Detecting Plant Stress Using Thermal and Optical Imagery From an Unoccupied Aerial Vehicle
Type
ArticleKAUST Department
Biological and Environmental Science and Engineering (BESE) DivisionEarth System Observation and Modelling
Environmental Science and Engineering Program
Water Desalination and Reuse Research Center (WDRC)
KAUST Grant Number
Award No. 2302-01-01OSR
URF/1/2550-1
URF/1/3413-01
Date
2021-10-27Submitted Date
2021-07-01Permanent link to this record
http://hdl.handle.net/10754/673017
Metadata
Show full item recordAbstract
Soil and water salinization has global impact on the sustainability of agricultural production, affecting the health and condition of staple crops and reducing potential yields. Identifying or developing salt-tolerant varieties of commercial crops is a potential pathway to enhance food and water security and deliver on the global demand for an increase in food supplies. Our study focuses on a phenotyping experiment that was designed to establish the influence of salinity stress on a diversity panel of the wild tomato species, Solanum pimpinellifolium. Here, we explore how unoccupied aerial vehicles (UAVs) equipped with both an optical and thermal infrared camera can be used to map and monitor plant temperature (Tp) changes in response to applied salinity stress. An object-based image analysis approach was developed to delineate individual tomato plants, while a green–red vegetation index derived from calibrated red, green, and blue (RGB) optical data allowed the discrimination of vegetation from the soil background. Tp was retrieved simultaneously from the co-mounted thermal camera, with Tp deviation from the ambient temperature and its change across time used as a potential indication of stress. Results showed that Tp differences between salt-treated and control plants were detectable across the five separate UAV campaigns undertaken during the field experiment. Using a simple statistical approach, we show that crop water stress index values greater than 0.36 indicated conditions of plant stress. The optimum period to collect UAV-based Tp for identifying plant stress was found between fruit formation and ripening. Preliminary results also indicate that UAV-based Tp may be used to detect plant stress before it is visually apparent, although further research with more frequent image collections and field observations is required. Our findings provide a tool to accelerate field phenotyping to identify salt-resistant germplasm and may allow farmers to alleviate yield losses through early detection of plant stress via management interventions.Citation
Stutsel, B., Johansen, K., Malbéteau, Y. M., & McCabe, M. F. (2021). Detecting Plant Stress Using Thermal and Optical Imagery From an Unoccupied Aerial Vehicle. Frontiers in Plant Science, 12. doi:10.3389/fpls.2021.734944Sponsors
MT and his team were supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. 2302-01-01 for undertaking the plant experiments. MM and his team were supported by Competitive Research Grant Nos. URF/1/2550-1 and URF/1/3413-01 for undertaking the UAV-based component of this research.Publisher
Frontiers Media SAJournal
Frontiers in Plant ScienceAdditional Links
https://www.frontiersin.org/articles/10.3389/fpls.2021.734944/fullae974a485f413a2113503eed53cd6c53
10.3389/fpls.2021.734944
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