Dynamic Growth Monitoring of Saccharomyces cerevisiae Based on Microwave Sensor Array

Saccharomyces cerevisiae YPH499 participated in the brewing process of alcoholic products as a key strain. However, there is no effective method for real-time and non-contact monitoring of the dynamic growth of YPH499. In this study, we proposed a nested split-ring resonator (NSRR) array and established a microwave monitoring system for real-time and non-contact monitoring of YPH499. The results demonstrated that microwave parameters can effectively characterize the dynamic growth of YPH-499 and exhibit regular variations. Using principal component analysis (PCA) to extract and integrate detection data from nine resonators (RM1-RM9) of the NSRR array. The results indicated that the first principal component (PC1) could serve as a composite parameter to more effectively characterize the dynamic growth process of YPH-499. Comparative analysis through Logistic dynamic growth curve fitting demonstrated that PC1 exhibited a higher fitting rate (R2) than RM1-RM9 for all four microwave parameters, confirming the necessity of employing the NSRR array for monitoring purposes. The four microwave parameters obtained from RM1-RM9 were fused using Dempster-Shafer (D-S) evidence theory to generate microwave synthetic parameters (MSP1-MSP9). To establish the mapping relationship among MSP, survival rate (ηs), and apoptosis rate (ηA) of YPH-499, we calculated ηs and ηA of YPH-499 at each growth period and established the mapping function based on the temporal relationship. After comparison, we select MSP3 to characterize the ηs and ηA according to R2. The R2 of MSP3 is as high as 0.9985, indicating a strong correlation among these parameters. It enhanced our ability to evaluate the brewing process.