Skip to main content
ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #329126

Research Project: Quantifying and Monitoring Nutrient Cycling, Carbon Dynamics and Soil Productivity at Field, Watershed and Regional Scales

Location: Hydrology and Remote Sensing Laboratory

Title: Evaluating leaf and canopy reflectance of stressed rice plants to monitor arsenic contamination

Author
item Bandaru, V. - University Of Maryland
item Daughtry, Craig
item Codling, Eton
item Hansen, D.j. - Oregon State University
item White-hansen, S. - Oregon State University
item Green, Carrie

Submitted to: International Journal of Environmental Research and Public Health
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/13/2016
Publication Date: 6/18/2016
Citation: Bandaru, V., Daughtry, C.S., Codling, E.E., Hansen, D., White-Hansen, S., Green, C.E. 2016. Evaluating leaf and canopy reflectance of stressed rice plants to monitor arsenic contamination. International Journal of Environmental Research and Public Health. 13:606. doi:10.3390/ijerph13060606.

Interpretive Summary: Arsenic contamination is a serious issue in rice cultivated soils of many countries and it is critical to monitor and control arsenic accumulation in rice plants to avoid adverse human health effects. We conducted a controlled study to assess the arsenic uptake in rice plants and the use of reflectance spectroscopy to monitor arsenic in rice plants. Results suggest that plants accumulate high arsenic amounts causing plant stress and changes in reflectance characteristics. For leaves, spectral vegetative indices (VI) were strongly related with arsenic content. However, at plant canopy scales, variations in soil reflectance and leaf area index (LAI) often confounded the relatively subtle differences in canopy reflectance associated with changes in leaf chlorophyll content due to arsenic. Pairs of vegetation indices that minimized variations in background reflectance and accentuated leaf reflectance were highly sensitive to arsenic levels in plant canopies. These pairs of vegetation indices could be useful tools to identify and monitor arsenic in rice grown on arsenic-contaminated soils.

Technical Abstract: Arsenic contamination is a serious problem in rice cultivated soils of many developing countries. Hence, it is critical to monitor and control arsenic uptake in rice plants to avoid adverse effects on human health. This study evaluated the feasibility of using reflectance spectroscopy to monitor arsenic in rice plants. Four arsenic levels were induced in hydroponically grown rice plants with application of 0, 5, 10 and 20 µmol L-1 sodium arsenate. Reflectance spectra of upper fully expanded leaves were acquired over visible and infrared (NIR) wavelengths. Additionally, canopy reflectance for the four arsenic levels was simulated using SAIL (Scattering by Arbitrarily Inclined Leaves) model for various soil moisture conditions and leaf area indices (LAI). Further, sensitivity of various vegetative indices (VIs) to arsenic levels was assessed. Plants that accumulate high amounts of arsenic exhibit less growth and lower chlorophyll concentrations which produce changes in leaf and canopy reflectance characteristics. For leaves, spectral vegetative indices (VI) were strongly related with arsenic content. However, at plant canopy scales, variations in soil reflectance and leaf area index (LAI) often confounded the relatively subtle differences in canopy reflectance associated with changes in leaf chlorophyll content due to arsenic. Some vegetation indices minimized variations in background reflectance (e.g., OSAVI, NIR/Red), while other indices accentuated variations in leaf and canopy reflectance (e.g., TCARI, MCARI). Pairs of these spectral indices were highly sensitive to changes in leaf chlorophyll concentrations associated with arsenic levels in plant canopies. Thus, these pairs of vegetation indices could be useful tools to identify and monitor arsenic in rice grown on arsenic-contaminated soils.