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Discovering opportunities to improve labour use efficiency through automation and improved management practices.
Mission of the project
Mission of the project
Like many other fruit crops, Australian rubus growers face significant challenges in managing labour costs. However, due to the high perishability and fragility of Rubus fruit, this issue is particularly acute for this crop.
To address this challenge, The Growth Drivers (TGD), with funding from Hort Innovation's Raspberry and Blackberry fund, have spearheaded an industry-led initiative aimed at discovering opportunities for improving labour efficiency through automation and management practices (RB21003). Through this project, TGD has crystallized five problem statements that provide a clear and comprehensive definition of the issue. These statements are crucial for addressing the critical factor of managing labour costs in the sector and serve as valuable assets for the development of sustainable solutions.
To solve these problem statements, TGD has identified an array range of solutions that have the potential to significantly improve on-farm labour effectiveness and productivity. TGD has taken a holistic approach to assess feasibility, viability, scalability, and desirability, in consultation with Rubus growers. Through careful consultation, five priority solutions have emerged
The Problem Statements
more efficient Harvest: picking activities
more efficient Harvest: picking activities
more efficient Harvest: NON-picking activities
more efficient Harvest: NON-picking activities
Row & fruit quality assurance
Row & fruit quality assurance
Crop presentation
Crop presentation
Cane selection & sucker removal
Cane selection & sucker removal
The Priority Solutions
Autonomous collaborative robots
Autonomous collaborative robots
Collaborative robots are increasingly being recognised as the future of agriculture in Australia. Offering improved efficiency and reduced labour costs by eliminating the need for farmhands to transport picked fruit and collect supplies, potentially saving up to 20% in labour costs across picking crews.
Advanced recruitment assessment
Advanced recruitment assessment
Utilising specialized assessment tools to evaluate physical attributes, hand-eye coordination, peripheral perception and psychological fit during the recruitment process can decrease hiring risks and accelerate the proficiency of new pickers.
Virtual reality training & assessment
Virtual reality training & assessment
Virtual Reality (VR) technology can recreate a wide range of horticultural scenarios, from identifying pests and diseases to pruning techniques and plant propagation. Allowing workers to gain hands-on experience in a safe and controlled environment, off-season and off-site.
Data empowered resource planning & deployment
Data empowered resource planning & deployment
A potential adaptation of the existing data capture and analysis tool, Bitwise, to support resource deployment decisions for various on-field tasks, such as crop presentation, sucker removal, and identifying pests and diseases.
Computer vision quality assessment
Computer vision quality assessment
Innovative technology using machine learning algorithms and computer vision quality assurance enables farmers to quickly and accurately grade fruit in the field, reducing costs associated with manual grading, increasing throughput, minimizing waste, and improving decision-making.
To stay up to date with solutions progress or if you are interested in becoming involved in the project, please register your interest via the form below.
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