Food, Farms and Forests

New fertilizer decision tool could save farmers money and help the environment

Arkansas Agricultural Experiment Station

FRST is an interactive online tool that provides soil testing data to farmers and scientists. This resource is free and aims to offer better and more information to farmers so that they can decide how to best treat their soil.

Nathan Slaton, associate vice president for agriculture and assistant director of the Arkansas Agricultural Experiment Station, was the principal investigator on the project. He explains the benefits of this online soil testing database, the first of its kind where scientists and universities from across the country can contribute data to continuously improve it.

This project was made possible by U.S. Department of Agriculture Natural Resources Conservation Service and Agricultural Research Service grants. Nearly 100 soil science and agronomic professionals from almost 50 universities, four USDA divisions, several nonprofit organizations, and one private-sector partner participated in developing FRST.

For more information about FRST, visit https://soiltestfrst.org

You can read more about this project here: https://aaes.uada.edu/news/frst-released 

[00:00 - 00:16]

Intro

Welcome to the Arkansas Food, Farms and Forests Podcast, the podcast bringing you the latest on food, fiber and forestry research from the Arkansas Agricultural Experiment Station. The research arm of the University of Arkansas System Division of Agriculture.

 

[00:16 - 00:43]

Jenifer 

Welcome to the Food, Farms and Forests podcast. I’m your host, Jenifer Fouch. Today, we are learning about a new tool that aims to save farmers money and help the environment by providing consistent soil fertilizing recommendations across state lines. FRST, or first, stands for Fertilizer Recommendation Support Tool. It's a free, web-based national soil fertility database for farmers and soil consultants.

 

Joining us to talk about FRST is Nathan Slaton, who was the principal investigator on this national project. He is the assistant director of the Arkansas Agricultural Experiment Station and professor in the crop, soil and environmental sciences department. Nathan, thanks for being here with us.

 

[01:02 - 01:03]

Nathan 

My pleasure.

 

[01:03 - 01:17]

Jenifer

We appreciate you making the time to talk to us about this. This is a big deal because this was a national project, years in the making, and now the website is up and running, people are using it. What is the latest update on FRST?

 

[01:18 - 01:43]

Nathan

Well, the latest update is that our decision support tool went live at the beginning of April, and that was after probably 4 to 6 months of troubleshooting. It was on the web and people could find it at that time, but we weren't, you know, actively asking people to find it other than some beta testers.

 

So, anyway, we got all that lined out and early April it went live. And basically the tool accesses a database that we have been putting together for about five years. And currently that database has information from about 2500 research trials that have been conducted, across about 40 states and over on over 20 crops.

 

[02:14 - 02:17]

Jenifer

So it's only been live for about a month or so.

 

[02:17 - 02:24]

Nathan

Correct. And, it is really just the first step of what we're looking to do.

 

[02:24 - 00:02]

Jenifer

Okay. So first let's take a few steps back and start with the basics. First, what is a fertilizer decision aid.

 

[02:32 - 03:21]

Nathan

Soil testing has been a discipline for about 100 years. And it came about from post-World War II really, when farmers, you know, were seeking help and what fertilizers to apply. So, it is standard practice now for farmers before they plant a crop to get a soil test. And what we have, you know, noticed and not just recently, but this has been a problem for years is that, states and, you know, that basically share the same weather patterns, the same soils, the same production systems, often have different fertilizer recommendations.

 

And that's even if they're using the same soil test methods. So when, you know, for example, a farmer that may farm near or on the border of, of, you know, two states, literally, he could have different regulations and or fertilizer recommendations coming from the land grant institutions for fields depending on which side of the state they're on.

 

So this, tool, and that's just one example, because there's also private soil test labs out there that, you know, have their own fertilizer recommendations. So this tool is really just, a resource for farmers, consultants, industry, anybody to use to be able to look at their crop, their soil test information and see what the data supports in regards to a fertilizer cut off.

