A novel vision based orchard system to maximize fruit tree yields and class 1 quality by 20% while reducing waste by 50%
The overall innovation project is intended to bring our novel ‘OrchardMan’ vision-based tree-fruit measurement technology to
European market-readiness. This will provide in-field data based on cost-effective image capture technology and novel
image processing algorithms, which can identify commercially relevant yield factors such as fruit size, growth and tree
architecture automatically in the difficult environment of the orchard under variable weather and lighting conditions. The
project will demonstrate that that the developed system has the capability to support precision horticultural management at
the single tree level, reducing waste from growing undersize fruit by up to 50%, and increasing overall tree yields by up to
20%, This would give European users a cumulative benefit of €1bn from 500 units implemented over the first five years.
This work is relevant to topic SFS-08-2014-1: “Resource efficient, eco-innovative food production and processing”,
particularly optimization of current food production systems, in the SME sector, with the aim of reducing water and energy
use and waste generation, and improving food quality, through the improving growers’ ability to increase overall fruit yield
per tree and the percentage of Class 1 quality reducing quality-reject waste, and reduction of imports, reducing transport
CO2.
There are techno-economic uncertainties that we must clarify before investing in a full development project, so we need to
carry out a thorough feasibility study, including the business plan for the phase 2 development and subsequent
commercialisation. Specific objective for the feasibility study is the elaboration and production of the Business Plan to
specify the second phase work needed to bring this technology to commercial readiness and replicate it through Europe,
including Techno-economic feasibility, Market studies, IP and dissemination work.