Australian Tree Crop Map (ATCM)
The mapping of Australia’s horticulture tree crops provides AOA with an accurate understanding of the extent (distribution and area) of production, at multiple-scales. Knowing the extent of our industry helps us to understand current and future industry growth, assist in national and regional yield forecasting, and to better respond to major events such as biosecurity threats and natural disasters. Without knowing where our groves are we simply can’t respond effectively.
Through this project, a freely available map of all commercial olive groves across Australia has been developed. The AOA are pleased to feature the map on our website. The mapping application shows the extent of our groves across Australia, including statistics of production area summarised by state/territory and local government area.
As already proven in managing the biosecurity response to Panama TR4 disease across banana plantations in North Queensland, knowing the location of groves is essential for containment and management of exclusion zones for biosecurity events, for example Xylella. Accurate and timely (current) spatial data for the location and extent of groves is fundamental for our biosecurity preparedness. Additionally, the spatial layer of all grove boundaries supports the rapid and regular monitoring of grove health at the national, regional and farm scale using remote sensing. This information is essential for detection and response in the occurrence of a significant pest or disease incursion.
“The map continues to be updated by researchers at the University of New England’s AARSC. The goal is to account for all our commercial groves in Australia > 1 hectare. Growers are encouraged to check their grove has been mapped, if not growers can simply complete the ATCM: Survey. This survey allows growers to quickly locate their grove and submit any other details for AARSC researchers to review and interpret the information and action updates in the map.” Said Craig Shephard, Scientist from the University of New England’s AARSC.
Privacy has been a key consideration, the ATCM is built to meet national standards and no personal or commercial i
nformation is captured or published. Additional applications of the map are available from the university’s industry applications gallery www.une.edu.au/webapps
Mapping yield variability and estimated yield
The project team has been trialling methods to estimate and map yield variability at the tree, block and farm levels. This has included the evaluation of high-resolution imagery acquired by satellite and airplane, combined with extensive in-field sampling. Accurate pre-harvest yield forecasting offers significant benefit at a range of scales. At the farm level, forecasts guide grower decisions around harvesting including lab
our, machinery, packaging, transport, and storage requirements, as well as their own capacity to meet market demands. All of these aspects have the ability to improve profitability for growers and industry stakeholders. At the tree level, crop heath variability can be identified, facilitating management decisions to boost low performing areas as well as optimise crop inputs.
In its second season, the project has achieved yield estimation accuracies from 75% up to 99% at the individual block level (6 ha – 60 ha). These accuracies were obtained across seasons, even with the substantial yield variability identified in Picual trees (around 300%) between 2020 and 2021 seasons.
The participating growers have access to yield prediction maps through web pages that are updated as soon as new information is available, allowing them to compare changes within the blocks across seasons and facilitating management operations. The ability to visually identify lower performing trees on a map and subsequently quantify yield variability in kg/tree, has given co-operators the opportunity to perform more targeted management.
To forecast yield early in the growing season and without infield counting, the project team is also evaluating a remote sensing approach proven to be very accurate in other tree crops. The AARSC team is seeking historical yield data for a number of different groves to enable the accuracies of this method to be determined over different growing seasons, locations, varieties and management. If you would like to take part please contact Dr. Angelica Suarez or Alex. Schultz (details below)
Irrigation trials
A further part of this project, the project team, together with collaborating growers, have established an irrigation deficit trial, encompassing two varieties (Arbequina and Picual), three irrigation deficits (standard practice, 75% and 50%), two vigour zones (high and low, classified using satellite imagery) and replicates of each of these treatments. The deficits have been imposed for two growing seasons, with the third season being planned. As expected there have been variable reductions in yield in deficit treatments (depending on variety and vigour), particularly in the second season. Areas with low vigour trees have been identified as less susceptible to water deficits, which is important if the grower needs to prioritise areas within the grove for irrigation. These findings will help guide water management decisions in years of water scarcity.
The project team has also evaluated a range of commercial technologies that will provide growers with an affordable, practical and accurate method for measuring early water stress. These include weather and soil moisture probes, dendrometers (measuring small fluctuations in trunk diameter), sap flow sensors, soil conductance and remote sensing provided by satellite and airbourne (CERES) platforms. The infield sensors are connected through a wireless network, providing hourly readings online. These have provided up-to-the-hour indications of water stress. From the results thus far, stem water potential and dendrometer measures appear to be the most responsive.. The aerial imagery (using both thermal and multispectral sensors) has identified water stress across a grove. A derived remote sensing index, which is normalised by temperature and tree vigour, has provided estimation of stress across the site.
The data from sensors, imagery, tree measurements and final yields and quality will be brought together to determine the best integration of technologies and models for supporting optimal water use efficiency by Australian olive growers. The outcomes will inform management decision to optimise the water/productivity trade off in periods of water scarcity, considering both spatial variability and dynamic time-dependent water demand (due to weather conditions). This is a comprehensive study that offers much to the industry.
This project is supported by Horticulture Innovation, through funding from the Australian Government Department of Agriculture, Water and the Environment as part of its Rural R&D for Profit program. The project team would also like to thank the continued support of the many project collaborators including AOA, NSW DPI, CERES, and participating growers.
Contact Details
Project leader: Prof. Andrew Robson arobson7@une.edu.au
Australian Tree Crop Map (ATCM)
Craig Shephard cshepha2@une.edu.au
Yield mapping and forecasting
Dr. Angelica Suarez lsuarezc@une.edu.au
Irrigation trials
Dr. Angelica Suarez lsuarezc@une.edu.au
Dr. James Briskhoff James.Brinkhoff@une.edu.au
Alex Schultz – NSW DPI alex.schultz@dpi.nsw.gov.au