Development of an integrated plant-based image sensing system for soil-water and nitrogen status estimation in cotton

McCarthy, Alison and Nguyen, Tai (2015) Development of an integrated plant-based image sensing system for soil-water and nitrogen status estimation in cotton. Project Report. University of Southern Queensland, National Centre for Engineering in Agriculture , Toowoomba, Australia. [Report]

Abstract

Optimal crop yields require optimisation of both water and nitrogen application. Industry-standard soil-water sensors require contact with the soil and provide information for a single point in the field although there is often spatial variability in soil type and crop growth. Nitrogen content is typically determined using destructive manual soil coring followed by laboratory testing. It is often not practical to install multiple soil-water sensors in a commercial field situation or to conduct multiple soil cores throughout the cotton season.

A non-contact soil-water and nitrogen estimation system offers growers potential savings by optimising water and fertiliser management and efficiency and crop productivity. Existing non-contact approaches typically have low spatial resolution and cannot discriminate plants from soil. An alternative approach is a camera-based sensing system that estimates soil-water and plant nitrogen status.

This project has developed a proof-of-concept infield sensing system and crop model to determine current and predict future soil-water, nitrogen and fruit load of cotton plants based on day of the season, weather data and visual plant response captured using cameras. Artificial intelligence was used to analyse the data and determine the model. These models have potential to be used instead of industry-standard models APSIM and OZCOT to predict crop production throughout the season as part of automated control systems to optimise irrigation and fertiliser application. The procedure used to developed model could be applied to any crop.


Statistics for USQ ePrint 27601
Statistics for this ePrint Item
Item Type: Report (Project Report)
Item Status: Live Archive
Additional Information: Permanent restricted access to report as author's request.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 24 Jun 2016 00:57
Last Modified: 06 Nov 2017 23:44
Uncontrolled Keywords: integrated plant-based image sensing system; cotton
Fields of Research : 09 Engineering > 0906 Electrical and Electronic Engineering > 090602 Control Systems, Robotics and Automation
07 Agricultural and Veterinary Sciences > 0799 Other Agricultural and Veterinary Sciences > 079901 Agricultural Hydrology (Drainage, Flooding, Irrigation, Quality, etc.)
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/27601

Actions (login required)

View Item Archive Repository Staff Only