Hyperspectral reflectance sensing to assess the growth and photosynthetic properties of wheat cultivars exposed to different irrigation rates in an irrigated arid region

Abstract

Simultaneous indirect assessment of multiple and diverse plant parameters in an exact and expeditious manner is becoming imperative in irrigated arid regions, with a view toward creating drought-tolerant genotypes or for the management of precision irrigation. This study aimed to evaluate whether spectral reflectance indices (SRIs) in three parts of the electromagnetic spectrum ((visible-infrared (VIS), near-infrared (NIR)), and shortwave-infrared (SWIR)) could be used to track changes in morphophysiological parameters of wheat cultivars exposed to 1.00, 0.75, and 0.50 of the estimated evapotranspiration (ETc). Significant differences were found in the parameters of growth and photosynthetic efficiency, and canopy spectral reflectance among the three cultivars subjected to different irrigation rates. All parameters were highly and significantly correlated with each other particularly under the 0.50 ETc treatment. The VIS/VIS- and NIR/VIS-based indices were sufficient and suitable for assessing the growth and photosynthetic properties of wheat cultivars similar to those indices based on NIR/NIR, SWIR/NIR, or SWIR/SWIR. Almost all tested SRIs proved to assess growth and photosynthetic parameters, including transpiration rate, more efficiently when regressions were analyzed for each water irrigation rate individually. This study, the type of which has rarely been conducted in irrigated arid regions, indicates that spectral reflectance data can be used as a rapid and non-destructive alternative method for assessment of the growth and photosynthetic efficiency of wheat under a range of water irrigation rates.

Ability of Modified Spectral Reflectance Indices for Estimating Growth and Photosynthetic Efficiency of Wheat under Saline Field Conditions

“…Various changes in biophysical and biochemical characteristics of the canopy (such as leaf chlorophyll and other photosynthetic pigments contents, leaf tissue structure, dry matter accumulation, photosynthetic efficiency, and plant water status) have been found to be change in relation to osmotic and ionic components of salinity stress, and these cause noticeable variability in the spectral reflectance of the canopy in the three parts of the spectrum (VIS, NIR, and SWIR) domains [4,21,25,26]. Therefore, several SRIs that incorporate wavelengths related to the abovementioned main physiological characteristics of plants were modified to indirectly estimate the growth and photosynthetic efficiency of crops under various environmental conditions.…”

“…Changes in photosynthetic pigments, internal leaf structure, biochemical components, and leaf water content due to salinity stress are determined by substantial changes in the reflectance signatures of the canopy in three parts of the spectrum: visible region (VIS, 400-700 nm), near-infrared region (NIR, 700-1300 nm), and shortwave-infrared region (SWIR, 1300-2500 nm). The close relationship between the physiological status, canopy spectral reflectance, and plant variables means that spectral reflectance information has the potential to be used in plant phenomics applications and enables indirect estimates and quantification of stress-related plant parameters in a faster and non-destructive manner than other techniques [3][4][5]. However, the large amount of data collected by this technique, which hold thousands of general wavebands between VIS and SWIR domains, often limits its high-throughput applications [6].…”

“…Several spectral reflectance indices (SRIs) have been proposed as a proxy for biomass production and photosynthetic efficiency under either normal or stress conditions. For instance, the photochemical reflectance index (PRI = (R 531 − R 570 )/(R 531 + R 570 )) has been used in several studies as an indicator for photosynthetic efficiency under stress conditions, and significant linear relationships have been found between this index and Pn and Gs in forest tree, olive, tomato, and wheat crops under water stress conditions [4,[7][8][9][10][11][12]. It has also been shown that the normalized difference vegetation index (NDVI = (NIR λ − Red λ )/(NIR λ + Red λ )), which combines different wavelengths (λ) from the red region (620-690 nm) and near infrared region (760-900 nm), is associated with various stress-related plant parameters in different crops [3,[13][14][15].…”

Monitoring of water stress in peanut using multispectral indices derived from canopy hyperspectral

“…These results also suggested that wavelengths in the VIS and NIR ranges that combined together may offer a considerable potential for monitoring water stress of peanut crops under drought stress. The reason might be related the fact that the response of peanut plants to drought stress in the VIS and NIR range is possibly associated with a drought stress induced decline in the concentration of chlorophyll content and leaf structure, respectively [13] .…”

“…However, the traditional measurement of these parameters based on plant sampling technique were destructive, time-consuming and inappropriate for real-time monitoring of the water status of plant. Additionally, the traditional method might provide information on a single leaf irrespective of age and positions of leaves [13] .…”