Mechanism for mixing and homogenization in beer fermentation

García, Ana I.; Pandiella, Severino S.; Garcia, LA; Díaz, Mario de Miguel

doi:10.1007/s004490050042

Cited by 5 publications

(12 citation statements)

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“…The flow rate in the scale down rig was then varied to match those estimated circulation times. The change of flow rates gave a temperature profile with time in the PFR that matched quite well that reported by Garcia et al (1994) (Figure 7), with variations between the inlet and the outlet. The temperature in the STR remained constant throughout.…”

Section: Using Mechanical Agitation To Eliminate Spatial Temperature supporting

confidence: 84%

“…It was found that without mechanical agitation, with both strong and weak flocculating yeasts, very high yeast concentrations existed in the cone, even when CO 2 evolution was still quite vigorous after about 50 hrs; and remained so for the remaining time of the 120 hrs fermentation. In addition, temperature variations were found, though contrary to the work of Garcia et al (1994), temperatures were some 2.5 C higher at the base. This higher temperature was ascribed to the high concentration of yeast in the cone leading to a locally high metabolic heat evolution that could not be dispersed because of the lack of adequate fluid motion .…”

Section: Discussioncontrasting

confidence: 71%

“…Thus, it can be seen that T  increases with scale due to both increasing size and in general, aspect ratio. For typical beer fermenters of the order of 400 to 500 m 3 of aspect ratio ~ 4 to 5 and a maximum CO 2 evolution rate of 1.2 x 10 -4 (m 3 /s)/m 3 (Garcia et al, 1994), During the fermentation studies (Boswell et al, 2002;Boswell et al, 2003b), standard parameters (specific gravity, dry cell weight, fermentable sugars, and flavour compounds) were monitored ( Figure 3  up to 0.25 W/kg, the overall batch fermentation time was significantly reduced from ~160 to ~100 h, with increased dry cell weight, an increase in higher alcohols, a reduction in esters and with the % of ethanol produced unchanged. These changes can be ascribed to improved transport of substrates in and desorption of products out across the cells cytoplasmic membrane.…”

Section: Impact Of Mechanical Agitation On Brewing Performance With Mmentioning

confidence: 99%

“…The temperatures reported by Garcia et al (1994) varied from ~ 5°C in the conical base of the commercial cylindroconical fermenter at the start and end of the fermentation when the CO 2 evolution rates were low, to ~ 12°C, the desired operating temperature, which was the same everywhere in the vessel during the period of peak evolution. These conditions were simulated at the bench scale using a stirred fermenter with plug flow loop (STR-PFR).…”

Section: Using Mechanical Agitation To Eliminate Spatial Temperature mentioning

confidence: 99%

“…Some lesser motion is also induced due to natural convection arising from temperature gradients either from heat release by the fermentation or from cooling of the walls of the fermenter, undertaken to maintain the desired operating time/temperature profile. Thus, for much of the fermentation time there is very limited fluid motion from any source, with Garcia et al (1994) reporting spatial variations in yeast concentration and temperature in a commercial scale fermenter. Nevertheless, it is still usual to assume that the contents of large scale cylindroconical beer fermenters are well mixed both by practitioners of brewing and when the process is modelled, as pointed out by Boulton et al (2007) and Hind (2000) respectively.…”

Section: Introductionmentioning

confidence: 99%

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Studies supporting the use of mechanical mixing in large scale beer fermentations

2010

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Section: Using Mechanical Agitation To Eliminate Spatial Temperature supporting

confidence: 84%

Section: Discussioncontrasting

confidence: 71%

Section: Impact Of Mechanical Agitation On Brewing Performance With Mmentioning

confidence: 99%

Section: Using Mechanical Agitation To Eliminate Spatial Temperature mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Studies supporting the use of mechanical mixing in large scale beer fermentations

2010

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Scale‐down/scale‐up studies leading to improved commercial beer fermentation

Nienow

Nordkvist²,

Boulton

2011

Biotechnology Journal

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Scale-up/scale-down techniques are vital for successful and safe commercial-scale bioprocess design and operation. An example is given in this review of recent studies related to beer production. Work at the bench scale shows that brewing yeast is not compromised by mechanical agitation up to 4.5 W/kg; and that compared with fermentations mixed by CO(2) evolution, agitation ≥ 0.04 W/kg is able to reduce fermentation time by about 20%. Work at the commercial scale in cylindroconical fermenters shows that, without mechanical agitation, most of the yeast sediments into the cone for about 50% of the fermentation time, leading to poor temperature control. Stirrer mixing overcomes these problems and leads to a similar reduction in batch time as the bench-scale tests and greatly reduces its variability, but is difficult to install in extant fermenters. The mixing characteristics of a new jet mixer, a rotary jet mixer, which overcomes these difficulties, are reported, based on pilot-scale studies. This change enables the advantages of stirring to be achieved at the commercial scale without the problems. In addition, more of the fermentable sugars are converted into ethanol. This review shows the effectiveness of scale-up/scale-down studies for improving commercial operations. Suggestions for further studies are made: one concerning the impact of homogenization on the removal of vicinal diketones and the other on the location of bubble formation at the commercial scale.

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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

2017

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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

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Mechanism for mixing and homogenization in beer fermentation

Cited by 5 publications

References 0 publications

Studies supporting the use of mechanical mixing in large scale beer fermentations

Studies supporting the use of mechanical mixing in large scale beer fermentations

Scale‐down/scale‐up studies leading to improved commercial beer fermentation

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

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