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Evaluation of Hyperspectral Reflectance Parameters to Assess the Leaf Water Content in Soybean

1
Department of Plant Physiology, Faculty of Agrobiology and Food Resources, Slovak University of Agriculture, Tr. A. Hlinku 2, 949 76 Nitra, Slovakia
2
Department of Water Resources and Environmental Engineering, Faculty of Horticulture and Landscape Engineering, Slovak University of Agriculture, Tr. A. Hlinku 2, 949 76 Nitra, Slovakia
3
National Agricultural and Food Centre, Research Institute of Plant Production, Bratislavska cesta 122, 921 68 Piešťany, Slovakia
*
Authors to whom correspondence should be addressed.
Water 2019, 11(3), 443; https://doi.org/10.3390/w11030443
Received: 21 January 2019 / Revised: 21 February 2019 / Accepted: 25 February 2019 / Published: 1 March 2019
(This article belongs to the Section Water Resources Management and Governance)
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Abstract

Nondestructive assessment of water content and water stress in plants is an important component in the rational use of crop irrigation management in precision agriculture. Spectral measurements of light reflectance in the UV/VIS/NIR region (350–1075 nm) from individual leaves were acquired under a rapid dehydration protocol for validation of the remote sensing water content assessment in soybean plants. Four gravimetrical approaches of leaf water content assessment were used: relative water content (RWC), foliar water content as percent of total fresh mass (FWCt), foliar water content as percent of dry mass (FWCd), and equivalent water thickness (EWT). Leaf desiccation resulted in changes in optical properties with increasing relative reflectance at wavelengths between 580 and 700 nm. The highest positive correlations were observed for the relations between the photochemical reflectance index (PRI) and EWT (rP = 0.860). Data analysis revealed that the specific water absorption band at 970 nm showed relatively weaker sensitivity to water content parameters. The prediction of leaf water content parameters from PRI measurements was better with RMSEs of 12.4% (rP = 0.786), 9.1% (rP = 0.736), and 0.002 (rP = 0.860) for RWC, FWCt, and EWT (p < 0.001), respectively. The results may contribute to more efficient crop water management and confirmed that EWT has a statistically closer relationship with reflectance indices than other monitored water parameters. View Full-Text
Keywords: water; dehydration; hyperspectral reflectance; vegetation indices; remote sensing; soybean water; dehydration; hyperspectral reflectance; vegetation indices; remote sensing; soybean
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Kovar, M.; Brestic, M.; Sytar, O.; Barek, V.; Hauptvogel, P.; Zivcak, M. Evaluation of Hyperspectral Reflectance Parameters to Assess the Leaf Water Content in Soybean. Water 2019, 11, 443.

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