Second Agri-Food Study Group with the Mathematical Sciences

Published: 04 August 2017 by KTN

Date: 21 February 2018 to 23 February 2018

Location: Edinburgh

  • agritech
KTN is inviting Agri-Food companies to take part in a three-day Study Group with maths experts to stimulate innovation in this exciting field. In collaboration with the International Centre for Mathematical Sciences, we will be hosting the Second Agri-Food Study Group with the Mathematical Sciences in Edinburgh on 21st – 23rd February 2018. At this stage we are inviting Agri-Food industry organisations of all sizes to get in touch if they would like to find out how they can participate. We are looking for companies with an industry challenge that could potentially be solved by the mathematical sciences. Please get in touch as soon as possible, by contacting Matt Butchers and David Telford who can explain more about the event and what could be taken through to the February Study Group. Background Although Agri-Food might have traditionally been viewed by some as a low-tech industry, the reality is very different. The Agri-Food industry is making rapid advances to adopt cutting-edge technology, to help it address the challenges it faces, such as feeding a rising world population, reducing environmental impacts, and improving food quality and safety. For example, agriculture is already utilising cutting edge technologies such as satellite imaging to monitor crop growth, and robots to milk cows, and many other technologies are under development and likely to be introduced in the coming years. As with other industries, all these technologies generate massive data sets, and have the potential to make food production systems more complex. Thus, there is an increasing need for agriculture to work with other sectors to turn ‘data into decisions’ that can help the farmer. At the KTN Mathematics in Agriculture Workshop at Harper Adams in 2015, Professor Graeme Wake commented that “Modern-day applied mathematics can be used with high impact on farm systems and precision agriculture. It provides excellent decision-support tools and brings a degree of rigour to the industry, which has often been lacking in the past. The agricultural industry has been relatively late in choosing to bring mathematics to bear on the processes involved”.
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