Counting is coming – Introducing the µCount 3D imaging technology.
Preregister your interest in the new microbial benchtop counter. The µCount 3D is developed to count bacteria and fungal spores.
Bacteria: Pipette pure culture bacteria samples into triplicate sample µCassettes. Insert and use the intuitive µExplorer software to run your sample. µCount 3D will count bacteria/ml down to 0.5µm in size and a measure a concentration range from 104 – 107. All in just 5 minutes.
Fungal Spores: For fungal spores the sampling principle is similar to bacteria – but with an innovative exception – Your sample matrix can be with particles. We employ deep learning algorithms to find and count spores in your sampl
The patented FluidScope technology is a tilted camera technology. When images are taken, we get to film a volume instead of a plane. Every image has a height of 150µm and since images overlap we get to create both a vertical and horizontal z-stack. All objects present in this volume, is captured in focus.
For bacteria counts we use volume imaging and count bacteria present in the entire volume. Bacteria settle very slowly and are present throughout the imaged volume. Using the sampling µCassettes with a defined inner height, we capture all bacteria down to our pixel size of 0,5µm.
Using the µCassettes with triplicate sample chambers the µExplorer software will provide bacteria/ml or fungal spores/ml and supply images for documentation.
µCount 3D Instrument
The µCount 3D instrument is in development and ready to service your lab from Q1 2024.
Size: H: 20cm W: 10cm D: 20cm
Species: Bacteria, Fungi, Yeast and Algae
Speed: 5 minutes analysis time
Output: Triplicate object/ml and images for documentation
Sample containers: BioSense Solutions µCount Cassettes
µCount 3D Technology
The µCount 3D technology will also be available for the oCelloScope platform. Using an adapter, µCount Cassettes can be placed in the instrument. The oCelloScope will have added features for analysis and an even lower detection limit of 103 bacteria/ml.
For fungal spores and yeasts we have developed a variety of specific deep learning algorithms, trained to find spores in pure and complex sample matrixes. We also have a user labelling app for scientists to label their own species. Labelling of own species, can be highly relevant if you work with the same sample conditions in QC or similar.