Part 2: The ASTA’s CSS 2018 & Seed Expo Debates What Tools Agriculture Will Need in the Future
By Dilara Ally
The American Seed Trade Association (ASTA)’s CSS 2018 & Seed Expo brought together both large and smaller growers to debate and share ideas on best practices for the future. In my previous blog post, I discussed how four leaders from BASF, Bayer Crop Science, Corteva AgriScience, and Global Seeds NA, China were evaluating the industry as a whole. In this post, I’ll dive into the talks that resonated with me about how we need to be thinking about innovation tools:
A Visionary Approach to Precision and Digital Agriculture
“Sometimes to look forward, you need to look back.” This forward-thinking session started with Scott Beck, president of Beck’s Hybrids, who harkened back to a white paper his father wrote when first thinking of purchasing a computer for Beck’s Hybrids. He made the analogy that today’s technologies bring a similar set of advantages if implemented with a thoughtful approach. While growers have found value in evaluating patterns of performance across their fields, they need insight into many of the most complicated relationships within the environment, which requires massive volumes of data from across millions of acres.
This presentation focused on the benefits digital tools were delivering today and how technology can provide an even higher value to the farms of tomorrow. Specifically, it explored how three technologies are shaping the future “smart farm”: the types of data used, seed production automation, and robotics.
Despite being the last talk, I thought the most visionary approach was the presentation of how the modern farm’s software operating system will be trackable, transparent, trusted but verified. It was interesting to hear over and over again how part of the reason digital has not made good on the promise to help with decision-making is the exponential growth in data creation, and that the increased complexity takes more and more work to make good on its pledge to increase the farmer’s profit.
Wheat and Plant Breeding Innovation
Agriculture needs to be open to all ways of addressing the challenges coming our way from climate change, sustainability, growing populations, and reducing our impact on the environment. That’s a key reason regulators and agribusinesses are continuously evaluating new tools and ways to make growing more efficient.
The importance of moving agricultural innovation forward was brought to life in two different sessions – one focused on wheat and the other on plant breeding innovation. First, Greg Marshall – a retired wheat breeder who worked for Dupont Pioneer – gave a perspective on the history of wheat breeding. I loved how he used the analogy of breeding as an art form, with the breeder as an artist. He expressed it best by saying, “The artist has a palette of full of colors, and you can select any color you want out of it and by looking at what the environment is giving you this year favors one type or one color over another. Technology offers a lot of promise to speed up this cycle.”
He went on to describe how one of the challenges an early generation breeder faces is that they only have a few seeds and that they don’t always get to see the variety in as many environments as they’d like so they are left trying to find uniform fields in the types of environments the variety is likely to be exposed, something that is becoming more difficult with the climate volatility. And while current technology can help knock years off the release of a new hybrid (takes 10-14 years), with each year that you knock off, you lose information. Ideally, as Marshall said, “The more you can expose what’s good about a variety the better.“
Some highlights of the second session were when Under Secretary for Marketing and Regulatory Programs from USDA, Greg Ibach, brought his unique perspective from Washington, D.C., and when Dr. Patrick Schnable provided a more technical perspective with his presentation entitled, “The Potential Of Predictive Plant Phenotyping To Address The Challenges Facing Crop Production.” I thought this talk was a nice complement to the wheat session because it likened how process-based, statistical, and predictive models could give us an enormous advantage because it would identify the genetic dogs before ever conducting the yield test, just as Netflix is better at picking the things we don’t like.
He then went on to describe what he thought was an essential ingredient when he said: “a community of plant scientists, breeders, plant physiologists, engineers, and computational scientists work together in a very trusting way.” This comment stuck with me because, at CiBO Technologies, that is our environment. Each day, experts in agronomy, data science, and engineering work together to build tools to help overcome the world’s most important agricultural challenges.
The critical theme that resonated for me throughout the conference was that the future of agriculture hinges on the value of insights that can be extracted from data and delivered to growers. The industry is at a pinnacle where the volumes of data are reaching unprecedented levels, and agribusinesses need to be equipped with the right advanced tools to turn the data into actionable insights that will help deliver a more efficient and higher crop yield.
Thank you to all the speakers and attendees. We look forward to seeing you next year!
About Dilara Ally
Dilara Ally is a Solutions Manager at CiBO Technologies, a science-driven software startup. She lives at the intersection of people, the business, data, and technical expertise. Throughout her career, she has led business critical, strategic initiatives, including one focused on the implementation of cross-functional data management and data analytics. Prior to joining CiBO, she was the Data Science Lead for the Biologics site in Bayer Crop Science, where she spent five years working in and across geographies and functions, prior to that she worked at SG Biofuels Inc for two years building a molecular breeding program and supporting both field and lab science using data science and bioinformatics. She holds a PhD in Plant Statistical Genetics from The University of British Columbia.