Yield Monitors

(Jim Shroyer) Good morning folks, welcome to That’s My Farm. I’m Jim Shroyer, your host and we’re in luck because we are on the K-State campus and we’re talking to two great Extension specialists. Dr. Ajay Sharda, he is our AG Engineer and Terry Griffin, our Crop and Systems Economist. I think you are going to want to hear what they have to say about yield monitors. We’ll be back after these words from our sponsors. See you in a minute.Closed Captioning Brought to you by Ag Promo Source. Together we grow. Learn more at agpromosource.com.

(Jim) Welcome back to That’s My Farm, I’m Jim Shroyer. And let’s first talk with Ajay Sharda. Ajay, thanks for being with us, and Terry, you too, I’ll get to you in a second. Let’s talk to you a little bit about the history of yield monitors and where we were and where we are now. Take it away. (Ajay Sharda) Thank you, Jim, again. Well, the whole concept of yield monitors started in terms of farmers trying to understand what is the value of their land in terms of productivity in a profitability aspect of it. The general concept was that I am putting a uniform application of seed, fertilizer and pesticide and I was expecting a uniform yield as well from every inch or every meter square of my field. Now that is not the case, you know. (Jim) That’s not realistic. (Ajay) That is not the realistic case. We have a lot of variability, which can be due to many reasons; a historic aspect of how the farm has been, the aspect of soil types, the elevation, the topography, and all that aspect. Right around 2000 or late 99, ’90s and 2000, that’s where the GPS technology came in which could actually tell us where I am on my field. That is when people tried to use the technology called yield monitors. The concept was that can we understand or we can document the yield in terms of different areas in my field. I don’t want to put it aside; specific yield is a difficult thing or absurd thing to say. What I want to know is what are my high yielding areas and what are my low yielding areas and then if I have that information in front of me I can start to sit down and do some soil analysis, I can look at the drainage aspect, I can talk about the nutrients in my soil or the management aspect of it. I can start to understand what needs to be done so I can keep my high yielding areas performing consistently better but at the same time, I can raise the productivity and the yields on some of my low yielding areas. (Jim) Right. Not only productivity but the economics of those poor sites. You may not want to put on as much nitrogen or fertility on those low yield areas because they won’t respond. (Ajay) Absolutely. (Jim) You can then be a little more efficient. (Ajay) Right. This is one of the biggest things because there are a couple of things we are moving in time in terms of those farm operations getting bigger and bigger. We have less number of people who are operating those farms. We need a lot of information in terms of how my fields are doing so that I can make a very informed decision in terms of input management. The cost of seed has gone up. The cost of fertilizer has gone up and so does the pesticide and herbicide aspect of it. But the thing is that I really want to understand what the needs of my field are. At the same time, I don’t want to over-apply something because some of the things can be out of my field impacting the environment and which is my money going leaving the field part of it. (Jim) Okay. Ajay, we are going to take a break so stay with us. Folks stay with us we’ll be right back after these words from our sponsors. See you in a minute.

(Jim) Welcome back to That’s My Farm. I’m Jim Shroyer, and with us, we have Ajay Sharda and Terry Griffin and we are talking about yield monitors. Ajay, you get a combine has that yield monitor on it and you go out to the field and start cutting. There’s more to it than that, right? You got to set it up, there’s some calculations or calibrations that you have to do. (Ajay) Right. And then I would like to talk a little bit about how, if somebody has a combine there are certain aspects, there are certain sensors, which are helping the producer in terms of documenting the right data for him. (Jim) Getting good data. (Ajay) Getting good data, yes. There are two or three components, which are very critical for us. One component is the aspect of the sensor, which is measuring the grain flow rate. How much grain has flown into my grain bin every certain unit of time. Say one second, two second, or whatever the time may be. Apart from that, there are other aspects which we need to set it right, there is the ground speed sensor. Mostly the speed is coming from my GPS receiver. I already have my header width input into my monitor so now my com, my grain monitor knows or my controller knows at how much distance I have traveled per second it multiplies by my header width and calculates the area I have harvested and then it goes back and looks at the amount of grain which has hit the sensor into the bin to calculate the amount of bushels harvested per acre. (Jim) Or in that area in total, eventually acres. (Ajay) Right. It calculates in that manner but it displays in the fashion in terms of bushels per acre harvested from that area. (Jim) Right. You also have to put in – I didn’t realize this – you have to put in the time it takes from the time grain enters the combine to the time it hits. (Ajay) Absolutely. (Jim) So you have to, what is an average time, five seconds? (Ajay) Well, it’s a little more than that. Well, if you will sit in the com you can very easily see what happens and the whole aspect is when you start to get into the headland, start harvesting grain, it has to move all the way from the header into the threshing cylinder in the cleaning aspect through the auger back to the bin, back to the grain bin that is where it starts to sense. When you get into the headland and start harvesting, the delays are in the range of 12 to 14 seconds, the same thing happens when you exert all of the headland because my cleaning system and harvesting system is full of grain, it’s going to still keep doing the whole aspect. Even if I have gone out of my harvesting zone it’s going to still keep dumping the grain in the grain mill for the next six to eight seconds aspect of it. I also want to talk about a couple of other things; the moisture sensor, which also has an inbuilt temperature sensor, is one of a very important aspect in calculating the yield in terms of bushels to be marketable. We have to have that sensor clean and calibrated so that we can document the data in a right manner. (Jim) Okay, thanks Ajay. Folks, we’ll be right back after these words from our sponsors, see you in a second.

