Optical photothermal infrared (OPTIR) spectroscopy assisted by machine learning for lactic acid bacteria identification at strain level

, covering both intra- and inter-species diversity. Spectral data from LAB were acquired using a mIRage LS OPTIR system, preprocessed, and used to train a fully connected neural network for each level. The models achieved macro F1-scores of 97% for species level and 91% for strain level classification. These results demonstrate the potential of OPTIR, when integrated with machine learning, as a robust tool for high-resolution bacterial classification, with promising applications in microbiological quality control, probiotic selection, and microbial ecology.