Abstract
The application of proximal hyperspectral sensing, using simple vegetation indices, offers an easy, fast, and non-destructive approach for assessing various plant variables related to salinity tolerance. Because most existing indices are site- and species-specific, published indices must be further validated when they are applied to other conditions and abiotic stress. This study compared the performance of various published and newly constructed indices, which differ in algorithm forms and wavelength combinations, for remotely assessing the shoot dry weight (SDW) as well as chlorophyll a (Chla), chlorophyll b (Chlb), and chlorophyll a+b (Chlt) content of two wheat genotypes exposed to three salinity levels. Stepwise multiple linear regression (SMLR) was used to extract the most influential indices within each spectral reflectance index (SRI) type. Linear regression based on influential indices was applied to predict plant variables in distinct conditions (genotypes, salinity levels, and seasons). The results show that salinity levels, genotypes, and their interaction had significant effects (p ≤ 0.05 and 0.01) on all plant variables and nearly all indices. Almost all indices within each SRI type performed favorably in estimating the plant variables under both salinity levels (6.0 and 12.0 dS m−1) and for the salt-sensitive genotype Sakha 61. The most effective indices extracted from each SRI type by SMLR explained 60%–81% of the total variability in four plant variables. The various predictive models provided a more accurate estimation of Chla and Chlt content than of SDW and Chlb under both salinity levels. They also provided a more accurate estimation of SDW than of Chl content for salt-tolerant genotype Sakha 93, exhibited strong performance for predicting the four variables for Sakha 61, and failed to predict any variables under control and Chlb for Sakha 93. The overall results indicate that the simple form of indices can be used in practice to remotely assess the growth and chlorophyll content of distinct wheat genotypes under saline field conditions.
Highlights
The scarcity of freshwater in arid and semiarid countries requires the use of brackish water as an alternative source for irrigation in agriculture sectors, consuming approximately75% of the available water supply in these countries [1]
Sakha 93, and this was more evident for Chl content variables than it was for shoot dry weight (SDW) (Figure 3)
This study evaluated the potential use of 60 spectral indices, including 49 published and newly constructed indices, for assessing SDW and Chl content (Chla, chlorophyll b (Chlb), and Chlt) of two wheat genotypes differing in their salt tolerance and exposed to three salinity levels: control, 6 dS m−1, and dS m−1
Summary
The scarcity of freshwater in arid and semiarid countries requires the use of brackish water as an alternative source for irrigation in agriculture sectors, consuming approximately75% of the available water supply in these countries [1]. The scarcity of freshwater in arid and semiarid countries requires the use of brackish water as an alternative source for irrigation in agriculture sectors, consuming approximately. Saudi Arabia, which represents an ideal model of arid countries, brackish groundwater represents approximately 90% of the water used in agriculture [2]. Previous studies have reported the feasibility of irrigating several field crops, including wheat, with brackish water once or twice during the crop’s life cycle [3,4,5]. Continuously irrigating crops with brackish water leads to salinization of the soil. Feasible strategies are urgently needed to sustain growth and productivity of wheat crops under salinity stress.
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