Award details

Achieving an optimal balance between machine vision capability and weed treatment effectiveness using competition models

Reference	D12732
Principal Investigator / Supervisor	Professor J Marchant
Co-Investigators / Co-Supervisors
Institution	Silsoe Research Institute
Department	Research Division
Funding type	Research
Value (£)	44,684
Status	Completed
Type	Research Grant
Start date	01/05/2000
End date	01/05/2003
Duration	36 months

Abstract

A programme of experimental work and mathematical modelling is proposed to establish the optimal balance of machine vision technological development and rigour of weed removal to achieve effective weed control. Machine vision algorithms will be developed at SRI to match finite sensor resolution to that required for effective weed control. The tolerance of resolution required for weed control will be established by further development and application of crop- weed competition models developed at HRI. This project will help establish the technologies for manipulation of crops at the level of the individual plant so enabling a reduction of inputs via precision targeting. (Joint with grant 207/D12731)

Summary

unavailable

Committee	Closed Committee - Agri-food (AF)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	X - not in an Initiative
Funding Scheme	X – not Funded via a specific Funding Scheme

Associated awards:

D12731 Achieving an optimal balance between machine vision capability and weed treatment effectiveness using competition models

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