A remote crop monitoring service is designed to accurately predict the yield, size distribution and value of potato crops.
Tuberzone CropCast from farmer-owned agritech business SoilEssentials draws on data from satellite and drone imagery, field-scale global weather records and other remote sensing tools to track and predict crop yield and tuber size distribution every day throughout the growing season.
Cloud-bases crop spatial model
This information is used through the cloud-based spatial crop model and integrated decision support system to guide growers on variable rate seed planting, fertiliser use and irrigation scheduling.
Traditional trial digs – but fewer than usual and located by the model to ensure accurate representation – then help calculate the best time to stop crop growth to meet market specifications.
“This is a precision farming solution that can cut costs, optimise saleable yield and improve resource-use efficiency,” says Jim Wilson, Managing Director at SoilEssentials.
The end result – greater control over crop yield, tuber size and size distribution.
“I believe it’s the perfect tool for growers who wish to increase financial yields more than physical ones, reduce food waste and have more control of their crop management.”
Tuberzone CropCast was developed over five years with the help of the James Hutton Institute, a crops, soils, land use and environmental research organisation in Scotland, and through a multi-partner £350,000 project supported by the British government’s Innovate UK funding programme.
This project, involving Newcastle University, equipment manufacturer Grimme and processor McCain, was followed last year by a Scottish government funded programme to test its practical application through the Grampian Growers co-operative, which encompasses 30 farms producing seed and the group’s own Gemson salad potato variety.
Stuart Wale, potato agronomist with SAC Consulting, said: “The thing about salad potato production is that you need large numbers of very small tubers and the difficult judgement is to know exactly when to stop the crop growing.
“Rate of growth is difficult to predict just by looking at the crop from above but the Tuberzone technology is exciting because it really helps us understand what is going on below ground.”
Growers who said they were sceptical about the new technology’s abilities say it produced highly accurate yield and size fraction predictions, in some cases better than the 90% accuracy target set by SoilEssentials.
Grampian group grower Matthew Steel said: “One of the stand-out moments for me was to get the figures that showed just how accurate the model was, with only about 5% difference between what the model predicted we would get in each size bracket and what we actually got.
Drones collecting crop-growth data for the Tuberzone CropCast predictive modelling service.
“This has practical benefits and really helps with our customers because then we’re delivering what they want at the quality they want, which has benefits for everybody in the supply chain.”