Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.1080/01431161.2025.2487249 |
Lizenz  |
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| Titel (primär) | Monitoring nickel and zinc accumulation in phytoremediation plants using spectroscopy and spectral indices: a pot study with Brassica juncea (Indian Mustard) |
| Autor | Kästner, F.; Kuester, T.; Feilhauer, H.; Sut-Lohmann, M. |
| Quelle | International Journal of Remote Sensing |
| Erscheinungsjahr | 2025 |
| Department | RS |
| Band/Volume | 46 |
| Heft | 9 |
| Seite von | 3618 |
| Seite bis | 3641 |
| Sprache | englisch |
| Topic | T5 Future Landscapes |
| Supplements | https://www.tandfonline.com/action/downloadSupplement?doi=10.1080%2F01431161.2025.2487249&file=tres_a_2487249_sm4115.png |
| Keywords | hyperaccumulator plant; phytoextraction; hyperspectral; plant stress; remote sensing; vegetation |
| Abstract | Soil contamination by potential toxic elements (PTEs) is a global issue resulting from various human activities like industry, agriculture and mining. These activities release harmful elements into the environment, posing risks to ecosystems and human health. To tackle this, methods like phytoremediation, which employs hyperaccumulator plants like Brassica juncea (Indian Mustard), are increasingly important. These plants absorb pollutants from soil, air or water, offering a natural remediation solution. An efficient implementation of phytoremediation requires a rapid, user-friendly and area-wide monitoring of the hyperaccumulator to first assess and estimate the PTE accumulation trend. An evaluation, whether this monitoring can be carried out on the basis of imaging spectroscopy data, is still missing. We cultivated B. juncea plants under varying nickel and zinc concentrations and analysed their leaf and canopy reflectance characteristics through hyperspectral measurements. Using Random Forest Regression (RFR), we identified relationships between PTE concentrations and reflectance data as well as spectral indices. Correlations between PTE concentration and spectral vegetation indices were quantified by distance correlations, due to non-linear data. We found that B. juncea effectively accumulates high Ni and Zn concentrations, altering its optical properties. The analysis revealed associations between PTE accumulation and specific spectral indices, indicating potential for PTE monitoring in B. juncea using imaging spectroscopy. RFR models demonstrated good performance in predicting PTE concentrations from canopy and leaf reflectance data. The RFR feature importance analysis showed that for canopy data the near-infrared spectral region has high importance for predicting Ni and the visible spectral region and the indices BRI, CVI, BGI, PPR, CARI and TCARI/OSAVI is important for Zn prediction. However, the importance of spectral regions varied for Ni and Zn prediction, highlighting the need for PTE specific monitoring approaches. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=30771 |
| Kästner, F., Kuester, T., Feilhauer, H., Sut-Lohmann, M. (2025): Monitoring nickel and zinc accumulation in phytoremediation plants using spectroscopy and spectral indices: a pot study with Brassica juncea (Indian Mustard) Int. J. Remote Sens. 46 (9), 3618 - 3641 10.1080/01431161.2025.2487249 |
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