This is a three part series focusing on ways to determine your field profitability using your technology. We will post the series over the course of two months. If you don't want to wait, you can get the full series here.
In the early 1970s, I was fortunate to work for a farming operation that was serious about soil conservation. Serving on State Soil Conservation boards, building terraces, implementing no-till, when planters and weed control options were crude by today’s standards – they were soil stewards. Because of their mentorship, I’ve always taken soil conservation seriously.
As farmers face another year with challenging markets and high inputs, we as agronomic advisors continue to work with our clients in order to find where we can remove some of the guessing when it comes to the decision-making process of planning another season. It comes as no surprise to anyone that is involved in Agriculture that many areas saw higher than normal precipitation in 2018.
Why should you test products on your own farm? Your farm is unique and you have the equipment capabilities and data to conduct those trials. With little risk, you can have a more robust dataset than many companies. I’ll explain…
Some people remember phone numbers or slender dates; I remember farm fields. Before the 2005 crop year, the program leaders for Central Advantage from Central Valley Cooperative in southern Minnesota asked me to help generate variable-rate planting prescriptions. The primary question was “agronomically, what makes sense?”
Throughout Premier Crop’s nearly 20-year history, we’ve perhaps been the most diligent at communicating that what we do – big data analysis – would be considered “observational data analysis,” which can show relationships and correlations, but stops short of providing cause and effect.
Topics: Enhanced learning blocks
A commercial partnership brings combined analysis of financial records and field productivity to Syngenta growers.
Topics: data analytics
You are likely asked for next years seed order many times before harvest even begins. In that case, one of the first decisions you probably will make using your yield data is which numbers to plant the following year.
Telling customers they are underperforming never seemed like a great business model to me. Benchmarking can have that exact effect – 60% aren’t performing well if you remember teachers grading on the curve back in school. Those at the top of the curve might enjoy the satisfaction of knowing they are the stars, but how do you gently push the below-average customers to step up their game?