Big Data, Precision Agriculture, and Manure

This last week I had the pleasure of attending the AgStar Technoledge Conference in Minneapolis.  The conference was filled with lots of good talks about how to incorporate new, innovative technologies into your farm (whether it be a crop or animal farm) and a chance to talk with famers who already are, or are thinking about ways to integrate these techniques into their operation. There were lots a great presentations on technology in agriculture. Topics ranged from an economist discussing how agriculture will respond to challenges over the next 35 years, housing the pig of tomorrow (check out Dr. Mike Brumm’s blog at http://forum.mnpork.com/forum/) , and even a panel discussion some of the things these farmers were already doing – row clutches, GPS guidance and auto-steer, and drones. Then there was me, brought in to discuss precision agriculture in relation to manure management. What was I going to talk about, I’m not a precision ag or big data guy, I’m a manure guy, but I was going to give it a try.

So, to get started on these things definitions are always good, so what is big data and precision ag. We probably all have some definition for these things in our head and mine are no better, but to me Big Data is having extremely large data sets that can be analyzed with neat computational techniques to reveal some pattern. Precision agriculture is then using these relationships to and improved understanding to make more specific management decision, such as managing different areas of a field separately or tailoring our treatment of one cow differently than another. The idea is that by tailoring our decisions to the specific needs of those different management zone or treating each animal a little differently we can improve the overall production.

This got me thinking, what does it take to make “big data” or “precision” anything successful. One example that we probably all have heard about is in sports, the Moneyball approach, so I figured I’d start there. Well as luck would have it, Nate Silver over at fivethirtyeight.com wrote an article about what made big data successful in sports. He said there are three things that have driven the data revolution in sports. 1. You need lots of data, and it needs to be of good quality, 2. You have to know the rules, and 3. You need a way to get meaningful feedback and clear ways of measuring success.

What does this mean for agriculture and the big data revelation? Well, in this regard agriculture offers some greater challenges than sports. Sure we can collect lots of data, but it’s not all available (and I’m not saying it should be), but one of things that drove the sports analytics movement was the access that everyday people having the sports data and working with it until they found an answer to some question that was important. More concerning is you have to know the rules. Sports are rigidly defined games, we picked the rules, so we know them. In agriculture it doesn’t work that way, we have been discovering the rules for the entire human existence, and we know now more than ever, but we don’t know them all. For example, we know that corn responds positively to nitrogen addition, but we still have trouble predicting how different soil and weather conditions interact to get the ideal nitrogen application rate. Finally, we know our goal is to increase productivity (or profit) per acre, or animal, but in many cases we don’t get a lot of samples (you only grow one crop on that acre every year).

Let’s look back at sports, for a long time pitchers were primarily judged by how often they won and lost. You only have to look back to 1990 to see an example of this. In 1990, among the two pitchers in the American League who lead the Cy Young voting Pitcher A went 21-6 and Pitcher B went 27-6. Pitcher B one the Cy Young; at its face, this seems fair, the guy won 6 more games, his results were better right. Since that times we’ve really started to focus on other stats when evaluating pitchers, it turns out wins are too dependent on other things, like how many runs your team scores, to be a good predictor of future success or really indicate how well you pitched that year. In this case, it turned out that pitcher A was better in almost every meaningful pitching category, his ERA was 1.93 as opposed to 2.95, he allowed 1.08 hits or walks per inning instead of 1.22, and most impressively, his ERA+ was 213 instead of 126. ERA+ is a stat that supposedly adjusts the pitchers ERA for the ballpark he pitched in and the ERA of the pitcher’s league, so you can compare pitchers across history, a higher number is better.

So what’s that story tell us about big data in agriculture? Well just because we made a better decision (or were a better pitcher) doesn’t mean we got better results. Sometimes the ball just doesn’t bounce are way. The important point to remember, is that by making a better decision and following the correct thought process are odds of succeeding increase. Focus on the process, not the results – the results will follow.

In manure, we’ve went from this

To this:

But the fundamental tenants have remained the same, it’s all about getting the right amount, in the right place, at the right time, and using the right method. No one knows for sure where you go from here, but figuring out the best ways to use and understand the data makes it an exciting time in agriculture.

Why is human waste treated and discharged and animal manure stored and land applied?

As you can tell from the title, I've branched out and decided to hit a topic that is a bit different than some of the others we’ve touched on. What I’m going to discuss is why we handle human waste and animal manures so differently. This is a fun topic with lots of nuances and unfortunately we won’t be able to hit on all of them, but as this is a pretty common question, i.e., why don’t our animal farms just treat their manures like cities do, I think its work talking about.

As you are probably aware, town and cities use sewage treatment facilities to process human wastes. The treatment process create a purified (at least to some level) liquid fraction that is usually discharged to surface water and often times, a solids rich portion that is land applied on farm fields. The approach on livestock farms is very different, in this case the manure is stored and then applied to crop ground as a fertilizer.

