Thermal imaging and passive reflectance sensing to estimate the water status and grain yield of wheat under different irrigation regimes

Elsayed, Salah; Elhoweity, Mohamed; Ibrahim, Hazem H.; Dewir, Yaser Hassan; Migdadi, Hussein M.; Schmidhalter, Urs

doi:10.1016/j.agwat.2017.05.001

Cited by 86 publications

(78 citation statements)

References 34 publications

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“…Variation in corn leaf temperature in response to drought is closely related to biomass accumulation [37]. Under water stress conditions, higher leaf temperatures provide reduced transpiration as a water-saving strategy, which results in low relative leaf water content [46] and low cell membrane stability, supported by a significantly higher injury rate [47]. According to Zia et al (2013) [10], the lower canopy temperature along with a satisfactory grain yield is probably associated with a more efficient or more developed, i.e., deeper root system.…”

Section: Discussionmentioning

confidence: 99%

Can Genetic Progress for Drought Tolerance in Popcorn Be Achieved by Indirect Selection?

et al. 2019

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The objective of this study was to estimate the direct and indirect effects of agricultural, morphological, physiological, and root traits of popcorn lines, under two conditions of water supply: full irrigation (FI) and drought stress (DS). A complete randomized block design with three replications was used to evaluate the following traits: expanded popcorn volume per hectare (EPV), 100-grain weight (100GW), mean ear length, mean ear diameter, number of grains per row (NGR), prolificacy (PRO), anthesis to silking interval, tassel length, number of tassel branches, plant height, shoot dry matter, green index (SPAD), and canopy temperature depression (CTD), root angle (RA), tap root volume (TRV), and crown root volume (CRV). Analyses of variance and path analysis, and subsequent partitioning of direct and indirect effects were performed. For the traits EPV, PRO, CTD, RA, CRV and TRV, the genotype x environment interaction was significant. Drought stress had significant effects on EPV (−7.15%), 100GW (−23.52%), SPAD (−29.31%), CTD (87.15%), RA (24.54%), and CRV (44.89%). The traits NGR and SPAD were found to be decisive for the expression of EPV. The exploitation of these traits by indirect selection is expected to induce increments in EPV in environments under DS and FI.

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Section: Discussionmentioning

confidence: 99%

Can Genetic Progress for Drought Tolerance in Popcorn Be Achieved by Indirect Selection?

et al. 2019

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“…The principle of elucidating plant evapotranspiration based on thermal remote sensing of CT has been used in a multitude of studies (Jones et al, 2009;Maes and Steppe, 2012;Khanal et al, 2017). It has been successfully applied to estimate grain yield (Elsayed et al, 2015;Becker and Schmidhalter, 2017;Elsayed et al, 2017), plant water, and plant drought stress (Calderón et al, 2013;Zarco-Tejada et al, 2013;Gómez-Candón et al, 2016), plant water status (Pou et al, 2014;Shafian and Maas, 2015;Bellvert et al, 2016), and soil water status (Hassan-Esfahani et al, 2015). unmanned aerial vehicle (UAV)-based thermography has been conducted in a multitude of studies as well (Zarco-Tejada et al, 2013;Gómez-Candón et al, 2016;Hoffmann et al, 2016;Ortega-Farías et al, 2016;Maes et al, 2017;Ribeiro-Gomes et al, 2017;Santesteban et al, 2017;Malbéteau et al, 2018;Sankaran et al, 2018;Sagan et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Multi-Image Unmanned Aerial Vehicle Based High-Throughput Field Phenotyping of Canopy Temperature

