Q1. Tell us a bit about your background and how you ended up in your current role.
My PhD is in evolutionary genetics and I worked as a professor for 10 years in this field in Canada and Germany. As technologies expanded I moved my research more and more into the area of genomics, using high-performance computing systems. I saw the opportunity at Plant and Food Research as a way to take my theoretical knowledge and apply it to real-world systems. This includes not only genetic and genomic research but computer vision, sensors and sensing systems, and consumer research.
Q2. What has been your biggest success for 2020 so far?
Plant and Food Research have many lab and field workers who were unable to perform their regular duties during level 4 and some extent level 3. We were able to utilize these staff for computer vision projects – we had 57 workers labelling images to seriously advance our automated monitoring programmes.
Q3. How do you address the ethical considerations and customers’ concerns regarding the secondary use of data?
One big issue for Crown Research Institutions is taonga data. For us, this includes not just data around native species but data on anything that is considered taonga by Plant and Food’s Māori collaborators and customers. So for example reusing information from genomic research requires full consent. This is an area that Plant and Food is currently working very hard to ensure we have the systems and practices in place to allow this to happen and we are striving to be world-leaders in this area.
Q4. Real-time, collaboration, open data: What is the importance of real-time data in your organisation?
Becoming more so. One aim of Plant and Food Research is to use real-time data to monitor crop development and condition to enable us to release crop management tools that sit alongside the cultivars that we release. This requires a change in thinking from investing in the manual collection of data to investing in wired orchards and growing systems. We are currently embarking on a number of projects to enable us to count, size, or otherwise measure key measures for each our cultivars.
Q5. What questions are you able to answer with real-time data that you were not able to answer before?
We have developed algorithms for automated monitoring in our aquaculture research facility to the level of individual fish. We are now working on scaling this to open ocean aquaculture facilities. This means we can track each fish over their lifetime to monitor health and nutrition, pest and disease and other indicators of fish quality. This information can then be incorporated into the supply chain to more fully tell the provenance story of each fish.