precision planting research farm

Get a digital copy of the 2023 Research Summary Results from the PTI Farm.

Latest News

Pti research farm- in pursuit of maximum roi, june 20, 2023.

Kevin Knisley, QLF Regional Sales Agronomist Illinois

When you talk to a farmer and ask them if they can name other farmers who are pushing the outer limits when it comes to yield, they might name several people. People like Randy Dowdy, David Hula, Kip Cullers and maybe even Dan Luepkes might be some of the farmers they would name.

One person we would add to the list is Jason Webster, Precision Planting Agronomist and director of the Precision Technical Institute or the “PTI Farm” in Pontiac, Illinois.  Jason and his team at PTI are working to push the envelope when it comes to crop yield but with a little different spin on the issue. Asking themselves, how do we maximize our return on investment (ROI)?  PTI started in 2018 with 200 acres along I-55 in Pontiac, Illinois, and has since grown to 400 acres with a shop and meeting space, grain bins, and a pond for collecting water that is recycled back for use in the fields.

PTI is a hands-on research farm where industry people come to learn about some of the latest ideas that the engineers at Precision Planting have come up with that can be used to improve farming practices.  During the summer, the public is invited to come to tour the research farm. PTI allows visitors to come and test drive tractors and planters to see how seed is placed or how liquid fertilizers are applied at different locations in and around the furrow.  They also give visitors the chance to go around to see the 400 acres of different trial plots where different products are being tested to see how they will affect yield.

QLF Agronomy has been involved with the PTI Farm from the beginning. Working with Jason Webster and his team to trial and evaluate Liquid Carbon-Based Fertilizers (L-CBF).  With so much interested in sugar products, and carbon, this relationship was win-win for QLF and PTI.  Today, QLF Agronomy’s Liquid Carbon Based Fertilizer products such as LCBF BOOST and Amino 15 are used at several different times and locations to help maximize ROI.

Throughout the research farm, there are both short-term and long-term trials to see how different cropping or tillage practices will affect yield.  Some of these trials are set to run for as long as 10 years.  The trials cover a variety of different farming practices including strip-till, cover crops, strip cropping, and water efficiency through drip irrigation.

At the end of the year, all the trial plots are harvested and the data is collected, analyzed, and published in a book that is available through your Precision Planting dealer.  For the past two winters, Jason and his team have gone on tour throughout the United States to share how the growing season went and what trials did the best. The winter tour also gives a chance for industry people to ask questions about the trials giving them a chance to learn what went well, what did not work out quite as well as they hoped, and how this trial data can apply to their farms.  After all the data is collected, a Top 10 List of the trial plots that had the highest ROI is put together. Many times, the trial plots that made it into the Top 10 were not necessarily the highest-yielding trial plots that gave the highest ROI.  Most likely you will hear Mr. Webster referring to profitability, and how he would rather have an ROI of $400 per acre versus a corn yield of 400 bushels per acre, stressing the agronomics of taking an ROI no matter how big or small every time.

Related News

Improving native range with qlf’s liquid-carbon based fertilizers, qlf agronomy grower testimonial – troy & cody burnside; vallonia, in, our newsletter, signup for the latest news.

• Search Search Please fill out this field.
• Manage Your Subscription

Q&A: Jason Webster, lead commercial agronomist at Precision Planting

Challenging the status quo in agronomy and taking control of the uncontrollable.

Whether it's relentlessly challenging the agronomic status quo, or trying to wrestle control from the extreme and unruly forces of nature, Jason Webster has a lot on his mind.

Webster is the lead commercial agronomist at Precision Planting, and acts as the key researcher and educator for Precision Planting. Part of his job is managing the Precision Technology Institute (PTI) farm, a 400-acre on-farm research site where his team tests hundreds of different agronomy trials.

During the summer months, Precision Planting invites growers to the farm where Webster leads "Agronomy 101." This class is a chance for Precision Planting to showcase the products and technology it's testing and talk to farmers about their practices and what they can do to improve.

SF: Tell me about your background in agriculture and agronomy.

JW: I grew up on a tractor watching my father and grandfather farm, and I knew it was something that I always wanted to do. I actually had the opportunity to start farming as a junior in high school; that was back in 1988. We've been doing it ever since, so 2022 will be my 35th year of farming, growing mainly corn and soybeans in Livingston and counties in Illinois.

We've been trying to farm our family farming operation — and then work with Precision Planting on the research farm — just trying to continue to challenge the status quo of trying to be better at farming, to increase yields, and most importantly, seeing what we can do to increase farm profitability.

SF: Working on your family farm and with Precision Planting, are there things you try on one farm that you implement on another? What's the overlap between the two?

JW: Pretty much everything is a test farm on our family farm, and it takes time, and it slows us down a little bit, but we're just continuing to try to test different things.

Every farm is just a little bit different. It may be because the soils are different and they respond differently and we're trying to test different things, but every farm is different and has its own set of testing on it. Doesn't matter if it's the Precision Planting PTI farm, or it's our own home farming operation with each individual field that we farm.

SF: Tell me more about your involvement with the PTI Farm and its origin?

JW: When I started with Precision Planting, we knew we wanted to bolster the on-farm research efforts, but it was originally going to be on my own farming operation. We were going to develop all of our research trials there, but we had a kind of a vision of the perfect research farm.

Everything kind of came together where we had this 400-acre piece of land available to us to do testing on. This is where we wanted to develop an area, our research forum, where we could study hundreds of agronomy trials at the same time, showcase Precision Planting products, and technology, and invite growers in to talk about challenges they have on their farm. Then hopefully, with the research we do here at the PTI farm, we can have a solution for them, or try to develop a solution for them. It developed into what we wanted as the perfect research farm, because it also involves an experience for growers.

One of the things I found as I was growing up, watching my grandfather and father farm, was "How in the world do the farmers go out and test different equipment to understand if it's what they really need for their farm?" What I realized was they have to go out and buy the equipment in order to figure out if they like it, and if it's something they really want on their farm. What we wanted to do at the PTI farm was to have all the agronomy trials here to understand what technology is available and how we're using it, but we also wanted to give them the experience to use it themselves.

This farm has what we call a "ride and drive" area. I affectionately call it "the sandbox," because it's an area where we just bring in equipment, give farmers the keys to tractors that have planters behind it, and we say, "Let's go plant corn." So in the middle of July, August, and September, every day here at the PTI farm when growers come visit us, farmers are planting corn so they can understand all the products and the technology on that planter and they can experience it. It's that demonstration, that ride and drive, to really understand if it's something they need on their farm.

SF: When you're planting that much corn on the PTI farm every single day, what happens to the seeds and crops?

JW: It's a challenge because we want the field to be fresh every day for a new set of growers coming in. We work with seed companies to get lower quality seed that don't have the germ normally used, so we have fewer plants coming up per acre. We do some tillage, and we start over again. Most of the time though, with GPS and auto steer on the tractor, we're planting down the same row multiple times. If the crop does germinate and emerge, we basically take it out with the new planting that occurs every single day.

We want a fresh environment every day for these growers to simulate seedbed conditions that they would have on their farm. It's extra management, and we do have to work a little harder to make sure that occurs every day.

SF: It seems like you really enjoy getting directly involved with your work. What is the furthest you ' ve gone out of your way, or maybe the most uncomfortable you ' ve gotten, for the sake of your work?

JW: Oh boy. Well, we're definitely passionate about our work, and the agronomy we're doing. Probably the most uncomfortable I've ever gotten was a project we worked on called multi-genetic planting. As a farmer myself, I saw how soil variability on my own farm affected decisions like seed or genetics that I could plant.

What would happen is as I'm planting my fields, I'm saying: "OK, in that planter, the seed I've loaded in it, is it the most appropriate genetics or seed for the acre that I'm planting right now?"

A lot of times the answer was no. [He laughs.] As soil variability increased in a given field, the answer was no a large part of the time. We had a mission to really study the feasibility or the ability to change corn, soybean hybrids, or varieties on the fly, based on the productivity of the soils on the farm. This technology was not available. We went to every planter company and said, "Hey, we'd like a planter to do this." And they said, "Well, good luck. There's nothing like this available."

We had to study the concept of it in the field to see if it could even work. This took time, and it was expensive. This was an expense that I had to take on my own home farm to really play around with to see if it was something growers could actually implement on their farm to increase yields and make money, and then ultimately become available in the marketplace.

SF: The COVID pandemic has changed a lot in the world, directly and indirectly. Have you noticed any trends affecting agronomy?

JW: I think COVID mainly affected the field of agronomy in supply issues and price increases of equipment, parts, fertilizer, and other crop inputs. It will be interesting to see how long it takes to ramp supply back up to maybe offset some of these challenges and normalize again.

SF: How have you and other farmers responded to these changes?

JW: It's definitely forced us to tighten the belt and understand what we actually need. We're seeing the highest prices we've ever seen with fertilizer. Now it's understanding what type of fertility we have as a baseline in every single field we farm. How do we become efficient so we can offset these high prices? That's going to affect the rate of fertilizer we're applying and the placement of it to be very efficient.

This is challenging the status quo, this is where it gets uncomfortable for growers, because they've never had to work this way. Now higher prices are affecting farm profitability. Guys are having to take a look at this and say, "OK, what do I need to do to save money, but not lose yield and increase profits?" It's really interesting to watch, and we have this discussion every day at the farm.

SF: If there ' s one thing I know about farmers, it's that they ' re resilient. It will be interesting to see how this all plays out in the next few years, but it sounds like most of them will be able to handle it.

JW: Yeah, I think so. And hopefully things will normalize again. But you're right. I think farmers are resilient and it forces them to change. I know thinking about change is uncomfortable for a lot of growers, but change can be a good thing and actually can make you be a better farmer.

SF: Speaking of change, another force affecting the agriculture industry is climate change. Can you tell me how that ' s affected your work now and what you see the next few years looking like for your field?

JW: We know as farmers we can't control the weather, and I quickly realized that my first year farming in 1988, one of the largest droughts in history. I saw firsthand how I have very little control over the weather and I just can't do anything about it. We consider climate change to be part of a risk to a grower or a farmer. At the PTI farm, what we do is we study how to mitigate risk of changing weather patterns. How do we limit that risk, how do we limit yield reduction as a result and not let productivity or profitability suffer?

What I mean by this is there are extensive ways of educating growers on fertility management, primarily split applications of nutrients, and we do this to limit nutrient loss and runoff. With climate change, we see events of the extremes. It's either way too much rain at one given time, or it's extreme drought. It's just very extreme from one end to the other. If a grower's putting all this nitrogen on in one application and we get a large rainfall, we're at risk to lose that. Environmentally, that's not a great thing either. We spend a lot of time talking with growers about how to manage risk when applying nutrients, such as nitrogen, phosphorus, or potassium.

As growers, and as a farmer myself, we need to be ready for it and have the flexibility of managing these variables. We work hard at the PTI farm to show ways to manage soil drainage. We show the benefits of tile drainage — what it costs, the return on investment — so when you get those large drain events, we have a system in place that can get rid of the excess water, introduce oxygen back into the soil, and we don't slow that crop down one single bit. We can control this. We can take control of the weather by having this drainage ability.

SF: What do you see as the next big thing in agronomy?

JW: We'll continue to measure. If we don't measure, we have no idea where we are, and if we need to be better or not. I think seeing what is happening in a grower's field, and managing it to the inch with this measurement, is going to be the ultimate technology going forward.

We need technology that can continue to have eyes of vision so we can see more in the field. We're going to see pests or problems that growers face each and every year. I've said for a long time that crop scouting is probably the No. 1 problem we have in the ag industry. No one wants to do it, or nobody's good enough at doing it to really understand all of the problems in a field — to measure, to react, and take control.

I think intelligence in the form of technology is going to be the next big thing in agronomy. It's one of the things I think about every single day as we're scouting fields and trying to figure out, "What can we give to this crop to make it respond to us, to get more yield, to get more bushels?" It's almost like listening to the heartbeat of a plant. When we go to the hospital, they can hook us up to a machine and figure out what's wrong. How do we do that to a crop?

I don't know if it's gonna be the next big thing in agronomy, but I know it's the thing I need with agronomy. We've mentioned it numerous times here in this conversation: taking control. That's the thing we want, but we have to have good information. We have got to measure it, know where we're at on the yardstick, and then we can react.

SF: You made the distinction of what "I need with agronomy." Is there anything you're doing that you wish that you saw other agronomists doing?

JW: I think more data and more research. Part of the reason we test things on the PTI farm is because I don't have data. I can't go out and get the data to understand if the concept of the technology is a good concept. So we do it here. We get firsthand data, firsthand experience, firsthand knowledge with it because we don't have access to it anywhere else. So I wish there were more data out there. Some of it we struggle on and we just attack it. We go after it ourselves and we go get it.

SF: What about your job keeps you awake at night?

JW: Probably the biggest thing is just staying new, fresh, and unique when it comes to the PTI farm. We get growers coming in from all over the country, all over the world to see the things that we're working on. One of the things that I just ultimately have to have at this farm are new concepts. We've got to be thinking outside the box at times, and that's challenging. What is that new idea or new concept? What turns the light bulb on in a farmer's brain, thinking about his operation and how that can be better?

I don't want a grower to say "You know what? I went to the PTI farm the last year or two. I don't have to go again because it's the same thing." I have got to have new, fresh, unique ideas at this farm and just continue to keep thinking outside the box.

SF: What gets you up in the morning? What drives you every single day?

JW: It's fun to wake up in the morning because we're going to go back to a job we just simply have fun with. You know what they say, if you love your job and you're having fun doing it, it's not really a job. I think we live that every day. We've been given the opportunity to farm and we love doing it, and we have the extended opportunity to work with growers day in and day out. Most days we don't even know what day of the week it is, because it doesn't matter. We're doing the same thing. We can't wait to get up and do it all over again.

Receive weekly videos from Precision Planting that will help you: » Get the trial results you want. » Find the agronomy explanations you need. » Learn insights that will help set you up for success.

What People Are Saying

Evan (with Precision Agri Services, Inc.) has been great to work with. Everything he told me he followed through on in a very timely response. Their product knowledge and support have been great.

Slight hills were drawing it down at C3 at around 10.0 mph going down to as low as 9.0. After the tune with AgroEcoPower we were in D1 at 12.2 mph and no draw down whatsoever.

Within thirty seconds I knew you knew what you were doing. I have no patience and I know if I call, I will get an answer. Product knowledge and service is everything.

Ashville, Ohio

Evan (with Precision Agri Services, Inc.) did a great job presenting me with options on a steering system I was not satisfied with. He helped me use Ag Leader technology I Already had to Convert it to steer my 8520 John Deere. Tech support is top-notch with him.

We had our 8320 ECU rewritten and are so happy we did! Tanner took the tractor from 260hp up to 305hp and it is a world of difference. We are pulling our digger faster at less rpm and can't wait to see what it will do on our vertical till!

Scott, Ohio

Just put it (Ag Leader InCommand 1200 with ISO serial bridge) to the test. Everything works really well. Each boom sections on and off, in and out of multiple different paint zones. Pretty sweet deal!

Hillsboro, Ohio

Tuned John Deere 8310R with Stock HP: 311hp Tuned: 360hp and Stock Torque: 1071lb/ft. Tuned: 1244lb/ft with AgroEcoPower.

This little workhorse just gained a few more horses [with AgroEcoPower]. I use this utility tractor for just about everything now the tractor has some more added power to complete my tasks. Stock HP: 36hpTuned 48hp with AgroEcoPower.

Belpre, Ohio

We are farmers, too.

We’ve been where you are, and we know how important it is to be able to count on good, reliable advice. Your success is our success—which is why we treat your farm like it’s our own.

