Design of a portable sensor suite for real-time monitoring of crop water stress index in maize breeding plots

In: Precision agriculture '19
Authors:
O.E. Apolo-Apolo Aerospace Engineering and Fluids Mechanics Department, University of Seville, Ctra. Sevilla-Utrera km 1, 41013 Seville, Spain.

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M. Pérez-Ruiz Aerospace Engineering and Fluids Mechanics Department, University of Seville, Ctra. Sevilla-Utrera km 1, 41013 Seville, Spain.

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J. Martínez-Guanter Aerospace Engineering and Fluids Mechanics Department, University of Seville, Ctra. Sevilla-Utrera km 1, 41013 Seville, Spain.

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G. Egea Aerospace Engineering and Fluids Mechanics Department, University of Seville, Ctra. Sevilla-Utrera km 1, 41013 Seville, Spain.

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Type:
Chapter
Pages:
249–254
DOI:
https://doi.org/10.3920/978-90-8686-888-9_30

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Field-based high throughput phenotyping techniques using remote sensors mounted on terrestrial platforms (HTPPs) have emerged as a promising tool for plant breeders. Among the several phenotypes and crop characteristics that can be monitored, crop temperature is a variable of great interest as it provides indirect information on crop water status. However, its absolute value is affected by the prevailing environmental conditions. There has been great interest in developing thermal indices, such as crop water stress index (CWSI) needed to normalize the crop temperature against the changing climatic conditions. Therefore, the aim of this research was to test the feasibility of new artificial wet and dry reference surfaces that would be suitable to be mounted on HTPPs for CWSI estimation. Paper-made hemispherical artificial surfaces were constructed using three RGB colours and three replications per colour for each artificial surface (wet and dry). Plastic-made structures printed in the lab with a 3D printer were used to hold and to moisten the hemispherical paper-based surfaces. Temperatures of artificial wet and dry hemispherical surfaces were evaluated against well-watered maize canopies and senescent maize plants, respectively.

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Cover Precision agriculture '19
E-Book ISBN:
9789086868889
Publisher:
Wageningen Academic
Print Publication Date:
08 Jul 2019
Front Matter
Section 1 – Precision agriculture
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Section 2 – Precision horticulture
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Section 3 – Precision viticulture
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Section 4 – Precision crop protection
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Section 5 – Proximal and remote sensing of soil and crop
Characterisation of fungal diseases on winter wheat crop using proximal and remote multispectral imaging
Assessing infield temporal and spatial variability of leaf water potential using satellite imagery and meteorological data
Characterisation of cereal morphology through proximal stereo vision under contrasting nitrogen inputs
Early detection of corn and sunflower stress induced by chemical spraying
Hyperspectral imaging application under field conditions: assessment of the spatio-temporal variability of grape composition within a vineyard
Potential of optical sensors for nitrogen management in spring barley
Disentangling the sources of chlorophyll-content variability in banana fields
Sentinel-2 vegetation indices and apparent electrical conductivity to predict barley (Hordeum vulgare L.) yield
Accessing the plant architecture in 3D for plant phenotyping - recent approaches and requirements
Vegetation indices from remote sensing imagery as proxies for yield and grain N in wheat
Using terrestrial photogrammetry for leaf area estimation in maize under different plant growth stages
Early detection of Fusarium infection in corn using spectral analysis
Proximal versus remote sensing to monitor pasture quality in a Mediterranean Montado ecosystem
Section 6 – Applications of unmanned aerial systems
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Section 7 – Satellite-based applications for precision agriculture
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Section 8 – Site-specific nutrient, lime and seed management
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Section 9 – Site-specific canopy and harvest quality
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Section 10 – Precision pasture management
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Section 11 – Drainage optimization and variable rate irrigation
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Section 12 – Geostatistics, mapping and spatial data analysis
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Section 13 – Robotics, guidance and automation
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Section 14 – Economics of precision agriculture
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Section 15 – Adoption of precision agriculture
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Section 16 – Small farms/small holders and precision agriculture
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Section 17 – On farm experimentation with site-specific technologies
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Section 18 – Software and mobile apps for precision agriculture
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Section 19 – Decision support for precision agriculture
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Section 20 – Data mining for precision agriculture
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Back Matter

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