Aerial imagery for yield prediction

McCarthy, Alison and Foley, Joseph (2018) Aerial imagery for yield prediction. In: 2018 Australian Cotton Conference, 7-9 Aug 2018, Gold Coast, Australia.

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Abstract

UAVs enable fast, high resolution image capture of cotton fields. These images are typically assessed manually to identify areas of stress or reduced productivity. However, these assessments are not currently linked directly with on-farm management decisions. NCEA has developed software that determines yield prediction and irrigation requirements from: (i) UAV images; (ii) automated image analysis that extract cotton growth rates; and (iii) biophysical cotton model. CottonInfo extension officers and agronomists collected imagery in three regions in the 2016/17 and 2017/18 cotton seasons. Yield predictions from the evaluations in the 2016/17 season were within 5% of the final yield.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Speech)
Refereed: No
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Institute for Advanced Engineering and Space Sciences - Centre for Agricultural Engineering (1 Aug 2018 -)
Faculty/School / Institute/Centre: Current - Institute for Advanced Engineering and Space Sciences - Centre for Agricultural Engineering (1 Aug 2018 -)
Date Deposited: 06 Feb 2020 06:41
Last Modified: 11 Feb 2020 23:33
Uncontrolled Keywords: Aerial imagery; cotton yield; yield prediction
Fields of Research : 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070104 Agricultural Spatial Analysis and Modelling
09 Engineering > 0906 Electrical and Electronic Engineering > 090602 Control Systems, Robotics and Automation
07 Agricultural and Veterinary Sciences > 0703 Crop and Pasture Production > 070302 Agronomy
Socio-Economic Objective: D Environment > 96 Environment > 9609 Land and Water Management > 960905 Farmland, Arable Cropland and Permanent Cropland Water Management
URI: http://eprints.usq.edu.au/id/eprint/35491

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