Abstract
Restrictions on soil water supply can dramatically reduce crop yields by affecting the growth and development of plants. For this reason, screening tools that can detect crop water stress early have been long investigated, with canopy temperature (CT) being widely used for this purpose. In this study, we investigated the relationship between canopy temperature retrieved from unmanned aerial vehicles (UAV) based thermal imagery with soil and plant attributes, using a rainfed maize field as the area of study. The flight mission was conducted during the late vegetative stage and at solar noon, when a considerable soil water deficit was detected according to the soil water balance model used. While the images were being taken, soil sampling was conducted to determine the soil water content across the field. The sampling results demonstrated the spatial variability of soil water status, with soil volumetric water content (SVWC) presenting 10.4% of variation and values close to the permanent wilting point (PWP), reflecting CT readings that ranged from 32.8 to 40.6 °C among the sampling locations. Although CT correlated well with many of the physical attributes of soil that are related to water dynamics, the simple linear regression between CT and soil water content variables yielded coefficients of determination (R2) = 0.42, indicating that CT alone might not be sufficient to predict soil water status. Nonetheless, when CT was combined with some soil physical attributes in a multiple linear regression, the prediction capacity was significantly increased, achieving an R2 value = 0.88. This result indicates the potential use of CT along with certain soil physical variables to predict crop water status, making it a useful tool for studies exploring the spatial variability of in-season drought stress.
Highlights
Published: 28 November 2021Drought stress is considered the most damaging of all of the abiotic stresses, limiting the growth and development of plants and their yield [1,2]
The results showed that silt content, soil resistance to penetration (SRP) at 0–0.1 m, and macroporosity presented greater variation among soil physical variables, with a coefficient of variation (CV) of 38.1, 28.7, and 23.3%, respectively
From unmanned aerial vehicles (UAV)-based thermal imagery, we were able to generate a thermal orthomosaic representing the spatial variability of a rainfed maize canopy temperature along a field of
Summary
Published: 28 November 2021Drought stress is considered the most damaging of all of the abiotic stresses, limiting the growth and development of plants and their yield [1,2]. Precision agriculture (PA) consists of a site-specific form of agriculture that focuses on optimizing farm inputs by conducting the right management practice at the right place, at the right time, and at the appropriate intensity [4–6] To implement this concept, a proper characterization of within-field spatial variability is essential to understand the potential limiting factors. When soil water becomes limiting, the plants respond promptly by regulating the stomatal conductance to reduce transpiration as a water saving strategy, which leads to a lower evaporative cooling while increasing leaf temperature [11–13]. For this reason, canopy temperature has long been used as a proxy to assess crop water status [14], with remotely sensed temperature being constantly used
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