PTI features agronomics in action

Showcasing in-field research.

Visitors to Precision Planting’s Summer Sessions at the Precision Technology Institute check freshly-cut furrows during a planter optimization demonstration. The session focused on all things planters, from setup to maintenance to performance evaluation. (AgriNews photo/Tom C. Doran)

PONTIAC, Ill. — Planting technology in action is on display for U.S. and international visitors to the Precision Technology Institute throughout the summer.

Precision Planting’s Summer Sessions began July 24 to showcase in-field agronomic research, planting and application equipment operating in the field.

When AgriNews visited on July 25, 11 states and two countries were represented, including a group from Australia.

“We open the doors up for this facility throughout July, August and September. This is our third week of having agronomy tours on this farm. Every day is a little different. We have different groups in,” said Jason Webster, Precision Planting commercial agronomist and PTI director.

“This is our second day of our first public week where our Precision Planting premier dealers invite their customers in.”

The 400-acre research farm on the southwest edge of Pontiac opened six years ago and has 150 to 160 research trials this growing season. Sharing results of those trials and seeing in-field practices is a primary focus of PTI.

Demonstrations during the summer sessions included planter optimization and furrow creation with visitors able to get their fingernails dirty checking different freshly-created furrows.

Chris Segelhurst, Precision Planting region manager in northern Wisconsin and southeastern Minnesota, was among several region managers across North America conducting the planter presentation.

“We’re going through not only furrow creation, but planter optimization as a whole, setting it up tip to tail, working through planter maintenance and then how to evaluate the planter as you set it and get it to perform properly in the field,” Segelhurst said.

“After that, we move into evaluating the actual stand and furrow creation that we get on the backside and then evaluating baby corn plants, not only placing them in their growth stage, but evaluating how we did on emergence and conditions that we set for that plant based on that planter pass.”

Highlighting the demonstration was all of the Precision Planting products and planter maintenance.

“We’re looking at things including our newer pieces like the DuraWear parallel arm, looking at our new gauge wheel arm that we have and then downforce control is a big one on furrow creation,” Segelhurst said.

“We’re controlling how much force we’re using to create and build our furrow so that we can get a seed to the bottom of the trench where we want it to be before it collapses back in.

“We also look at adjusting not only our row cleaners up front with Reveal frame mounted row cleaners, looking at the amount of residue we’re cleaning and how we’re building that runway for our furrow to be created in, but also looking at our closing system with FurrowForce.”

Tom C. Doran

Field Editor

• Visit the University of Nebraska–Lincoln
• Apply to the University of Nebraska–Lincoln
• Give to the University of Nebraska–Lincoln

Search Form

Planting with precision.

Advancements in planting equipment and data acquisition systems have driven significant improvements in how precisely farmers can plant their acres. Paul Harms, Product Support Manager at Precision Planting, joins us for this episode to talk about Precision Planting's technology offerings. Topics covered in this episode include data acquisition and utility, calibrating sensors mounted on planters, different control paradigms, and the value proposition of planting technology for farmers. As Paul mentions in the interview, the Precision Planting's mission is to make their partners "smarter every season" by providing actionable information that gives them greater insight into and control of their planting operations and spatial variability. If there's one episode in the planting series not to miss, it's this one. Buckle up for a great conversation!

Opinions expressed on FarmBits are solely those of the guest(s) or host(s) and not the University of Nebraska-Lincoln.

On this episode

Precision Planting Information:

Website: https://www.precisionplanting.com/

Podcast: https://go.unl.edu/smartereveryseason

Twitter: https://twitter.com/precisionplant

Facebook: https://www.facebook.com/precisionplanting

YouTube: https://www.youtube.com/channel/UCEpmx3aav2gO7Ig9lE7dDww

Paul Harms Information:

LinkedIn: https://www.linkedin.com/in/paul-harms-b08a6023/

FarmBits Team Contact Info:

E-Mail: [email protected]

Twitter: https://twitter.com/NEDigitalAg

Samantha's Twitter: https://twitter.com/SamanthaTeten

Jackson's Twitter: https://twitter.com/jstansell87

Opinions expressed by the hosts and guests on this podcast are solely their own, and do not reflect the views of Nebraska Extension or the University of Nebraska - Lincoln.

Jackson: Welcome to the FarmBits podcast a product of Nebraska Extension Digital Agriculture. I'm Jackson Stansell Samantha: And I'm Samantha Teten. And we come to you each week to discuss the trends, the realities and the value of digital agriculture. Jackson: Through interviews and panels with experts, producers and innovators from all sectors of digital technology we hope that you step away from each episode with new practical knowledge of digital agriculture technology. Samantha: Welcome back to the FarmBits podcast. We are continuing to roll through our planting technology series and are very excited about this episode. Jackson: Planting equipment continues to advance significantly in the modern ag tech landscape. This episode features a company at the forefront of planting technology innovation. Samantha: Paul Harms, product support manager at Precision Planting, joins this episode of the FarmBits podcast to discuss Precision Planting's mission, product platform and vision for future innovation. Jackson: We dive into many topics from data to sensors to equipment and how Precision Planting is doing exactly what their name suggests, enabling precise planting operations, so here's our interview with Paul Harms. Paul: I am super excited to be here, I appreciate you guys reaching out and getting the invite in. I'm well my name's Paul Harms in case you haven't seen that or read that yet, but I started with precision planting about 13 years ago, and I work in the product support department. So, I grew up on a farm. We had 2,500 acres of row crop and then 300 head sow operation, which we did feeder and farrow to finish so came from the farm background, spent some time in the seed industry kind of got in the door here on a whim just on a flyer and have loved the role, the task, the people, the culture and the mission. So, that's that's been a blast that I just can't walk away from. Jackson: Awesome and where are you from originally? Paul: I grew up in central Illinois right here, about an hour to north of here. (awesome) Yeah, I'm located right at the home facility here in Tremont, Illinois. Samantha: Good deal, so since you brought up the mission of Precision Planting, can you talk a little bit about the company and what kind of role they are fulfilling within the industry? Paul: Absolutely, I would say our mission is very similar to the title of our podcast- the Smarter Every Season podcast. It's our goal is to help growers improve year over year and we feel it's our role to try and provide education opportunities and solutions to problems that they're seeing you know we do that through our precision technology institute, our winter conferences, our field demonstrations. We provide our solutions in a retrofit fashion and our factory installed through our partnerships there and it's all about taking advantage of every time we go to put a crop in, trying to put the best crop in and make our operations as secure as possible. Jackson: That's really cool stuff, and I think the retrofit aspect of things is a really important asset for farmers and from an engineering standpoint, I just think it's a really important way to design things. Can you tell us a little bit about some of the great lineup of technologies that y'all have including some of those retrofit pieces of equipment that that you offer to people? Paul: Yeah, the retrofit is actually our bread and butter so we approach problems that we find in the industry first and foremost towards that that retrofit solution. We want to make whatever problems we can solve with a product or a design. We want to make sure that that's applicable to as many people as possible and there's a much larger portion of the industry that has an existing implement in their shed then there is new going out every year, so we don't want to just make it tied to that. It's important for us to be able to continue to add value to that existing implement, you know our start with that was the keaton seed firmer which was just an attachment onto a rail unit to help firm the seed down in the soil and that's our focus there is finding those solutions. Jackson: Awesome so, it's really interesting that you know kind of your you know you're talking about the seed firmer but those seed firmers have kind of morphed themselves or not necessarily morph themselves but you've expanded from that point to doing a whole lot of more high-tech things than just firming seed into the ground. I mean you've got different you know you have your smart firmers out there, flow sense furrow force. I mean we could go on and on, I mean can you tell us a little bit more about some of the technological advancements that have happened from those regular seed firmers? Paul: Yeah, so a lot of that does track along the same path where when we started we were focused just about helping that seed with emergence and ensuring it gets good solid seed-soil contact and that was adding a firmer onto the back of the rail unit made sure that the seed was placed fully into seed contact and then that has grown into well I made sure all the seeds were starting and emerging correctly. Why do I still have an erratic stand? Okay, so then we start looking at the meter, what's the next problem and a lot of times it's just continuing to advance and look into what are those next problems and then understanding how they occur, finding a good solution that provides value in the operation and then putting that product out. So, you know as we worked through all those a great anecdote is one of those stories where one of the first engineers took his laptop and he was doing some testing, looking at meters. He was using the existing sensors that were on the planter and for us sensors and information drive a lot of where you can improve because until you can measure something it's hard to improve on it or advance that against that problem. So, he would take his laptop out, plug into the planter and all of a sudden the operator could see so much more than what the existing technology in the cab offered him and the engineer would get what he needed and x laptop up and go back and do some design work. Well, what the driving piece came out of that was no don't go away with that, I can see more. I'm not adding any new sensor. I'm doing more with the data in real time and I can make better decisions with that in the cab seat while I still have time to impact my yields for this year and that was one of those light bulb moments for ourselves while we were designing towards one thing and we still continued with that, but it also opened an opportunity of knowledge is was a big driver, being able to make the right decisions. Sam: That's awesome, yeah so thinking about that collecting data but more importantly using that data- can you talk about the smart firmware which is that reflectance-based sensor for people who may not be familiar with that. But, what are some challenges that are associated with this technology particularly with making sure that data is accurate but how does it adjust with different conditions and some effects? Paul: Okay how far in the weeds do you want to get with the, so the smart firmware is a great example where we have gone from a product that solved an immediate solution or an immediate problem, it was a quick solution to a problem of seed to soil contact and uniform emergence. As we progressed along, we got to the point where we wanted that or we had the desire towards you know- I just want a window into the furrow to what my seeds are seeing. If I knew that I could make a better decision and this is from us as operators and and time in the seat wanting to do better with this season's crop. So, we said okay let's let's find out what instruments and things we can put on that to give us that window in there and the smart firmware is the tool that we came out with. What it's doing is it is a reflectance-based sensor, so we have some lights in there and they're shining against the soil. The major hurdle is when you get that reflectance back you have to correlate it to some known okay what does this data mean right? Whe way you figure that out from all the distant different datas is a bunch of backbreaking work in validating it and testing it in a known condition against every possible iteration, so we went from this great idea of I want a window into the soil. I want visibility into the furrow to a warehouse portion of the warehouse that's full of five gallon buckets of soil from all around the world as many places we could and then not not just getting the samples but then testing them and going what is it at zero percent moisture five ten fifteen twenty 30 40. What does it look like, what are the reflectance values and smart firmer is really beautiful in the way that it doesn't just tell me how much moisture is in the soil because that would be potentially a misinformation, and I'll go into why in just a bit. But, it actually is reporting to the user how much moisture a seed can pull out of that soil over the next three days because that's the inhibition we're period that's when the seed is going to start suck that moisture and we need that to all happen uniformly and enough to initiate the germination process. So, we didn't just look at the soil and say okay at this amount of reflectance for this type of soil we're going to get or this is how much moisture is in the soil. We actually then took it and said with this soil at this amount of moisture, if nothing changes will the seed have enough to begin germination in three days and the example and the reason back for that is I can have a sandy soil and it can have 30 moisture in it right think of it like a wall tank, right my sand won't hold as much as a clay. I have a smaller gas tank but on a clay, a clay won't give me every bit of water that's in it like a sand will. Sand will give you every ounce of gas in the tank a clay holds on to half of it same 30 moisture on both of them is a different amount on how much my seed can get, so when we put a number on our monitor in this in the cab we're constantly driving towards the number that affects seed germination. So, we want to stay over a 30%, we want enough moisture to be in this soil type that over the next three days that seed will have enough be able to pull enough moisture out of the soil to gain 30 percent of its weight by volume. Jackson: Sure, and so is that moisture aspect than kind of the primary value driver for smart firmers right now at least on the real-time side and then the organic matter is a little bit more of kind of a post-processing side, or I guess how does that work because it does both right? Paul: Yeah, so there are six layers of data that come out of smart firmer. When we launched and announced smart firmer, we were super excited about hey and we can do organic matter. We initially went into it with the moisture focus and then halfway through that we're like well we can easily correlate this to organic matter. We're getting that number and our data. We can just start to present that as well and it was kind of that wow, we're excited. We can also include that but that took a lot of the notoriety but there of those six, of those six data layers that we're getting three are extremely valuable to the operating in the cab year in year out, acre by acre. Three of them are great for informing and influencing long-term decisions. So, the six that we have are furrow moisture, so that's how much moisture is in there my furrow, uniformity and my clean residue or my firm residue. What amount of trash is in my furrow? The last ones are temperature, organic matter and CEC. So, those first three are the ones that drive best practices and can save this crop from having a skip or a large gap as I wait for seeds to get enough moisture to germinate. So, those are the three that really help an operator do a better job this year. Sam: Can you elaborate a little bit more on that value proposition when you say it can help make management decisions? So if let's say a farmer says or they get that message that says oh it's not enough moisture to last those three days what can they do about that how is it actually changing their management does that make sense? Paul: Yeah, yeah so and this is a great question that we will commonly have with growers and they'll ask us at farm shows and things so what's the value prep on that and or how do I make a change or how do I utilize that information and we'll commonly ask or at least I'll ask the question back. So, what depth do you plan your seed at and varying number of answers will come back and it'll depend on crop and it'll depend on where they're at in the world. When it comes down to it, what does the seed need to begin germination, temperature, water a little bit of air right. So, we can really affect mostly moisture. So, if we have a measurement of what's in the soil, where the seed is the one of those three that we can target we go after. So, if it's dry and we don't have moisture present, we'll stop, get out, go back around the planter set your planter just target a little deeper until you do find moisture or even better yet maybe you can't find moisture and it's this seed and this field is better saving my yield with that seed in the back. Yeah, no matter how bad it is and sometimes this isn't an equation. If I have a fully irrigated field, and I'm going to water the crop in, great but that can also be a big value out indicator of hey there was enough soil or there was enough moisture in that soil, I don't have to water it in. I can save myself one cycle around on that and that can be a huge impact on how much water you use in a year and just an additional pass cost, so those are some easy simple ways that inform that operation and gives that operator, the guy in the seat the right information at the right time. So, then some of those we can continue to automate and the same way that our smart our seed firmer, our standard poly heat and seed firmer that has grown into a smart firmer. We added a sensor and gave it some more value to us and some more input. Now, we can take smart firmer. Now that we can measure that moisture on the fly, well the first thing you would react to on chasing much moisture would be depth, so now we have a smart depth system that solves a couple mechanical problems and gives us the ability to respond in real time to that moisture value. Sam: So, all this data is really valuable if it is accurate right you always talked about your validation process, you guys are lots of soil types lots of different moistures but is there a way for a producer to potentially calibrate this information on their own field so potentially taking moisture samples, organic matter samples or anything like that to potentially better inform these data layers? Paul: Yeah, we're kind of riding the smart firmer horse on this one. So, that example but smart firmer is a great example for this reason- its primary goal in the field is not to create the absolute value of organic matter or any of these values, our full target is to create the spatial variability right. So, I can then understand how this portion of my field behaves differently than another portion of my field, and I can always correct that legend later. So, if I see a variability from one to three on a field and that really needs to be from two to four I can go correct that after the fact. What I'm most focused on is that I'm able to control real time to the variations in the field as it goes from one to three back and forth across the field. So, sure all those data points so specifically on Smart Firmer you can take your smart former data and and send it up we have a server that has a program built on it, and you put in all of your soil samples and if they have GPS data points it will correct that map and legend to a correct value to that absolute value that a soil sampling test like site would would give you. Jackson: Yeah, I think that's extremely valuable. I mean just thinking about dealing with relatives instead of dealing in absolutes right like that's really what we're trying to get to here is like if you can if you know I guess and this is how I would interpret it- if you know that you're planting at the right depth for a certain moisture right and you know that all of a sudden your soil has gotten drier well you're probably gonna have to you know increase your depth in order to get there. It doesn't necessarily matter exactly what that moisture is, but if you know that relatively speaking this part of the field is drier than another part of the field at certain depth you still have enough to kind of make that decision is that am I interpreting that the right way Paul? Paul: Yeah, so going into smart depth smart up for us has a few different ways we can control it. Hey we can just put in a value and say, I want this thing to be planting at two inches. It always plants at two inches, straight forward very simple. We can also put it on a moisture basis, which says here's my preferred depth. If I fall below this certain amount of moisture, go deeper if I get too wet come shallower right and you can figure it so you know it stays within a window or range that's right for your acres, for your locale and then we can control within that to make sure that we're giving the seed the best opportunity because you don't want to go too deep if you don't have to because then you're just making it harder for that seed to get through up to the surface and actually see the sunlight so we want to keep that as short as possible to reduce that resistance. The last way we can control it is off of a prescription, so if I know I have an extremely distinct soil type difference in my field and I normally would love to plant the left or the south half of my acres on two inches and the north half at two and a half, I can do that. I draw a prescription and then my default depth goes to that, and I can still control the moisture. I'm just affecting my default depth and allowing the system to do what's correct and all that's changeable or modifiable on the fly, which is really interesting the engineers were actually able to make it so that that prescription and the controls could be read by the system and controlled to we can edit, make live edits make the update and it's a faultless process, so that it's a read and update at the same time it's pretty impressive.

