# Quantifying Moss Response to Metal Contaminant Exposure Using Laser-Induced Fluorescence
## 5 Conclusions  
The research presented throughout this paper aimed to design and implement a new, repeatable methodology applying a new LIF technology (Biofinder) [26] for the detection of Cu contamination in moss. Fluorescence in moss samples was captured through images, which were processed into color histograms that showed that modes of red and green color histograms from Cu-treated trials were shifted compared to the control. Color comparison was achieved through the successful application of scaled histogram differences and DTW for single- and two- color analyses. Quantitative analysis of results proves that metal contamination at a level of 0.034 mg/cm\({}^{2}\) or higher in moss samples can be identified using the Biofinder and that there is a predictable relationship between Cu dose and color shifts. Though the levels of Cu tested were much higher than those found in background sources or urban settings, the current system could still have applications in highly toxic sites affected by industry, mining, Superfund, or sewage sludge deposit sites. To make the technique more applicable, improving the sensitivity by two to three magnitudes will be the focus for future work. Distinguishing lower and higher toxicities will help separate PTEs from background levels and provide better guidance for identification of the degree of contamination present at any given site.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app122211580/s1](https://www.mdpi.com/article/10.3390/app122211580/s1)]([https://www.mdpi.com/article/10.3390/app122211580/s1](https://www.mdpi.com/article/10.3390/app122211580/s1)), File S1: 48 h image analysis (48 master); File S2: DTW function for use with other files (dtw); File S3: Histogram code for running qualitative analysis on Green Laser images only (GreenQualitative); File S4: Histogram code for running qualitative analysis on Both Laser images (Qualitative); File S5: Density Difference and DTW analysis for Both Laser images (Quantitative). Each File is provided in its original Matlab version (.m) and with code copied to Word (.docx) for viewing use.  
Conceptualization, K.T., H.D. and A.M.; methodology, K.T. and H.D.; software, K.T.; validation, K.T., H.D., W.K. and P.F.; formal analysis, K.T., H.D. and P.F.; investigation, K.T. and H.D.; resources, K.T., H.D. and A.M.; data curation, K.T.; writing--original draft preparation, K.T.; writing--review and editing, K.T., H.D., A.M., W.K. and P.F.; visualization, K.T., H.D. and P.F.; supervision, K.T.; project administration, K.T.; funding acquisition, H.D. and K.T. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was funded by the Consortium for Monitoring, Technology, and Verification under the Department of Energy National Nuclear Security Administration award number DE-NA0003920. A.M. acknowledges support from ONR and NASA. This is SOEST publication number 11595.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The datasets and images analyzed for this study can be found in the following Google Drive folder: Quantifying Moss Response-Frontiers-Data Availability at [[https://drive.google.com/drive/folders/11](https://drive.google.com/drive/folders/11) eRay%cpX2g543 ilekbw1 vHpFX3_1 eqBusp=sharing]([https://drive.google.com/drive/folders/11](https://drive.google.com/drive/folders/11) eRay%cpX2g543 ilekbw1 vHpFX3_1 eqBusp=sharing) (accessed on 12 August 2022).  
**Conflicts of Interest:** The authors declare no conflict of interest.