Laser-Induced Fluorescence for Monitoring Environmental Contamination and Stress in the Moss Thuidium plicatile .
Kelly TruaxHenrietta DulaiAnupam MisraWendy KuhnePeter FulekyCelia SmithMilton A GarcésPublished in: Plants (Basel, Switzerland) (2023)
The ability to detect, measure, and locate the source of contaminants, especially heavy metals and radionuclides, is of ongoing interest. A common tool for contaminant identification and bioremediation is vegetation that can accumulate and indicate recent and historic pollution. However, large-scale sampling can be costly and labor-intensive. Hence, non-invasive in-situ techniques such as laser-induced fluorescence (LIF) are becoming useful and effective ways to observe the health of plants through the excitation of organic molecules, e.g., chlorophyll. The technique presented utilizes images collected of LIF in moss to identify different metals and environmental stressors. Analysis through image processing of LIF response was key to identifying Cu, Zn, Pb, and a mixture of the metals at nmol/cm 2 levels. Specifically, the RGB values from each image were used to create density histograms of each color channel's relative pixel abundance at each decimal code value. These histograms were then used to compare color shifts linked to the successful identification of contaminated moss samples. Photoperiod and extraneous environmental stressors had minimal impact on the histogram color shift compared to metals and presented with a response that differentiated them from metal contamination.
Keyphrases
- human health
- heavy metals
- risk assessment
- health risk
- health risk assessment
- energy transfer
- deep learning
- climate change
- sewage sludge
- drinking water
- single molecule
- healthcare
- public health
- machine learning
- bioinformatics analysis
- convolutional neural network
- optical coherence tomography
- water soluble
- social media
- heat stress
- antibiotic resistance genes