Analytics in Agriculture

Now, more than ever, food is scarcer and harder to grow. Analytics plays a significant role in the creation of genetically modified crops that account for increasing populations, climate change, pests, and disease. Syngenta, a globally recognized agriculture company, specializes in healthy, sustainable crop production as conveyed by their website. They collect seeds from all over the world and group them by desired qualities. Sweet potatoes, for example, would be classified as naturally drought tolerant. Scientists extract DNA splices from these seeds that correlate to the specific trait of interest and surgically insert them into the DNA of other plants. These genetically modified crops are then lab-grown and evaluated. Data analytics is used to maximize genetic gain throughout the process.

Professional headshot of Abigail

Abigail McCauley, a graduate of the Institute for Advanced Analytics at NC State University, is currently employed by Syngenta. She developed a passion for botany at an early age and especially enjoyed gardening with her grandfather. After earning a bachelor’s in Plant Biology and a master’s in Crop Science, Abigail realized she loved data analysis more than the data collection process. The following interview details her experience with analytics in agriculture.

Margeaux: What step in the process of creating, for example, corn that is resistant to droughts, does analytics come in?

Abigail: That is one of the exciting things about this role. Analytics is used at every step – I specifically perform analytics in the corn breeding pipeline. It is used to determine what materials we will be working with, what data is collected from the field, what we should be testing, and how to use the data. When we have good products, analytics helps decide where these should go and to whom they should be targeted.

Margeaux: What type of data is used, and does it often require clarification or scientific understanding?

Abigail: I spend a huge portion of my time working with genetic data. It might help to understand genetics, but it is not necessarily required. There are protocols for collecting data and there is background information that provides context to the data we use. What surprised me the most about my role is that I use more of what I learned at the Institute than the work I did previously. You need to know how to run analysis, perform data cleaning, and improve the data you are working with to help make better decisions. Many analyses can be routine, but there are a lot of chances to change how you run the analysis and what factors you consider. As new genetic combinations come in, we are constantly improving to make sure the data is as good as possible. Also, the communication aspect is often overlooked and is more important than you think.

Margeaux: On average, how many different crop analyses do you perform each year? And how long do you typically spend on each project?

Abigail: I have worked on the same project the past three years (finding the best corn hybrids) – think of it as a growth process. It is always evolving because plant breeding is coming out with new genetics. We are trying to constantly do better and get higher yields. If we look at pests, one solution is not going to work until the end of time. That is something you must keep evolving for us to put products out that meet demands. There is a wealth of information, and what your data looks like depends on the goal and how it was collected, like insect damage data or disease data. There are different smaller projects that we are all involved with as well. Every year, the projects I am involved in, and the day-to-day tasks, are very different. Sometimes I collaborate with different teams and my role changes.

Margeaux: Other than creating genetically modified crops that have higher yields, are resistant to climate change, and can survive pest or disease influx, how else can this industry provide healthy food to hungry people?

Abigail: We want to help farmers grow a better field and reduce inputs. We are not just talking about how to reduce pest pressure in a field, but that can lead to fields being more sustainable if the farmer doesn’t have to go out and constantly spray. Other branches of Syngenta work with horticultural crops or flowers, and these are the areas you might see products with more traits appealing to the end consumer. I grew Syngenta flowers in my garden, and I loved them – they were much easier to grow. Making it easier for farmers to grow reliable food is a big motivation for the work I do.

Margeaux: How do you see the work that you do come to life, whether in a greenhouse, or through the sale to local farmers? What do you get from seeing the results of your work?

Abigail: The most exciting Zoom calls I’ve had are with team members showing me what our corn fields look like. We also hear from growers who talk about their experiences: what their end of the process looks like and how things look on their farms. It can be different from grower to grower and different depending on the region. You get to hear some of these stories and understand what it is like to be in their shoes or what problems they want you to address. These opportunities make a big difference to the farmers who choose our corn hybrids.

As Abigail McCauley put it, “I think the work we do is very rewarding and raising awareness about this field is important because there is so much more to be done.”

The world is ever-changing. Farmers must mitigate and adapt to the effects of global warming, disease influx, and pest infestations to ensure sufficient food supply while protecting the fragility of our ecosystem. Even though skilled data scientists are one of the most sought-after professions, the use of analytics in agriculture is not a trending topic. It is time for action! While food banks are happy to take your donations to help feed the 828 million people affected by hunger worldwide, consider where that food came from, and how important analytics is to the future success of agriculture.

Columnist: Margeaux Johnson