The agricultural sector is facing a huge challenge: to produce more crops using fewer resources while reducing any negative effects on society and the environment. Smart Farming and Big Data are often seen as ways to achieve this goal, but how can they benefit agriculture?
“Realising interventions at the right time, in the right place and on the smallest possible scale is the essence of smart agriculture or Smart Farming,” says precision agriculture scientist Corné Kempenaar from Wageningen University & Research. “Big Data can provide support. Digitally connecting sensors to various equipment within and outside of a company provides large amounts of data. Via analysis and interpretation, this data can provide farmers with valuable information.”
Big Data in agriculture
Big Data applications are already available in agriculture. For example, meteorological information and data on soil conditions are already linked in systems that warn farmers against break-outs of infectious diseases. And portals such as Akkerweb combine data on individual lots in a central platform. Arable farmers, large or small, can then use this collective knowledge for Smart Farming: bespoke crop protection and fertilisation which results in a higher yield with a reduced environmental impact.
Another potential future option is a system in which farmers use information from passing cars to determine whether it has rained on their land. Kempenaar: “Drivers switch on their window wipers when it rains. With more precipitation, they switch their wipers to a higher speed. It should be technically feasible for these cars to pass on this data. The resulting information may even be much more reliable and cheaper than radar images or private weather stations.”
Big Data demands trust
Kempenaar has seen that agriculture has a great interest in Big Data: “Farmers definitely understand the added value but they also have reservations. Big Data should enable much more precise predictions regarding potato or onion yields, for instance. Although this is useful for growers, these predictions are also of major interest to buyers. Regional yield predictions enable them to anticipate shortages and keep costs low. This is obviously not in the interests of farmers, who would shoot themselves in the foot by releasing these predictions. Remember that there is an imbalance in a market: with tens of thousands of sellers and only a handful of large buyers. The success of Big Data relies on people being able to trust that the information won’t be abused.”
Although there are plenty of obstacles to overcome, Big Data can undoubtedly help the sector move forward says Kempenaar: “By linking satellite data to soil data and weather information and using agronomical models that apply these data, farmers can increase their yields in percentage terms while also causing less harm to the environment. If the parties in the chain and knowledge providers jointly succeed in resolving the issues regarding ownership, privacy and data application, and develop the required models and analysis methods, the path to useable Big Data applications is wide open. Technology is no longer a limiting factor.”