Automated camera-based height and flower detection for wheat and chickpea

McCarthy, Alison and Tscharke, Matthew (2014) Automated camera-based height and flower detection for wheat and chickpea. In: 5th International Workshop on Applications of Computer Image Analysis and Spectroscopy in Agriculture (ASABE 2014), 12-13 Jul 2014, Montreal, Canada.

Abstract

The National Variety Trials (NVT) involve a yearly coordination of 630 grain trials conducted across 250 locations in Australia. At different stages of the crop season Trial Service Providers visually assess the attributes of the grain plants in each trial-plot to evaluate the growth and development of the different grain varieties. This involves manual measurements related to: (i) plant dimensions (height, canopy size); (ii) different stages of growth (seedling, tillering, jointing, boot and flowering); and (iii) germination rate. However, the availability of personnel to perform this monitoring is likely to be constrained to larger research stations.
A camera-based remote crop monitoring system and image analysis algorithms have been developed to automatically capture images of the trial plots, identify flowers and extract plant growth. This camera system would be permanently installed at the trial site to continuously collect images of the plots throughout the crop season. The system will reduce labour requirements and travel costs associated with manual inspection of grain variety trials, and improve timeliness and accuracy of growth stage identification.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: No
Item Status: Live Archive
Additional Information: This publication is copyright. It may be reproduced in whole or in part for the purposes of study, research, or review, but is subject to the inclusion of an acknowledgment of the source.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering
Date Deposited: 05 May 2015 04:19
Last Modified: 18 Jul 2017 03:28
Uncontrolled Keywords: image analysis; camera; automation; grain crops
Fields of Research : 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling
07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070101 Agricultural Land Management
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective: D Environment > 96 Environment > 9609 Land and Water Management > 960904 Farmland, Arable Cropland and Permanent Cropland Land Management
URI: http://eprints.usq.edu.au/id/eprint/26885

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