2) Analytics and Machine Learning
These connected sensors will produce huge amounts of information, but none of it is useful unless it’s presented in a meaningful way. This is where analytics comes in.
Using Machine Learning – a subset of Artificial Intelligence which gives computers the ability to look at sets of data and ‘learn’ from them without the guidance of a human – analytics software can make sense of the huge amounts of data and make predictions about what might happen next.
Back decision-making up with hard data and these insights mean farmers can make better decisions about farm and animal management – for example, the best time to apply fertiliser or to irrigate, maximising outputs while minimising inputs.
3) Doing anything anywhere
Mobile technology has transformed the global economy, with smartphones and data networks enabling a new wave of innovation which has re-shaped the way we interact with the world – changing everything from taking photos to getting around.
Mobile data networks continue to provide more coverage and faster speeds to more people, which brings the same capabilities on-farm.
Not having to wait to get back to the computer in the evening means farmers can make use of analytics and management software throughout the day – tools like Agrigate -- putting the power to get detailed information and insights in real-time, literally in their hands.
4) Robotics and Automation
Self-driving tractors have been capturing the imagination since the 1940s, but are closer to reality than ever before, driven by labour shortages and huge leaps in technologies like LIDAR and Machine Vision. Autonomous tractors will allow farmers to manage their tractors remotely, or eventually allow them to manage themselves.
Automation is not just transforming agriculture on the land. With the help of drones, it’s also transforming things from the air.
Drones already help farmers quickly carry out time-consuming tasks ordinarily done on-foot or by multiple people – such as doing inspections, monitoring pasture, livestock and water levels, and some farmers even use them to move stock and apply sprays to their crops.
As they improve, such as getting longer battery life and more powerful engines, their capabilities to carry out more on-farm tasks will grow.
Artificial Intelligence, Machine Learning, and Machine Vision are also being used by equipment companies like John Deere to automatically identify, analyse and make management decisions about plants and crops at an individual level, reducing the need to use herbicides by up to 90 per cent and helping fight weed resistance.
5) Doing it on the Blockchain
Blockchain might be a buzzword associated with cryptocurrencies like Bitcoin, but the technology has far wider applications and the potential to revolutionise traceability for food.
At its most basic, blockchain is a way of verifying and permanently storing a record of an event, but without a central authority. For cryptocurrencies, the blockchain plays the role of a bank – it is the authority on all transactions, recording and verifying who sent what to who, when and how much.
In agriculture, blockchain can be used to trace a product every step of the way, from pasture to plate. The decentralisation of blockchain means it can be authoritative but open and accessible at the same time, allowing anyone to track a product’s history at any point.
As food safety and authenticity becomes more important for consumers and farmers alike, blockchain can be used to give people uncorrupted and authoritative records on exactly where their food has been and where it has come from.
Blockchain implementations face issues with their power consumption, as the computing power required to do the ‘proof of work’ and validate transactions can be very high. Private blockchains are already reducing the computation work required to reduce power consumption, while public ones and other start-ups are looking at tweaks and further changes to how the operate in order to do the same.
Fonterra has already started a pilot programme with Alibaba for food traceability on blockchain.