Detecting the attributes of a wheat crop using digital 3D imagery acquired from a low-altitude platform
Article
Article Title | Detecting the attributes of a wheat crop using digital 3D imagery acquired from a low-altitude platform |
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ERA Journal ID | 41630 |
Article Category | Article |
Authors | Jensen, T. (Author), Apan, A. (Author), Young, F. (Author) and Zeller, L. (Author) |
Journal Title | Computers and Electronics in Agriculture |
Journal Citation | 59 (1-2), pp. 66-77 |
Number of Pages | 12 |
Year | 2007 |
Publisher | Elsevier |
Place of Publication | Amsterdam, The Netherlands |
ISSN | 0168-1699 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.compag.2007.05.004 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0168169907001391 |
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 and 120 units of N at 40 unit increments. Each plot had received the same application rate for 10 years. Colour and near-infrared 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 (R2 = 0.91) and a moderate correlation between the image and grain protein content (R2 = 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 |
ANZSRC Field of Research 2020 | 401304. Photogrammetry and remote sensing |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | Department of Primary Industries, Queensland |
Australian Centre for Sustainable Catchments | |
Department of Primary Industries and Fisheries, Queensland |
https://research.usq.edu.au/item/9y572/detecting-the-attributes-of-a-wheat-crop-using-digital-3d-imagery-acquired-from-a-low-altitude-platform
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