Assessing plant pigmentation impacts: A novel approach integrating UAV and multispectral data to analyze atrazine metabolite effects from soil contamination
The objective of this study was to evaluate the levels of desethylatrazine (DEA), a hydrophilic metabolite of atrazine, and its impact on plant health. This was achieved by utilizing multispectral imagery captured by Unmanned Aerial Vehicles (UAVs) in combination with ground-measured data to assess...
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Elsevier
2024-12-01
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| Series: | Smart Agricultural Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375524001758 |
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| author | Thirasant Boonupara Patchimaporn Udomkun Simon Gibson-Poole Alistair Hamilton Puangrat Kaewlom |
| author_facet | Thirasant Boonupara Patchimaporn Udomkun Simon Gibson-Poole Alistair Hamilton Puangrat Kaewlom |
| author_sort | Thirasant Boonupara |
| collection | DOAJ |
| description | The objective of this study was to evaluate the levels of desethylatrazine (DEA), a hydrophilic metabolite of atrazine, and its impact on plant health. This was achieved by utilizing multispectral imagery captured by Unmanned Aerial Vehicles (UAVs) in combination with ground-measured data to assess photosynthetic pigment levels in Green Cos lettuce following atrazine application in agricultural soil. Strong correlations were found between DEA levels and chlorophyll a, chlorophyll b, and anthocyanin levels in lettuce (R² > 0.70), while the correlation with carotenoid levels was weaker (R² = 0.55). This disruption to the pigments could interfere with photosynthesis, potentially hindering the plant's growth and development, and ultimately leading to a reduction in yield. The Anthocyanin Reflectance Index (ARI) demonstrated a robust positive correlation with DEA, whereas the Normalized Difference Red Edge (NDRE), Leaf Chlorophyll Index (LCI), and Normalized Difference Vegetation Index (NDVI) displayed pronounced negative correlations. Incorporating ARI, LCI, and NDRE, with or without NDVI, provided the most accurate prediction of DEA levels, with an R² exceeding 0.96. NDRE emerged as the most efficient index for forecasting chlorophyll a and chlorophyll b levels. Modified Chlorophyll Absorption in Reflectance Index (MCARI) demonstrated the best fit for carotenoids, while ARI performed exceptionally well in describing actual measurements of anthocyanins (R² = 0.90). The best-performing VI models, developed from the selection of effective single variables, exhibited the best fit to actual pigment measurements (R² > 0.83). These findings underscore the role of UAV-derived multispectral imagery in assessing DEA levels and improving environmental monitoring, aiding in better planning for agriculture and environmental remediation to enhance ecosystem health and resilience. |
| format | Article |
| id | doaj-art-9e870d0eb53942c5965e5b75042a5fda |
| institution | Kabale University |
| issn | 2772-3755 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj-art-9e870d0eb53942c5965e5b75042a5fda2024-12-13T11:07:54ZengElsevierSmart Agricultural Technology2772-37552024-12-019100570Assessing plant pigmentation impacts: A novel approach integrating UAV and multispectral data to analyze atrazine metabolite effects from soil contaminationThirasant Boonupara0Patchimaporn Udomkun1Simon Gibson-Poole2Alistair Hamilton3Puangrat Kaewlom4Department of Environmental Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai, 50200, Thailand; Living Soil Co., Ltd., Chiang Mai, 50120, ThailandDepartment of Environmental Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai, 50200, Thailand; Office of Research Administration, Chiang Mai University, Chiang Mai, 50200, ThailandScotland's Rural College, Peter Wilson Building, Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UKScotland's Rural College, Peter Wilson Building, Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UKDepartment of Environmental Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai, 50200, Thailand; Living Soil Co., Ltd., Chiang Mai, 50120, Thailand; Corresponding author.The objective of this study was to evaluate the levels of desethylatrazine (DEA), a hydrophilic metabolite of atrazine, and its impact on plant health. This was achieved by utilizing multispectral imagery captured by Unmanned Aerial Vehicles (UAVs) in combination with ground-measured data to assess photosynthetic pigment levels in Green Cos lettuce following atrazine application in agricultural soil. Strong correlations were found between DEA levels and chlorophyll a, chlorophyll b, and anthocyanin levels in lettuce (R² > 0.70), while the correlation with carotenoid levels was weaker (R² = 0.55). This disruption to the pigments could interfere with photosynthesis, potentially hindering the plant's growth and development, and ultimately leading to a reduction in yield. The Anthocyanin Reflectance Index (ARI) demonstrated a robust positive correlation with DEA, whereas the Normalized Difference Red Edge (NDRE), Leaf Chlorophyll Index (LCI), and Normalized Difference Vegetation Index (NDVI) displayed pronounced negative correlations. Incorporating ARI, LCI, and NDRE, with or without NDVI, provided the most accurate prediction of DEA levels, with an R² exceeding 0.96. NDRE emerged as the most efficient index for forecasting chlorophyll a and chlorophyll b levels. Modified Chlorophyll Absorption in Reflectance Index (MCARI) demonstrated the best fit for carotenoids, while ARI performed exceptionally well in describing actual measurements of anthocyanins (R² = 0.90). The best-performing VI models, developed from the selection of effective single variables, exhibited the best fit to actual pigment measurements (R² > 0.83). These findings underscore the role of UAV-derived multispectral imagery in assessing DEA levels and improving environmental monitoring, aiding in better planning for agriculture and environmental remediation to enhance ecosystem health and resilience.http://www.sciencedirect.com/science/article/pii/S2772375524001758Environmental monitoringRemote sensingSoil contaminationPlant healthPesticidesHerbicides |
| spellingShingle | Thirasant Boonupara Patchimaporn Udomkun Simon Gibson-Poole Alistair Hamilton Puangrat Kaewlom Assessing plant pigmentation impacts: A novel approach integrating UAV and multispectral data to analyze atrazine metabolite effects from soil contamination Smart Agricultural Technology Environmental monitoring Remote sensing Soil contamination Plant health Pesticides Herbicides |
| title | Assessing plant pigmentation impacts: A novel approach integrating UAV and multispectral data to analyze atrazine metabolite effects from soil contamination |
| title_full | Assessing plant pigmentation impacts: A novel approach integrating UAV and multispectral data to analyze atrazine metabolite effects from soil contamination |
| title_fullStr | Assessing plant pigmentation impacts: A novel approach integrating UAV and multispectral data to analyze atrazine metabolite effects from soil contamination |
| title_full_unstemmed | Assessing plant pigmentation impacts: A novel approach integrating UAV and multispectral data to analyze atrazine metabolite effects from soil contamination |
| title_short | Assessing plant pigmentation impacts: A novel approach integrating UAV and multispectral data to analyze atrazine metabolite effects from soil contamination |
| title_sort | assessing plant pigmentation impacts a novel approach integrating uav and multispectral data to analyze atrazine metabolite effects from soil contamination |
| topic | Environmental monitoring Remote sensing Soil contamination Plant health Pesticides Herbicides |
| url | http://www.sciencedirect.com/science/article/pii/S2772375524001758 |
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