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Thermal stress in an Agroforestry System: a case study of the use of a thermal sensor and unmanned aerial vehicle

Year: 2025
Type: article
Abstract: An agroforestry system (AFS) is a multifaceted agricultural practice that integrates the cultivation of shade-providing trees and understory crops. These systems have been shown to play a crucial role in mitigating extreme temperatures, reducing soil evapotranspiration, and shielding crops from wind damage. Effective management practices, including pruning, ensure optimal light distribution and temperature regulation in the AFS. The employment of unmanned aerial vehicles (UAVs) has led to significant advancements in the evaluation of crop traits, including the assessment of heat stress. However, research addressing thermal stress and temperature variations across AFS areas is limited. It is evident that thermal stress exerts a substantial influence on the physiological and genetic processes within plants. The present study investigated the relationship between temperature, insolation, and thermal stress in a 0.5-hectare AFS at Universidade Federal de São Carlos, Brazil. A Unmanned Aerial Vehicle (UAV) equipped with a thermal sensor was utilized to capture thermal and RGB images in four regions. These images were then analyzed with software such as Agisoft Metashape and QGIS to calculate the Thermal Condition Index (TCI). This index enabled the quantification of plant stress. The findings indicated that the midday period experienced the highest levels of stress, particularly in open pasture areas. The correlation between insolation exposure and higher surface temperatures (up to 40.56 °C) was significant in these areas. In contrast, tree-covered areas demonstrated a lower level of stress. TCI variations have been shown to align with temperature trends, underscoring the significance of microclimatic data for optimizing AFS management practices, including pruning and crop selection.
Language: English
Subfield: Forestry
Open Access status: gold
Estimated APC paid: $19
OpenAlex ID: W4414243767
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