The invention relates to the technical field of
data analysis, particularly discloses a microbial colony quantitative
analysis method based on fusion of conductance change and a TOC (
Total Organic Carbon) model, and aims to solve the problems that a traditional plate counting method is time-consuming and large in manual error, an existing automatic method is easy to interfere and ignores
carbon dioxide dynamics, and a single
data source method is poor in robustness. According to the method, a multi-source input vector is formed by collecting a microbe sample
conductivity difference value,
carbon dioxide concentration and temperature and
humidity in real time, the
conductivity difference value is mapped into a carbon
base number value through a TOC
algorithm, microbe quantity characteristics are extracted in combination with
machine learning, microbe quantity probability distribution is obtained through Kalman filtering
smoothing and state
estimation and
Gaussian process regression, and the microbe quantity probability distribution is calculated. Outputting a
bacterial colony equivalent and a
confidence interval, and verifying and ensuring the accuracy by using sterilized
sucrose. A closed-loop mechanism is verified through sterilized
sucrose, the accuracy of quantitative analysis results is further ensured, and the problem of deviation caused by neglecting the dynamic nature of
carbon dioxide in an existing method is effectively solved.