## 5 Conclusions  
In this research, we presented the results of simulations and validation of the LSTLS system with the \(R^{2}\) measure. Analysis of the spectral output for different LED configurations revealed certain wavelengths significantly contributing to reducing the overall spectral mismatch, mainly due to low FWHM, in the violet-blue light region \(<\) 500 nm and deep red region \(>\) 700 nm. When there is a wider spacing between peaks, indicating fewer LED channels in the LED source, color LEDs emitting a narrow spectral spectrum should be substituted with phosphor-based LEDs emitting a broader spectral spectrum. For instance, replacing narrowband LEDs at 640 nm and 650 nm with broadband sources smoothed the final SPD curve in the 600-700 nm range, optimizing the overall spectral output. However, this adjustment for more channels in LSTLS had minimal impact on the \(R^{2}\) value, suggesting the robustness of the selected LED configurations against minor spectral shifts. The results of our study also suggest the benefits of integrating phosphor-converted LEDs and adjusting the bandwidth of narrowband LEDs to enhance the overall spectral output. These strategies may contribute to smoother spectral profiles and reduced overall mismatch errors, demonstrating the potential for hybrid LED configurations in critical photometric applications but providing new technological challenges. The optical properties of phosphor-based optical sources derive from several factors, such as the synthesis methods of nanoparticles embedded within the host matrix. Ion implantation as a synthesis technique allows for the precise control of nanoparticle size, distribution, and density within, which in turn affects the photoluminescence and nonlinear optical properties [37]. Our study aimed to evaluate the efficacy of Gaussian modeling and R-squared fitting criteria in designing and simulating multi-emitter LED systems, which has provided critical insights and actionable recommendations. While these traditional methodologies offer a solid foundation for the initial design phases of LSTLSs, they require significant adaptations to fully accommodate LEDs' unique spectral characteristics and performance variabilities. The comparison of the spectral output of optimized versions of the LSTLS indicated high fidelity between simulated and actual SPDs, with \(R^{2}\) values exceeding 0.993 for most sets. However, comparing the errors and their spread among the spectrum, particularly in the green region, emphasized the need for refined evaluation metrics beyond \(R^{2}\), suggesting a more complex approach to evaluating spectral matching. Our results show that the most popular measure does not provide an obvious result in selecting the best solution for the photometric application. The transition from simulations to the implementation phase confirmed this gap in the quality criteria. If a specific application is considered, the most popular spectral matching measure misses important information, which can be revealed only if the measurement data are used for modeling. If the shapes of the SPDs are carefully analyzed, high values of \(R^{2}\) do not include information on the spectral distribution of the discrepancies, which is critical in some applications. That makes it difficult to select the best set of components without a very wide measurement procedure of a high number of sample components. That suggests the need for more refined evaluation metrics that can effectively capture the nuances of spectral fidelity beyond what R-squared values can provide and facilitate the design process. Such metrics should account for the locations of the component's SPD mismatch and the photometric importance of different spectral regions. This study serves as a step toward enhancing the reliability of the prediction of LED-based illuminants for photometric applications. Identifying gaps and searching for new modeling methods may contribute to improving the quality of predictions of solutions using LSTLS.