Video Presentation Speakers
Martin Correa-Luna - Dairy Research Scientist Dairy Up (University of Sydney)
Josh Hack - dairy farm agronomist and Dairy Up technical officer
Chloe Wilson - Dairy Up technical officer
Pat Neal - Oxley Island (farm owner)
Allen Hook - Oxley Island (farm manager)
Peter Beale - NSW Land Services - Tocal
Video Presentation Transcript
Martin:
So for P1 A. We know that the dairy grazing systems in New South Whales are typically pastures that are temperate pastures throughout winter and then which are high-yielding and have very good nutritive value. And then they switch to Kaikuyu in summer, and that gives us seasonality in pasture production.
Martin:
Composition and also nutritive value. And that on top of that, if we have the weather, then the pasture growth changes very rapidly. And that is a limitation or becomes a limitation or a problem or a challenge for the farmers to just manage pasture properly. Any farmer wants to allocate feed accurately to cows just to increase pasture production. And milk production too. So management needs to be taken in order to monitor this pasture to have accurate information.
Martin:
From P1 A, our angle is to use remote sensing technologies just to see if we can improve if we can manage these pastures and also if we can assist farmers with new tools. To just ease this management.
Martin:
As we heard from yesterday, from the farmer from this farm (where the presentation is held), the owner of this farm. He was switching to a total mixed ration (TMR) system because he says that managing pasture here is really complicated and it's a challenge. So our case is to try to assist farmers for those that are deciding to stay on grazing their system. So our approach is the following. So we have 14 farms distributed on the coast of New South Whales. Then we have three, four. Sorry, four wonderful technical officers. We have Chloe, Josh and Zack over there. And then we have Jaco in Tocal who couldn't make it today. And those farmers are working with us. In this project.
Martin:
We are taking measurements on the ground. On a weekly basis, we are collecting Sentinel images from satellites, and also we are using Pasture IO. That is a well-positioned tool that is in the industry just to monitor pasture for decision-making.
Martin:
So now I'm going to hand it to Josh.
Josh:
Thanks, Martin. Thanks, everybody. My name is Josh Hack, and I'm an agronomist local around Taree who go up and down the coast, but I've been lucky enough to be involved with the P1 project.
Josh:
Along with Zac and Chloe. Chloe's doing down the South Coast. And as we can just see on here (presentation slide) just to try and get a bit of an image around it, we're here on the mid-coast, here. We've got four farms here. We've also got one down in the Hunter. Okay. And we've also got five farms down at Bega, and we've got four farms up around the Lismore area. Okay. So that's where the data's come along. And I think that's a really special part is that this is probably, you know, some research. That's being done right up and down the areas of the dairy areas, not just all done in one single spot, you know, in the past, possibly in Camden or at a University. So this is actually being done on farms and getting real information of what farmers are actually doing. So I think that's a really big, positive.
Josh:
Martin's already explained about the stuff that we're trying to do and all that sort of stuff. So, all I wanted to do now is just quickly, we're going to give an example and talk to Pat Neal and Allen Hook, who are local dairy farmers here at Oxley Island.
Josh:
But before we go there, I just wanted to point out that we have different, you know, we've got a good example here of a farmer that has been using this technology. And where they’ve been going with it and what it means to them on their farm and where you know, the potential is going forward. But we want to stress that, you know, it's not the same for everyone, and everyone uses data differently and everyone use it, you know, in different ways.
Josh:
So you know, we all have different decision pathways, the way we want to go about and make those decisions. And I'll and even in the project, we have farmers that are, you know, really wanting to get on board and have a crack at it and then some that have, you know, struggling a bit more because, you know, they want the actual data. So there's a different sort of thing because what we do know is its early days and when the data isn't 100%, right? Sometimes some people that think differently, you know, really want that perfection. They want to know exactly how many kilos it is and all that’s the stuff. And the fact is we don't know at the moment, right. So that's why research gets done. So we can try and improve these things. Okay. But trying to get the exact number and get that right. And that data means something to them. And then they don't get the confidence in it. So they sort of go, I don't want to use it. Okay.