Samantha: So, thinking about how planting conditions are not always optimal, as we would like them to be can you talk a little bit about maybe some calibration challenges or with any of these technologies- how are you making planting more stable across multiple soil types, maybe different moisture conditions what kind of technologies are making that where you're consistently planting how you want to plant at different conditions? Paul: We want to be able to know when situations change, when the environment demands something different out of the implement and be able to respond to that. So, commonly if it's an automated control system, if the soil has just gotten a little tighter well maybe the system can just auto it has a target value and it will push down until it hits that target, so it kind of overcomes some of that need to calibrate. Probably the biggest part that's still an unknown and that won't go away is the the ground truth, the value of ground truthing or data validation is always going to be there. And we can automate a control to any target that the operator wants us to right within our control range. We can do all the automation, we don't know that the control target is 100% perfect. That's left to the grower, we know we need the grower to say this is where I should be doing for this field, so some of that is still you know down on your hands and knees you say a prayer and then and evaluate what the equipment is doing to the ground and making sure that it's accurate for what you're doing. Jackson: Sure so, when you think about a product kind of like active downforce, the delta four systems that you all have- I guess that's kind of one of those examples that comes to my mind when I think about you know the farmer still needs to kind of set the right down pressure, but I'm also thinking there's got to be some there has to be some truth out there right of like this is too much down pressure given these moisture conditions and or you know soil type right and then this will lead to compaction. So, you know I guess how are you all going about you know implementing this delta force and how is it bringing value and potentially helping farmers to make better decisions as far as how much downforce they're applying out there in the field? Paul: That's a multi-headed beast. That's a good topic to unpack because there's a lot to that one so downforce I've never given a direct answer of what's the correct answer you know what's the correct downforce amount because even in the field that's right next door that we've seen and I've been on a dozen years in a row, I don't know its conditions its moisture, how the winter affected the soil structure it's gonna handle different this year than probably it has in any one of the previous ten yeah maybe some similarities but it's going to be unique, and I need to be able to confirm that I'm setting the right target the system will go and I've got some presets I can affect how I do towards that and simplify my life in setting that target, but I do need to be able to make the correct decision or make the correct target point that the system controls to and that would be that's going to be present you know pretty straightforward across all of the products or or any of the actions we do across the field. We do need to have that ground truth to know that we're doing the right thing with the equipment, with downforce we don't technically target what the right amount of push down is. We know we need to push the row unit down. We'll continue to do that until we get the correct amount measured on our depth stop so we just keep pushing down on the rail unit until we've hit our target of force against the gauge wheels and the example you go in your garden if you guys do any gardening at home yeah okay so in your garden your garden is probably like like my wife helps me make ours perfect, super fluffy nice no no problems weeds or anything and so when I go to plant that it's make a little hole put the seed in cover it up and then what do you do. So, there's a certain amount of that where you're resetting the the soil structure and the density of the soil above the seed you want it firm enough that it holds air and water correctly but you don't want it so firm that the seed can't get that generation yeah absolutely yep so the gauge wheels on a row unit on a planter row unit are for a good portion of that you're firming action they have an impact on what your soil structure is around that your closing system is like the wax job after a good car wash if you don't wash and shammy and wax it, the wax and the shammy can make the make a wash look really bad that finishing touch. So, all of that without resetting. We want to make sure that our push down is as it should be but that takes the operator to choose that so we'll push down as hard as you need anything up to 650 pounds to push down, or we will remove weight for the rail unit as much as 450 pounds and we can make those changes extremely, rapidly probably more rapidly than should be needed in the soil, but the focus is just having the ability to hit that target very accurately. Each row behaving independently and hitting its own target because as this row is going through a tire track and the row next to it is not they're going to have different demands on what's needed to push that row unit down to get the right measurement on my gauge wheels that says hey yes, I've met my depth and I'm doing the right thing to the firm the soil around the seed. Jackson: If you think about some of these other measurements that are going on out there as well, you know we're thinking about how much you know down pressure is being applied. We've already talked about the moisture you know kind of ad nauseam but you know I'm sure there are other you know measurements out there, temperature whatnot if any decisions are being made on these from the cab how important is it to be able to filter that noise and you know how much of a challenge is that for real-time control having this really noisy system out there in the field? Paul: So, as soon as we were approaching and starting the product design process for a high-speed solution- we knew that every one of our products would then get applied in a high-speed environment and needed to be able to maintain performance and accuracy across there, so like we designed furrow force our closing system high speed was a prerequisite before that could be a viable solution to solving closing as a problem, so all of that that you know as soon as we decided yes planters can and should be able to cover more acres or or cover acres in a more timely fashion yeah all of the pre-work had to be done on the other components, Jackson: Carrying the data. I'm sure but as the noise I mean the noise has to be something that's pretty significant to deal with I'm sure you know on the monitor side and kind of the engineering side they they've obviously done a whole lot of work with being able to filter any bad data or you know any of that noise from vibrations or other things out? Paul: Yeah and again it comes back to the the the engineers that get the boots dirty in spring riding with it and understand that I don't need to just bring forward the data, I need to bring forward the piece of information that drives the right behavior in the cab by the operator at that at the right time so again smart firmer is a great example, I don't want to just bring them how much moisture is in soil. I want to tell them for this soil how much moisture can my seed get out of it, right that's actionable. Samantha: Yeah, I think the one product that we haven't really touched on a lot yet is the furrow force can you maybe talk about that a little bit and how is it adjusting in real time to make sure that seed to soil contact is there? Paul: Okay, what we're doing on the closing side is more of tackling the two biggest problems, what the row unit did to get the seed there to begin with. First it had to carve the soil open, so I need to first remove that and then because I carved it open I messed with the soil structure. I need to reset that, so our closing system the furrow force closing system is targeting those two actions first. I need to destroy or undo what my real unit did to create a furrow and then I need to reset the soil density above the seeds. So, it's not an air packet or it's not a dry space, can't hold moisture. And then two I don't make it so firm or tight that the seed can't sprout through there. So, that's what furrow force is doing. What we do is we have three different versions of our control aspects on there, so one is a manual only you would just manually fill a pneumatic bag to your desired amount of force pushing down and and run with it. The second way would be you would have some sensors on there that would tell you am I holding my closing system down hard enough again? This is a control or a target set point that you're going to be choosing which of the the right set point is but we continue to push down on the closing system as a whole until we meet a measured weight on that that stitching wheel on the back. So, that's how much I'm firming the soil back together with we'll continue to push down until we measure that. We've attained that amount of force, you set that target rate and we chase it with that middle layer there. We put the sensors on there, we give you what you're measuring but you have to manually adjust it to hit that target the last one is we put an automated control piece on each row and you tell it a target and it maintains it. So, as you go into softer soils it lets air out makes it walk across the soil a little lighter. In harder soils we continue to push down until we measure that right amount. I can also do that to solve agronomic problems as well. Maybe I'm in a an overly tilled environment. I got wet, I had to till it to get moisture out now I've got a little bit of clods. So, I hit it again and now I've got overly fluffy soils. So, I can actually add extra pressure on my closing system to maybe firm that soil back up and retain a little bit more moisture than would normally be available. So, I can use it as a tool to help me out of bad situations as well. Jackson: That's really cool, and I think just thinking about the value proposition for all this you know we think about how much farmers would have to get out for the operator the you know of the planting system to get out and go and reset all these things without kind of the automated control right it's really going to slow down your planting operation, which we all know has to be timely. So, I mean is that is that the biggest value proposition for some of these tools is that you know really you don't ever have to stop you can make those adjustments on the fly is that that what a lot of people are seeing out there as a value? Paul: So, there's got to be an agronomic value to it. Stand alone we have to be solving a problem and that goes back to our entire mission of we like to make sure that what we're doing is solving a problem right. Farmers are an amazingly industrial people and if there's a problem that that they know about they can solve it and they can do a better job they want they have that innate desire we have that inner desire to do better and so that's why a lot of our mission is on focusing on encouraging that education and helping people understand where problems come from so they can solve it. The timing and the operation and what the impacts are there. Our first solution has to be we actually solve an agronomic problem. The speed or ease that we can do to maintain the optimal performance that's an added benefit. So, I don't have to choose between beating the rain, managing the other activities and operations that are going on on my farm because most often the operator in the cab is not the the second or third person on the operation. They're usually the primary person on the operation who has to direct the entire choir of activities and make sure that no horns get out of tune and a lot of times what will happen is there's not a loss of desire to hit that perfect or to hit the optimal performance. It's a priority choice of I can either continue to strive for performance or I can keep that problem that's another aspect of my operation from hitting a dead end or stopping completely and in the larger sense those priority decisions sometimes have to be made but if we can make them the tools that allows them to make those changes or create a set point that they're confident in and let the system maintain that performance while they can then do their operation management that's a a great side benefit, but the product itself needs to stand on its own its value. Samantha: So yeah, thinking about this value I'm gonna ask kind of a two-part question. Can you maybe first tell us what is current adoption with some of these technologies is these things with planting a huge priority to producers right now and then the second part is what are producers most excited about where do you guys think this adoption is going? Paul: I don't have hard numbers on what current adoption is so I as an anecdotal answer when I started 10 years ago 13 years ago whatever a lot of the conversations I would have say downforce is a great example. We're explaining how a miss setup or a miscalibrated system would give you an agronomic cost. It was very heavy on the education of where a problem existed and how to solve that you know that was truly a cost to their business then once we when we understood where that fault could come it became more of a how do I select the right tool, how do I operate the tool the best what's the right tools for my operation and how do I use them? Simple part. My conversations in the last 10 years have shifted as I talk to growers across the nation across the world those conversations have shifted from what is it to which ones are the right tools and how do I employ them best. So, as a whole our our industry has gotten more aware of problems, are still looking for the right ways to identify them timely and you know as soon as they know they have them they know the solutions are out there they just need a little help in choosing making sure they get the right one and it's employed correctly. And then come back to your second half of your question, what's the most exciting one again I'm sorry I have to knuckle out on this one as well because if you the most exciting thing to any one farmer is going to be the problem that's costing them the most, solving that problem means the most to them for some that may be a low sidewall tire on the tractor or the combine right if you can solve that problem that's the greatest thing. What we want to do is work with our regional sales managers who are working with our dealers and our resellers who have that one-on-one relationship with our customers because they then are that trusted advisor that knows hey you know Bob, your biggest you know problem right now is not the planting process it's it's the people in your operation all going in a bunch of different directions. Is there a tool I can help you with, sometimes that's the answer it's education, it's communication. So, we want to try and make sure that we're focusing first on solving that farmer's problem. Most often that comes with visibility of the problem, shine a flashlight on what's occurring so we know what to solve. We get to focus very narrowly on the agronomic and the control and the operation portion of different implements and up and activities across the field. That's where our bread and butter is, but that's that's coming from that heart of we want to identify what's costing those farmers you know yield grain and solve that for them because that's what they want. Samantha: So, where can people go to learn more about what Precision Planting is offering uh maybe talk about where they can go to learn more information but also maybe your podcast can talk about that a little bit. Paul: Absolutely thank you for the queue up on that first and foremost and probably the best recommendation is there's a local regional regionally placed next next to our listeners there's a precision planting dealer there's got to be one close to you, we're we're pretty widespread that's going to give the best experience right they're going to know your neck at the woods, they're going to know your challenges unique from someone else. We are never pushing anyone away but we do understand that the best is our team of dealers that are out there because every one of them I believe does have the customer's best interest at heart and they're here because they have the same mission as us and that's our growers success. So, we want to make sure that they're learning and growing with us, and that's where I'd start. Outside of that we do have a lot of outreach things, so we'll partner with our dealers and do field demonstrations and local farm shows of that nature sales experiences we have a precision technology institute in Pontiac, Illinois and that's very close to us where we have a little playground. We have equipment running you can come in climb up in the cab operate it yourself you don't want to test drive on it's not your you know Ford f-150 test drive. It's the half million dollars of equipment right at 13 miles an hour but yeah it's fun those are some ways. We do have a winter conference which is a our annual event where we get to put the engineers on the stage and let them share what they've learned over the last year and make them a little uncomfortable. You have us on the podcast which is Smarter Every Season and that's available Stitcher, Apple podcasts, anywhere you normally see. Jackson: Very cool awesome, so to to kind of wrap up what's been a really cool conversation I've learned a lot from- what's one piece of advice that you would offer to our listeners who are wanting to maybe solve that problem that they have in their operation and have been wanting to solve for a while or just be more precise in their planting overall, what's one thing you can make it three or four however long you want but if you can distill it to one I'll be impressed. Paul: Information, so whether that's adding a monitor adding a sensor probably best yet starting a relationship with a trusted advisor who can help you along that process, getting and learning more because the more we learn and the more we can help each other grow on or learn or overcome problems the better and and that may that may not have an individual economic value that's definitely going to have a and a solid intrinsic value to their operation. So, I'd say first and foremost it's you know it's the gi joe knowing is half the battle there you go I think I can end on a gi joe reference now absolutely never thought you'd do that one before. Jackson: Thank you to Paul Harms from Precision Planting for joining us today on the FarmBits podcast. I personally thought that was a really really fun interview, I liked how we kind of mixed up the engineering side and a lot of the really technical aspects of what they do with some of the bigger picture aspects of what precision planting mission is and how they're going about achieving that. I think my favorite part of the episode was when Paul talked about kind of the three different levels of control that they give folks in terms of their furrow force right, where you can actually have something that you go out and adjust manually to create the right setting. You can actually do the setting within the cab manually, you're getting sensor feedback but you still have to set it manually or you can have it just be fully automated where the the monitor actually will set the correct set point in accordance with the sensors and just make sure that the system is maintaining what it should be and all that is kind of embodied in this whole sense that they have of trying to make sure that everything is rooted in agronomic value, but at the end of the day they're also enabling additional value propositions right and how however far that farmer wants to go if they don't want to have to get out of the tractor to go fix whatever's going on back there there's a next step right and so multi layers of value yeah it's not just collecting all the data they are using it and and if the farmer's not ready for that step they can be very customizable and so yeah. Samantha: That exactly, like what you said leads me to what I thought. My I mean what my favorite part was which was that it is so customizable we asked about where adoption was going and there he was like well it really depends on what an individual farmer needs it's so different based on what region you're in what your soil types are what your challenges are on your farm and so it's not about making a product that fits across the entire United States. It's finishing a product for a farmer, and I just think that is such a cool mentality so with that thank you so much for joining us today on the FarmBits podcast hope you enjoyed learning more about Precision Planting and we look forward to having you again next week.

