# A Photonic Label-Free Biosensor to Detect _Salmonella_ spp. in Fresh Vegetables and Meat
## 1 Introduction
The selection of these bioreceptors is critical and requires comprehensive characterization and optimization. This initial phase lays the foundations to create nanophotonic-based biosensors that can discern specific pathogenic microorganisms. It requires thoughtful evaluation of their specificity and binding affinity toward the target analyte. It also depends on the nature of the analyte and the desired sensitivity of the sensor. The effectiveness of the antibodies immobilized on a biosensor's surface in their role as probes depends on their specificity in recognizing the target of interest [15]. Therefore, pre-validation of how the selected target antigen interacts with various antibodies is crucial [16; 17; 18] to account for potential non-specific interactions during the experimental process [19]. For this purpose, microarrays, referred to as detection platforms, can be generated by depositing microdroplets of different antibodies to be used as probes [20; 21]. _Salmonella_ detection using optical and electrochemical biosensors is common. They are often integrated into microfluidic devices to develop microfluidic-based biosensors for the detection of _Salmonella_[22; 23; 24; 25; 26; 27]. These miniaturized systems are used to enable automation and miniaturization, enhance performance analysis, reduce reagent consumption, lower processing time, and ensure high portability to combine several laboratory functions [28; 29; 30; 31]. Microfluidic-based biosensors are composed of microchannels through which fluidic samples circulate to allow an immunoassay on a chip [32]. These devices enable the simultaneous in situ application of laboratory processes such as sampling, separation, mixing, and detection [33; 34]. Biosensors employing optical transduction systems have several advantages. They require considerably smaller sample volumes, thanks to the integration of microfluidic and nanophotonic systems. Hence, analyses can be performed on the nanometric or micrometric scale. Additionally, such biosensors offer label-free detection, allowing for real-time monitoring and streamlining of the procedure by reducing the required number of steps and reagents. SPR biosensors enable control of the interaction between targets and ligands in terms of changes in the refractive index [35]. Their performance has improved thanks to the ability to control immunoassay reactions (target-ligand) in real time, which is coupled with their simplicity and low cost [36; 37]. _Salmonella_ spp. can generally be detected using two types of biosensors: label-free and label-based. Simplified procedures combined with label-free surface-enhanced Raman scattering (SERS) biosensors are in demand for _Salmonella_ detection [38]. However, although label-free SERS methods have substantial intrinsic advantages, they still have limitations in terms of sensitivity and reproducibility. The limit of detection (LoD) is usually unsatisfactory (10\({}^{8}\) CFU/mL). Detecting low concentrations of _Salmonella_ remains a challenge, especially in food samples. This issue is closely related to the selection of bioreceptors and transducers, as well as the development of suitable sample pre-treatment methods. Analyzing natural foods using biosensors is more complicated than analyzing artificial samples doped with _Salmonella_ antigens in the same way. The reason is the effect of each matrix on the refractive index. This effect has been confirmed in some research, revealing that food matrices adversely affect detection performance [39]. Photonic biosensors on silicon photonic integrated circuits (PICs) enable label-free performance with high detection sensitivities. They are ultimately disposable, which is helpful for point-of-care diagnostics without specialized personnel [40]. Sensitivity is intrinsically connected to key sensing parameters, including LoD and limit of quantification (LoQ). The outcomes related to the sensitivity of waveguide sensors are influenced by the degree of overlap between the evanescent field and the analyzed sample [41; 42].