Josh:
Whereas someone like Pat and Allen, and that are probably more along the lines that they're not too worried about the actual number or the perfection of it. They're trying to use it as another tool in their business to help them make more informed decisions. Okay. So they say, well, we're using it as a guide. And gives us trends. So it gives us trends across the farm, across products, within products and also across time. Okay. So are things improving or they slowing down? And that gives us information we make better decisions on. Okay. So some people we know require that accuracy. Like I said, and some people can just do things with concepts.
Josh:
And one thing I've learnt with farmers. And I was, you know, early on in my career, I actually enjoyed data and I enjoy making things and like, it's really cool when you can get the exact data and draw some graphs. And everything looks perfect. But we know in farming we can't always make decisions based on all those numbers and all that stuff because sometimes they're a bit rubbery. But if we can get concepts and yeah, for me, feeding pastures for profits is one of those things where there's a lot of concepts that really make change on farm. Okay. That farmers can make really big decisions about by using concepts rather than actual numbers or data. Okay. And you guys, as farmers doing that every day that you do, okay. So I just wanted to get to that.
Josh:
And the other one is, you know, from that sort of side is, you know, the challenge of experience. So I've got experience that I think that their cows are reading 'X'. But now I've got this program that someone's asking me to use and it's saying, it's 'Y'? Okay. And there's that challenge of going, oh, I think it's wrong. I think it's right or etc. Rather than sort of going, well, even if it is wrong, can I use that information for something in terms of a trend and a concept rather than having to worry about challenging that you know, is it right or wrong all the time. And then there's the model. Like I'm saying. And then somewhere in there there's an actual right. And that actually was always changing. And in some way there would be an actual that would be ideal. But what we also know is, you know, the model might be right sometimes. And your gut feeling or your experience will be right sometimes. But to me, it's about having some objective information that can then help you make better decisions in more informed decisions.
Josh:
So without more to do I want to invite Pat and Allen up. So, Pat Neil owns a dairy farm at Oxley Island, only about 25 minutes from here on the coast and been dealing with a lot of water very similar to like Sam Nicholson you seen there yesterday. Over the last two years, and Allen is the farm manager there with Pat as well. So.
Josh:
I'm just going to, you know, hand it over to Allen now, okay. And I'll help Allen. We'll talk about what they've been using this information for. Okay. So we just got some snapshots of the app that is Pasture IO it's called that Allen and Pat have been using during the project again. Like I said, we're early days running twelve months into this, but I think there's a really good story here to tell about how these guys have been working together on their farm and how it's been coming out for these guys. So, Allen, I'll hand it over to you, mate.
Allen:
Hey, how are you going guys. One thing is really. Like about it is the map. You can see the different colors. The blue is paddocks that are ready to graze. The Orange ones that sort of just being grazed. And the green one is at your pre cover.
Josh:
The good thing about this, this was last week when we done it and there was a lot of silage cut. So that's why we've got a lot of orange paddocks. Okay. So we had a lot of wet conditions we couldn't get on to cut silage and things were getting past their best. So a lot of paddocks got cut at once and Pat worked pretty hard the weekend before his wedding to get it all off. Pat also got married on the weekend too congratulate him as he's going around. That's one of the reasons why the paddocks they're all orange like that.
Allen:
Yep. And the paddocks we currently have the outs of silage at the moment is this blue one here. What's the other one. Yeah. And one thing too is I really like about it is the pasture feeds wedge where you actually set your pre-cover. There's four things to get your pre cover numbers, your stocking rate. Your leaf stage. Yeah. How quick you're going around and your residual. You do all those calculations, and that will give you your pre cover where you want to target at and you can say that these paddocks here, they're reaching pre cover. You can see we're starting to drop below the target cover line. And hopefully once we graze these ones, these ones will get up to that target line. Otherwise, if we start falling below, that's where we've sort of got to start adding something to the diet, like probably an extra kilo of grain.