(Jim) Welcome back to That’s My Farm. I’m Jim Shroyer and with us we have Ajay Sharda and Terry Griffin. Now it’s Terry’s turn to talk to us a little bit about what do we do with that data because it’s, I wouldn’t say it’s real clean, it’s not as clean as the grain going into the bin. You’ve got to do a little – (Terry Griffin) It’s messy. (Jim) – messy data. (Terry) Yield monitor data is messy data. Ajay was just talking about how to set up the combine for collecting grain in good data in the field. Well, even if that’s set up properly we’ve got a lot of errors that we need to address and that is that the yield monitor can only collect good data under a certain range, in a range that it was calibrated for. If anyone’s ever looked at yield monitor data you’ve probably seen some jagged edges around some features in the field, one way of looking at this is, I say it’s out of focus and we need to change the flow delay, we’re just talking about the 12 to 14 seconds on average that takes grain from being at the head to the plate to be measured. Well, that’s usually off a little bit and we need to adjust that flow delay settings, the primary thing we need to do. There’s some other things too that we need to worry about but all these things are really important because my research shows that about say 70% of time when we’re doing an on-farm experiment that we do not clean the yield monitor, data will arrive at a different conclusion or different production farm management decision between cleaned and uncleaned data. (Jim) That’s when you run into the situation where they say no data is better than bad data. (Terry) I would agree with that, yes. We come to the wrong conclusion, make the wrong decision based upon data. (Jim) Okay. When you talk about clean the data what do you exactly mean, it’s not like cleaning grain? (Terry) No. We’re not modifying the data to rather a predetermined conclusion but what we want to do is relocate observations to what they’re supposed to be, maybe we do the flow delay setting but about a fourth of the yield monitor data points are measured erroneously or they’re recorded under situations where the combine and yield monitor cannot make accurate measurements. We’re not saying this yield monitor data point is low or high or getting rid of it, that’s not the philosophy we’re using. We’re using the philosophy that we’re trying to detect points that were measured when the machine could not make accurate measurements such as speeding up or slowing down or being driven too fast or driven too slow and that we’ll stop to decisions. (Jim) Okay. Hang on here a second. Excuse me here. Let me start this. Okay, Ajay. (Ajay) Terry has brought up a really good point on when you’re in the field, you’re really required, recommended or required to drive the common way at a certain speed because that is the ideals. It’s not about the ideal speed as well but you want a constant flow, a uniform flow of grain into the grain bed so that you can make a better estimation of yield in the field. When you really speed up or slow down those certain changes in the speed is where some of those erroneous points come onto the data part. (Jim) What do you do with those data points? (Terry) We can detect when the machine is speeding up or slowing down too quickly. We get rid of them. We’ll omit them from any further analysis. We flag them and delete them from that data set before we use this for management decision-making. (Jim) We’re not talking about a whole lot. I guess you said 25% but it’s just a few seconds at a time basically. (Terry) These are very localized. It’s not chunks of data in any part of the field so most yield monitor data has 50,000 observations. We cleaned it. We may lose 10,000-15,000 observations. We still have a lot. (Jim) We got to take a break. Folks, we’ll be right back after these words from our sponsors.

