Abstract
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 high-throughput 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, low-altitude and high-resolution remote sensing proved suitable to assess the CT of crop genotypes in a large number of small field plots as is required in crop breeding and variety testing experiments.
Highlights
In view of current scenarios for climate change, canopy temperature (CT) is considered an important trait to select for adapted genotypes
A field experiment was conducted at the ETH field phenotyping platform field phenotyping platform (FIP) (Kirchgessner et al, 2017), a one-hectare field (“FIP field”) located at ETH Zurich's plant research station [47°27′01′′N and 8°40′57′′E, the World Geodetic System (WGS) 84]
Analysis of Orthomosaics Resulting From Different Blending Modes
Summary
In view of current scenarios for climate change, canopy temperature (CT) is considered an important trait to select for adapted genotypes. Low CTs have been associated with a 30% increased yield an increased water uptake by deeper roots (Lopes and Reynolds, 2010), when measured during grain filling. A greater transpiration is a major driver leading to high yield potential of C3 crops under conditions characterized by low to moderate stress (Roche, 2015). It is, still a challenge to obtain reliable quantitative CT measurements for larger breeding experiments with small plots, since plot-by-plot CT measurements generally have a low repeatability (Pask et al, 2012; Rebetzke et al, 2013; Sukumaran et al, 2015; Deery et al, 2016) and are very time consuming
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