et al. 2020

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Canopy temperature (CT) has been related to water-use and yield formation in crops. However, constantly (e.g., sun illumination angle, ambient temperature) as well as rapidly (e.g., clouds) changing environmental conditions make it difficult to compare measurements taken even at short time intervals. This poses a great challenge for highthroughput field phenotyping (HTFP). The aim of this study was to i) set up a workflow for unmanned aerial vehicles (UAV) based HTFP of CT, ii) investigate different data processing procedures to combine information from multiple images into orthomosaics, iii) investigate the repeatability of the resulting CT by means of heritability, and iv) investigate the optimal timing for thermography measurements. Additionally, the approach was v) compared with other methods for HTFP of CT. The study was carried out in a winter wheat field trial with 354 genotypes planted in two replications in a temperate climate, where a UAV captured CT in a time series of 24 flights during 6 weeks of the grain-filling phase. Custom-made thermal ground control points enabled accurate georeferencing of the data. The generated thermal orthomosaics had a high spatial accuracy (mean ground sampling distance of 5.03 cm/pixel) and position accuracy [mean root-mean-square deviation (RMSE) = 4.79 cm] over all time points. An analysis on the impact of the measurement geometry revealed a gradient of apparent CT in parallel to the principle plane of the sun and a hotspot around nadir. Averaging information from all available images (and all measurement geometries) for an area of interest provided the best results by means of heritability. Correcting for spatial in-field heterogeneity as well as slight environmental changes during the measurements were performed with the R package SpATS. CT heritability ranged from 0.36 to 0.74. Highest heritability values were found in the early afternoon. Since senescence was found to influence the results, it is recommended to measure CT in wheat after flowering and before the onset of senescence. Overall, lowaltitude and high-resolution remote sensing proved suitable to assess the CT of crop

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“…Several multivariate analyses, such as partial least square regression (PLSR) models, are typically used to create a reliable linear relationship between a set of independent variables, such as full-spectrum ranges and SRIs, and response variables, which are often measured parameters. These analyses consider a set of SRIs as a single independent index and create a more flexible model for indirect estimation of measured parameters when the number of SRIs exceeds the number of measured parameters substantially [12,27,33,34]. Generally, hyperspectral data allow various multivariate analyses to consider the full VIS-SWIR spectrum and various SRIs.…”

Section: Introductionmentioning

confidence: 99%

Combining Hydrogeochemical Characterization and a Hyperspectral Reflectance Tool for Assessing Quality and Suitability of Two Groundwater Resources for Irrigation in Egypt

Gad

El-Hendawy

Al-Suhaibani

et al. 2020

Water

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Hyperspectral reflectance sensing provides a rapid and cost-effective technique for assessing the suitability of groundwater for irrigation by monitoring real-time changes in its quality at a large scale. In this study, we assessed the quality of 15 groundwater samples from El Fayoum depression in the Western Desert (WD) and 25 groundwater samples from the Central Nile Delta (CND) in Egypt using a traditional approach of the physiochemical parameters, irrigation water quality indicators (IWQIs), and hydrochemical facies. The spectral reflectance data of the water surface was used to build new simple reflectance indices (SRIs), and the performance of these indices for assessing IWQIs was compared with those by partial least square regression (PLSR) that was based on all SRIs or the full-spectrum ranges. Generally, the groundwater of the CND was fresher and more suitable for irrigation purposes than those of the WD. Based on the six IWQIs, ~6.7–60.0% and 85.0–100.0% of the groundwater samples of the WD and CND, respectively, were categorized as highly suitable for irrigation purposes. Based on hydrochemical facies, Na-Cl and Ca-HCO3 were dominant in the WD and CND, respectively, as well as the alkali earth metals (Na+ + K+), which significantly exceeded the alkaline earth metals (Ca2+ + Mg2+) in the WD, with the reverse for the CND. Most developed SRIs had a moderate, weak, and moderate to strong relationship with physiochemical parameters and IWQIs in the WD, CND, and across both regions, respectively. The PLSR models based on all SRIs provided a more accurate estimation of IWQIs in calibration and validation datasets than those based on full-spectrum ranges, and both PLSR models provided better estimation than the individual SRIs. These findings support the feasibility of using ground reflectance measurements as a fast and low-cost tool for the assessment and management of groundwater for irrigation in arid and semiarid regions.

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Thermal imaging and passive reflectance sensing to estimate the water status and grain yield of wheat under different irrigation regimes

Cited by 86 publications

References 34 publications

Can Genetic Progress for Drought Tolerance in Popcorn Be Achieved by Indirect Selection?

Can Genetic Progress for Drought Tolerance in Popcorn Be Achieved by Indirect Selection?

Assessment of Multi-Image Unmanned Aerial Vehicle Based High-Throughput Field Phenotyping of Canopy Temperature

Combining Hydrogeochemical Characterization and a Hyperspectral Reflectance Tool for Assessing Quality and Suitability of Two Groundwater Resources for Irrigation in Egypt

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