Detecting the attributes of a wheat crop using digital imagery acquired from a low-altitude platform

Abstract

A low-altitude platform utilising a 1.8-m diameter tethered helium balloon was used to position a multispectral sensor, consisting of two digital cameras, above a fertiliser trial plot where wheat (Triticum spp.) was being grown. Located in Cecil Plains, Queensland, Australia, the plot was a long-term fertiliser trial being conducted by a fertiliser company to monitor the response of crops to various levels of nutrition. The different levels of nutrition were achieved by varying nitrogen application rates between 0-120 units of N at 40 unit increments. Each plot had received the same application rate for 10 years. Colour and nearinfrared images were acquired that captured the whole 2 ha plot. These images were examined and relationships sought between the captured digital information and the crop parameters imaged at anthesis and the at-harvest quality and quantity parameters. The statistical analysis techniques used were correlation analysis, discriminant analysis, and partial least squares regression. A high correlation was found between the image and yield (R 2 = 0.91) and a moderate correlation between the image and grain protein content (R 2 = 0.66). The utility of the system could be extended by choosing a more mobile platform. This would increase the potential for the system to be used to diagnose the causes of the variability and allow remediation, and/or to segregate the crop at harvest to meet certain quality parameters.Keywords: grain protein, grain yield, low altitude, digital camera This is the authors' final pre-print version of: Jensen, Troy and Apan, Armando and Young, Frank and Zeller, Lez (2007) Detecting the attributes of a wheat crop using digital 3D imagery acquired from a low-altitude platform.

Deploying four optical UAV-based sensors over grassland: challenges and limitations

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Acquisition of NIR-Green-Blue Digital Photographs from Unmanned Aircraft for Crop Monitoring

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Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum

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