Yeast is the fundamental part of fermentation, the desired flavour profile and an efficient and reliable attenuation a brewer is looking for, depends on his work. However, in Argentina and Chile the great majority of brewers are using new dehydrated yeast for every batch and only a few of them are storing and reusing yeast in-house. This situation implies not only the waste of yeast itself, as an important and expensive coproduct of beer making, but also is detrimental in terms of quality, repeatability and differentiation of products. Most brewers use just a few brands and strains of yeasts (mainly S-04, Notthingham, US-05).
In order to consistently manage yeast in breweries the use of a microscope becomes fundamental. It allows to count and evaluate the viability of cells and to determine the optimal pitching rate for every new batch. Moreover, this practice is an excellent starting point for brewers to increase knowledge and experience about the microbiology involved in brewing.
The standard procedure of counting requires an optical microscope and a Neubauer chamber where the yeast sample is quantified. Recent approaches to DIY microscopy in the biohacker movement can be tested and improved to communicate and facilitate this task to brewers.
The goal of our design is to allow the consistent evaluation of viability and count of yeast cells from a digital image taken with a low-cost DIY microscope.
The materials for the microscope prototype should be easily available.
Integrate the hardware output with already existing informatic tools for manual and automatic yeast counting.
This was our point of departure (before the project) with a Community microscope of Public Lab
So far we have tested 4 different setups of cameras and optics. In order to keep an order in the project we have stablished a nomenclature for the prototypes. Every prototype is named as BM_camera_optics
This is the result of our BM4 setup
We need to characterize further our prototypes (ie. resolution, field of view, magnification) and improve things as the illumination and the manipulation of samples (see Issues).
Once we can have a fully working prototype that can distinguish clearly between dead (stained) and live yeast cells we will start with the image analysis to advance in ways of automatic counting.
All the documentation and results of the project can be consulted in our Gitlab repository