8,400. The number of bread loaves that can be lost if a farmer loses two bushels of wheat per acre over 100 acres (from extensive research in the form of a quick Google search that turned up Kansas Wheat documentation).
Population Growth Demands More Food
120 years ago agriculture faced a large change with the mechanization of standard farming practices. At the same time, the human population started on its exponential
growth trend. After the world wars, fertilizers became common practice in ag. A few decades later, chemicals for weed and pest control started emerging. Today, genetically enhanced seeds with a host of traits help with everything from drought tolerance to naturally produced chemicals.
All of these agricultural advancements help keep food production in line with the demands of a growing population. The question that continues to plague minds is how do we maintain the business of growing food at the at the same rate as population growth (which is expected to double by 2050)?
The obvious answer? Help farmers do their job better.
Farmers have to make a plethora of operational decisions on the fly to ensure they are maximizing yield and profit potential. These decisions can be as granular as how many seeds to plant per acre, to how many inches apart the sieves on a combine (harvester) should be to maximize yield based on test weight, crop type, fan speed, etc.
Any slip-ups in decisions and farmers can cause productivity to go down a few bushels per acre to several bushels per acre (assuming the crop in question is measured in bushels). Or simply, 8,400 loaves of bread lost. Believe me, after growing up on a farm it’s not a hard stretch of the imagination to make that kind of judgement error.
Hello Big Data. Meet Your Friend, Agriculture.
So what’s the next big, hot item in ag? I’m going to claim that it is big data. But the even bigger question: Big data for whom and why does it matter?
If a farmer is already making highly technical operational decisions, how do they come close to capturing enough data to make it useful? And to layer on more, the big points that are the easiest to capture are already understood such as what type of fertilizer brings the most impact to certain geographical areas.
Farmers are in flux. How can they capture enough data to make it useful, i.e., stuff they don’t already know off the top of their head? And still not have it so time consuming and complicated that it is actually feasible to capture and analyze it?
As any farmer will tell you, there are only so many ways to influence yield during the growing season. For example, you cannot change the variety of seed after it has been planted. This leaves us with the fundamental understanding of what influences yield in the first place. I believe it can be broken down into two categories:
- Environmental: Were the conditions such that yield was maximized i.e. growing degree days, pest pressure, rain amounts, etc
- Mechanical: Is everything operationally correct? Is the planter set up correctly and going the right speed? Is chemical applied at the right time? Is the harvester set up correctly? Was the field cultivated in the right direction the last season?
Once the environmental and mechanical influencers are understood, how to measure each yield influencer becomes clear. From there, farmers can determine what to do about each influencer during the current growing season and beyond.
Capture the Data
Now that we know why big data is important and how it can help farmers, let’s start to plan how to capture it. Here are three simple steps to get started.
- Farmers need to decide which items most influence yield on their land. Two paradigms should be examined: a) Season to season influencers and b) Growing season influencers.
- Then farmers can determine which data is important to collect. What environmental and mechanical influencers are important to document?
- Lastly, creating a plan on how to collect data and making sure to explore how much it could be worth to collect data is an important step for farmers. Collecting data can be done in several ways. Weather stations measure temperatures so you can calculate growing degree days. Free software, such as Virtual Farm Manager, allows farmers to enter how certain operational items are setup in each field and track the setups over time to determine differences.
If farmers use software and mobile apps to help operational efficiency and capture season to season data, with any luck we can start adding food to the supply chain. Possibly, 8,400 loaves of bread at a time.