Articles
Drone-based thermal imagery for detecting water stress in a commercial apple orchard
Article number
1409_4
Pages
23 – 30
Language
English
Abstract
Drone based thermal imagery is a cost-effective technology that is potentially able to detect water stress on a scale that is commercially viable.
However, several parameters need to be quantified for a drone-based approach to be capable of practical use for identifying crop water stress.
In this regard, a pilot study was performed in a mature, commercial, ‘Cripps Red’, 0.36-ha apple orchard in the Elgin Valley, Western Cape, South Africa, during the 2021-2022 season.
Remote detection of water stress was tested by taking airborne thermal images at specific times, using the data to calculate crop water stress indices (CWSI), comparing the indices to stem water potential (SWP) measurements taken simultaneously, and comparing the indices and SWP measurements to expectations for trees in a sample that was subjected to water stress, and to expectations for those in a sample that was not water stressed.
The well-watered and water stressed trees were in a randomised design.
Images were captured using a DJI Mavic 2 Enterprise Dual drone equipped with a visual and thermal camera, at 80 m above ground, creating 640×480-pixel thermal images.
The initial results indicated that drone-based thermal imagery has the potential for use as an alternative, cost-effective method of detecting crop water stress on a commercial scale.
There was a significant level of correlation between the calculated CWSI and SWP measurements, and the water deficits that were engineered.
While the method delivers useful information in a timely manner and in a usable format, more needs to be done to develop methods of interpreting the data.
The thermography research applied to apple orchards to date has limited practical application at block/orchard scale, and the interpretation methods, similarly, require further research.
However, several parameters need to be quantified for a drone-based approach to be capable of practical use for identifying crop water stress.
In this regard, a pilot study was performed in a mature, commercial, ‘Cripps Red’, 0.36-ha apple orchard in the Elgin Valley, Western Cape, South Africa, during the 2021-2022 season.
Remote detection of water stress was tested by taking airborne thermal images at specific times, using the data to calculate crop water stress indices (CWSI), comparing the indices to stem water potential (SWP) measurements taken simultaneously, and comparing the indices and SWP measurements to expectations for trees in a sample that was subjected to water stress, and to expectations for those in a sample that was not water stressed.
The well-watered and water stressed trees were in a randomised design.
Images were captured using a DJI Mavic 2 Enterprise Dual drone equipped with a visual and thermal camera, at 80 m above ground, creating 640×480-pixel thermal images.
The initial results indicated that drone-based thermal imagery has the potential for use as an alternative, cost-effective method of detecting crop water stress on a commercial scale.
There was a significant level of correlation between the calculated CWSI and SWP measurements, and the water deficits that were engineered.
While the method delivers useful information in a timely manner and in a usable format, more needs to be done to develop methods of interpreting the data.
The thermography research applied to apple orchards to date has limited practical application at block/orchard scale, and the interpretation methods, similarly, require further research.
Authors
K. Cluver, E. Lötze, M.A. Vivier, C. Poblete-Echeverría
Keywords
crop water stress index, stem water potential, thermography, water deficit
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