Precision agriculture

Agriculture 4.0:
Using Big Data to help us farm smarter

Smart Crop Protection

Making effective use of data in agri­cul­ture is the key to secur­ing our food future.

—Blair Edwards, Research Staff Member

Population growth and climate change are putting pressure on our food supply, increasing the need for higher yields, whilst at the same time giving us a more challenging environment to work with. Precision agriculture has the potential to address these challenges, both enhancing agricultural efficiency and helping to reduce environmental impacts.

Globally, 30% of crop yield is lost to insect pests, plant pathogens and weeds. Protecting crops more efficiently and sustainably represents one of the most accessible ways to intensify agriculture. Smart Crop Protection adopts a systems-based approach, integrating chemical, genetic, biological, ecological, mathematical and agronomic approaches to deliver more targeted, “evolution-smart” strategies that minimise adverse environmental impacts.

Yet, it poses a challenge in data processing and analysis due to the large volume and fast accumulation of real-time geospatial data, the diversity of historic data and research outputs produced on a daily basis. At IBM Research UK we are actively working to support researchers in both exploring the genetic make-up of different crops, as well as building a scalable data platform to deliver insight and support decision making for farmers, researchers and industry stakeholders.

Through metagenomic analysis we are exploring taxonomical and functional diversity of microbes in a soil environment. Our efforts are aimed to investigate how we can manipulate and manage the soil microbiome to increase soil fertility, improve crop production and enhance our understanding of how terrestrial ecosystems will respond to environmental change.

Use case

Smart Crop Data Platform

Helping agricultural researchers make better models and serve their insights to farmers

The agriculture sector has many different stakeholders from farmers to suppliers and researchers to supermarkets. What all have in common, is large amount of data which hide useful insights and, if utilised efficiently, can benefit everyone. In collaboration with Rothamsted Research, we created a platform and workflows that utilise the group’s expertise and existing strength in infrastructure, by leveraging high-performance computing (HPC) and Big Data technology.

The result is built on IBM Research’s geospatial data repository PAIRS (Physical Analytics Integrated Data Repository), which provides a central data store where data is aligned, indexed and retrieved quickly through a powerful data spatiotemporal query engine. On top of this, we built additional apps andservices, either for researchers to analyse their data or to inform stakeholders about latest trends and forecasts.

With moth migration data from Rothamsted Research, we can store data efficiently in PAIRS, query relevant data as model input for moth migration predictions and inform farmers depending on weather conditions when moths are expected.

We demonstrated how we can combine Rothamsted’s insect observation data with different models that incorporate weather patterns to prediction insect migration routes and provide forecasts about the arrival of insects in any given location. Such forecasts can allow farmers to make informed decisions about the amount and schedule for pesticide usage, significantly reducing costs and maximising yields. This is just one of the many examples where an easy-to-use geo-spatial data platform can provide real benefit in the real world.