Classification of <i>Latilactobacillus sakei</i> subspecies based on MALDI-TOF MS protein profiles using machine learning models

<i>Latilactobacillus sakei</i> plays a significant role in the realm of food bacteria. One particular subspecies of <i>L. sakei</i> is employed as a protective agent during food fermentation, whereas another strain is responsible for food spoilage. Hence, it is crucial to precisely differentiate between the two subspecies of <i>L. sakei</i>. In this study, machine learning models based on protein mass peaks were developed for the first time to distinguish <i>L. sakei</i> subspecies. Furthermore, the efficacy of three commonly used machine learning algorithms for microbial classification was evaluated. Our results provide the foundation for future research on developing machine learning models for the classification of microbial species or subspecies. In addition, the developed model can be used in the food industry to monitor <i>L. sakei</i> subspecies in fermented foods in a time- and cost-effective method for food quality and safety.