Josh:
Just to back that up. Like I think this target thing of being able to just click on a paddock and then work how many feeds we have based on some objective data. Is really, really cool. So moving forward once we do do that, you want to explain now, what this this photo here is.?
Allen:
Yep. There's a new update they've just done is the target rotation. You can actually you can filter it by day and night. That's actually filtered by paddock E42. You can click on it and it'll actually tell you, by your target rotation. That's how many that's how many feeds are in that paddock. And that's pretty much gives you a rough estimation of kilograms of dry matter per cow. You can actually look here too how many days ago that will graze and we're grazing it 16 days ago. Another good thing, too. When Pat gets around, he does a lot of fertilising and I can look on there too. And it'll actually tell me that if we've got a withholding of twelve days on the fertilizer. And I can say, Well, you know, like we've got fertiliser on it and we can't accidentally put cows in there.
Josh:
Yeah. And just to come back up on that. So if they've got a twelve day with holding period on that fertiliser or chemical that they put into the system when they do it. Okay. These bars around that paddock will turn Orange. So you actually recognise that paddock is still within withholding and also in the paddock view, it'll come up around the paddock as an orange bar as well.
Josh:
Just so that that safety point of view from nitrate poisoning or other chemicals getting into the milk and etc etc. It's really good as a safety option to be able to put in there as well. So just to before we come off to this one, I think it's really important, this target rotation. And this is what I think's really, really good about this project. It's not just about, you know, us using someone's software and then these guys having to crack at it. What it's really good about is this has actually been put in there because of feedback from farmers.
Josh:
Okay. So as Allen said before, he would have to do all his number crunching and working at how much grass he had divided by the days work out how many cows he's got try and work his fence areas. The system actually knows all that. So we've given some feedback to them. They've taken that on board, and within two weeks, they put this in there. And this basically here is very similar to if anyone's used the Rotation Rght tool. Okay. Also takes that sort of stuff into account. So now we've got a bit of a digital way of doing it rather than and that's we're going to talk about next is how this digital stuff, you know, being able to access it better in the paddock. Thanks, Allen.
Josh:
Yeah, well. At the end of day, all these things are just tools and everyone can choose what tool they want to use, the feeding pastures for profit (FPFP) concepts and the way they do and just quickly Allen, I'll get you to mention or Pat. You know the importance of these tools, but they still got to use their skills. Okay. So this isn't an autopilot, such a thing where you'll forget and get. But these guys are still got to train themselves train their workers all that sorts of stuff so they can look at the residuals. They can look at the pre cover, they can set what they want in the app based on what's happening in real time. Okay.
Pat:
Yeah, we agree with that.
Josh:
So just moving forward now. So, you know, I think what we want to do here is just sort of just a couple of things that we think that we've got change. Not from a data sense, but from a management point of view and where these guys are at from twelve months ago, when we implemented where we were at so Pat do you want to give us a call about, you know, obviously your skill sets and you've been using rotation right tool for years. But then over the last twelve months, you've progressed to this sort of thing (Pasture.io).
Pat:
Both Allen and myself have done the pasture for profit program and the basic skills of using that and using leaf appearance to manage our pasture. And previously we've used like plate meters. We've used scanners on motorbikes to use for our help us with our management. So basically. When we're doing that, we're looking at growth rate and average pasture cover. So, if that's lifting or getting faster, we know we can start planning for what we do. And so this is what two of the main figures that I look at. And it'll give me the growth rate and the average cover so I can see where I am, where I'm planning, how much I need to be moving forward.
