Vesca

Strawberry harvesting is a labour intensive task that depends critically on the availability of a large amount of low-cost labour. Growers are increasingly vulnerable to labour market price fluctuations and burdened by high employment overheads. Building on Dogtooth's proof of concept strawberry picking robot (developed during Innovate UK project Ananassa), project Vesca will deliver commercially viable picking performance using cutting edge machine learning and computer vision techniques to facilitate more efficient localization of target fruit (by more nearly optimal control of robot motion) and more accurate determination of suitability for picking. The project will also provide ancillary benefits such as yield mapping and prediction that are of significant importance to growers.

Economic benefits for those involved at the project:
1) The results of this work will add to the capability of Dogtooth's current robotic platform to drive progress against
commercially important goals through increasing yield, quality of the picked product and picking performance. The timeline
for exploitation of this project is, July 2017, first production units, offered as a picking service to 1 customer (turnover 2017,
£25 K); 2018, V2.0 - incorporating technology developed in this project, roll out picking service to 2-3 customers (turnover
2018, £800K); 2019, make first machinery sales, capture 7% of UK market and release of V3.0 with increased picking
efficiency, first revenue from Australia (turnover 2019, £5.8 M). 2020, migrate from picking service to machinery sales
dominated income to achieve scale, roll out on limited basis in EU (turnover 2020, £15.8 M); 2021 exploration of markets in
North America (turnover 2021, £75 M.)

2) NIAB will decrease the phenotyping costs on research projects and at the strawberry breeding program and will help to
improve selection efficiency by providing superior pre-breeding material to meet grower and consumer demands for elite
lines that can be used in future breeding programmes. Phenotyping for fruit quality characteristics and shelf life potential is
time-consuming, labour intensive and costly.

3) Hugh Lowe Farms will be the first farm implementing Dogtooth's robotic platform improved the consistency of supply of
high-quality fresh fruit with an assured shelf-life leading to reduced wastage in store, greater resource use efficiency
leading to cost savings and will improve grower competitiveness nationally and internationally. Human pickers give
inconsistent results with direct consequences for profitability (punnets containing strawberries with inconsistent size or
shape or showing signs of mishandling would typically be rejected by customer QC procedures). Farmers use a variety of
training and monitoring procedures to increase consistency but these greatly increase costs.
Wider impact:
1) Strawberry producers will benefit from reduced risk of failing to recruit enough pickers, a better price at market (for a
more consistent product), and reduced labour overheads.
2) The energy needs of the electrically powered robots will be mostly met from renewable sources, however, emissions
arising from flights taken by migrant workers will be very significantly reduced.
3) Breeders, biotechnologists all over the world will benefit from lower phenotyping costs as well as improved phenotyping
precision and will help improve selection efficiency by providing superior pre-breeding material to meet grower and
consumer demands.
4) Higher paid and higher skilled jobs will be created, by creating jobs in science, software development, mechanics, R&D,
manufacture, operations and sales.
5) More accurate and timely yield estimation with less uncertainty about the availability of labour will help maximising profit
while reducing the risk of unfulfilled contracts. All of this will contribute to a more reliable and lower cost supply for retailers
and consumers.