(Jim) Welcome back to That’s My Farm. I’m Jim Shroyer and with us, we have Ajay Sharda and Terry Griffin. Terry, let’s continue that post-harvest cleansing of the data. Let’s talk about what to do with the data. (Terry) Sure. Well, once we have yield monitor data, especially if we have multiple years of data, it’s time to look at multi-year yield analysis. Looking for areas of stable highs, stable lows, areas of unstable yield that may have high yielding areas in some years and some years below yielding areas or special– (Jim) That makes you scratch your head. (Terry) We can make some very complicated models really quickly. That’s the big barrier with precision AG data right now. It’s not intuitive of how to use. It doesn’t make life better. It gives you more opportunity if you’re ready to make those hard management decisions. One of the most common uses of a yield monitor is to conduct on-farm experiments. We have some statistics to back this up and we want to make a good point that it’s really important to have clean data because my research shows that about 70% of the time, if you have on-farm experiments and you don’t clean the data, you’ll arrive at a different farm management production decision than if you had cleaned that data. That could lead to the idea of no data is better than bad data. (Jim) Okay, so Ajay? (Ajay) Well, Terry has brought up a great point about doing on-farm experiment. I would say apart from that, some of the large producers who are collecting multiyear yield data. They are getting better and better in terms of understanding the performance of their farms and where are some of the more productive, more consistently productive areas versus others. They have been able to manage some of the areas, which were not doing better over the years and there have been few areas which are not manageable. There are aspects which can be managed and there are aspects which cannot be managed but they have really driven the aspect of input management, the aspect of variable-rate seeding. We talked about how can we maximize the yield aspect of it so people have started to go the route of variable-rate seeding, to go the route of variable rate, and nutrient management. All this is driven by the cost and profit aspect, which Terry talks about it all the time. It’s all about bottom line. Those things are very, very critical and I also want to bring back another point, which Terry talks about in terms of the data part of it, is a lot of farmers ask us a question that, “Can I use a scale ticket to clean or to remove the errors? If I haven’t calibrated my combine can I use that data to fix?” Our answer unanimously is, no. (Jim) No. I wouldn’t think so. You’ve got this high-tech information here. Let’s use it. (Terry) There’s a myth that says if my yield monitor data averages are the same or close to my scale tickets, it must mean that my yield monitor data is good. (Jim) I wouldn’t think that’s correct. (Terry) It’s not correct. (Jim) Hang on here. We got to take a break so folks, stay with us. We’ll be right back.

(Jim) Welcome back to That’s My Farm. I’m Jim Shroyer. Ajay and Terry haven’t run off during that last break so Ajay, tell me how can farmers use this data. They’re collecting it. They’ve collected for years. How can they get the biggest bang for the buck out of this data? (Ajay) First and foremost is that they have to collect good quality data. That everything starts with making sure your yield monitor and all those components associated with these are perfectly in line in terms of calibration, your yield monitor, impact craters calibrated, your speed aspect is calibrated, your moisture sensor is calibrated and you have a good GPS receiver on top of it so that you are collecting good quality data which can be then utilized to do the magic in terms of software which probably taken- [crosstalk] (Jim) The magic huh? (Terry) The magic. (Jim) The magic in that software. [Laughs] (Terry) Yes. There’s a lot of magic. (Ajay) Right. (Terry) Producers have a lot of options when it comes to software and are traditionally been desktop or laptop – (Jim) Right. (Terry) – installed software but now there’s also cloud-based systems as well. Lots of opportunity there. A big question between the two is it’s a matter of trust when a farmer wants to keep their data locally and in control of it on a laptop with locally installed software is sort of the answer. (Jim) Not the cloud. (Terry) Not the cloud, but for those farmers who do have trust in the systems and in their trusted advisors then the cloud-based systems offer a lot of advanced opportunities which give a long benefit from. That leads to the next point, the elephant in room: data ownership. This is a question that we’re addressing pretty often. It’s not one that’s been resolved in the industry. There are a lot of legal aspects of it in economic aspects of data ownership. The fact is our current laws have not kept track with the technology. (Jim) But you would have to say that we’re a long ways from all the producers utilizing that data. (Terry) Sure. There’s a lot of opportunity to use data. There’s also some dependence that the farmer gives up when they start sharing data from their production in their acreage in the community or even with trusted advisors. This is a barrier in the industry right now. Because it’s not easy. Automated guidance would’ve made life a little bit easier, not as tired at the end of the day. Yield monitors cannot say that. Adding data to an operation doesn’t make the operation run smoother if the manager, the farmer, is not ready to make use of that data. (Jim) Right. Not using that. Right. Folks, thanks for being with us on this episode of That’s My Farm. Don’t forget about the same time next week we’ll have another one. See you then.

Closed Captioning Brought to you by Ag Promo Source. Together we grow. Learn more at agpromosource.com.

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