 

You know, just like anything, whether it's sports and coaching, you know, everybody kind of has their own philosophy of, how to fertilize a crop. Sure. And a lot of those philosophical differences have, been incorporated into fertilizer recommendations at different labs, regardless, again, of whether it's a private lab or a public institution lab. And, what the tool does is it it basically takes the information from the, from the field trials.

 

It's all in a database. And, it is, other than the implicit biases that modeling, you know, certainly possesses, it takes away, you know, the Nathan Slaton philosophy of this is the way you need to fertilize, which may be different than, you know, doctor Somebody Else at a neighboring state that has a slightly different philosophy or thought process on how to fertilize crops and manage soil fertility.

 

[05:28 - 05:44]

Jenifer

So, let's talk about how it works. You go on the website, you put that information in there and you use this resource. Can you kind of walk us through what does that look like? What information is it asking you and what the website shows you?

 

[05:44 - 06:15]

Nathan

Yeah. So like I say, this is the first phase of the tool. And right now it helps us with what we call soil test correlation, which, really identifies the critical soil test value, which is defined as the soil test value above which a significant yield response to fertilization with that nutrient will not occur. So the tool has several filters on it.

 

Those filters allow the end user to identify the nutrient. And right now, the nutrients that are in the tool are phosphorus and potassium. It also allows the user to select an individual crop, corn, soy beans, rice, etc.. And then as you continue to narrow down, you know, the, the nutrient, the crop, it will also allow you to select from the database, the soil depth that was sampled.

 

And then eventually you get down to selecting, the soil test method that was used. Because soil test methods are, they vary from one lab and typically from one state to the next. And, they can significantly influence the soil test values that are generated. So once you make all those selections, the soil test method is the last one.


 And once you select the soil test method, it will show you how many observations there are in the database for that information, apply a model to it and eventually show the data with a model overlaying on it, along with information about the the magnitude of yield from that data. And it will also show you the individual site years of data.

 

Really the intention, at this point is that they would have their soil test recommendation from their lab using the same soil test method. They can look at their fertilizer, you know, whether or not they get a recommendation to apply fertilizer. And they would be able to run this tool to see whether they should expect a yield increase from fertilization.

 

It doesn't mean that fertilizer should not necessarily be applied because many farmers, you know, it's just like filling up your gas tank, right? You don't necessarily wait until your car stops before you put fuel in it. It's the same way with fertility. Some philosophies, if you will, are that when we remove a nutrient with a harvested crop that we're going to put some of that nutrient back as well.

 

[08:39 - 08:44]

Jenifer

And the tool is available for 40 states and Puerto Rico right now. Is that correct?

 

[08:44 - 09:12]

Nathan

Well, the tool technically is available for all states. It's just the data that we currently have in the tool is coming from 40 states and over 20 crops. when you first pull up the tool, there will be a map of the United States and the territories that shows up. And anywhere there is a green blotch, at least I think it's green because I'm red-green colorblind.

Wherever there is a green means that that county has data in the national database. And as you select nutrient, crop, only the counties that have data will remain highlighted. So, you know, you will be able to literally see where in the United States the research has been conducted and archived into the database as you use the tool.

And just as a side note, that's another fantastic feature of this tool is that, it allows us to see where the research has been conducted and where we really need to put more effort into soil test correlation research.

 

[10:03 - 10:31]

Jenifer

Yeah, you're correct. It is green in there. Green dots. I played with the map. And it is very interesting. As you're selecting the different options, the little dots will pop up or not. So it is very user-friendly, very interesting tool. And you mentioned a little bit of this, but I want to dive deeper into the benefits of having this information and having this database available for farmers, for soil scientists, and then the environment overall.

 

[10:31 - 10:58]

Nathan

So I guess, the first thing I would say is that, soil testing, it's a great tool, but it's in many respects misunderstood. Many farmers and consultants have realized this across time because, at least when I first came into, into, this position, more than 20 years ago, it was not uncommon for somebody to take a small sample, mix it up.

