Papers by Alison McCarthy
UAVs enable fast, high resolution image capture of cotton fields. These images are typically asse... more 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.
Automated site-specific irrigation framework and evaluation
The spatial variability of plant available water content and irrigation requirement within a sing... more The spatial variability of plant available water content and irrigation requirement within a single field can be up to 200%. Measuring this variability typically requires either aerial vehicles (remotely piloted or piloted) with cameras and optical and depth sensors, or ground vehicles (e.g. tractors, mopeds) carrying electrical conductivity and optical sensors over the field. However, conducting these surveys multiple times during the season is time consuming. Alternatively, a fixed sensor could be installed in each management zone in the field, and the infield variability estimated using spatial interpolation. Fieldwork and spatial analysis has been completed to identify the errors in the spatial interpolation and impact on irrigation requirement calculated. Fieldwork was conducted on 5 ha of two surface-irrigated cotton fields in 2014/15 in Yargullen, Queensland. A weather station and fixed soil moisture sensors were installed. Fortnightly spatial measurements of soil electrical ...
Automated irrigation and fertigation site-specific control systems offer labour and water savings... more Automated irrigation and fertigation site-specific control systems offer labour and water savings, and crop productivity improvements for growers, where spatial variability of water requirements exists within a field. Real-time irrigation control strategies for surface and pressurised irrigation systems have been developed that adapt to infield soil and plant measurements collected in real-time. 'Sensor-based' control strategies directly use measurements to make irrigation decisions; and 'model-based' control strategies use a model (often calibrated with sensor input) to aid irrigation decisions. Model-based control strategies can aim for specific end of season characteristics. However, model-based control strategies often use off-the-shelf, black box industry models that may not be updated with the development of the new varieties, and may not consider all the soil-plant-water relations. A hybrid Artificial Neural Network (ANN) and Bayesian model is being used for t...
Control and sensing systems for automated site-specific irrigation
Overview of sensing and control systems for surface and overhead-irrigated cotton and horticultur... more Overview of sensing and control systems for surface and overhead-irrigated cotton and horticulture crops.
Computers and Electronics in Agriculture, 2014
Model-based irrigation control strategies applied to irrigation make decisions (on water applicat... more Model-based irrigation control strategies applied to irrigation make decisions (on water application and/or timing) using a crop and/or soil production model. Decisions are made with respect to an optimisation objective which, for irrigation, can be either short-term (e.g. achieving/maintaining a set soil-water deficit) or predicted end-ofseason (e.g. maximising final yield) by predicting how the crop will respond at the end of the season. In contrast, sensor-based irrigation strategies rely on achieving a performance that is measurable during the crop season to provide the feedback control, and may not necessarily optimise overall crop performance. Model-based control potentially avoids this limitation. This paper describes the application of Model Predictive Control (MPC) methodology to the feedback control of irrigation via a model-based irrigation strategy implemented in the irrigation control simulation framework 'VARIwise'. The requirement to also accommodate spatial and temporal differences in crop water requirement across a heterogeneous field is met by defining management 'zones' according to differing soil and crop properties across the field and separately applying the control algorithm for each of these zones. Case studies were conducted to evaluate MPC for a centre pivot irrigation machineirrigated cotton crop (under typical Australian growing conditions) with: (i) different in-season performance objectives (maintaining soil-water deficit; maximising square count); (ii) different predicted end-of-season performance objectives (maximising yield; maximising water use efficiency); and (iii) maximising yield with different field data inputs for model calibration. The model predictive control strategy produced 3 significantly higher simulated yields and water use efficiency than an industrystandard irrigation management strategy; and (in most but not all situations) direct sensor-based adaptive control strategies. Research Highlights • Model Predictive Control was simulated for site-specific irrigation in 'VARIwise' • MPC accommodated both short-term (in-season) and long-term performance objectives • MPC delivered the best performance when optimising crop yield • MPC resulted in higher (simulated) yield than sensor-based strategies • MPC required extensive data to accurately calibrate crop model
The spatial variability in soil properties across irrigated broadacre fields in Australia can be ... more The spatial variability in soil properties across irrigated broadacre fields in Australia can be up to 500%. Currently irrigation for these fields is typically applied uniformly. Manual monitoring and processing soil moisture and crop measurements to implement site-specific irrigation and optimise water productivity is labour-intensive and expensive. A control system which automatically determines and delivers irrigation and fertiliser requirements has been developed to identify spatial irrigation requirements, and only apply water when and where it is needed. This system consists of: (i) sensors that measure weather, soil and plant response; (ii) a control system that automatically analyses the sensor data and determines irrigation and fertiliser requirements; and (iii) actuation hardware that applies site-specific irrigation and fertiliser requirements. This paper details the evaluation of irrigation control strategies in horticulture crops for centre pivot irrigation sites in Kal...
Automated variety trial plot growth and flowering detection for maize and soybean using machine vision
Computers and Electronics in Agriculture, 2022
Australian Journal of Multi-Disciplinary Engineering
Spatial variability in crop production occurs as a result of spatial and temporal variations in s... more Spatial variability in crop production occurs as a result of spatial and temporal variations in soil structure and fertility; soil physical, chemical and hydraulic properties; irrigation applications; pests and diseases; and plant genetics. It is argued that this variability can be managed and the efficiency of irrigation water use increased by spatially variable application of irrigation water to meet the specific needs of individual management zones (areas of crop whose properties are relatively homogenous). The prospects for spatially varied irrigation applications and the need for adaptive control of irrigation application systems are identified. Current work at USQ directed toward adaptive control of furrow irrigation and centre pivot and lateral move machines is described.