Transcripts are generated using a combination of speech recognition software and human transcribers, and may contain errors. Please check the audio before quoting in print and write [email protected] to report any errors.

Precision Planting Market to Reach USD 12.2 Billion by 2031 Driven by Surge in Demand for Increased Farm Productivity

Growing Demand for Efficiency and Sustainability

The SNS Insider report highlights a market driven by the need for efficient and sustainable agricultural practices. Factors such as rising pressure on the agriculture industry to increase food production, integrated with the growing demand for precision planting due to its benefits, are Driving market growth. These benefits include optimal plant growth, higher crop yield, and substantial cost savings associated with precision planting and seeding equipment.

The Growing adoption of advanced technologies in precision agriculture to reduce labor costs and the increasing promotion of precision planting techniques by governments worldwide are significant contributors. Climate change and the need to meet the rising demand for food will further propel the industry’s growth in the coming years.

Get Free Sample Report of Precision Planting Market @ https://www.snsinsider.com/sample-request/3035

Top Companies Featured in Precision Planting Market Report:

• AG Leader Technology
• Bourgault Industries Ltd.
• Buhler Industries Inc.
• Crh Industrial N.V.
• Davimac Group
• Deere & Company
• Dendra Systems
• Dickey-John Corporation
• Hexagon Agriculture
• Kasco Manufacturing Inc.
• Kinze Manufacturing Inc

Cost-Savings and Technological Advancements

Precision planting and seeding equipment, when used effectively, can ensure high returns in agribusiness. This equipment offers precision, ensuring accurate depth of sowing and proper seed distribution. The launch of equipment with advanced features like smart connector systems, controllers, and liquid control and delivery systems has further boosted adoption.

These advancements enable farmers to achieve uniformity of seeds, control seed placement depth, and safeguard crops from natural disasters by collecting real-time data on soil, crop yield, weather conditions, and plant health. Additionally, precision planting equipment promotes the efficient use of seeds, fertilizers, nutrients, herbicides, and pesticides, minimizing resource wastage. The integration of mapping software, variable rate technology (VRT), smart sensors, and yield mapping further enhances crop yield, land fertility, and profitability. Moreover, these systems utilize satellite guidance technologies like GPS or GIS for navigation, reducing energy and fuel consumption.

Smartphones Revolutionize Data Access for Farmers

The increasing presence of smartphones, with nearly half the global population using them, plays an Important role in precision planting. These devices offer user-friendly applications that assist farmers in day-to-day tasks. Agriculture-based companies are developing mobile apps that provide farmers with real-time weather and climate information, enabling quick and informed decision-making. These apps connect to hardware such as sensors, GPS receivers, and cameras to collect data, analyze it, and offer actionable insights, ultimately saving farmers time and money.

Segment Analysis

By Offering, the hardware segment holds the highest market share, This dominance is attributed to the increasing adoption of automation and control devices Such as drones, GPS devices, control systems, guidance systems, and display systems. Agricultural vehicles Depend on GPS-based auto-guidance technology to minimize overlapping during field mapping, consequently saving fuel, labor, and time while reducing soil compaction. The rising adoption of advanced planting and seeding equipment with features like VRT and guidance systems for precision planting is anticipated to further propel the hardware segment’s growth.

By Drive type, The electric drive segment is dominant with a higher growth rate within the market. Electric drives simplify precision planter and seeding systems. Farmers cultivating corn as a secondary crop often resort to repairing, modifying, and upgrading older planters due to the high cost of new ones. Electric motors enable farmers to control individual row units at a variable rate. They offer a clear advantage over mechanical, hydraulic, and pneumatic components as energy consumption on farm equipment increases. The consistent and uniform power delivery of electric motors translates to more accurate seed placement functions in planters and drills. Additionally, electric drive metering eliminates the need for hydraulic components such as chains, sprockets, and gears, simplifying the metering system and reducing maintenance requirements. Electric drives power a shaft that turns

Ask Your Query Before Buying this Research Report @  https://www.snsinsider.com/enquiry/3035

Recent Developments in Precision Planting Technology

• In February 2022, Case IH launched the 2150S Early Riser front-fold trailing planter, providing a high-performance split-row configuration option for increased planting productivity.
• October 2022 saw Trimble Inc. introduce the next-generation Trimble GFX-1060 and GFX-1260 guidance displays for precision agriculture applications. These displays empower farmers to map and monitor field information with precision in real time, facilitating efficient in-field operations.
• Kinze Manufacturing introduced its new 3505 True Speed high-speed planter in February 2022 for the 2023 planting season, offering advanced technology and improved productivity for smaller farms and fields.

Impact of Global Disruptions on the Precision Planting Market

– The Russia-Ukraine war has disrupted the global agricultural landscape, The war has caused a global surge in fuel prices, impacting the operational costs of farm machinery used in precision planting practices. This can discourage farmers, particularly those with smaller margins, from adopting or expanding their use of precision planting equipment. war has Increased global food security concerns, potentially leading governments to prioritize staple food production over crops that benefit more from precision planting techniques. This could cause a temporary shift in agricultural focus, impacting the immediate growth of the precision planting market.

– A global economic slowdown could also impact the precision planting market, decrease Investments in new precision planting equipment, potentially slowing down market growth. The long-term outlook remains positive. Precision planting offers significant benefits in terms of resource optimization and yield improvement, which can become even more important during economic hardships. Farmers Looking to maximize profits with limited resources may find precision planting a valuable tool in the long run.

Key Regional Development

North America is expected to remain the dominant region in the precision planting market, driven by North America as a hub for innovation in agricultural technology. Leading manufacturers and research institutions are constantly developing new and advanced precision planting solutions, making the region a leader in this field. Governments in North American countries often offer subsidies and incentives for farmers to adopt sustainable and efficient agricultural practices. Precision planting aligns well with these goals, encouraging its adoption. North America has a higher prevalence of large-scale farms compared to other regions. These farms have the capital and resources to invest in sophisticated precision planting equipment, driving market growth.

Example: Government Support in the US, The United States Department of Agriculture (USDA) offers various programs and initiatives that support the adoption of precision agriculture practices. The Environmental Quality Incentives Program (EQIP), for instance, provides financial assistance to farmers for implementing conservation practices, including those that utilize precision planting techniques.

Key Takeaways for the Precision Planting Market Study

• Technological advancements are continuously improving the capabilities and usability of precision planting equipment.
• Global disruptions like the Russia-Ukraine war and potential economic slowdowns pose challenges but may not derail the long-term growth trajectory of the market.
• This report by SNS Insider provides valuable insights into the current and future landscape of the precision planting market.

Major Key Points from Table of Content

1. Introduction 2. Research Methodology 3. Market Dynamics 4. Impact Analysis 5. Value Chain Analysis 6. Porter’s 5 forces model 7. PEST Analysis 8. Precision Planting Market Segmentation, By Offering 9. Precision Planting Market Segmentation, By System Type 9. Precision Planting Market Segmentation, By Drive Type 9. Precision Planting Market Segmentation, By Farm Size 9. Precision Planting Market Segmentation, By Application 10. Regional Analysis 11. Company Profile 12. Competitive Landscape 13. USE Cases and Best Practices 14. Conclusion

Continued….

Access Detailed Research Insight with Full TOC and Graphs @  https://www.snsinsider.com/reports/precision-planting-market-3035

About Us: SNS Insider has been a leader in data and analytics globally with its authentic consumer and market insights. The trust of our clients and business partners has always been at the center of who we are as a company. We are a business that leads the industry in innovation, and to support the success of our clients, our highly skilled engineers, consultants, and data scientists have consistently pushed the limits of the industry with innovative methodology and measuring technologies.

Contact Us:

Akash Anand – Head of Business Development & Strategy

Phone: +1-415-230-0044 (US)

Cultivating Efficiency: The Evolution of Planting Machinery

Packaging And Construction | 26th April 2024

Introduction: Top Planting Machinery Trends 

Planting machinery has long been a cornerstone of agricultural productivity, enabling farmers to sow seeds with unprecedented speed and precision. As global food demands rise and agricultural practices modernize, the technology behind planting machinery continues to evolve. Today’s machines are not only designed to enhance efficiency but also to reduce environmental impact and adapt to varying agricultural conditions. This blog explores five key trends in the development of Planting Machinery Market , showcasing how innovations are reshaping planting processes to meet the challenges of modern farming.

1. Automation and Precision Technology

One of the most transformative trends in planting machinery is the integration of automation and precision technology. Todays planters are equipped with GPS and sensor technology that allows for precise seed placement and spacing, minimizing seed waste and maximizing crop yields. These technologies also enable variable rate planting, where the amount of seeds planted is adjusted automatically based on soil fertility and other field conditions. Automation extends to self-driving tractors and robotic systems that can operate with minimal human intervention, significantly reducing labor costs and increasing planting efficiency.

2. Increased Adaptability to Soil Variability

Modern planting machinery is increasingly designed to adapt to different soil types and conditions without compromising performance. Innovations in this area include adjustable downforce systems that prevent compacting the soil while ensuring that seeds are planted at the correct depth. This adaptability is crucial for maintaining high yields across diverse farming landscapes and contributes to more sustainable soil management practices.

3. Eco-Friendly Designs

Environmental sustainability is driving innovations in planting machinery, with manufacturers focusing on reducing the carbon footprint of their machines. This includes the development of electric planting machinery that offers a cleaner alternative to traditional diesel-powered engines. Additionally, newer machines are designed to operate more efficiently, requiring less power to operate and reducing overall energy consumption during the planting process.

4. Enhanced Seed Treatment Capabilities

The integration of on-the-go seed treatment technologies in planting machines is a growing trend. These systems allow seeds to be treated with fungicides, pesticides, and nutrients during planting, which enhances the growth environment and protects against pests and diseases from the outset. This integrated approach not only improves plant health and yield potential but also reduces the need for additional passes over the field, saving time and reducing soil disruption.

5. Connectivity and Data Integration

Connectivity and data integration features in planting machinery are enhancing the way farmers plan, monitor, and analyze their planting activities. Modern planters can connect to farm management software, allowing farmers to access real-time data about planting progress, weather conditions, and crop health. This data can be used to make informed decisions that optimize planting strategies and improve crop management throughout the growing season.

The evolution of planting machinery is marked by significant technological advancements that are transforming agricultural practices. The trends discussed in this blog highlight ongoing innovations that improve planting precision, efficiency, and sustainability. As planting machinery continues to evolve, it will play a critical role in addressing global food production challenges, enhancing the productivity of the agricultural sector, and ensuring environmental sustainability. The future of planting machinery looks promising, with technological advancements poised to continue driving improvements in agricultural efficiency and output.

Recent Blogs

• Shuffling the Deck: Evolving Trends in the Poker Market Consumer Goods January 2024
• Shaping Sustainable Growth: The Evolution of Greenhouse Films Agriculture April 2024
• Sustaining Cold-Blooded Companions: Emerging Trends in Reptile and Amphibian Nutrition Agriculture April 2024
• Enhancing Small Mammal Care: Trends in Food Treats for Tiny Companions Agriculture April 2024
• Nourishing Noble Steeds: Innovations in Horse Food Food And Beverages April 2024
• Cultivating Efficiency: Trends Shaping Commercial Greenhouse Equipment Aerospace and Defense April 2024
• Enhancing Growth Naturally: The Rise of Biostimulants in Agriculture Agriculture April 2024
• Cultivating Innovation: The Rise of Plant Growth Chambers Agriculture April 2024

Recent Reports

Advertise Follow Us

Farm Equipment's Best of the Web: April 26, 2024

Farm Equipment editors encounter a variety of articles, social media posts, podcasts and videos that offer a unique look at various aspects of our great farm machinery industry. Here is our favorite content from the past week from across the web:

Deere Debunks EV Myths

Spring madness: precision specialist prepares customers for planting season, are your customers brand loyal, 18-dealer operation uses ai to boost customer service, product video of the week: roller crimper offerings from i&j manufacturing.

Best of the Web This Week is brought to you by Dealership Minds Summit .

Join top farm equipment dealerships from around North America on August 6-7, 2024 in Madison, Wis., for 2-days of unrivaled learning and networking during the 2024 Dealership Minds Summit. No other event gives you a FOR DEALERS ONLY learning opportunity featuring targeted sessions that deliver the latest research, ideas and tools to help your dealership reach its top potential.

In a recent article on its website, John Deere says, “Why are we introducing battery electric vehicles (BEVs) to some product lines? Because industries we support, like high value crop farming (things like nuts and fruits), as well as customers working in turf care and construction, need it.

Go behind the scenes with Chad Baker, co-owner of Baker Precision Planter Works in Orangeville, Ill., as he hits the road for on-farm visits and pre-season maintenance checks. Baker helps a first-generation no-tiller prepare for planting season, and later runs into a couple big challenges with a customer’s new, high-speed, 24-row planter.

In this YouTube Short from Barn Talk they break down how common brand loyalty is in their area. Ag Equipment Intelligence is surveying farmers on brand loyalty, and will release its latest update on brand loyalty later this summer. 

In this short video , Wally Butler from Mazergroup, the largest New Holland dealer in Canada, chats with AgvisorPRO CEO Robert Saik about the dealership’s experience using the visorPRO.ai program to improve the overall efficiency within their service department.

In this week's video , we’re showcasing product offerings from I&J Manufacturing, including their lineup of Crop Rollers, which come in a variety of mounting options including a 60ft buffet-roller, a raised bed roller, a roller on Front End Load and more.

Is there something you want to share in "This Week"? Send us an email.

More from this series

Click here to view past " Best of the Web This Week " updates.

This month's digital sponsors:

Post a comment, report abusive comment, top articles.

• UPDATED: CNH Names Gerrit Marx CEO
• Dealers Report Decline in Customer Brand Loyalty
• Farm Equipment News IQ: April 2024 Quiz
• Farm Equipment's Best of the Web: April 26, 2024
• Oklahoma Dealer Great Plains Acquires Arnette New Holland Stores

Current Issue

Farm Equipment

5 Dealers Share Latest Facility Projects

Dealers Better Prepared for Softening in Used Market

Strong customer relationships, parts inventory central to spring success, don’t get caught fighting the last war, must read free eguides.

Download these helpful knowledge building tools

• Ag Equipment Intelligence Book of Lists (2nd Edition)
• Ag Equipment Intelligence Book of Lists
• 7 Different Technician Pay Rates eGuide by Skill Level
• Export with Confidence: Tools and Opportunities for the Agriculture Industry

Farm Equipment Videos

Analysts Comment on CNHI CEO's Departure

Yetter Farm Equipment

Montag is the industry’s innovative leader for precise, accurate metering of fertilizer, seed and other nutrients. The Montag system has become the standard for deep banding of fertilizer. Montag is also pioneering the technology for cover crop seed application. The new Cover Crop+ is able to meter the smallest seed, and can be mounted to tillage implements, combines, plus Hagie sprayers and detasselers.

Finance Scope

Check Out 2023's Workshop... Stay Tuned For What Will Be Offered in 2024!

Attend an exclusive pre-conference workshop at the Precision Technology Institute (PTI) Farm on Wed., Aug. 2!

