Foundations of agronomy and geography are the starting place for data-driven decisions.
Dan Frieberg
Recent Posts
Long before GPS was part of our acronym vocabulary, my early agriculture career started in eastern Iowa and northern Illinois. On one of those scorching hot July days, as you were driving through the area, every so often the road would be higher than the fields and you could visually capture a birds-eye view of the fields below. You could see parts of the fields, where the corn was rolled up tight as the plants went in to "protection" mode – while other parts of the field look perfectly normal. Images like that help make me an advocate that managing parts of the fields differently would make agronomic and economic sense.
Topics: Enhanced learning blocks, learning blocks, variable rate
At this time of the year, it's easy to feel like yields are largely a function of weather – temperature and rainfall. Over the years in hundreds of grower meetings, I've heard that sentiment repeatedly. If you are inclined to think that way, think about this scenario.
Topics: Farming, data analytics, data driven decisions
Every week I see ads using the latest marketing buzzwords to describe how a company is going to use your/their big data to revolutionize how you farm. Estimated rainfall using radar images is being claimed as “hyper-local”. UAV’s, imagery and crop models being claimed to replace scouting for diseases and insects. Proprietary algorithms use big data to manage all your inputs so efficiently it will be “game-changing.” That’s one of my favorite buzzwords- “game-changing.”
Topics: data analytics
Increasing return on investment for every input is clearly on the mind of every grower. They are in an economic squeeze, but that doesn't mean they won't invest more in crops. It does mean they are scrutinizing every dollar they spend. The current success measure now goes beyond yield increase to include which inputs offer better return on investment.
Topics: cost per bushel, seed selection
I'm always looking for parallels – examples from other industries on how they use data to drive better decisions. While on the road, I listened to several Freakonomics podcasts. One that related well was titled Bad Medicines, Part 2: (Drug) Trials and Tribulations.
Topics: Enhanced learning blocks, trials
Virtually every precision ag survey done with growers and industry over the last 20 years would rank "getting different systems to work together" as the greatest frustration and obstacle to growing the overall market.
Topics: Farm technology
Dan Frieberg talks about the Silver Bullet of precision ag and how there is no "Silver bullet". The point is the "Silver Bullet" for growers changes within every part of every field and can change every year. Watch now...
Topics: Precision ag
I’m a big believer in the practice of split-applying nitrogen – specifically sidedress – applying a portion of the nitrogen after planting. Being able to apply part of the nitrogen closer to plant uptake always made sense to me because the nitrogen is less available for loss before that time. However, oftentimes it is difficult to find the advantage of sidedressing in the data.
Topics: variable rate