Abstract
Plant breeding trials are extensive (100s to 1000s of plots) and are difficult and expensive to monitor by conventional means, especially where measurements are time-sensitive. For example, in a land-based measure of canopy temperature (hand-held infrared thermometer at two to 10 plots per minute), the atmospheric conditions may change greatly during the time of measurement. Such sensors measure small spot samples (2 to 50 cm2), whereas image-based methods allow the sampling of entire plots (2 to 30 m2). A higher aerial position allows the rapid measurement of large numbers of plots if the altitude is low (10 to 40 m) and the flight control is sufficiently precise to collect high-resolution images. This paper outlines the implementation of a customized robotic helicopter (gas-powered, 1.78-m rotor diameter) with autonomous flight control and software to plan flights over experiments that were 0.5 to 3 ha in area and, then, to extract, straighten and characterize multiple experimental field plots from images taken by three cameras. With a capacity to carry 1.5 kg for 30 min or 1.1 kg for 60 min, the system successfully completed >150 flights for a total duration of 40 h. Example applications presented here are estimations of the variation in: ground cover in sorghum (early season); canopy temperature in sugarcane (mid-season); and three-dimensional measures of crop lodging in wheat (late season). Together with this hardware platform, improved software to automate the production of ortho-mosaics and digital elevation models and to extract plot data would further benefit the development of high-throughput field-based phenotyping systems.
Highlights
Crop breeding requires continued investment to maintain performance, against the evolving resistances of pests and diseases to control measures, and to improve yields as crop production spreads into increasingly marginal environments that are subject to the additional risk of the negative impacts of climate change
We provide an evaluation of the performance of the platform for field-based phenotyping (FBP) applications in multiple crops, considering the use of aerial imagery to detect crop cover and crop canopy temperature and to generate digital elevation models of variations in crop height related to the lodging of the plots
This would allow high-quality masking from those images to be transferred to thermal images, e.g., for estimation of the thermal effects associated with lodging events or with canopy height, per se, which has been shown to be genetically associated with effects on canopy temperature [23]
Summary
Crop breeding requires continued investment to maintain performance, against the evolving resistances of pests and diseases to control measures, and to improve yields as crop production spreads into increasingly marginal environments that are subject to the additional risk of the negative impacts of climate change. While ground-based vehicles may be suitable for research farm applications, plant breeding typically entails multiple field experiments grown on commercial properties over a large geographic area spanning >1000 km in extent for sorghum, wheat, cotton or sugarcane in Australia These trials may only be visited on three or four occasions, including when the plots are harvested, so that timely visits with FBP ground vehicles would be greatly constrained by transport and operator costs, as well as the ground conditions at the time of visit. The paper does not provide comprehensive ground-truthing of the datasets, as these analyses are still on-going, but rather aims to overview the performance and capabilities of the system and to identify research needs for improvement
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