Award details

16AGRITECHCAT5: GrassVision: Automated application of herbicides to broad-leaf weeds in grass crops

Reference	BB/P005039/1
Principal Investigator / Supervisor	Professor Melvyn Smith
Co-Investigators / Co-Supervisors
Institution	University of the West of England
Department	Bristol Robotics Laboratory
Funding type	Research
Value (£)	107,053
Status	Completed
Type	Research Grant
Start date	01/09/2016
End date	30/08/2018
Duration	24 months

Abstract

The aim of the project is to develop a novel spray apparatus for precision application of herbicides to broad-leaf weeds in grass crops. The consortium is comprised of three partners; (1) Centre for Machine Vision (CMV), a leading research centre in 3D machine vision, with past success in the agri-tech field, (2) Aralia Systems Ltd (AS), an international security company with a wide R&D portfolio in data-mining and complex feature analysis on videos, (3) Soil Essentials Ltd (SE), a leading precision agriculture company specialising in GPS machinery guidance, implement control, cloud based decision support systems and emerging grassland agronomy technologies. The primary focus will be to detect weeds in grass such as dock and ragwort using novel 3D machine vision techniques. The project will use off-the-shelf machinery to spray an area around each weed, activating the relevant nozzles on the boom. The role of the CMV team will be to realise novel 3D imaging hardware and software for detecting the weeds in the grass while moving on a tractor. We also aim to recognise the weed species.

Summary

The aim of the project is to develop a novel spray apparatus for precision application of herbicides to broad-leaf weeds in grass crops. Such a system, using a spray boom covering a 10x.5m area of ground, could feasibly run at upwards of 1m/s, allowing precision spraying of weeds at between 1 and 2 hectares/hr. The consortium is comprised of three partners; (1) Centre for Machine Vision (CMV), a leading research centre in 3D machine vision, with past success in the agri-tech field, (2) Aralia Systems Ltd (AS), an international security company with a wide R&D portfolio in data-mining and complex feature analysis on videos, (3) Soil Essentials Ltd (SE), a leading precision agriculture company specialising in GPS machinery guidance, implement control, cloud based decision support systems and emerging grassland agronomy technologies. The primary focus will be to detect weeds in grass such as dock and ragwort using novel 3D machine vision techniques. Initially the project will use off-the-shelf machinery to spray an area of roughly 50x50cm around each weed, activating the relevant nozzles on the boom with an estimated aimed decrease in herbicide use of around 75%.The project will then look to determine the limits of precision by refining the boom itself, allowing nozzles to move linearly across the boom as on an inkjet printer, or in rotation using servo motors. Using this approach, we aim to provide potential reductions in herbicide use in excess of 90%. The role of the CMV team will be to realise novel 3D imaging hardware and software for detecting the weeds in the grass while moving on a tractor. We also aim to recognise the weed species. This data will be used to both direct the automated weeding system in real-time (developed by SE) and to create a detailed weed data map (developed by AS) of the entire field.

Impact Summary

The main impact will be on beef and dairy farmers who will be provided with a tool to control weeds in pasture, thereby offering increased productivity of grass swards. End-user farmers are expected to see substantial reductions in herbicide use in excess of 90%. There are also wider environmental and social benefits. Environmental benefits will accrue from a more efficient, precision application of herbicides and increased pasture yield. Precision application will reduce the environmental impact and economic losses from the industry and help to improve feed conversion efficiency from pasture, boosting food security. Considerable environmental benefits will accrue from a more efficient, precision application of herbicides. Benefits include, reduced environmental contamination, eg of water sources, ability to treat larger grassland areas, increasing yields reducing the need for purchasing feed, ability to spray in environmentally sensitive areas where spraying is currently not possible, reduction of herbicide costs and clover damage. Better management of pasture will allow longer herd life will reduce the environmental impact and economic losses from the industry and help to improve feed conversion efficiency in beef and milk production, boosting food security. Benefits will accrue beyond the project as improvements in pasture and its management grow. The economic and environmental potential of grassland weed control is very high due to the extensive area grassland covers, the economic loss of untreated weeds and the high cost (both economic and environmental) of blanket application of herbicide. Economic Impacts - The development of the technology, data handling, benchmarking systems and pasture weed control and health monitoring will increase the SME partners' profile in R&D, leading to further opportunities and developments within the value chain. An increased turnover and profitability following the project will help to increase employment and job security.

Committee	Not funded via Committee
Research Topics	Crop Science, Plant Science
Research Priority	X – Research Priority information not available
Research Initiative	Agri-Tech Catalyst (ATC) [2013-2015]
Funding Scheme	X – not Funded via a specific Funding Scheme

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