Posted: March 30, 2023

Personalizing the agricultural information stream.

While working with farmers, I have always been struck by their honesty in asking questions or providing reasons for why they adopted specific approaches to their farm operations. This has been no different when it comes to digital technology and what it offers agriculture.

The tremendous amount of data generated in today's world allows us to explore new and old farming practices in ways we didn't think about all that many years ago. Nonetheless, understanding the range of disciplines employed when collaborating with our stakeholders will help us improve data-centric approaches to agriculture.

Sometimes the reason to adopt a new technology involves considerations beyond the scientific. One of the clearest examples I remember occurred more than 10 years ago when a dairy farmer told me they had invested almost $1 million in a robotic-milking system. Part of this investment was improved knowledge generation with the automated data collection on each cow, along with physical health improvements by no longer needing to milk their herd multiple times per day. Still, it was as important that they could take time for other activities, such as attending their grandchildren's baseball games in the summer.

More recently, a key stakeholder asked me the following: "I have access to all of these maps, but can you tell me how to interpret them in a useful manner?" This is not an isolated comment. For many farmers, the major limiting factor is having the time available to sift through all the information and data they collect.

Data standardization also impedes utility. Animal agriculture benefits from a range of technologies, but using the data more efficiently, given that it can vary widely across systems in a nonstandardized manner, poses a major challenge. This lag, or lack of clear interpretation, affects decisions that could improve farming operations.

Digital technologies continue to evolve, so let's consider some terminology: Data analytics, robotics, drones, sensor technology and automation are just some of the potentially confusing terms producers now encounter in farm journals or newspapers. Furthermore, these terms are often integrated into broader concepts like precision agriculture, climate-smart farming, emerging technologies and e-agriculture. In an overly simplified way, all these concepts aim to improve agricultural production and sustainability by enhancing the links between data, interpretation and implementation. This may occur at the field scale or through improved connectivity from farm to table or policy and program development.

In working with farmers to develop cloud-based decision support systems, our team has learned we must consider numerous other aspects of digital technology like trust, consent, data privacy, security and equity. This has pushed us to expand beyond the college, strengthening our collaborations with other experts at the University in data sciences, informatics and computer programming, helping us to explore and strengthen new initiatives within the college.

A Community of Practice

The College of Agricultural Sciences' broad portfolio and expertise provides tremendous opportunities to tackle challenging questions in digital technologies for agriculture. One new effort is strengthening the networking and research opportunities in the college and beyond.

This new effort integrates research and extension efforts into an emerging and advanced technology community of practice under the college's Institute for Sustainable Agricultural, Food, and Environmental Science (SAFES).

This community is composed of faculty, postdocs, staff and graduate students, to create a network of researchers located in a single place that members of our community can search out when looking for collaborators, expertise and interest in expanding their research-teaching-extension portfolios.

Long term, we see tremendous opportunities for developing transdisciplinary grant projects to tackle the most significant issues impacting agriculture, leveraging our strong expertise in quantitative methodology.

Paul Esker is an associate professor of epidemiology and field crop pathology and a co-leader in the college's emerging and advanced technology community of practice. More information about the initiative can be found at SAFES Communities of Practice.