Good, send part of it to the University of Arkansas and send the other portion to a private lab that was in Memphis. And at the time, we didn't even use the same exact soil test methods and units. So when they got the results, even though it was the same soil sample, the information was different. That is the first benefit is it allows the farmer to to see how the information is interpreted very uniformly.

Again, without professional bias or judgment.

 

[11:38 - 12:02]

Jenifer

And then, for soil scientists, you talked about how even looking at the map now, scientists can look at it and see, okay, we have information for these states, for these areas, we need to do more research on these crops or this region. Talk to me about how that's beneficial to scientists and the information that you are gathering and the information you're realizing that you still need.

 

[12:02 - 12:35]

Nathan

Yeah. So again, we have a little over 2500 trials in the database. Probably 2000 of those are for corn and soybean. Not surprising simply because they dominate the landscape in regards to row crop fertilization. There's not another crop in the database that has over 100 observations. So Bermuda grass, forage, cotton, rice, I think are between 50 and 100 observations.

And then, you know, we start getting down to less than 50. For many of our minor crops, we are still trying to collect data from what we call legacy data, information that has been published, or researched in prior years. That has been difficult simply because that data could be in file cabinets. It could be on somebody's computer drive and getting that information and as well as all of the metadata that, that is associated with it, that is really important, has been difficult.

Probably, again, 50% or more of the data is more than 20 years old. So, older production systems, older cultivars. we are encouraging the, the soil fertility community of scientists across the United States as they conduct trials to provide that information to us. with what we call a minimum data set. And that minimum data set is really important because classical soil fertility has focused on soil test phosphorus alone for predicting whether or not we need phosphorus fertilizer.

And we know from much smaller studies that, you know, if we take into account soil pH, soil texture, perhaps even other nutrients in the soil, that we can become more accurate with our recommendations. The problem is, as you add other covariates, if you will, to data analysis, you need more and more observations. So that's why, putting this database, as well as all of the other associated metadata with it is really important.

And it goes beyond, you know, what we're currently doing that would require more complex models and information, but it would provide more accurate recommendations in the end.

 

[14:50 - 15:00]

Jenifer

Very good. And what about the bigger picture? How could this potentially benefit the environment? And how does that translate on a bigger scale?

 

[15:00 - 15:24]

Nathan

One of the major problems from an environmental standpoint is putting nutrients out where they don't belong. So if we can, you know, think back to the for our mentality. Right nutrients, right source, right place. Figuring out whether or not the crop is going to respond to fertilization is extremely important for responsible nutrient management.

 

[15:24 - 15:38]

Jenifer

And how did this project come about? You were the principal investigator on this portion of the national project. How did Arkansas come to play a significant role in this national project?

 

[15:39 - 16:04]

Nathan

Well, this, really the the roots of this, you know, date back 50 years again to, scientists coming together and what we call regional soil test groups. There's one in the northeast, one in the South, one in the Midwest. It's called the North Central Group, and one in the West. So we've known for years that our fertilizer recommendations from one state to the other.

And, you know, vary. That's kind of been the elephant in the room that nobody has really wanted to talk about because we are all, you know, kind of encapsulated in our state boundaries. And we work, you know, for the University of Arkansas or Mississippi State University. And certainly we recognize that there is the need for more collaborative work and that, we can, if we join forces, we can do more with what everybody has.

So, part of this project really got sprouted legs about ten years ago when a scientist who was, at that time, with Purdue, basically came to a national meeting and was like, why can't, you know, why do recommendations change when you cross that little sign on the interstate that says, Welcome to Arkansas or Oklahoma? It doesn't need to be that way.

It took about another five years for a group of us in the South to really digest that information and come together, and we started comparing our recommendations that are supposed to be, you know, land grant institution, the latest and the greatest. And we saw that for the same soil test method, the same crop, huge differences in the amount of fertilizer and where we were starting and stopping fertilization.

So that was 2017, in Athens, Georgia. With the leadership of Deanna Osmond , who is at the North Carolina State University. We came together as a group and, we found some funding, from Pete Kleinman and USDA ARS to kind of get us started. Then we got a, Deanna got a grant from USDA NRCS that allowed us to start developing the database and to start thinking about what our vision would look like in a program.