Pat:
And I guess it's the same with Allen, like we're looking at these numbers and allocating the feed and one of the things we've just done. We're looking at it and it was the issue we have and we talk about it and I guess it is that skill from the pasture from profit program and knowing what to look for, with the residuals in paddocks and I noticed I said to Allen, I said, well, it looks like they're eating it down too low. And so we've gone, well, we've got them allocated seven kilos I think of grass morning and night. And the residual was set at 1500. And they were cleaning it down to that. And I guess what I saw was they were eating into the clumps. So we've said, Well, let's try and move that and we'll give them another kilo a day, both morning a night, and I guess what we saw was some movement in milk. And so but we did see that they did leave, with that extra kilo, they did leave a lot more residual. So we dealt with that. So then we reduced it back to half a kilo, morning, a night, and they're cleaning it up. And I guess those kind of figures, like, when you look at that, I think it's close to a litre and a half a cow. And that's just money in the back bank and the cream in the crop. So I guess what this gives us, this is the conversation started to start making good decisions on the farm.
Josh:
I know Allen, yourself. Obviously very now involved like I know early on when I used to come to your farm, it was obviously driven quite a lot by Pat. And now it looks like, the reigns have been handed over, but I see a lot more confidence, Pat, you have in Allen. And you know Allen as well. You can use this thing remotely now rather than having to go back to the dairy and use the dairy computer and work everything out.
Josh:
Allen rings me on his holidays and you know, talks to me about the grass that's grown because he's using the app and making some decisions even when he's on holidays for the workers as well.
Pat:
I guess one of the other apps we use is Field Margin. And what Allen does is he able to say if there was a paddock.
Pat:
One of these paddocks and we're getting three days out of it. He's we know the area, and he can break it up for them into three equal sections and allocate the strip. And then they've got to put the fence, out where it's showing. That was one of the things my father had like. Growing up was one of his main complaints. The cows had gone to a paddock and they'd lift in milk, which was supposed to get three days and then the following two days they've got half the allocated feed in the first day and then the rest got split in half. So, it takes a lot of the guess work out of it for people and it just makes it and it is it's just taking the guesswork out of it. And. We're a lot more accurate. We're probably being quite fortunate that we've had some breaks in the weather and being able to really take advantage of that and have confidence to cut the silage. Yeah. We've done a lot more planning. Ordered stuff. Ordered silage wraps. So that we're fully organized in what we're doing.
Josh:
Yeah, beautiful. And just to finish up I think you know. The building confidence and the challenge and the decisions. And I see that a lot more now between you two, and when I'm out there, I'm able to I'm going to out to measure the grass for the project, but I can send them photos. I can look on the app as well and know exactly when it was grazed. Okay. So for me, for information, if I'm going out as an advisor, I've got all the information at my fingertips. I don't need to ring Pat and go, when did you graze that product? And he goes well, last week, when the tractor fell off the tire broke or you know, because usually what you've done to something that went wrong or etc. So you know, you're not sort of guessing when you last grazed those paddocks. It's all there at the touch of a button. And you know, the fact that Allen can go out there and make informed decisions while he's in the paddock and not have to go back to the dairy. Sit down, take time out. I think it's another one.
Josh:
So, that's it from up here. So we're gonna hand over to Chloe now just to give a bit of an overview of what's going on down on the South Coast as well
Chloe:
Hi, everyone. So my name is Chloe, and I'm part of the P1 A team down south. So we're monitoring five farms on a weekly basis. With regular communication between farmers and myself. Chat about updates on the farm. Herd health, paddock activities, irrigation status. But all five farms, they do differ in practice, management practices, pasture species, herd size, but all are using Pasture IO to make on farm decisions.
Chloe:
So we have some farmers who use the Pasture IO app in conjunction with a visual assessment and their Rotation Right Tool to best pick the next week's worth of grazings. We have farmers that have been short on time at some points and have been in the dairy and relied solely on the tool to make that grazing decision for the next day. And then we have farmers who have used it rather than for direct grazing, have used it for forward planning and thinking, where they look at features on the app, such as days to next leaf emergence, and there's also a seven day pasture forecast which tells the user is growth rate or leaf appearance increasing or decreasing? And then these farmers have used it to sort of plan and cut for silage.