**Attendees are responsible for arranging their own travel to and from PTI Farm.**

Just a short drive from the host hotel, you’ll experience hands-on learning at Precision Planting’s renowned 400-plus acre research farm. Rotate through 3 guided programs (PTI Farm Agronomy Tour, Strip-Till Equipment Sandbox, Soil Nutrient Management & Precision Application) that immerse you into the latest in strip-till technology and research from Precision Planting’s 150-plus agronomic plots. Participate in in-field equipment demos, review plot trial results, and see the leading edge of agronomy first-hand.

After a day of learning in the field, join all conference attendees for the official National Strip-Tillage Conference Welcome Reception & Supper — onsite at the PTI Farm — in the evening! (Evening reception open to all registered attendees. No additional fee is required, but an attendee badge is required.)

When: Wed., Aug. 2, 1p.m. - 5:30 p.m. CT Where: PTI Farm at 1701 S Deerfield Rd, Pontiac, IL 61764 Who:  Open to registered conference attendees only Cost:  $149 per attendee Capacity: 150 attendees. Save your spots!

Join Us For The Official Welcome Reception, On-Site at PTI Farm!  Open To ALL Attendees!

Join your fellow conference attendees from 5:30 p.m. - 8 p.m. Wednesday at Precision Planting’s Precision Technology Institute Research Farm at 1701 S. Deerfield Rd, Pontiac, Ill., for the official National Strip-Tillage Conference Welcome Reception & Supper. Get ready to see new and old friends at this special event. A light dinner and drinks — plus engaging discussion with suppliers and your fellow farmers — makes the annual welcome event the perfect place to find like-minded strip-tillers to share ideas and solutions over the next 1.5 days. This reception is included with your conference registration and is open to all registered attendees. No additional fee is required, but an attendee badge is required. Pick up your attendee badge when you arrive at PTI Farm

Complete your online conference registration now and choose the workshop option to reserve your spots!

Questions about the National Strip-Tillage Conference?

For general conference inquiries contact  Strip-Till Farmer by phone at (866) 839-8455 or (262) 432-0388; by fax at (262) 786-5564; or by email at [email protected]

To learn about sponsorship opportunities contact Michael Ellis at (262) 777-2432 or [email protected]

To learn about group attendance discounts contact Dallas Ziebell at (262) 777-2412 or [email protected]  

• Visit the University of Nebraska–Lincoln
• Apply to the University of Nebraska–Lincoln
• Give to the University of Nebraska–Lincoln

Search Form

Nebraska on-farm research network releases 2023 research results publication.

The Nebraska On-Farm Research Network (NOFRN) is placing research results into producers’ hands through its 2023 Research Results book — a publication that highlights findings from approximately 80 on-farm research studies conducted in Nebraska during the 2023 growing season.

"The research results in this book equip producers with the tools to harness local insights, enabling them to make well-informed decisions that optimize both productivity and profitability on their own operation" said Taylor Lexow, NOFRN Project Coordinator.

Studies in the 2023 Research Results book cover various topics, including crop production, fertility and soil management, non-traditional products, cover crops, crop protection and equipment. The 2023 publication, along with publications from previous years, is now available on the NOFRN’s website.

With planting season upon us, now is the time to dig deeper into agricultural practices and determine what best fits the needs of every operation. Download a copy of the 2023 Research Results book today from the NOFRN site .

For more information about the 2023 Research Results book or the NOFRN, please contact Taylor Lexow at 402-245-2222 .

About the NOFRN

The Nebraska On-Farm Research Network (NOFRN) is a program of Nebraska Extension that partners with farmers to evaluate agricultural practices and provide innovative solutions that impact farm productivity, profitability and sustainability. It is supported by the Nebraska Corn Board, the Nebraska Corn Growers Association, the Nebraska Soybean Checkoff and the Nebraska Dry Bean Commission. To learn more about the NOFRN, visit its website .

2023 Research Results Book

Online Master of Science in Agronomy

With a focus on industry applications and research, the online program is designed with maximum flexibility for today's working professionals.

Solvency Trends for Illinois Grain Farms

• Gerald Mashange
• Department of Agricultural and Consumer Economics
• University of Illinois
• Bradley Zwilling
• Illinois FBFM Association and Department of Agricultural and Consumer Economics

This article examines the debt-to-asset ratio trends of Illinois grain farms using data obtained from the Illinois Farm Business Farm Management (FBFM). The debt-to-asset ratio is a measure of solvency and financial risk that expresses the share of a farm’s total assets that are owed to creditors. It is calculated by dividing the value of a farm’s total liabilities by its total assets. In other words, it measures a farm’s ability to pay off all of its liabilities with its total assets. [1] In our analysis, we report the annual average total assets and total liabilities of grain farms in Illinois by the size of their gross farm returns— small , medium -sized, and large . We define small farms as those with gross farm returns less than $350,000, medium -sized farms as those with returns between $350,000 and $999,999, and large farms as those with returns greater than $999,999. We then use these total liability and total asset values to calculate the implied debt-to-asset ratio (hereafter, debt-to-asset ratio). This approach will also allow us to discuss the relative changes in total assets and total liabilities driving the debt-to-asset ratio trends.

According to the Farm Financial Scorecard [2] developed by the Center for Farm Financial Management , a farm with a debt-to-asset ratio that is greater than 0.6 is categorized as vulnerable , a ratio between 0.3 and 0.6 is categorized as stable , and a ratio that is less than 0.3 is categorized as strong . The greater the debt-to-asset ratio, the greater the financial risk a farm faces. A ratio greater than 0.5 indicates a greater proportion of a farm’s assets are financed by debt rather than the owner’s equity. In our figures below, we use the color-coding system of the Farm Financial Scorecard to indicate the category under which the average farm’s debt-to-asset ratio belongs. The region shaded in red indicates a vulnerable ratio, while yellow indicates a stable ratio, and green indicates a strong ratio.

How Has the Debt-to-Asset Ratio Trended over the Past 20 Years?

Figure 1 shows the average fair market value of total assets, the average total liabilities, and the debt-to-asset ratio of grain farms in Illinois. Over the past two decades, the debt-to-asset ratio for Illinois grain farms has shown a downward trend. In 2003, the debt-to-asset ratio was 0.273 ( strong ), with average total liabilities of $342,821 and average total assets of $1,256,014. Except for one year, between 2003 and 2012, total assets grew faster than total liabilities, which improved the ratio from 0.273 ( strong ) to 0.189 ( strong ). This growth in total assets was due to increases in grain prices, which led to higher ending inventory values. Furthermore, changes in tax laws [3] permitted larger year-of-purchase tax deductions on capital assets used in farming operations. By 2012, average total assets had grown to $3,413,395, a 171.76% increase, while average total liabilities had increased by 88.49% to $646,176.

However, in all but one year from 2013 to 2020, average total liabilities grew faster than average total assets. The decrease in grain prices over this period resulted in lower ending inventory prices, which in turn lowered current assets. Moreover, the combination of lower prices and higher operating expenses led to lower net farm incomes, resulting in less operating cash. As a result, farming operations had to increase their operating debt. This shift pushed the debt-to-asset ratio up slightly and increasingly higher over the years, peaking at 0.212 ( strong ) in 2019 and 2020. During this period, average total assets had increased by 22.52% from $3,413,395 to $4,182,158, while average total liabilities had increased by 37.34% from $646,176 to $887,479. Subsequently, the debt-to-asset ratio fell to 0.197 ( strong ) and 0.189 ( strong ) in 2021 and 2022, respectively, as average total assets increased at a faster pace than average total liabilities in both years. The rise in grain prices resulted in higher inventory prices and increased farm incomes, reducing the need for operating debt. As of 2022, average total assets stood at $5,161,982, while average total liabilities stood at $974,505.

How Does the Debt-to-Asset Ratio Trend Vary by Farm Size?

Figure 2 shows the average fair market value of total assets, the average total liabilities, and the debt-to-asset ratio of grain farms in Illinois, categorized by the size of their gross farm returns. Over the past two decades, grain farms with smaller gross farm returns have consistently maintained a stronger solvency position compared to their larger counterparts. In 2003, the debt-to-asset ratio of small grain farms was 0.232 ( strong ), compared to 0.336 ( stable ) and 0.483 ( stable ) for medium -sized and large farms, respectively. The solvency positions for all three farm size categories strengthened from 2003 to 2012. Small grain farms improved their debt-to-asset ratios from 0.232 ( strong ) to 0.118 ( strong ), whereby average total assets increased by 73.38%, while average total liabilities decreased by 11.78% over the period. The debt-to-asset ratio of medium -sized grain farms improved from 0.336 ( stable ) to 0.171 ( strong ), driven by a 60.39% increase in average total assets and an 18.06% decrease in average total liabilities over the same period. Large farms had a considerably higher debt-to-asset ratio compared to small and medium -sized farms in 2003. However, they managed to improve their ratio from 0.483 ( stable ) to 0.231 ( strong ) by 2012 as average total assets increased by 37.03%, while average total liabilities decreased by 34.47%.

During the first half of the period from 2013 to 2022, the debt-to-asset ratio weakened across all three farm size categories before eventually improving, mainly due to lower prices and accrual net farm incomes. Small farms saw their ratio increase from 0.127 ( strong ) in 2013 to a peak of 0.136 ( strong ) in 2019, before improving to 0.114 ( strong ) in 2022. During this period, the average total assets of small grain farms increased by 33.24%, while average total liabilities increased by 19.14%.

Medium-sized grain farms experienced a similar trend, with their debt-to-asset ratio increasing from 0.185 ( strong ) in 2013 to a peak of 0.213 ( strong ) in 2015. The ratio then gradually fell over the next few years and sharply declined in 2021 to 0.159 ( strong ). As of 2022, the debt-to-asset ratio of medium-sized grain farms was 0.147 ( strong ). Over the period, total assets for medium-sized farms increased by 10.72%, while total liabilities fell by 12.05%.

Large grain farms experienced the sharpest increase in debt-to-asset ratio during the period, rising from 0.251 ( strong ) in 2013 and peaking at 0.295 ( strong ) in 2019, before falling sharply to 0.222 ( strong ) in 2022. Over the same period, the average total assets of large grain farms increased by 11.77%, while average total liabilities decreased by 0.80%.

Overall, the debt-to-asset ratio of Illinois grain farms has trended downward over the past two decades, indicating an improvement in solvency and a reduction in financial risk. The debt-to-asset ratio has consistently been lower for smaller farms compared to medium -sized and large farms. Some of the differences in farm size and debt-to-asset ratios can be attributed to the age of the farmer. Typically, younger farmers have smaller farm sizes and much higher debt-to-asset ratios. When farmers reach the age group of 50 to 59 years, the size of the farm begins to decrease while debt-to-asset ratios continue to increase. Initial findings from 2023 indicate that the average debt-to-asset ratio remained similar to that of 2022, despite much lower prices at the end of the year. However, projections for 2024 suggest that lower prices, as well as the potential for higher operating loan balances and accrued interest, may increase debt-to-asset ratios.

Acknowledgment

The authors would like to acknowledge that data used in this study comes from the Illinois Farm Business Farm Management (FBFM) Association. Without Illinois FBFM, information as comprehensive and accurate as this would not be available for educational purposes. FBFM, which consists of 5,000+ farmers and 70 professional field staff, is a not-for-profit organization available to all farm operators in Illinois. FBFM field staff provide on-farm counsel along with recordkeeping, farm financial management, business entity planning and income tax management. For more information, please contact our office located on the campus of the University of Illinois in the Department of Agricultural and Consumer Economics at 217-333-8346 or visit the FBFM website at www.fbfm.org .

[1] We use the market value of total assets in our analysis.

[2] The Farm Financial Scorecard adheres to the guidelines set by the Farm Financial Standards Council .

[3] This includes a larger expense election and the introduction of special depreciation at 30%, which can be increased to 100% of the purchase price deduction in the year of purchase.

Disclaimer: We request all readers, electronic media and others follow our citation guidelines when re-posting articles from farmdoc daily . Guidelines are available here . The farmdoc daily website falls under University of Illinois copyright and intellectual property rights. For a detailed statement, please see the University of Illinois Copyright Information and Policies here .

