Document Type : Research Paper
Authors
1
professor, Department of Irrigation and Drainage, Facualty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
2
1. Ph.D. student, Department of Irrigation and Drainage, Faculty of Water and Environmental, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
3
Department of Environmental Engineering, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
4
دانشیار دانشگاه شهید چمران اهواز
5
5. Professor of Remote Sensing and GIS, Faculty of Earth Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
Abstract
Early detection of plant water status is essential to optimize crop water use, and to implement water savings methods. Remote sensing methods such as the spectrometric method are applied. These methods are reliable, fast, and non-destructive for studying the biochemical parameters of plants, including their water conditions. The purpose of this study was to investigate the potential of plant water spectral indices, which include water indices 1–4 (WI1–4), normal water index 5(nwi5), spectral vegetation indices RDVI, NDVI, and OSAVI, for the detection of water content in tomato plants. The experimental treatments involved silica nanoparticles with concentrations of 0 and 100 mg/L and three water regimes (100%, 80%, and 60% of crop water requirement). The results showed that the relative water content (RWC) of leaves in tomato plants under deficit irrigation treatments in different months and throughout the study period decreased with increasing water stress. However, the difference in the amount of this index was significant only in the treatment with full irrigation and 60% of the plant water requirement. In addition, the relative water content of tomato leaves in nanoparticles with concentrations of 100 mg/l was higher than 0 mg/l. Among all tested spectral indices, NWI5 and WI1, WI2 showed the least and greatest consistent association with relative water content, respectively. In conclusion, spectral reflectance could be useful for fast, non-destructive, and reliable assessment of the water status of tomato plants in greenhouse conditions.
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