Chloe:
A lot of farmers have also expressed that the platform is good to store all the information. All the grazing records, historically, and up to date, as well as all the paddock activities. As you've seen. But yeah, it's really interesting that all these farmers have really welcomed the platform.
Chloe:
And we're excited to see the results and the changes in productivity and profitability that will come over the next year.
Josh:
Thanks very Much, Chloe. So that's the end of that presentation now. But we've got question time now for Chloe Martin, myself or Pat, and Allen.
Audience #1:
I've got a question, It's sort of for you Chloe and sort of for Martin, but. Thanks so much for the help on P2 as well. We really appreciate it. And Josh as well. But I'm just looking at the R squared of the different areas. And that's just how they're different. Like, you've got a really good fit here and then it's not quite as good down you know the mid-coast. Well, the mid coast is not quite as good as the north coast. And the south coast is really different. Why?
Martin:
Well, yeah, yeah. Same thing for the them just to give more on that. We just wanted to highlight. The different regions we are having, like, different. We are seeing different things. Pasture types are completely different. So. It's really nice to see this across the dataset. The data there is only organized by region, but then if we subdivide in all the information by season, for instance, in summer, autumn, winter, and spring. So the slopes are changing. So we are implementing all those calibration. So every single dot that you see there on those scatter plots is a single cut.
Martin:
So then we are implementing each single calibration for each farm and for each moment of the year. So, we see that it's changing. So in the first time. So we wanted to have our dream is to have, like, a single regression for all the pastures across New South Whales. So then we can implement that calibration throughout New South Whales. But then we see that it's changing. It's changing a lot. So the good thing is that we have the guys taking this really good measurement. So we are classifying all the calibration cuts in terms of pasture composition. In terms of that dry matter, the dry matter content, and in terms of everything. So we can then use those callibrations to our plate meter so we can have an accurate plate meter. So then we can test how the satellite is striking in on that one.
Josh:
A thing I would add to that is seasonal conditions as well. So with all the weather and flooding up here was a lot worse than what we had done on the south coast. So we weren't able to keep the pasture under control. So we've had pasture getting a lot out of control. So you know, the measurements. When you got kikuyu you get completely out of control, then we also have some paddocks in the data set that, you know, may have been too wet and not been grazed, you know, for two or three grazings. Okay. So that's adding some muddiness in there. So what you're seeing there is is all the raw data. And I think there's going to be needing some cleaning up of certain paddocks because we've got a lot of photos of these paddocks as well, so obviously, with satellites, we think, you know, once they get to a certain height, you know, the saturation goes out so we can't get that relationship anymore. Okay. But the other one, my gut feeling, is the better the pastures managed and better it's under control. And the better grazing management we get. We seem to get a better relationship. Okay. And we sort of see that and when we compare a couple of different farms as well.
Martin:
Any other questions.
Audience #2:
Probably a bit of a silly question, but have you picked up any different in managing flat, flat pastures versus sort of hilly, or hilly type farms. And do you correct for that are any differences?
Josh:
So there is some paddocks that are on hills, and there are some paddocks that are on flat and nothing again, it's all just raw data. So we wouldn't have segregated any of that hill and flats at the moment, but I'm guessing there could be something, but we'll have to wait until the data comes out and then he has time to to pull it all apart and have a look at that. That's another PhD project after the project after the project it's a good thing about data.
Audience #3:
Can you use it historically to check out how much actual you got off the paddocks, to work out whether you need to resow it or how much fertiliser you need to apply. And can you use that information for the food safe?
Josh:
So the question is can we use it historically, the question is the data does go back so the satellites are always kept and then they can go back. They go back for 5 or 10 years, etc. Okay. Problem is a lot of these things need input. So they need to know when they're grazed, they need to know when they're fertilized because that all goes into the algorithms. So if all that information hasn't been put in, it won't be as accurate.
Audience #3:
But if you have like, say when you start, January. And then you have a full 12 months. Can you go back on that twelve months to see actually which paddock performed the best?
Josh:
You will be able to. Yes.
