Isaac L Ahuvia, Kathryn R Fox, Jessica L Schleider
Adolescents' beliefs about what symptoms constitute depression: Are more expansive definitions helpful or harmful?
SSM. Mental health
contaminated fresh produce remains prominent catalyst foodborne illnesses prompting need swift precise pathogen detection mitigate health risks paper introduces innovative strategy identifying foodborne pathogens fresh produce samples local markets grocery stores utilizing optical sensing machine learning core approach photonicsbased sensor system instantaneously generates optical signals detect pathogen presence machine learning algorithms process copious sensor data predict contamination probabilities real time study reveals compelling results affirming efficacy method identifying prevalent foodborne pathogens including escherichia coli e coli salmonella enteric across diverse fresh produce samples outcomes underline approachs precision achieving detection accuracies 95 surpassing traditional timeconsuming less accurate methods methods key advantages encompass realtime capabilities heightened accuracy costeffectiveness facilitating adoption food industry stakeholders regulatory bodies quality assurance safety oversight implementation holds potential elevate food safety reduce wastage research signifies substantial stride toward development dependable realtime food safety monitoring system fresh produce future research endeavors dedicated optimizing system performance crafting portable field sensors broadening pathogen detection capabilities novel approach promises substantial enhancements food safety public health