# A Photonic Label-Free Biosensor to Detect _Salmonella_ spp. in Fresh Vegetables and Meat
## 3 Results and Discussion
### Sensor Selectivity and Efficiency
The negative predictive value of the biosensor method was also 100%, indicating that it was highly reliable in correctly identifying negative samples. The results imply that _Salmonella_ spp., in both meat and vegetable samples, can be effectively detected using either of the two tested methods. The reason for this conclusion is that the two methods share the same level of specificity, which indicates that they are equally capable of correctly identifying the presence of _Salmonella_ species in the samples. The results also indicated high reproducibility. Detections based on the specific binding of _Salmonella_ species antigens were observed in 96.8% of the contaminated samples. This high reproducibility implied a 96.8% probability of observing the same detection result when analyzing identical samples at different times under standard reproducibility conditions. Reproducibility results are presented in Table 1. They provide strong evidence of the reliability and consistency of both detection methods for _Salmonella_ spp. This characteristic is valuable because it indicates that the methods can consistently produce accurate results across multiple analyses under varying conditions. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Target Sample 1  & **Comt on Selective Agar (CFU/mL)*** \\ \hline Fresh salad 04/2023 & + & \(1.1\times 10^{3}\) \\ Fresh salad 04/2023 & + & \(6.5\times 10^{5}\) \\ Fresh salad 04/2023 & + & \(3.0\times 10^{2}\) \\ Fresh salad 04/2023 & + & \(4.2\times 10^{1}\) \\ Fresh chicken 05/2023 & + & \(2.0\times 10^{5}\) \\ Fresh chicken 05/2023 & + & \(5.6\times 10^{3}\) \\ Fresh chicken 05/2023 & + & \(6.2\times 10^{2}\) \\ Fresh chicken 05/2023 & + & \(2.0\times 10^{1}\) \\ Fresh chicken CECT4266 & + & \(1.0\times 10^{2}\) \\ Fresh chicken CECT4266 & + & \(2\times 10^{1}\) \\ Fresh chicken CECT4266 & + & \(3.0\times 10^{5}\) \\ Fresh chicken CECT4266 & + & \(1.5\times 10^{7}\) \\ Fresh chicken CECT4266 & + & \(6.0\times 10^{6}\) \\ Fresh chicken CECT4266 & + & \(1.5\times 10^{4}\) \\ Fresh chicken CECT4266 & + & \(5.6\times 10^{3}\) \\ Red Batavia CECT4266 & + & \(2\times 10^{1}\) \\ Red Batavia CECT4266 & + & \(4.8\times 10^{10}\) \\ Red Batavia CECT4266 & + & \(1\times 10^{2}\) \\ Red Batavia CECT4266 & + & \(1.5\times 10^{7}\) \\ Red Batavia CECT4266 & + & \(1.9\times 10^{3}\) \\ \hline \hline \end{tabular} 1  
\end{table} 
Table 2: Comparison of results for contaminated food samples. Interestingly, the results were influenced by bacterial concentration. Samples with higher dilution factors produced weaker optical signals, indicating that the optical response was less intense for more diluted samples. This concentration-dependent relationship between the bacterial concentration and the optical signal is reflected in Figure 8. This figure illustrates the photonic measurements, particularly the microring resonance notch shift, quantified in picometers (pm). These measurements were taken during the _Salmonella_ spp. experiment with different dilution factors, ranging from 10 to 10\({}^{10}\) CFU/mL in buffered peptone water. The data showed successful detection for samples with dilution factors up to 10 CFU/mL. This immunoassay method was assessed for its capacity to provide a quantitative response. Such a response is particularly valuable for enumerating _Salmonella_ spp. to determine the food safety of a food product. Calibration curves were generated by plotting the resonance in picometers (pm) against the known concentrations of _Salmonella_ spp. in CFU/mL, as shown in Figure 8. This approach enabled quantitative assessment of bacterial concentration based on the immunosensor's optical response. As shown in Figure 8, the linearity of the analysis was qualitatively evaluated and confirmed by calculating the correlation coefficient. This qualitative assessment of the linear relationship was employed to ensure the working interval and verify that the relationship between the X and Y variables was indeed linear.