Effect of spatial variability on data requirements for site-specific irrigation
Irrigation control strategies that consider infield spatial variability can lead to improved crop... more Irrigation control strategies that consider infield spatial variability can lead to improved crop productivity and water use efficiencies. The irrigation control approach that optimises crop and water productivity is expected to depend on the variability of irrigation infiltration and soil and plant properties within specific fields. Field data collected in 2013/14 was combined with a simulation study to determine the spatial and temporal data requirements for site-specific irrigation, relative to the amount of infield variability. This paper presents an exploration of the number of data points/furrows to monitor irrigation application, soil moisture, plant growth and fruit load to control irrigation application and optimise productivity.
Advanced data-driven irrigation
VARIwise: site-specific surface irrigation and fertigation using adaptive control
This presentation gives an overview of a trial that aims to identify the number and type of soil ... more This presentation gives an overview of a trial that aims to identify the number and type of soil and plant sensors and variable-rate irrigation hardware required for surface irrigation management using adaptive control. This involves comparing different spatial and temporal resolutions of data collection.
The dairy industry is the second largest user of irrigation water in Australia. Increasing compet... more The dairy industry is the second largest user of irrigation water in Australia. Increasing competition, climate variability and costs of irrigation water, along with reduced water availability are driving farmers to adopt innovative practises and technologies that utilise water as efficiently as possible. The average water usage of Australian dairy farms is 6.3ML/ha, with each ML generating a value of approximately $430. Over 75 percent of the dairy farms in Australia are pasture-based systems. In spite of this fact, and the importance of pasture utilisation in pasture-based dairy systems, pasture utilisation across the industry has remained at 50-60 percent of what is potentially possible. Effective management of the spatial and temporal variability in water demand is viewed as the key to optimising pasture production. Automated precision irrigation is now possible with the deployment of cheap sensors, crop models, and irrigation control systems bundled in appropriate built-in tech...
Plant growth and irrigation advance rate monitoring is required for crop and irrigation managemen... more Plant growth and irrigation advance rate monitoring is required for crop and irrigation management in broadacre surface irrigated fields. However, this monitoring is typically manual, labour-intensive and conducted in a limited number of locations in the field which may not represent the whole field. A thermal camera on a tower has been used to determine location of water in the field during surface irrigation events; and low-cost cameras on field vehicles and irrigation machines have been used to map cotton growth and fruiting. These systems potentially enable automation of surface irrigation cut-off to improve water use efficiency and improve agronomic and irrigation management.
Automated site-specific control and sensing for irrigating dairy pastures
The National Centre for Engineering in Agriculture (NCEA) is investigating the use and field impl... more The National Centre for Engineering in Agriculture (NCEA) is investigating the use and field implementation of real-time adaptive control of irrigation application and timing to improve irrigation management. The Rural R&D for Profit project 'Smarter Irrigation for Profit' is enabling the development of site-specific irrigation control systems to dairy pastures with the University of Tasmania.
Dr Alison McCarthy was awarded the NPSI/IAL Travel Fellowship Award in 2010 and conducted a study... more Dr Alison McCarthy was awarded the NPSI/IAL Travel Fellowship Award in 2010 and conducted a study tour of the US in March 2011 to investigate the development of sensors and control systems for automated real-time site-specific irrigation. Current research has identified that determining irrigation prescriptions is the greatest difficulty in implementing site-specific irrigation. Alison visited Washington State University, commercial variable-rate irrigation companies in Omaha (Nebraska), and United States Department of Agriculture research stations in Sidney (Montana), Maricopa (Arizona), and Bushland and Lubbock (Texas). She looked at the development of spatial sensors for irrigation control systems, the implementation of variable-rate hardware and work towards autonomous irrigation systems.
Irrigation control strategies can be used to improve site-specific irrigation. These control stra... more Irrigation control strategies can be used to improve site-specific irrigation. These control strategies generally require weather, plant and/or soil data to determine irrigation volumes and/or timing that improve crop water use efficiency while maintaining or improving crop yield. A simulation framework ‘VARIwise’ has been created to develop, simulate and evaluate site-specific irrigation control strategies for centre pivot and lateral move irrigation machines (McCarthy et al., 2010), and the cotton crop growth model OZCOT is currently integrated to evaluate strategies. In VARIwise, the field is divided into 1 m2 cells to accommodate spatial variability and alternative irrigation control strategies have been implemented (McCarthy, 2010). The spatial variability of natural rainfall in Queensland summer cropping areas is observed to be substantial on a scale of 10s to 100s of metres due to highly-localised cumulonimbus storms. Typically an automatic weather station or other data sourc...
Crop and irrigation water use efficiencies may be improved by managing irrigation application tim... more Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotto...
Data requirements for automated model-based control of irrigation and fertiliser application
Model-based adaptive control strategies can be used to determine site-specific irrigation and fer... more Model-based adaptive control strategies can be used to determine site-specific irrigation and fertiliser volumes with the aim of maximising crop water use efficiencies and/or yield. These strategies use a crop model to predict the crop's response to climate and management throughout the crop season, and identify which irrigation and fertiliser application volume and timing produces the desired crop response or condition (e.g. maximum yield). The model can be calibrated with infield weather, soil and crop measurements to ensure the model predictions accurately reflect infield measurements. However, data collection of soil and plant parameters spatially over a field and throughout the crop season will potentially lead to a large sensed data requirement which may be impractical in a field implementation. In addition, not all the data may be required to calibrate the crop model with sufficient accuracy. A smaller dataset consisting of only the most influential sensor variables may b...
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Papers by Alison McCarthy