DisplayTitle

Utilizing Cellpose 2.0, an Open-Source Deep Neural Network, for Yeast Cell Counting

MBAA TQ https://doi.org/10.1094/TQ-60-4-0202-01 |

Austin Patterson. Quality Manager, Pryes Brewing Co., Minneapolis, MN, USA

Abstract

Cell counts are a crucial component of well-designed brewery laboratories but can be time-consuming and are prone to variability among analysts. Cellpose 2.0, a freely available and user customizable artificial intelligence (AI) software, was implemented to perform cell counts with high accuracy, speed, and repeatability. A dual validation approach confirmed the use of Cellpose 2.0 in establishing brewing yeast cell counts with minimal equipment requirements and no additional costs to the user. Further investigation into Cellpose 2.0 could yield potential applications in yeast cell shape analysis and viability determination.

DisplayTitleUtilizing Cellpose 2.0, an Open-Source Deep Neural Network, for Yeast Cell Counting​​

Utilizing Cellpose 2.0, an Open-Source Deep Neural Network, for Yeast Cell Counting​

DisplayTitle

Utilizing Cellpose 2.0, an Open-Source Deep Neural Network, for Yeast Cell Counting

Utilizing Cellpose 2.0, an Open-Source Deep Neural Network, for Yeast Cell Counting