Related Posts

• Cost to Produce Corn and Soybeans in Illinois—2023
• Solvency Trends for Illinois Grain Farms: The Distribution of Debt-to-Asset Ratios by Gross Farm Returns
• Market Prices
• farmdoc Team
• Ryan Batts (34)
• Joana Colussi (59)
• Jonathan Coppess (484)
• A. Bryan Endres (40)
• Jason Franken (28)
• All Articles
• Biodiesel Production Profits
• Biodiesel Supply
• Ethanol Outlook
• Ethanol Production Profits
• Gasoline Blending
• Gasoline-Diesel Prices
• Renewable Diesel Boom
• Biodiesel Tax Credit
• RIN Market and Pricing
• SREs and the RFS
• Milestones and Announcements
• USDA Reports
• Grain Miscellaneous
• Ending Stock Models
• New Era Projections
• Growing Season Yield Forecasts
• Late Planting Impacts on Yield
• Trend Yields and Yield Risks
• USDA Acreage and Production Reports
• Joe Janzen (63)
• Maria Kalaitzandonakes (27)
• Michael Langemeier (173)
• Dale Lattz (34)
• Gerald Mashange (8)
• Nick Paulson (567)
• Gary Schnitkey (1046)
• Bruce Sherrick (72)
• Mark White (9)
• Carl Zulauf (644)
• Brad Zwilling (157)
• All Authors
• April 2024 (18)
• March 2024 (20)
• February 2024 (21)
• January 2024 (21)
• December 2023 (20)
• November 2023 (18)
• October 2023 (21)
• September 2023 (20)
• August 2023 (17)
• July 2023 (21)
• June 2023 (21)
• May 2023 (20)
• April 2023 (20)
• March 2023 (23)
• February 2023 (20)
• January 2023 (16)
• December 2022 (18)
• November 2022 (18)
• October 2022 (13)
• September 2022 (17)
• August 2022 (21)
• July 2022 (13)
• June 2022 (19)
• May 2022 (19)
• April 2022 (18)
• March 2022 (15)
• February 2022 (15)
• January 2022 (13)
• December 2021 (14)
• November 2021 (11)
• October 2021 (10)
• September 2021 (12)
• August 2021 (14)
• July 2021 (12)
• June 2021 (15)
• May 2021 (16)
• April 2021 (20)
• March 2021 (22)
• February 2021 (14)
• January 2021 (17)
• December 2020 (13)
• November 2020 (14)
• October 2020 (16)
• September 2020 (18)
• August 2020 (16)
• July 2020 (22)
• June 2020 (21)
• May 2020 (18)
• April 2020 (21)
• March 2020 (26)
• February 2020 (19)
• January 2020 (21)
• December 2019 (17)
• November 2019 (19)
• October 2019 (23)
• September 2019 (20)
• August 2019 (25)
• July 2019 (20)
• June 2019 (20)
• May 2019 (22)
• April 2019 (23)
• March 2019 (22)
• February 2019 (19)
• January 2019 (21)
• December 2018 (18)
• November 2018 (18)
• October 2018 (20)
• September 2018 (18)
• August 2018 (22)
• July 2018 (21)
• June 2018 (21)
• May 2018 (22)
• April 2018 (21)
• March 2018 (21)
• February 2018 (20)
• January 2018 (20)
• December 2017 (16)
• November 2017 (20)
• October 2017 (22)
• September 2017 (18)
• August 2017 (22)
• July 2017 (20)
• June 2017 (18)
• May 2017 (22)
• April 2017 (19)
• March 2017 (22)
• February 2017 (20)
• January 2017 (20)
• December 2016 (15)
• November 2016 (20)
• October 2016 (20)
• September 2016 (20)
• August 2016 (22)
• July 2016 (20)
• June 2016 (21)
• May 2016 (20)
• April 2016 (20)
• March 2016 (23)
• February 2016 (20)
• January 2016 (19)
• December 2015 (22)
• November 2015 (19)
• October 2015 (22)
• September 2015 (21)
• August 2015 (20)
• July 2015 (19)
• June 2015 (21)
• May 2015 (20)
• April 2015 (21)
• March 2015 (23)
• February 2015 (20)
• January 2015 (19)
• December 2014 (19)
• November 2014 (17)
• October 2014 (23)
• September 2014 (22)
• August 2014 (25)
• July 2014 (21)
• June 2014 (21)
• May 2014 (22)
• April 2014 (22)
• March 2014 (19)
• February 2014 (22)
• January 2014 (21)
• December 2013 (19)
• November 2013 (19)
• October 2013 (23)
• September 2013 (20)
• August 2013 (21)
• July 2013 (21)
• June 2013 (20)
• May 2013 (25)
• April 2013 (22)
• March 2013 (21)
• February 2013 (22)
• January 2013 (21)
• December 2012 (18)
• November 2012 (20)
• October 2012 (23)
• September 2012 (19)
• August 2012 (24)
• July 2012 (22)
• June 2012 (21)
• May 2012 (23)
• April 2012 (20)
• March 2012 (20)
• February 2012 (21)
• January 2012 (19)
• December 2011 (19)
• November 2011 (18)
• October 2011 (18)
• September 2011 (21)
• August 2011 (22)
• July 2011 (21)
• June 2011 (23)
• May 2011 (21)
• April 2011 (26)
• March 2011 (17)
• February 2011 (13)
• Conservation and Other
• Environmental Policy
• Farm Program Analysis and Outlook
• Farm Program Description
• Food Policy
• Gardner Policy Series
• Risk Management
• Energy Markets
• Legal and Regulatory
• Profitability
• Renewable Fuels Standards
• Premiums and Payouts
• Prevented and Delayed Planting
• Land Prices
• Rental Arrangements
• Rental Forms
• Agricultural Credit
• Farm Income
• Financial Management
• Interest Rates
• Profitability Benchmarks
• Costs of Production
• Crop Economics
• Decision Aids
• Livestock Economics
• Machinery Economics
• Precision Conservation Management (PCM)
• Weekly Farm Economics
• Ag Market Insights
• Crop Yields
• Futures and Options Markets
• Grain Outlook
• Livestock Outlook
• Long-Term Outlook
• Marketing Strategies and Basis
• USDA reports
• Weekly Outlook
• Coronavirus (Covid-19) and Ag
• 20th Anniversary Series
• The State of Soybean in Africa
• AgMAS Reports
• Farm Economics Facts & Opinions (FEFO)
• Marketing and Outlook Research Briefs
• Marketing and Outlook Research Reports
• Weekly Outlook (Before 2011)
• Crop Insurance Decision Tool (Sheet)
• Crop Insurance Payment Evaluator
• Crop Insurance Premium Calculator
• ECO/SCO Payment Estimator (Sheet)
• Post Application Coverage Endorsement Tool (Sheet)
• Price Distribution Tool
• Farm Bill What-If Tool
• Balance Sheet & Historical Financial Statements
• Cash Rent with Bonus Worksheet
• Crop Insurance Decision Tool
• Farm Projection Tool
• Land Purchase Analysis
• Planting Decision Model
• Appraisal of Current Financial Position
• Beef Profitability Model
• Biomass Crop Budget Tool – Corn Stover
• Briomass Crop Budget Tool – Miscanthus & Switchgrass
• Capital Budgeting Analysis
• Carbon Calculator
• Cash to Accrual Income Approximation
• Corn & Soybean Basis Tool
• Cost of Feedstuffs Calculator
• Dairy Profitability Model
• Earned Net Worth Allocation
• Enterprise Allocation Module
• Estimation of Deferred Taxes
• Ethanol Dry Mill Plant Simulator
• Farm Rent Evaluator
• Grain Storage Purchase Analysis
• Grain Inventory Management
• Grain Pricing Tool
• Illinois Soil Productivity & Yield Utilities
• Lease vs Purchase Analysis
• Loan Amortization
• Loan Comparison
• Machinery Financing
• MACRS Calculator
• Marketing & Crop Insurance Risk Model
• Monthly Cash Flow Planning
• New Company Simulator
• Personal Financial Statements
• Quick Cash Flow Projections
• Repayment Capacity Analysis
• Revolving Loan Calculator
• Savings Calculator
• Specialty Commodity Breakeven Analysis
• Time Value Tools
• Yield Risk Evaluator
• Farmland LEasing Facts Sheets & Pricing Information
• Illinois Crop Budgets & Historic Returns
• Illinois Farmland Leasing & Rental Forms
• Machinery Cost of Operations Estimates
• Whole Farm & Other Reports
• 2018 Farm Bill What-If Tool (Sheet)
• ARC/PLC Calculator (Online)
• farmdoc daily live Archive
• 5-minute farmdoc Archive
• Illinois Farm Economic Summit
• IFES Archive
• Sponsorship Program
• Friends of farmdoc
• Donation Form
• Digging Deeper
• Connect / Subscribe
• 20th Anniversary
• Department of ACE

The Ohio State University

• BuckeyeLink
• Find People
• Search Ohio State

CFAES COVID-19 Resources:    Safe and Healthy Buckeyes   |   COVID-19 Hub   |   CFAES Calendar

Ohio State University Extension

Search form

Battle for the belt: season 2 episode 4- chilling injury, breadcrumb menu.

Episode 4 of battle for the Belt is now available: https://www.youtube.com/watch?v=T5_QXF-Px7s

In Episode 4, Dr. Alex Lindsey, Associate Professor of Crop Ecophysiology & Agronomy, walks us through his current research project on how cold temperatures and water can affect early planted soybeans within the first 24 hours of planting.

How does cold temperature and water affect germination and emergence?

We have been studying how cold temperatures and water affect soybeans under ultra-early planting conditions using some lab experiments. We planted soybeans into field soil (starting at 20% or 60% available water content) at 1” (shallow) or 1.5” (normal) planting depths, and exposed them to different combinations of cold temperatures and water treatments during the first 24 hours after planting (Table 1). After the first 24 hours, we raised the temperature in the chamber to 70°F and measured emergence.

Table 1. Temperature and water treatments evaluated during the first 24 hrs after planting.

Preliminary results suggest that no water application (even if temperature dropped to 35°F) resulted in the greatest emergence (75%) after 11 days. Water application immediately after planting, regardless of whether it was 50°F or 35°F, cut the emergence totals in half. Application of ice after planting was less damaging to emergence but still reduced germination compared to where water wasn’t applied. This suggests that avoiding precipitation within the first 24 hours of planting is key to ensuring good emergence.

Does planting depth matter?

Interestingly, shallowly planted seeds (1-inch depth) had slightly lower emergence totals (10-15% less) compared to those planted at the normal depth of 1.5-inch when the soil was drier (20% available water content). The effect of planting depth on emergence was less noticeable when soils had 60% available water content at planting.

These results suggest it is possible that a 1.5-inch planting depth for ultra-early planting may result in better emergence than a shallower planting depth, but these results should be field tested before further recommendations can be made. Avoidance of precipitation of any sort in the first 24 hrs after planting was key to ensure best emergence with cold temperatures.

What is happening in the field?

The Western Agriculture Research Station is still the only location planted as much of the state has been water-saturated with little available suitable field work days since March 25 th . However, southern Ohio last week was dry enough for planting in areas, so planting date 2 went in on April 16 th (Table 1).

Planting date one (March 25) in both corn and soybeans have emerged! The high temperatures through last weekend helped to accumulate the required GDD for plant emergence (Table 2). The corn is between VE and V1 (first leaf collar) and the soybeans have the cotyledons coming through the soil (Figure 1). Temperatures were lower at this location the weekend of April 20th; cold injury will be scouted for this week.

Table 1. The planting date conditions for planting date two at the Western Agricultural Research Station.

Table 2 . Weekly weather conditions for planting dates one and two at the Western location with day of planting, soil, air temperature averages, and Growing Degree Days (GDDS) from April 15 to April 21. Information from CFAES Weather System ( https://weather.cfaes.osu.edu/ ).

Additional Authors: Anu Neththasinghe Appuhamilage

Crop Observation and Recommendation Network

C.O.R.N. Newsletter is a summary of crop observations, related information, and appropriate recommendations for Ohio crop producers and industry. C.O.R.N. Newsletter is produced by the Ohio State University Extension Agronomy Team, state specialists at The Ohio State University and the Ohio Agricultural Research and Development Center (OARDC). C.O.R.N. Newsletter questions are directed to Extension and OARDC state specialists and associates at Ohio State.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Vavilovskii Zhurnal Genet Selektsii
• v.26(4); 2022 Jul

Language: English | Russian

Investigation of genetic polymorphism of Russian rape and turnip rape varieties using SSR and SRAP markers

Изучение генетического полиморфизма российских сортов рапса и сурепицы с использованием ssr- и srap-маркеров, i.a. klimenko.

Federal Williams Research Center of Forage Production and Agroecology, Lobnya, Moscow region, Russia

V.T. Volovik

A.a. antonov, v.a. dushkin, a.o. shamustakimova, yu.m. yu.m. mavlyutov.

Rapeseed (Brassica napus L.) and turnip rape (B. rapa L. subsp. campestris (L.)) are important agricultural plants widely used for food, fodder and technical purposes and as green manure. Over the past decades, a large number of perspective varieties that are being currently cultivated in every region of Russia have been developed. To increase the breeding eff iciency and facilitate the seed production, modern molecular-genetic techniques should be introduced as means to estimate species and varietal diversity. The objective of the presented research study was to investigate DNA polymorphism of the rapeseed and turnip rape varieties developed at Federal Williams Research Center of Forage Production and Agroecology and detect informative markers for varietal identif ication and genetic certif ication. To genotype 18 gDNA samples, 42 and 25 combinations of respective SSR and SRAP primers were used. The results obtained demonstrate that SRAP markers were more effective for polymorphism analysis: 36 % of the tested markers revealed genetic polymorphism compared with only 16.7 % of microsatellite loci. Molecular markers to detect differences at interspecif ic and intervarietal levels have also been found. For the investigated set, such microsatellite loci as Na12A02, Ni2C12, Ni02-D08a, Ra02-E01, Ni03H07а and SRAP-marker combinations as F13-R9, Me4- R7, F11-Em2, F10-R7, F9-Em2 and F9-R8 proved to be informative. Application of the two marker techniques made it possible to detect a higher level of DNA polymorphism in plants of different types (spring and winter varieties) if compared against the intervarietal differences within a species or a group. According to Nei’s genetic diversity index, in the cluster of winter rapeseed, VIK 2 and Gorizont varieties had the longest genetic distance, and in the spring cluster, these were Novosel and Veles. A high level of similarity was found between Vikros and Bizon winter rapeseed varieties. The results obtained have a high practical value for varietal specif ication of seed material and genetic certif ication of rapeseed and turnip rape varieties.

Рапс (Brassica napus L.) и сурепица (B. rapa L. subsp. campestris (L.)) – важные сельскохозяйственные культуры, широко используются для продовольственных, кормовых и технических целей, а также в качестве сидератов. За последние десятилетия создано большое количество перспективных сортов, культивируемых практически во всех регионах России. Для повышения эффективности селекционного процесса и успешного развития семеноводства необходимо внедрять современные молекулярно-генетические методы оценки видового и сортового разнообразия. Цель настоящей работы заключалась в изучении ДНК-полиморфизма сортов рапса и сурепицы селекции Федерального научного центра кормопроизводства и агроэкологии им. В.Р. Вильямса и выявлении информативных маркеров для сортовой идентификации и генетической паспортизации. Для генотипирования 18 образцов геномной ДНК использовали 42 и 25 комбинаций SSR- и SRAP-праймеров соответственно. Результаты показали, что маркеры SRAP более эффективны для анализа полиморфизма изучаемого материала: 36 % от общего числа испытанных маркеров демонстрировали генетический полиморфизм, тогда как для микросателлитных локусов этот показатель равнялся 16.7 %. Определены молекулярные маркеры для выявления различий на межвидовом и межсортовом уровнях. Информативными для исследуемой выборки сортов оказались микросателлитные локусы Na12A02, Ni2C12, Ni02-D08a, Ra02-E01, Ni03H07а и комбинации SRAP-маркеров F13-R9, Me4-R7, F11-Em2, F10-R7, F9-Em2 и F9-R8. Анализ сортового материала по двум системам маркирования показал более высокий уровень ДНК-полиморфизма у образцов растений разного типа развития (яровой/озимый) в сравнении с различиями между сортами в пределах вида или группы. Согласно индексам генетического разнообразия Нея, в кластере сортов озимого рапса наибольшей генетической удаленностью выделялись ВИК 2 и Горизонт, среди яровых – Новосёл и Велес. Высокий уровень сходства обнаружен между яровыми сортами рапса Викрос и Бизон. Полученная информация имеет практическое значение для контроля сортовой принадлежности и генетической паспортизации семенного материала сортов рапса и сурепицы.

Introduction

Cabbage oilseed crops such as rapeseed (Brassica napus L.) and turnip rape (B. rapa L. subsp. campestris (L.)) are cultivated in almost every region of Russia, and, for the foreseeable future, are regarded as the main reserve for increasing the production of vegetable oil and fodder protein. These plants are widely used in food, fodder, technical purposes and as green manure that increases soil fertility thanks to the plants’ root remains containing up to 6 tons of organic maters, 80 kg of nitrogen, 60 kg of phosphorus and 90 kg of potassium per hectare. As for their food and fodder properties, rapeseed and turnip rape exceed many other cultivated crops since their seeds are 40–48 % fat and 21–33 % protein and contain a high amount of essential amino acids (Volovik, 2015). Rapeseed can provide livestock with green forage from early spring to late fall thanks to their cold hardiness and fast regrowth after mowing. They are also an excellent silage material, and their seeds and seed by-pass products are processed to produce seed cake and coarse meal. In the recent years the varieties of rapeseed and turnip rape with low or no erucic-acid content became available and seed production has increased more than 7 times to reach the world’s third place after soybeans and cotton. Russia’s short-term plans are to increase rapeseed planting acreage to 2.5 mln he.

As for Russian research institutions working intensely to select cabbage oilseed crops, the leading ones are All-Russian Research Institute of Rapeseed, All-Russian Research Institute of Oilseed Crops and All-Russian Williams Fodder Research Institute. For the two last decades, they have produced the perspective varieties of rapeseed, turnip rape, white mustard and oil radish that have been recommended for oil production, livestock and poultry green forage, combination fodder, seed cake and coarse meal production. In 2021, “State Register” of the Russian Federation included 13 varieties of rapeseed and 3 varieties of turnip rape selected by Federal Williams Research Center of Forage Production and Agroecology (Kosolapov et al., 2019; State Register…, 2021).

For preservation and rational use of newly available varieties, intensification of the selection process and protection of intellectual property, modern and effective methods to estimate species and varietal diversity at a genetic level are to be introduced. One of such techniques that has been successfully applied in the recent years is molecular DNA markers, which, if compared against the traditional morphological indicators, possess a number of advantages. These include a high level of polymorphism; even genome distribution; reliability; a possibility to automate the assay procedure that does not depend on environmental conditions or a plant development phase (Agarwal et al., 2008; Khlestkina, 2011; Chesnokov, 2018). If the most informative and convenient DNA markers are selected, their capabilities to estimate the genetic variability of selection material are regarded as unlimited.