 

And more recently, that initial project ended and, another project from USDA NRCS started in August of 2023. And that is the one that, here at the University of Arkansas that we are leading. But this is a national effort. We have scientists from, really 45 states that are participating either in a committee or have coauthored, presentation or coauthored papers working together in this project.

 

[18:43 - 18:52]

Jenifer

And the project was made possible by those grants. Can you, clarify for us, the USDA, the NRC is the Natural Resources.

 

[18:52 - 18:53]

Nathan

Conservation Service.

 

[18:53 - 18:58]

Jenifer

Conservation Services. And the other one was a ACR.

 

[18:58 - 19:01]

Nathan

USDA ARS or Agricultural Research Service.

 

[19:01 - 19:05]

Jenifer

Okay, great. Anything else you'd like to mention that maybe I didn't ask.

 

[19:05- 19:44]

Nathan

Well, I would like to mention that, you know, we are trying to certainly involve industry. You don't have to be, you know, a federal USDA worker or a land grant university scientist to join. We have, certainly encouraged staff from private labs to join. And you know, we're trying to bring them into this project because we know within the US, Arkansas, North Carolina State have large public school testing programs, but, other states don't have the funding that we have.

So most of the soil samples and fertilizer recommendations are coming from private labs. So that's the first thing I would say is that we want, participation from farmers consultants and the broader industry. The second thing I would say is that, we have had industry participation, OCP North America, as a phosphorous manufacturer. And they have actually funded research with scientists across the United States.

And one of the requirements of that funding was that they would provide the results and the soil test information to the first project to go into our database. And that has been really a huge step forward to encourage our scientists to provide up to date, you know, current soil test correlation information.

 

[20:44 - 20:54]

Jenifer

And what is it like for you to see this project come to fruition, to see the website up and running the first of its kind and see it come to fruition?

 

[20:54 - 21:20]

Nathan

it's very exciting. Soil fertility is something I've been passionate about for my career. I’m kind of in the last five, ten years. I don't know what the number is of my career. So it's, great for me to be able to take, you know, the data that I've collected and try to get it in the tool to make sure that, you know, it lives beyond my, my career.
 
 

The other thing that is really neat is the fact that, you know, folks that don't have hair like me or have gray hair and are at the end of their career, allows us the opportunity to mentor, you know, some much younger scientists and that is greatly needed across the U.S. simply because there's fewer scientists today than what there were 20 or 40 years ago.


 So, one of the one of the other problems that this project addresses is that, we are not really good data managers as scientists sometimes. So making sure that all of the data is archived, allows the next generation of scientists to come in. And when they are challenged about a recommendation, instead of saying, you know, I don't know where that data is or what was used to develop our recommendations.

Hopefully we have done a really good job of finding that information, getting it into our archived published database. So that they can know, or at least have information to develop and support their recommendations.

 

[22:34 - 22:38]

Jenifer

I can only imagine what it's like to be part of something so, so big like this.

 

[22:38 - 22:41]

Nathan

I so it's a good end of career capstone.

 

[22:41- 23:01]

Jenifer

Yeah for sure. The cherry on top. And to learn more, use this tool, find more information, it is soil test f--r-s-t dot org, is that website, again that soil test f-r-s-t dot org . Nathan, thank you so much for being here with us.

 

[23:01 - 23:06]

Nathan

Thank you for having me today. It's been great to talk about this project.

 

[23:06 - 23:21]

Jenifer

That was Nathan Slaton, assistant director of the Arkansas Agricultural Experiment Station and professor in the crop, soil and Environmental Science Department. Thanks for joining us for this episode of Food, Farms and Forests. I'm Jenifer Fouch. Don't forget to subscribe.

 

[23:21- 23:42]

Outro

The Arkansas Food, Farms and Forests podcast is produced by the Arkansas Agricultural Experiment Station, the research arm of the University of Arkansas System Division of Agriculture. Visit aaes.uada.edu for more information.