7/29/2019 Viabilidad de Levaduras en Fermentacion

1/2

Particle Analysis with VisionFlowCAM Application Note

Objective

An important component o

ermentation processes is to continuallymonitor yeast growth and viability. Temost common method or doing thisis using the ASBC hemocytometercount method. In this method, samplesare taken rom the ermentation vessel,stained with methylene blue, and thencounted manually under a microscopeusing a hemocytometer.

While this method is well known anddocumented, it is, at best, an estimatebased upon a very small sample count.Te hemocytometer, when viewedunder a microscope, presents a grid omeasurement areas as seen below.

Because o the time involved or anoperator to do manual counting, onlya small number o actual grid cells arecounted, with the results then beinginterpolated as an averagenumber.Not only is the sample size very small,

which yields low statistical signicance,but it is known that up to 25% errorcan be introduced merely by operatorinterpretation.

It was desired to develop a method ormaking the yeast counts more precise,increase the statistical signicanceby looking at a larger sample, andto eliminate the time and potentialoperator error or this procedure.

= Grid Cell Counted

= Grid Cell Not Counted

Method

Te FlowCAM is ideally suited toautomate this process. It can image,count and measure thousands oindividual yeast cells in the time ittakes or an operator to count onlytens o cells using the hemocytometermethod. Te VisualSpreadsheetsotware automaticallyproduces acount o live, dead and budding yeastcells without any operator beinginvolved. Tis normalizes out humanerror, and provides extremely preciseand repeatable results. Further, thenumbers have a much higher statisticalsignicance due to the larger datapopulations obtained by the FlowCAM.

Te yeast samples are taken rom theermentation vessel and prepared just asthey are or the hemocytometer methodby staining with methylene blue.

Te sample is then run through theFlowCAM in autoimage mode at sevenrames per second as it ows throughthe ow cell. Every yeast cell is imaged,stored and measured during acquisition.

As seen above, the FlowCAMautomatically captures each yeastcell as a single stored image rom theuid ow. During image capture, upto 26 dierent spatial and gray-scalemeasurements are recorded and indexedto the individual cell images.

When the yeast cells are stained with themethylene blue, dead cells will uptakethe stain, causing them to appear blueto the camera. Te diagram below showshow the cells would be counted in thehemocytometer.

For the FlowCAM, dierentiatingbetween the live and dead cells is quitestraightorward, and is based primarily

on the average blue value recordedor the cell image (along with severalshape measurements). Te buddingcells present a bit more difcultchallenge, however, due to the act thatthe resolution needed to accuratelydierentiate a single live cell rom abudding cell is much higher than canbe obtained with the FlowCAM.

However, a simple solution to this isto simply look or doublets, whichare two yeast cells which have alreadybudded and about to separate. Tekey thing we are looking or whencounting budding cells is that theyeast is still viable and growing. So, tomeasure budding, we simply lteror the doublets, and then count eachone o these as two live cells, and onebudding. Te trendis the importantmeasurement, not the absolute number.

Live

Dead

Budding

Doublet

Yeast Viability Measurements in

Fermentation Studies

7/29/2019 Viabilidad de Levaduras en Fermentacion

2/2

Fluid Imaging Technologies, Inc | 65 Forest Falls Drive, Yarmouth, ME | 04096 | (207) 846-6100 | www.fluidimaging.com

Particle Analysis with Vision

Results and Conclusions

Te images above show how theFlowCAM automaticallycalculates theconcentration o live, dead and buddingyeast cells. A total o 8,709 yeast cellswere automatically charcterized by theFlowCAM in 35 seconds! Unlike thehemocytometer counts, this is not anestimate based upon extrapolation,rather it is a real count. Te FlowCAMalso automatically calculates theconcentration or each cell type as parto the process.

Tis large amount o data makesthe FlowCAM results much morestatistically signicant. And because

Budding: Count = 1,494

Concentration = 891K cells/ml

Total Time to acquire, measure and characterize

8,709 cells = 35 seconds

o the elimination ohuman interpretation,the FlowCAM resultsshow extreme precisionover multiple runs, withgenerally as small as 1%variability.

As stated previously,the lters to be used orcharacterizing the yeastsonly need to be denedonce. Ater the lters are dened,they can be re-used or all subsequentsamples. Te lters are easily denedin VisualSpreadsheet; the operatormerely identies particle images o thedesired type by clicking on them, and

then instructs the sotware to save theseas a lter. Te lter then simply looksor similar particles using statisticalpattern recognition. From that pointon, the analysis is entirely automated.

Live: Count = 6,823

Concentration = 4.07M cells/ml

Dead: Count = 392

Concentration = 234K cells/ml