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Agronomy 2014, 4(3), 349-379; doi:10.3390/agronomy4030349

Proximal Remote Sensing Buggies and Potential Applications for Field-Based Phenotyping

1
High Resolution Plant Phenomics Centre, Australian Plant Phenomics Facility, CSIRO Plant Industry, GPO Box 1600, Canberra, ACT 2601, Australia
2
Plant Science Division, College of Life Sciences, University of Dundee at The James Hutton Institute, Invergowrie, Dundee DD2 5DA, Scotland, UK
3
School of Plant Biology, University of Western Australia, Crawley, WA 6009, Australia
*
Author to whom correspondence should be addressed.
Received: 10 March 2014 / Revised: 23 May 2014 / Accepted: 30 May 2014 / Published: 10 July 2014
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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Abstract

The achievements made in genomic technology in recent decades are yet to be matched by fast and accurate crop phenotyping methods. Such crop phenotyping methods are required for crop improvement efforts to meet expected demand for food and fibre in the future. This review evaluates the role of proximal remote sensing buggies for field-based phenotyping with a particular focus on the application of currently available sensor technology for large-scale field phenotyping. To illustrate the potential for the development of high throughput phenotyping techniques, a case study is presented with sample data sets obtained from a ground-based proximal remote sensing buggy mounted with the following sensors: LiDAR, RGB camera, thermal infra-red camera and imaging spectroradiometer. The development of such techniques for routine deployment in commercial-scale breeding and pre-breeding operations will require a multidisciplinary approach to leverage the recent technological advances realised in computer science, image analysis, proximal remote sensing and robotics. View Full-Text
Keywords: LiDAR; time of flight; hyperspectral; RGB camera; thermal imaging; chlorophyll fluorescence; image analysis; data processing; field experiments; wheat LiDAR; time of flight; hyperspectral; RGB camera; thermal imaging; chlorophyll fluorescence; image analysis; data processing; field experiments; wheat
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Deery, D.; Jimenez-Berni, J.; Jones, H.; Sirault, X.; Furbank, R. Proximal Remote Sensing Buggies and Potential Applications for Field-Based Phenotyping. Agronomy 2014, 4, 349-379.

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