Audience #3:
And then can you take the data to prove to food safe that you've done the right thing like with holding?
Josh:
Yeah, that's right. And then you've got information there to say that these are these are the grazing periods, this is when it all went on. This is the withholding periods. So all that data is there.
Martin:
For Pasture IO is not only to follow the productivity of the paddocks, but also it's like a cloud. I mean, everything is going in that direction. So all the data is there. We put it in the handout. We have the Auto Grazer. So all the farms that we have they have like GPS collars. So all the grazings, all the recorders are entering into a system automatically. Plus they can put all the fertilizer activities, all those things. So it all stays there. And there is another feature for the system too and keeps the app nice and simple
Josh:
One more question. But can we have a question for Pat or Allen, if there is one. Yep.
Audience #4:
You've got to yield. Pasture yield, rotation, residuals and pasture mass. Are you able to correlate back to milk yield with pasture growth rate at this stage?
Martin:
That is our dream, we want to play with the data. That is why we are interacting with P2, as they are following cow performance. So our dream is to follow that one, to follow cow production. And then because everything in the end is measuring milk production. So milk response needs to be there. Yeah, perfect.
Josh:
And the goal for me and I've done this in the past, but the goal for me is to have that all live. So a farmer has a dashboard and they do their grazing. And then all of a sudden, the milk tanker comes, that feeds into it. Back calculations happen like dairy base. And everytime the milk tanker comes, you're getting feedback in terms of profitability, feed harvested, feed inputs, all that sort of thing with turn on milk solids, all that sort of stuff. Now that's the dashboard everyone should have every time tanker comes.
Peter:
I mean one of the objectives with kikuyu is to actually give quality things. So while this gives very good correlations with biomass on ryegrass. With kikuyu, we want good quality. So it's hopefully predicting. You know, in time, going to predict you need to graze at a certain time. Not for dry matter but for quality and maintaining that quality.
Josh:
Did you have a question for Pat or Allen?
Audience #5:
How valuable is this Pasture IO in saving time and what you do with your pasture and grazing now?
Pat:
Allen uses it and I glance at it, but yeah, it's probably helped with grazing allocations and feed wastage so that we're not doing it. And I guess. We've probably learning something too. Like. People talk about allocating. Or intake from cows there's so much of their body weight. And we're probably exceeding that. So it's all about testing it and know when you're testing it. So that the other day, when. We worked out they could eat another half a kilo morning and night. We were like looking at this and that's where doing pastures for profit and understanding what you're looking at. And all those key things. And I guess it's still coming back to us putting quality feed in front of the cows.
Audience #5:
So it gives a good indication of when you should actually harvest a paddock for silage or if it has grown too much.
Pat:
Oh, yes, it's just the record. So we know. Yeah. Like Allen's got that black line (target cover line). And so we know exactly. And so that he's got these are all the paddocks that are in. And so these ones. He's taken out this one, this one. They're actually not in the rotation. So we know that's what we need to keep going.
Audience #5:
Do they automatically pop back in once they're ready to enter the grazing round?
Pat:
Oh, it's a manual thing to put them back in. But that's how we're using it. It's just like the Pastures for Profit program the paper, except we don't have, there's no pegs. And we're doing it and we're getting it to it's right.
Allen:
There's also an image that can bring up from the satellite. The user can actually filter it and it can actually filter a tree out and actually tell you that a paddock has gone past it and should be out for silage.
Josh:
And we had that this year, when it kept running every week. So, most of the farm was nearly canopy closure apart from 4 or 5 paddock. That sort of thing happens. But then they were able to recognize which paddocks to pull out. They pull them out so they're not in the feed wedge.
Martin:
And also there is the intra-paddock variability, because this is at the paddock level. And then you have like the variability not just within the paddocks but at the regional level.
Josh:
Okay, so that's the time for questions. Unfortunately. Sorry. I've been given the hurry up. Thank you for your time.
- The Dedicated Team of Pasture.io, 2023-01-10