Hyperspectral imaging in the short-wave infrared range for rapid detection of PFAS in Cannabis sativa L. during phytoremediation

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are anthropogenic compounds that pose significant threats to water quality and food safety worldwide. Phytoremediation, a nature-based, cost-effective and scalable solution, has shown great potential for treating PFAS-contaminated sites. Among plants, Cannabis sativa L. (hemp) could be a promising plant species due to its ability to tolerate and accumulate PFAS, when grown in soil supplemented with these compounds. However, little is known about hemp's ability to phytoextract PFAS from contaminated water. Furthermore, the efficiency of PFAS absorption can be influenced by environmental conditions and the chemical structure of PFAS, making the need for rapid and efficient analytical techniques to monitor plant health and contamination levels compelling. Hyperspectral imaging (HSI) in the short-wave infrared (SWIR) range could be a valuable tool for this purpose. HSI is widely used in agriculture to assess plant health, monitor growth processes, and evaluate stress response related to contamination. In this study, different organs of Cannabis sativa L., including roots, stems, leaves and flowers, were analyzed after 15 days of growth in hydroponic culture in the presence of PFOA and PFOS separately. The aim was to detect potential spectral variations by comparing control plants grown in uncontaminated medium and plants grown in PFAS-contaminated medium. This study aims to utilize the spectral differences to develop a predictive model for monitoring PFAS contamination. By identifying specific spectral signatures associated with PFAS exposure, the research seeks to improve the efficiency of phytoremediation processes by rapidly assessing contamination levels in Cannabis sativa L. This approach could offer a practical and scalable solution for managing PFAS pollution and protecting environmental and human health