Laboratory for Molecular and Genetic Studies in Federal Williams Research Center of Forage Production and Agroecology has been developing a system for DNA identification and genetic certification of Russian fodder crops. For the time being, the varietal identification techniques have been adapted for perennial legume grasses such as red clover and different species of alfalfa (Klimenko et al., 2020a, b). The assay uses samples of the summary total DNA obtained through a modified method from an arbitrary selected sample of every variety’s germinants. Two types of molecular markers were used: SSR (simple sequence repeats), which detect the variability of microsatellite genome sequences, and SRAP (sequence related amplified polymorphism), which is based on PCR with a pair of primers for amplification of intron/exon regions (open reading frames). The techniques have been tested on different species of fodder crops to optimize the amplification conditions, detection and analysis of results.

A problem of reliable varietal identification is particularly topical for rapeseed due to its limited genetic variability conditioned by the intensive selection aimed at higher content and quality of oil. Currently, a significant number of published studies have been devoted to using different DNA markers for estimation of the genetic diversity of rapeseed varieties and hybrids (Plieske, Struss, 2001; Snowdon, Friedt, 2004; Klyachenko et al., 2018; Mozgova et al., 2019); to genetic mapping (Piquemal et al., 2005; Gao et al., 2007; Geng, 2012) and marking the genes of economically valuable traits (Chen et al., 2010; Ananga et al., 2012). However, only a few such studies have investigated Russian varieties. Four varieties of winter and spring rapeseed (Podmoskovniy, Vikros, VIK 2 and Severyanin) were studied by Byelorussian researchers to identify the gene alleles determining the concentration of oleic and linolic acids in rapeseed oil (Lemesh et al., 2015). The same varieties were investigated to detect the DNA markers of the genes responsible for erucic-acid synthesis (Amosova et al., 2014). Microsatellite markers were used to study the genetic polymorphism of Russian varieties Ratnik and SNK- 198 (Satina, 2010) as well as the genetic homogeneity of spring rapeseed varieties Bulat and Forward (Rogozhina et al., 2015). Such winter varieties as Stolychniy, Laureat, Gorizont, Nord and Severyanin were investigated to detect the quantitative trait loci (QTLs) associated with high winter hardiness (Mozgova et al., 2019).

The objective of the presented study was to investigate DNA polymorphism of rapeseed and turnip rape varieties developed by breeders of Federal Williams Research Center of Forage Production and Agroecology and to identify the informative markers for varietal differentiation and genetic certification.

Materials and methods

Plant material. The study investigated 15 varieties of winter (Severyanin, Stolychniy, VIK 2, Nord, Laureat, Gorizont, Garant) and spring (Vikros, Novik, Novosel, Veles, Grant, Podmoskovniy, Lugovskoy, Bizon) rapeseed and 3 varieties of winter (Zarya) and spring (Nadezhda, Svetlana) turnip rape.

DNA extraction and PCR analysis. The gDNA was extracted from 30 germinants of each abovementioned variety (bulk samples) using the basic SDS method (Kirby, Cook, 1967; Dellaporta et al., 1983) with some modifications (Klimenko et al., 2020b). The quality and concentration of the obtained DNA fractions were verified with agarose gel (1.5 %) electrophoresis and using a Nabi spectrophotometer (MicroDigital, South Korea).

To carry out SSR analysis, 42 markers from the database Brassica info (https://www.brassica.info) and available publications were applied. The efficiency of the primers devised for these markers had been demonstrated in the studies devoted to development of the technology of rapeseed genotyping (Satina, 2010) and selection of the samples with low erucic-acid and glucosinolate content (Hasan et al., 2008). A part of the markers included in the analysis was used for hybridization control and detection of Alternaria blight resistant genotypes in Indian mustard (B. juncea L.) (Chandra et al., 2013; Sharma et al., 2018).

The PCR-mixture of 20 μl contained 3 μl 10 × PCR buffer (Taq Turbo Buffer), 0.5 μl 50 × dNTPs mix, 0.4 μl Taq polymerase (5U), forward and reverse primers (0.1 μl each, 100 μm) and 0.1 μl of DNA sample (20 ng/μl). The amplification was performed in a T-1000 thermal cycler (Bio-Rad, USA) at two different temperature regimes. The first amplification program was an initial 3-min denaturation at 95 °C followed by 30 cycles of 30 s at 94 °C, 30 s at 55–57 °C, 30 s at 72 °C and a final 5-min elongation at 72 °C (Satina, 2010). The second program included an initial 5-min denaturation at 95 °C followed by 39 cycles of 1 min at 94 °C, 2 min at 46–51 °C (depending on the primer pair in use), 2 min at 72 °C and a final 10-min elongation at 72 °C (Chandra et al., 2013). The reproducibility of obtained results was attested in three-fold replication.

SRAP analysis was carried out using 25 primer combinations comprised from 10 single oligonucleotides: F9, F13, Me4, F10, F11, R9, R7, Em2, R14, R8 (Li, Quiros, 2001; Rhouma et al., 2017). The amplification program was an initial 4-min denaturation at 94 °C followed by 10 cycles with changing temperature and duration parameters (1 min at 94 °C, 1 min at 35 °C, 1 min at 72 °C); followed by 30 cycles (1 min at 94 °C, 1 min at 50 °C, 1 min at 72 °C) and a final 5-min elongation step run at 72 °C. The PCR-mixture composition was similar to that used for the microsatellite analysis.

PCR-products were separated using 90-min 50-V agarosegel electrophoresis (4 % MetaPhorR Agarose, Rockland or 1.6 % LE, Lonza, USA). As the reference markers, 20 bp DNA Ruler (Bio-Rad), 100 kb DNA Ladder (Thermo Fisher Scientific, USA) and 100 bp + 1.5 kb (SibEnzyme, Russia) were applied.

Analysis of the obtained results. PCR-product detection and size measurement was performed using a GelDoc XR+ imaging system (Bio-Rad) and the ImageLab software (Bio- Rad Lab., Inc.) for molecular-mass markers. The obtained results were transformed into a binary matrix, and PopGene v. 1.32 (Yeh et al., 2000) was applied to determine such genetic diversity indices as the effective number of alleles per locus; Shannon’s index; expected heterozygosity; Nei’s genetic distance (Nei, Li, 1979). Polymorphism information content (PIC) for every pair of primers was calculated by the formula presented in the study (Chesnokov, Artemyeva, 2015). To build the genetic similarity dendrogram, the unweighted pair group method with arithmetic averages was applied in NTSYSpc v 2.10 (Rohlf, 2000).

To obtain gDNA from the rapeseed and turnip rape germinants, a modified SDS method was used. The applied protocol proved more effective and less costly compared to other known protocols and commercial reagents kits. The results of electrophoresis and spectrophotometry attested to the DNA’s high concentration and purification degree from protein compounds and polysaccharides for all experimental samples (Fig. 1, 2).

Lanes 1–15 (rape varieties): Severyanin, Stolychniy, VIK 2, Nord, Laureat, Gorizont, Garant, Vikros, Novik, Novosel, Veles, Grant, Podmoskovniy, Lugovskoy, Bizon; 16–18 (turnip rape varieties): Zarya, Nadezhda, Svetlana.

SSR-analysis

For genotyping the full variety collection, out of 42 SSR primers, 7 primers providing stable and reproducible amplification were selected (Table 1).

Analysis of the amplification fragments obtained using the listed primers detected 42 alleles. Their number per locus was 6 on average, varying from 3 (Ni2C12 and Bna.M.010) to 10 (Ra02-E01a). The fragment size varied from 110 bps (Ni2C12) to 1200 bps (Ni02-D08a). The maximum allele frequency was registered for Bna.M.010 (0.83), and the minimum – for Ni03H07a (0.27); the mean value was 0.42. The primers developed for Ni03H07a, Ni02-D08a and Ra02-E01a markers made it possible to detect 8–10 alleles per locus and had the highest PIC (0.82).

SRAP-analysis

Based on the results of preliminary testing, the initial 25 combinations of SRAP primers were reduced to 10 pairs, amplifying stable polymorphic DNA fragments (Table 2). In total, 53 PCR fragments of 132–1674 nucleotide pairs in size were obtained. One combination contained from 4 (F9-R9) to 7 (F10-R8, F11-Em2, F10-R7) amplicons. A part of the markers proved to be informative to detect the amplification fragments for differentiating the type of plants (winter/ spring). Using 6 combinations made it possible to obtain the amplicons specific for varieties identification (marked with a star in the Table 2).

Fig. 3 demonstrates the electrophoregram of PCR results with the F9-R8 primer combination. Significant DNA profile differences were found between winter (I) and spring (II) rapeseed varieties (joined in curly brackets). The arrows mark the variety-specific PCR products characteristic for Stolychniy winter rapeseed (508 bps) and Nadezhda spring turnip rape (700 bps) as well as the absence of an amplicon in size of 460 bps in spring rapeseed Podmoskovniy though it was a specific characteristic for other varieties in this group. The performed analysis demonstrated that it is possible to identify rapeseed varieties Grant and Novosel with 3 marker combinations (F11-Em2, F10-R7 and Me4-R7), and Gorizont and Lugovskoy – with 2 (F13-R9 and Me4-R7). Variety VIK 2 was identified with SRAP primers F9-Em2, and spring ones Veles – with F10-R7. Specific DNA spectra for rapeseed varieties Stolychniy, Podmoskovniy and turnip rape Nadezhda were obtained with F9-R8 combination.

Winter rapeseed varieties: Severyanin (1), Stolychniy (2), VIK 2 (3), Nord (4), Laureat (5), Gorizont (6), Garant (7); spring rapeseed varieties: Vikros (8), Novik (9), Novosel (10), Veles (11), Grant (12), Podmoskovniy (13), Lugovskoy (14), Bizon (15). Winter turnip rape: Zarya (16); spring turnip rape: Nadezhda (17), Svetlana (18). H2O control (19). M – molecular weight marker (100 кb DNA Ladder).

The performed analysis demonstrated that it is possible to identify rapeseed varieties Grant and Novosel with 3 marker combinations (F11-Em2, F10-R7 and Me4-R7), and Gorizont and Lugovskoy – with 2 (F13-R9 and Me4-R7). Variety VIK 2 was identified with SRAP primers F9-Em2, and spring ones Veles – with F10-R7. Specific DNA spectra for rapeseed varieties Stolychniy, Podmoskovniy and turnip rape Nadezhda were obtained with F9-R8 combination

The obtained data were transformed into a binary matrix to calculate Nei’s genetic distances (Table 3). The lowest genetic similarity coefficient (0.7069) was found between rapeseed varieties Gorizont, Novosel and Grant, the highest – between spring varieties Vikros and Bizon (1.0) as well as Veles and Bizon (0.9655). A similarly high genetic distance (0.3228) indicated significant differences between pairs: Grant and VIK 2, and Lugovskoy and Stolychniy. Low distance values and high genetic similarity were demonstrated by spring varieties Bizon and Vikros (zero distance) and winter varieties Garant, Severyanin, Stolychniy, Nord, Laureat (0.0174).

Notе. According to the data of 1 (Rhouma et al., 2017); 2 (Сатина, 2010); 3 (Chandra et al., 2013).

The results of PCR analysis for SSR and SRAP markers were used to determine the genetic variability indices and build an UPGMA dendrogram depicting the varieties’ phylogenetic relationships. The variety material had a low degree of genetic heterogeneity, while higher values of expected heterozygosity (He) and the number of effective alleles (ne) were determined with SSR markers: 0.25 on average against 0.14 and 1.47 per locus if compared to 1.24, respectively. However, the SRAP method has enabled obtaining more PCR products applicable for varietal differentiation (Table 4).

Notе. No. 1–15 – rapeseed varieties Severyanin, Stolychniy, VIK 2, Nord, Laureat, Gorizont, Garant, Vikros, Novik, Novosel, Veles, Grant, Podmoskovniy, Lugovskoy, Bizon.

Analysis of the UPGMA dendrogram demonstrated that the winter/spring rapeseed varieties were divided into two distinguishable clusters (Fig. 4). The first one united such winter cultivars as Severyanin, Garant, Stolychniy, Nord, Laureat, Gorizont, VIK 2; the second – all the spring ones. In the winter cluster VIK 2 and Gorizont were the most distant from the other varieties. The distances between Stolychniy, Nord, Laureat as well as between Garant and Severyanin were much shorter, which was confirmed by their high genetic similarity indices being 0.9655 and 0.9828, respectively (see Table 3). The most distant among spring rapeseed were twozero varieties Novosel, Grant and Lugovskoy, which had the longest genetic distances in the cluster (0.3469 and 0.3228). Bizon and Vikros belonged to one subgroup, sharing a common branch of the dendrogram.

The bulk strategy of DNA sampling from 30 germinants per variety has significantly reduced the labor efforts and cost of the research if compared to the traditional method of individual sample genotyping. The method has proved its efficiency for different cultures especially in large-scale studies of vast populations (Liu et al., 2018). However, this approach is only justified if the analyzed set of samples is representative. For cross-pollinating species with a high level of intrapopulation variations, it should include at least 30–50 plants per variety, which significantly increases the likelihood of registering a rare alleles, the occurrence of which in the population does not exceed 10 % (Crossa, 1989; Semerikov et al., 2002). The plants of winter rapeseed are known for their high self-pollination capacity (up to 70 % of flowers) (Shpaar, 2012), many varieties are linear; while in spring rapeseed this capacity reaches 40 % (Osipova, 1998). That’s why in our study we used budk samples that combined 30 seedlings from each variety.

A significant part of SSR primers tested in our study generated monomorphic amplification fragments. They did not allow us to properly estimate the genetic variability and had low reproducibility in replicated experiments. A proportion of the markers proven effective for intervarietal DNA polymorphism detection comprised 16.7 %, being much lower than in other studies (Plieske, Struss, 2001; Hasan et al., 2008; Tian et al., 2017). It was probably due to the composition of the tested collection that had a narrow genetic basis considering the varieties’ pedigree. At the same time, such parameters of genetic variability as the number of allelic variants, singleallele frequency, PIC and He were comparable to those found in published data (Satina, 2010; Klyachenko et al., 2018).

In general, the used markers made it possible to detect DNA polymorphism between rapeseed and turnip rape as well as between the winter and spring varieties within each species. However, Na12A02 marker turned out to be variety-specific for Bizon winter rapeseed and Zarya spring turnip rape, and Ra02-E01а – for VIK 2 winter rapeseed and Svetlana spring turnip rape. The unique alleles of Podmoskovniy and Lugovskoy rapeseed were detected using Ni02-D08a loci. The indicated markers can be used for varietal DNA identification and genetic certification.

SSR primers for the markers of Indian mustard’s Alternaria blight resistance genes (Chandra et al., 2013), such as Ni02- D08a, Ni03H07a and RA02-E01a, proved to be the most effective. Their application enabled us to detect the specific amplification fragments for linear winter rapeseed variety VIK 2. They also proved effective for Gorizont, which had been obtained on the base of VIK 2 by seed freezing followed by their selection at low-temperature stress. These two varieties share high winter hardiness and are resistant to Alternaria blight. Thereby the results of our study can be useful for further selection of perspective breeding material and QTL analysis on disease resistance.

Among the spring rapeseed, Veles variety turned out to be substantially different while Lugovskoy and Garant had many similarities in the studied microsatellite parts of regions of the genome. Veles is a new perspective variety that has been approved for use since 2021 and was selected based on Vikros using the method of chemical mutagenesis, producing a high frequency of nucleotide changes. This is possibly the reason for Veles having unique alleles in three loci: Ni2C12, Ra02- E01a, Na12A02. For Vikros variety, a specific DNA profile was also obtained with Ni2C12 marker.

