Field Phenotyping for the Future

Atkinson, Jonathan A.; Jackson, Robert J.; Bentley, Alison R.; Ober, Eric S.; Wells, Darren M.

doi:10.1002/9781119312994.apr0651

Cited by 25 publications

(13 citation statements)

References 64 publications

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“…The current food demand will double by 2050 because of projected population and socio-economic growth. For developing countries to meet this challenge, cereal yields need to increase by 40%, and net irrigation water requirements will increase by 40–50% (Atkinson et al, 2018). It is necessary to accelerate plant breeding efforts to increase potential yields and achieve maximum production per unit of applied irrigation water.…”

Section: Introductionmentioning

confidence: 99%

Maize Canopy Temperature Extracted From UAV Thermal and RGB Imagery and Its Application in Water Stress Monitoring

et al. 2019

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To identify drought-tolerant crop cultivars or achieve a balance between water use and yield, accurate measurements of crop water stress are needed. In this study, the canopy temperature (Tc) of maize at the late vegetative stage was extracted from high-resolution red–green–blue (RGB, 1.25 cm) and thermal (7.8 cm) images taken by an unmanned aerial vehicle (UAV). To reduce the number of parameters for crop water stress monitoring, four simple methods that require only Tc were identified: Tc, degrees above non-stress, standard deviation of Tc, and variation coefficient of Tc. The ground-truth temperatures obtained using a handheld infrared thermometer were used to calibrate the temperature obtained from the UAV thermal images and to evaluate the Tc extraction results. Measured leaf stomatal conductance values were used to evaluate the performance of the four Tc-based crop water stress indicators. The results showed a strong correlation between ground-truth Tc and Tc extracted by the red–green ratio index (RGRI)-Otsu method proposed in this study, with a coefficient of determination of 0.94 (n = 15) and root mean square error value of 0.7°C. The RGRI-Otsu method was most accurate for estimating temperatures around 32.9°C, but the magnitude of residuals increased above and below this value. This phenomenon may be attributable to changes in canopy cover (leaf curling) under water stress, resulting in changes in the proportion of exposed sunlit soil in UAV thermal orthophotographs. Therefore, to improve the accuracy of maize canopy detection and extraction, optimal methods and better strategies for eliminating mixed pixels are needed. This study demonstrates the potential of using high-resolution UAV RGB images to supplement UAV thermal images for the accurate extraction of maize Tc.

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Section: Introductionmentioning

confidence: 99%

Maize Canopy Temperature Extracted From UAV Thermal and RGB Imagery and Its Application in Water Stress Monitoring

et al. 2019

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“…Plant phenotyping-the assessment of complex plant traits (architecture, growth, development, physiology, yield, etc.) and quantification of parameters underlying those traits [1][2][3]-is a rapidly developing transdiscipline of vital importance when addressing issues of global food security [4,5]. High-throughput phenotyping in controlled environments (growth chambers and glasshouses) is often delivered via large, expensive installations, leading to limited access and an increased relevance of "affordable phenotyping" solutions [6,7].…”

Section: Introductionmentioning

confidence: 99%

Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping

Bagley

Atkinson

Hunt

et al. 2020

Sensors

Self Cite

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High-throughput plant phenotyping in controlled environments (growth chambers and glasshouses) is often delivered via large, expensive installations, leading to limited access and the increased relevance of “affordable phenotyping” solutions. We present two robot vectors for automated plant phenotyping under controlled conditions. Using 3D-printed components and readily-available hardware and electronic components, these designs are inexpensive, flexible and easily modified to multiple tasks. We present a design for a thermal imaging robot for high-precision time-lapse imaging of canopies and a Plate Imager for high-throughput phenotyping of roots and shoots of plants grown on media plates. Phenotyping in controlled conditions requires multi-position spatial and temporal monitoring of environmental conditions. We also present a low-cost sensor platform for environmental monitoring based on inexpensive sensors, microcontrollers and internet-of-things (IoT) protocols.

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“…Conventionally, punctual detection of the physiological status of plants, a range of technologies and/or their combinations have been applied 43 – 45 , such as electrical impedance spectroscopy (EIS) 24 , 25 ,chlorophyll fluorescence imaging 46 , 47 , multispectral imaging 48 , thermal imaging 49 and electric signals 50 .…”

Section: Discussionmentioning

confidence: 99%

Real-time monitoring of Arundo donax response to saline stress through the application of in vivo sensing technology

Janni

Cocozza

Brilli

et al. 2021

Sci Rep

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One of the main impacts of climate change on agriculture production is the dramatic increase of saline (Na+) content in substrate, that will impair crop performance and productivity. Here we demonstrate how the application of smart technologies such as an in vivo sensor, termed bioristor, allows to continuously monitor in real-time the dynamic changes of ion concentration in the sap of Arundo donax L. (common name giant reed or giant cane), when exposed to a progressive salinity stress. Data collected in vivo by bioristor sensors inserted at two different heights into A. donax stems enabled us to detect the early phases of stress response upon increasing salinity. Indeed, the continuous time-series of data recorded by the bioristor returned a specific signal which correlated with Na+ content in leaves of Na-stressed plants, opening a new perspective for its application as a tool for in vivo plant phenotyping and selection of genotypes more suitable for the exploitation of saline soils.

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Field Phenotyping for the Future

Cited by 25 publications

References 64 publications

Maize Canopy Temperature Extracted From UAV Thermal and RGB Imagery and Its Application in Water Stress Monitoring

Maize Canopy Temperature Extracted From UAV Thermal and RGB Imagery and Its Application in Water Stress Monitoring

Low-Cost Automated Vectors and Modular Environmental Sensors for Plant Phenotyping

Real-time monitoring of Arundo donax response to saline stress through the application of in vivo sensing technology

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