Image analysis and artificial intelligence based approach for soil-water and nitrogen status estimation
Presentation
McCarthy, Alison, Nguyen, Tai and Raine, Steven. 2015. "Image analysis and artificial intelligence based approach for soil-water and nitrogen status estimation." 2nd Australian Cotton Research Conference 2015: Science Securing Cotton's Future. Toowoomba, Australia 08 - 10 Sep 2015 Australia.
| Paper/Presentation Title | Image analysis and artificial intelligence based approach for soil-water and nitrogen status estimation |
|---|---|
| Presentation Type | Presentation |
| Authors | McCarthy, Alison (Author), Nguyen, Tai (Author) and Raine, Steven (Author) |
| Journal or Proceedings Title | Proceedings of the 2nd Australian Cotton Research Conference 2015 |
| Number of Pages | 1 |
| Year | 2015 |
| Place of Publication | Australia |
| Web Address (URL) of Paper | http://www.cottonresearch.org/Welcome |
| Conference/Event | 2nd Australian Cotton Research Conference 2015: Science Securing Cotton's Future |
| Event Details | 2nd Australian Cotton Research Conference 2015: Science Securing Cotton's Future Event Date 08 to end of 10 Sep 2015 Event Location Toowoomba, Australia |
| 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 camera-based plant sensing system and model that estimates soil-water, plant nitrogen status and fruit growth for cotton. A data fusion algorithm was developed that can 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. 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 develop the model could be applied to any crop. |
| Keywords | irrigation; fertiliser; non-contact; machine learning; automation |
| ANZSRC Field of Research 2020 | 300206. Agricultural spatial analysis and modelling |
| 400799. Control engineering, mechatronics and robotics not elsewhere classified | |
| 300403. Agronomy | |
| Public Notes | Abstract only published in Proceedings. |
| Byline Affiliations | National Centre for Engineering in Agriculture |
| Computational Engineering and Science Research Centre | |
| Institute for Agriculture and the Environment | |
| Institution of Origin | University of Southern Queensland |
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An-Vo, D.-A., Mushtaq, S., Nguyen-Ky, T., Bundschuh, J., Tran-Cong, T., Maraseni, T. N. and Reardon-Smith, K.. 2015. "Nonlinear Optimisation Using Production Functions to Estimate Economic Benefit of Conjunctive Water Use for Multicrop Production." Water Resources Management. 29 (7), pp. 2153-2170. https://doi.org/10.1007/s11269-015-0933-yAssessing erosion processes associated with establishment of coal seam gas pipeline infrastructure in Queensland, Australia
Vacher, Cameron A., Antille, Diogenes L., Huth, Neil I. and Raine, Steven R.. 2016. "Assessing erosion processes associated with establishment of coal seam gas pipeline infrastructure in Queensland, Australia." 2016 ASABE Annual International Meeting. Orlando, Florida 17 - 20 Jul 2016 United States. American Society of Agricultural and Biological Engineers. https://doi.org/10.13031/aim.20162461210Automated 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." 5th International Workshop on Applications of Computer Image Analysis and Spectroscopy in Agriculture (ASABE 2014). Montreal, Canada 12 - 13 Jul 2014 St. Joseph, MI. United States.Real-time irrigation decision-making and control for site-specific irrigation of cotton using a centre pivot, 2012/13
McCarthy, Alison, Smith, Rod and Hancock, Nigel. 2014. "Real-time irrigation decision-making and control for site-specific irrigation of cotton using a centre pivot, 2012/13." Irrigation Australia Conference 2014: Water for Life, Future for All. Gold Coast, Australia 02 - 06 Jun 2014 Sydney, Australia.VARIwise: towards autonomous irrigation and a grower's guide
McCarthy, A. C.. 2014. "VARIwise: towards autonomous irrigation and a grower's guide." IRRICOMM – communication of irrigation research in cotton (2014). Narrabri, Australia 11 - 12 Mar 2014 Narrabri, Australia.