Rapeseed Grant was selected using the method of interspecies and intervarietal hybridization of early-maturing foreign breeding samples and the high-yielding varieties Lugovskoy and Vikros, developed at Federal Williams Research Center of Forage Production and Agroecology. Their common origin is probably the reason for the genetic similarity found between Grant and Lugovskoy varieties.

In general, SSR analysis failed to achieve optimum effect in identification of the investigated varieties: from the total set, including 42 primers for microsatellite genome loci, only four were attested as variety-specific for rapeseed, and only one (Ni03H07а) – for Nadezhda spring turnip rape.

For further investigation of DNA polymorphism, SRAP analysis was applied. SRAP is the third generation of molecular markers that were initially designed for the genes of B. oleracea L. (Li, Quiros, 2001) and are successfully used these days for genetic variability estimation and genetic mapping in different plants (Aneja et al., 2012; Rhouma et al., 2017; Liu et al., 2018). This is a cheap, effective and highly reproducible technique

2017; Liu et al., 2018). This is a cheap, effective and highly reproducible technique

The final dendrogram of phylogenetic relations made it possible to visually estimate the degrees of genetic similarities and differences of the studied material. For instance, close placing of such rapeseed varieties as Stolychniy, Nord and Laureat was probably determined by the features of their origin: they were selected for winter hardiness from a combination, in which one of the parental forms was Promin’, a well-known winter rapeseed variety

Garant, selected for winter hardiness, and Severyanin, which was obtained by seed freezing in a climatic chamber and the following individual-family selection, turned out to be in the common subgroup and at a short genetic distance (0.0174) from each other. In addition to high winter hardiness, these varieties are resistant to lodging and to damage by pathogenic fungi

A two-zero spring variety Novosel takes a special position in his group (Nei’s distance is 0.3469). Novosel was developed based on the foreign breeding samples and Russian varieties Lugovskoy and Vikros, characterized by early maturing and high yield. Specific properties of the new breeding achievement are shorter maturation period in comparison to standard varieties and high resistance to Alternaria blight.

Spring rapeseed Bizon and Vikros take the common branch of the dendrogram. The varieties were developed using the method of interspecies hybridization but from different parental forms; characterized by high yield productivity, early maturation and low glucosinolate content.

The presented study has proved the efficiency of SSR and SRAP markers for estimation of DNA polymorphism in rapeseed and turnip rape varieties developed in Federal Williams Research Center of Forage Production and Agroecology. During the study, SRAP technique has demonstrated a higher level of informativity: 36 % of the tested markers were polymorphic, while for the microsatellite loci this rate did not exceed 16.7 %.

Both techniques of molecular analysis enabled detecting the DNA markers for identification of 10 out of 15 rapeseed varieties tested and for 2 turnip rape samples. Microsatellite loci Na12A02, Ni2C12, Ra02-E01 and Ni02-D08a allowed obtaining unique PCR products for Bizon, Veles, Vikros, VIK 2, Podmoskovniy and Lugovskoy rapeseed varieties. Marker Ni03H07а proved effective for identifying Nadezhda turnip rape. In the used SRAP test kit, such primers as F13-R9, Me4- R7, F11-Em2, F10-R7, F9-Em2 and F9-R8 proved effective for detecting variety-specific amplicons or obtaining unique DNA profiles for different types of plants (winter/spring) in rapeseed varieties Grant, Novosel, Gorizont, Stolychniy, Lugovskoy, Podmoskovniy and in spring turnip rape Svetlana.

The results of the study can be used for development of the perspective breeding samples and hybrids, for genetic certification and seed material purity control.

Conflict of interest

The authors declare no conflict of interest.

Agarwal M., Shrivastava N., Padh H. Advances in molecular marker techniques and their applications in plant sciences. Plant Cell Rep. 2008;27(4):617-631. DOI 10.1007/s00299-008-0507-z.

Amosova A.V., Zemtsova L.V., Grushetskaya Z.E., Samatadze T.E., Mozgova G.V., Pilyuk Y.E., Volovik V.T., Melnikova N.V., Zelenin A.V., Lemesh V.A., Muravenko O.V. Intraspecific chromosomal and genetic polymorphism in Brassica napus L. detected by cytogenetic and molecular markers. J. Genet. 2014;93:133-143. DOI 10.1007/s12041-014-0351-6.

Ananga A.O., Cebert E., Ochieng J.W., Kumar S., Kambiranda D., Vasanthaiah H., Tsolova V., Senwo Z., Konan K., Anike F.N. Prospects for transgenic and molecular breeding for cold tolerance in canola (Brassica napus L.). In: Akpan U.G. (Ed.). Oilseeds. London: IntechOpen, 2012;108-129. DOI 10.5772/32721.

Aneja B., Yadav N.R., Chawla V., Yadav R.C. Sequence related amplified polymorphism (SRAP) molecular marker system and its applications in crop improvement. Mol. Breeding. 2012;30:1635-1648. DOI 10.1007/s11032-012-9747-2.

Chandra V., Pant U., Bhalan R., Singh A.K. Studies on genetic diversity among Alternaria blight tolerant Indian mustard genotypes using SSR markers. Bioscan. 2013;8(4):1431-1435.

Chen G., Geng J., Rahman M., Liu X., Tu J., Fu T., Li G., McVetty P.B.E., Tahir M. Identification of QTL for oil content, seed yield, and flowering time in oilseed rape (Brassica napus). Euphytica. 2010;175:161-174. DOI 10.1007/s10681-010-0144-9.

Chesnokov Yu.V. Genetic markers: comparative classification of molecular markers. Ovoshchi Rossii = Vegetable Crops of Russia. 2018;3: 11-15. DOI 10.18619/2072-9146-2018-3-11-15. (in Russian)

Chesnokov Y.V., Artemyeva A.M. Evaluation of the measure of polymorphism information of genetic diversity. Agric. Biol. 2015;50(5): 571-578. DOI 10.15389/agrobiology.2015.5.571eng

Crossa J. Methodologies for estimating the sample-size required for genetic conservation of outbreeding crops. Theor. Appl. Genet. 1989;77:153-161.

Dellaporta S.L., Wood J., Hicks J.B. A plant DNA mini preparation: Version II. Plant Mol. Biol. Rep. 1983;1(4):19-21. DOI 10.1007/ BF02712670.

Gao M., Li G., Yang B., Qiu D., Farnham M., Quiros C.F. High-density Brassica oleracea map: Identification of useful new linkages. Theor. Appl. Genet. 2007;115(2):277-287. DOI 10.1007/s00122- 007-0568-3.

Geng J., Javed N., McVetty P.B.E., Li G., Tahir M. An integrated genetic map for Brassica napus derived from double haploid and recombinant inbred populations. Hered. Genet. 2012;1(1):103. DOI 10.4172/2161-1041.1000103.

Hasan M., Friedt W., Pons-Kühnemann J., Freitag N.M., Link K., Snowdon R.J. Association of gene-linked SSR markers to seed glucosinolate content in oilseed rape (Brassica napus ssp. napus). Theor. Appl. Genet. 2008;116(8):1035-1049. DOI 10.1007/s00122- 008-0733-3.

Khlestkina E.K. Molecular methods of analysis of structural and functional organization of genes and genomes in higher plants. Vavilovskii Zhurnal Genetiki i Selektsii = Vavilov Journal of Genetics and Breeding. 2011;15(4):757-768. (in Russian)

Kirby K.S., Cook E.A. Isolation of deoxyribonucleic acid from mammalian tissues. Biochem. J. 1967;104(1):254-257. DOI 10.1042/ bj1040254.

Klimenko I.A., Kostenko S.I., Mavlutov Yu.M., Shamustakimova A.O. The efficiency of SSR-and PawS markers for genetic polymorphism evaluation of red clover (Trifolium pratense L.) varieties. Trudy po Prikladnoy Botanike, Genetike i Selektsii = Proceedings on Applied Botany, Genetics, and Breeding. 2020a;181(3):100-109. DOI 10.30901/2227-8834-2020-3-100-109. (in Russian)

Klimenko I.A., Kozlov N.N., Kostenko S.I., Shamustakimova A.O., Mavlyutov Yu.M. Identification and Certification of Forage Grass Varieties (Red Clover, Sand Alfalfa, Common Alfalfa, and Black Medick Alfalfa) on the Base of DNA Markers: Methodological Recommendations. Moscow: Ugresha T Publ., 2020b. DOI 10.33814/ 978-5-6043194-9-9. (in Russian)

Klyachenko O.L., Prysiazhniuk L.M., Shofolova N.V., Piskova O.V. Polymorphism in spring and winter rapeseed varieties (Brassica napus L.) identified by SSR markers. Plant Var. Stud. Prot. 2018; 14(4):366-374. DOI 10.21498/2518-1017.14.4.2018.151898.

Kosolapov V.M., Shamsutdinov Z.Sh., Kostenko S.I., Pilipko S.V., Tyurin Yu.S., …, Ivanov I.S., Saprykina N.V., Truzina L.A., Chuikov V.A., Georgiadi N.I. Varieties of Forage Crops Bred at Williams Federal Scientific Center for Fodder Production and Agroecology. Moscow: Ugreshskaya Tipografiya Publ., 2019. (in Russian)

Lemesh V.A., Mozgova G.V., Grushetskaya Z.E., Sidorenko E.V., Pilyuk Ya.E., Bakanovskaya A.V. The use of specific DNA markers for the identification of alleles of the FAD3 genes in rape (Brassica napus L.). Russ. J. Genet. 2015;51(8):765-773. DOI 10.1134/ S1022795415080049.

Li G., Quiros C.F. Sequence-related amplified polymorphism (SRAP) a new marker system based on a simple PCR reaction: its application to mapping and gene tagging in Brassica. Theor. Appl. Genet. 2001;103(2):455-461. DOI 10.1007/s001220100570

Liu S., Feuerstein U., Luesink W., Schulze S., Asp T., Studer B., Becker H.C., Dehmer K.J. DArT, SNP, and SSR analyses of genetic diversity in Lolium perenne L. using bulk sampling. BMC Genetics. 2018;19(1):10. DOI 10.1186/s12863-017-0589-0.

Mozgova G.V., Khoruzhy N.E., Amosova A.V., Pilyuk Ya.E., Belyavskiy V.M., Khramchenko S.Yu., Muravenko O.V., Lemesh V.A. Genetic polymorphism of Brassica napus related to cold tolerance. Molekulyarnaya i Prikladnaya Genetika = Molecular and Applied Genetics. 2019;26:34-44. (in Russian)

Nei M., Li W.H. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. USA. 1979;76(10):5269-5273. DOI 10.1073/pnas.76.10.5269

Osipova G.M. Rapeseed in Siberia: Morphological, Genetic, and Breeding Aspects. Novosibirsk: Siberian Branch of the Russian Academy of Agricultural Sciences, 1998. (in Russian)

Piquemal J., Cinquin E., Couton F., Rondeau C., Seignoret E., Doucet I., Perret D., Villeger M.-J., Vincourt P., Blanchard P. Construction of an oilseed rape (Brassica napus L.) genetic map with SSR markers. Theor. Appl. Genet. 2005;111(8):1514-1523. DOI 10.1007/s00122- 005-0080-6.

Plieske J., Struss D. Microsatellite markers for genome analysis in Brassica. I. Development in Brassica napus and abundance in Brassicacea species. Theor. Appl. Genet. 2001;102(5):689-694. DOI 10.1007/s001220051698.

Rhouma H.B., Taski-Ajdukovic K., Zitouna N., Sdouga D., Milic D., Trifi-Farah N. Assessment of the genetic variation in alfalfa genotypes using SRAP markers for breeding purposes. Chil. J. Agric. Res. 2017;77(4):332-339. DOI 10.4067/S0718-58392017000400332

Rogozhina T.G., Aniskina Yu.V., Karpachev V.V., Shilov I.A. An application of microsatellite analysis for detection of biotypes from spring rapeseed cultivars (Brassica napus L.). Maslichnye Kultury. Nauchno-Tekhnicheskiy Byulleten Vserossiyskogo Nauchno-Issledovatelskogo Instituta Maslichnykh Kultur = Oil Crops. Scientific and Technical Bulletin of the All-Russian Research Institute of Oil Crops. 2015;2(162):27-33. (in Russian).

Rohlf F.J. NTSYS-pc: Numerical Taxonomy and Multivariate Analysis System. Version 2.10 manual. Applied Biostatistics. Inc. New York: Exeter Software, 2000.

Satina T.G. A protocol for genotyping based on microsatellite analysis in rapeseed (Brassica napus L.) breeding: Cand. Sci. (Biol.) Dissertation. Moscow, 2010. (in Russian)

Semerikov V.L., Belyaev A.Y., Lascoux M. The origin of Russian cultivars of red clover (Trifolium pratense L.) and their genetic relationships to wild populations in the Urals. Theor. Appl. Genet. 2002; 106:127-132.

Sharma M., Dolkar D., Salgotra R., Sharma D., Singh P.A., Gupta S.K. Molecular marker assisted confirmation of hybridity in Indian mustard (Brassica juncea L.). Int. J. Curr. Microbiol. Appl. Sci. 2018; 7(9):894-900. DOI 10.20546/ijcmas.2018.709.107.

Snowdon R.J., Friedt W. Molecular markers in Brassica oilseed breeding: current status and future possibilities. Plant Breeding. 2004; 123(1):1-8. DOI 10.1111/j.1439-0523.2003.00968.x.

Shpaar D. Rapeseed and Wild Cabbage: Cultivation, Harvesting, Storage, and Utilization. Kiev: Zerno Publ., 2012. (in Russian)

State Register of Selection Achievements Admitted for Use for Production Purposes. Vol. 1. Plant Varieties (official publication). Moscow: Rosinformagrotekh Publ., 2021. (in Russian)

Tian H.Yu., Channa S.A., Hu Sh. Relationships between genetic distance, combining ability and heterosis in rapeseed (Brassica napus L.). Euphytica. 2017;213(1):1-11. DOI 10.1007/s10681-016-1788-x.

Volovik V.T. Brassicas: the Economic Importance. In: The Basic Species and Varieties of Fodder Crops: Results of the Research Activity of the Central Breeding Center. Moscow: Nauka Publ., 2015;249- 253. (in Russian)

Yeh F.C., Yang R., Boyle T.J., Ye Z., Xiyan J.M. PopGene 32, Microsoft window-based freeware for population genetic analysis, version 1.32. Molecular Biology and Biotechnology Centre, University of Alberta, Edmonton, Alberta, Canada, 2000.

Acknowledgments

The presented investigation was supported by the means of the federal budget, directed for performing the government assignment (project No. 0442-2019-0001АААА-А19-119122590053-0).

Contributor Information

I.A. Klimenko, Federal Williams Research Center of Forage Production and Agroecology, Lobnya, Moscow region, Russia .

V.T. Volovik, Federal Williams Research Center of Forage Production and Agroecology, Lobnya, Moscow region, Russia .

A.A. Antonov, Federal Williams Research Center of Forage Production and Agroecology, Lobnya, Moscow region, Russia .

V.A. Dushkin, Federal Williams Research Center of Forage Production and Agroecology, Lobnya, Moscow region, Russia .

A.O. Shamustakimova, Federal Williams Research Center of Forage Production and Agroecology, Lobnya, Moscow region, Russia .

Yu.M. Yu.M. Mavlyutov, Federal Williams Research Center of Forage Production and Agroecology, Lobnya, Moscow region, Russia .

• Find a journal
• Publish with us
• Track your research