Austerjost Jonas, Marquard Daniel, Raddatz Lukas, Geier Dominik, Becker Thomas, Scheper Thomas, Lindner Patrick, Beutel Sascha
Institute of Technical Chemistry Leibniz University Hannover Hannover Germany.
Institute of Brewing and Beverage Technology, Forschungszentrum Weihenstephan Technische Universität München Munich Germany.
Eng Life Sci. 2017 Aug 28;17(8):959-966. doi: 10.1002/elsc.201700056. eCollection 2017 Aug.
The manual counting of colonies on agar plates to estimate the number of viable organisms (so-called colony-forming units-CFUs) in a defined sample is a commonly used method in microbiological laboratories. The automation of this arduous and time-consuming process through benchtop devices with integrated image processing capability addresses the need for faster and higher sample throughput and more accuracy. While benchtop colony counter solutions are often bulky and expensive, we investigated a cost-effective way to automate the colony counting process with smart devices using their inbuilt camera features and a server-based image processing algorithm. The performance of the developed solution is compared to a commercially available smartphone colony counter app and the manual counts of two scientists trained in biological experiments. The comparisons show a high accuracy of the presented system and demonstrate the potential of smart devices to displace well-established laboratory equipment.
通过在琼脂平板上人工计数菌落来估算特定样本中活生物体的数量（即所谓的菌落形成单位 - CFU），是微生物实验室常用的方法。借助具有集成图像处理功能的台式设备实现这一艰巨且耗时过程的自动化，满足了更快、更高样本通量以及更高准确性的需求。虽然台式菌落计数器解决方案通常体积庞大且价格昂贵，但我们研究了一种经济高效的方法，利用智能设备的内置摄像头功能和基于服务器的图像处理算法实现菌落计数过程的自动化。将所开发解决方案的性能与一款商用智能手机菌落计数器应用程序以及两名接受过生物实验培训的科学家的人工计数进行了比较。比较结果显示了所提出系统的高精度，并证明了智能设备取代成熟实验室设备的潜力。
