Earlier this month, we set out to one of the UK's largest agriculture innovation events – Agri-Tech East’s REAP 2016 conference. And with the digital agriculture sector growing by 20% every year, it’s a key area of interest for us.
All sorts of gadgets from start-up inventors to big agribusinesses were on display. These included exciting products like Hummingbird Drone Solutions which uses the latest unmanned aerial vehicle systems to provide amazing data capture and analysis. There was also FungiAlert , with its clever early detection devices for plant pathogens, and Dogtooth’s robot for autonomous and automatic strawberry harvesting.
What struck us however, was a contrast between the large numbers of brilliant products developed to address very specific farming challenges and the complex and interdependent needs of the agriculture community.
With increasing pressures to produce more for less, and still enable individuals to make a living, it’s clear innovation in technology has an important role to play – and that digital agriculture has the potential to transform traditional farming.
To get there, most of those at the conference were exploring three core challenges, which are underpinning innovation in digital agriculture:
And according to the speakers of the day, the improvements they could yield are great – long-term yield could rise by over 50% and water usage could be cut by 30%.
Digitising agriculture: how organisations can unlock the potential in the agricultural value chain
Even though many brilliant hardware and software products already exist (from sensors and robots to data imaging and field-specific vegetation indices), most of these products only address a few, at best, of the many pain points farmers and other stakeholders in the agriculture value chain are confronted with.
What’s missing is the ability to integrate and customise these offerings, combining and tailoring them into solutions specific to the individual users’ needs and environment. An individual farm may have many challenges that technology could address, but they will be highly reluctant to buy a different system for each. Similarly, a system developed for an agribusiness to detect infestation levels in cereals might prove highly valuable to another business if it could do the same with corn or even beet. And if the burgeoning data sets were combined, they’d be able to deliver far more intelligence to the community.
If the ultimate goal is to make the farming and subsequent food chain more productive, efficient and precise, then we believe this can best be achieved by combining and integrating existing stand-alone technologies and adapting them to the following specific stakeholder needs:
It’s clear from what we saw at REAP 2016 that the digital agriculture revolution is in full swing. And for progress to be made, an appetite for collaboration and openness across the community is essential.