Wednesday 13 – Friday 15 June 2018 | International Convention Centre, Sydney

Dr Alison McCarthy

Research Fellow, University of Southern Queensland

Dr Alison McCarthy

Research Fellow, University of Southern Queensland

Dr Alison McCarthy is an irrigation and mechatronic Research Fellow within the National Centre for Engineering in Agriculture at the University of Southern Queensland in Toowoomba.  She has a BEng (Hons) in Mechatronics and PhD in Irrigation Engineering from the University of Southern Queensland.  She has been involved with research projects in the cotton industry since 2007 funded by the Cotton Research and Development Corporation.  This research has led to the development of real-time adaptive control and low cost camera-based sensing systems to reduce labour in plant growth monitoring, and improve and potentially optimise the irrigation of field crops. Her current projects involve the variable-rate irrigation of cotton, dairy, horticulture and sugarcane crops via lateral move and centre pivot irrigation machines and surface irrigation systems.

Where: International Convention Centre, Sydney – Room E5.2 – E5.3

When: Day 1 – Wednesday, 13 June 2018, 16.00 – 16.30

Abstract Outline: Variable-rate irrigation technology typically reports yield improvements and water savings of up to 20%. This is through reduced under- and over-watering within spatially variably fields. However, these have low uptake in industry because of upfront cost and lack of decision support in determining irrigation prescription maps. NCEA has developed an automated irrigation control system ‘VARIwise’ that develops irrigation prescription maps from: real-time soil and weather sensors; infield camera imagery; and adaptive control strategy.

This presentation presents an overview of the trials conducted in 2016/17 for the cotton and dairy pasture industries. Weather stations, soil moisture and irrigation machine-mounted cameras for plant growth tracking were installed. Image analysis algorithms were developed to detect cotton flowering and fruiting and perennial ryegrass height, density and colour. Adaptive control strategies automatically analyse the incoming data and develop an irrigation prescription map. This map is then automatically and remotely transferred to the variable-rate control panel.

For the 2017/18 season, the sensor data pre-processing, image analysis algorithms, adaptive control algorithms, and irrigation prescription map development procedures have been transferred to execute on a server. This presentation will also discuss the implementation of these algorithms for automated analysis across the multiple sites as data inputs are received.

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