been shown to affect the starch hydrolysis process itself [13,14].…”

Section: Introductionmentioning

confidence: 99%

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A Multi-Parameter, Predictive Model of Starch Hydrolysis in Barley Beer Mashes

2020

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A key first step in the production of beer is the mashing process, which enables the solubilization and subsequent enzymatic conversion of starch to fermentable sugars. Mashing performance depends primarily on temperature, but also on a variety of other process parameters, including pH and mash thickness (known as the “liquor-to-grist” ratio). This process has been studied for well over 100 years, and yet essentially all predictive modeling efforts are alike in that only the impact of temperature is considered, while the impacts of all other process parameters are largely ignored. A set of statistical and mathematical methods collectively known as Response Surface Methodology (RSM) is commonly applied to develop predictive models of complex processes such as mashing, where performance depends on multiple parameters. For this study, RSM was used to design and test a set of experimental mash conditions to quantify the impact of four process parameters—temperature (isothermal), pH, aeration, and the liquor-to-grist ratio—on extract yield (total and fermentable) and extract composition in order to create a robust, yet simple, predictive model. In contrast to previous models of starch hydrolysis in a mash, a unique aspect of the model developed here was the quantification of significant parameter interaction effects, the most notable of which was the interaction between temperature and mash thickness (i.e., the liquor-to-grist ratio). This interaction had a sizeable impact on important mash performance metrics, such as the total extract yield and the fermentability of the resultant wort. The development of this model is of great future utility to brewery processing, as it permits the multi-parameter optimization of the mashing process.

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Section: Discussionmentioning

confidence: 75%