Escherichia coli (E. coli) is a common source of contamination in dairy products and other beverages. In this paper, Ultraviolet-visible (UV-Vis) spectroscopy is applied to measurement of E. coli biomass concentration in milk due to its fast and non-contact advantages. Standard Normal Variable (SNV) combined with Multivariate Scattering Correction method (MSC) was used to processes the obtained Ultraviolet-visible spectrum to improve the feature intensity and reduce noise. Two-dimensional correlation analysis is used to capture the absorption characteristics of E. coli after red shift. The characteristic band of E. coli extracted from the two-dimensional correlation analysis was used as the initial data, combined with the Extreme Learning Machine network to establish a prediction model, and compared with the result of the plate counting method. It proves that the method in this paper is reasonable and effective. The results show that the accurate prediction model is coefficient of determination (R2) = 0.92741, mean squared error (mse) = 0.051274. Compared with the traditional method, the time in the analysis process is greatly shortened, from 10 min to 1 min, which means that the new method is more in line with the requirements of online measurement of dairy companies.
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