So let's cut to the chase, why is human waste treated and discharged and animal manure stored and land applied? There are a few differences and I’ll try to hit on them, but the big one is WATER consumption! There are lots of things in both animal manure and human waste that can impact water quality… nitrogen, phosphorus, potassium, solids, and even pathogens…, but one big difference is how much water is used, and as a result how much manure/waste is generated.

You’ll often hear things like a farm of 10,000 finishing pigs will produce as much nitrogen of phosphorus as a city of 46,000 people, but it only takes about 550 people to use as much water as those 10,000 pigs! Why does this matter… well, it means our animal manures are a lot more concentrated than human waste! This means it doesn’t take as much to cause and environmental issues and that conventional waste treatment systems used for human waste often won’t perform well when used for animal waste. However, just as importantly the lower water use at swine farms makes it much, much more feasible and economical to collect, store, and apply it to our crop fields as a fertilizer.

Let’s play with a few numbers on this to get some idea about the economics; with swine manure it probably costs about $0.02 per gallon to land apply. My math says that 10,000 pigs will make about 4.4 million gallons of manure per year, meaning our manure application cost would be about $88,000, but this swine manure contains about $200,000 worth of fertilizer value based on the nitrogen, phosphorus, and potassium it contains, making our storage and land application approach a very viable utilization strategy. So what about our human waste? Well in this case since the manure is much more dilute our costs to land apply it are probably a bit cheaper, let’s say $0.005 a gallon. In this case a city of only 550 people with generate the same about of water so it would cost $22,000 to land apply, but it would only contains a little more than 1% of the nutrient value  of the swine manure, so it only has a fertilizer value of around $2,500. So in this case this doesn’t seem like a very good approach to managing our human waste since the cost to handle it is more than the fertilizer value it would provide.

In large part, this is the fundamental difference. The reason we store and land apply our animal manures is because they are concentrated enough that often times utilizing the manure as a fertilizer source is economical. In the case of human wastes, this isn’t the case because of how much water we use. Several other factors also play a role, but at the fundamental level, it really comes down to water use and our ability to economically use it as a fertilizer.

Manure Analysis - As Is versus Dry Basis, what does it mean, and which one to use

I received a question the other day about poultry litter and the variability of the manure samples they were collecting over the last few years. There are lots of things that can cause variability in our manure, for example, the diet of the birds, the management of the litter, the age of the birds, weather conditions and a host of others. We discussed this but my follow-up question was are your sample results on an “as-is/wet” basis or were they on a “dry” basis. So today’s post is about why I asked that, and just as importantly, what the difference is, and which one should I be using in my manure planning?

So let’s start with the difference, when we talk about an “as-is” or “wet” basis we are talking about the amount of some item (let’s say phosphorus) per unit of mass of the manure in its current condition, that is as it sits in our storage or loaded in our spreader. When samples results are reported on a “dry” basis, the laboratory has measured the solids content of the sample and is reporting how much of that item is present per unit of solids.

 

So when is one presentation advantageous over the other one. When we apply manure we are always applying it on an “as-is” basis, so when we are figuring application rates it is most useful to have the  nutrient contents on an as-is basis. For example, if we know our manures phosphorus content on an as is basis,110 lb P2O5/ton, and the amount of that nutrient we want to apply is 250 lbs of P2O5 per acre, then we can estimate that we want to apply 2.3 tons of that manure per acre. Is we were told that the manure had a phosphorus content of  225 lbs P2O5/ton on a dry basis, we still wouldn’t be able to estimate how much of our manure to apply, because our actual manure has some of its mass from water. So typically in our manure management planning we want to work on an “as-is” or wet basis.

So when is it advantageous to work on a “dry-basis?” Well, there are a few times when this may be useful. For example, the consistency of our manure samples from one year to the next or between barns. Adjusting to a dry-basis in these cases provides us a way to normalize our data for a specific variable, in this case moisture that can be influenced by the amount of water used in the barn. One way to think of this is in a pig barn it’s a way to account for differences in water wastage (or perhaps if I’ve washed my barn 3 times in one year and only twice the next), or in the case of feedlot manure, how wet it was when I scraped my lots. As an example of this I recently looked at a series of 275 manure samples from swine deep-pit barns in two ways, on an as-is basis and a dry-basis. What I found, is that by looking at the phosphorus content on a dry-basis as opposed to a wet-basis, the variability was reduced from 49% to 35%. Similarly, in the case of nitrogen, the variability was reduced from 19% to 11%. For similar reasons your soil sample results are also presented on a dry basis.

 So the take home message is usually the wet basis presentation is more useful to us in terms of our manure management planning, but if we are trying to learn something about the consistency of our manure samples it is often useful to look at the data on a dry-basis.