2796: Cultivating Tomorrow's Farms: Land O'Lakes' Tech-Driven Agriculture Revolution | The Tech Talks Network

How is technology transforming the landscape of agriculture, making it more efficient, profitable, and sustainable? Today's episode delves into the exciting world of agricultural innovation and technology. Teddy Bekele, the CTO at Land O'Lakes, takes us on a journey through the cutting-edge initiatives that are reshaping the future of farming and ensuring a resilient and sustainable food system.

Land O'Lakes, a renowned agricultural cooperative, is harnessing the power of AI and machine learning to provide hyperlocal, customized insights to farmers. Discover how these digital tools enable real-time decision-making in the field and empower farmers to optimize their operations.

Our conversation also explores Land O'Lakes' commitment to sustainability. Teddy discusses how precision agriculture technologies such as GPS, sensors, and imagery are pivotal in promoting sustainable farming practices. Learn how Land O'Lakes quantifies sustainability gains, potentially monetizing them through carbon credits.

Teddy unveils Land O'Lakes' digital transformation strategy, focusing on data, AI/ML, IoT, automation, and other emerging technologies. Discover how these innovations deliver actionable insights to farmers, strengthening connections across the food value chain.

Tune in to gain valuable insights into the intersection of technology and agriculture and how Land O'Lakes is paving the way for a more efficient, profitable, and sustainable future in farming.

Check out the Sponsor of Tech Talks Daily.

Step into the future of secure managed file transfer with Kiteworks.

Visit kiteworks.com to get started.

[00:00.000 --> 00:08.920] Are you aware of the remarkable ways in which technology is revolutionizing agriculture? [00:08.920 --> 00:16.160] From AI to IoT, the agriculture sector is not just about tractors and soil. It's now [00:16.160 --> 00:24.200] about smart, sustainable farming. The promises are bright a future for all. So today on Tech Talks [00:24.200 --> 00:31.600] Daily, I'm going to be joined by the CTO at Lando Lakes. My guest name's Teddy. He's [00:31.600 --> 00:39.000] at the forefront of using innovative technologies to reshape agriculture, ensuring a more resilient [00:39.000 --> 00:45.280] and sustainable food system. So how is Lando Lakes leveraging technology to make farming [00:45.280 --> 00:49.920] more efficient, profitable and sustainable? Before I invite today's guest on, I've just [00:49.920 --> 00:54.360] got to give a quick shout out to the sponsors of Tech Talks Daily right now. And there's [00:54.360 --> 00:59.760] a company called Kiteworks. And I've partnered with them because legacy managed file transfer [00:59.760 --> 01:05.400] tools are dangerously looking dated and sometimes lack the security that today's remote workforce [01:05.400 --> 01:10.160] demands. So companies that continue relying on outdated technology, obviously they put their [01:10.160 --> 01:17.680] sensitive data at risk. So when we're discussing the landscape of secure MFT solutions, Kiteworks [01:17.760 --> 01:21.960] is one of those companies that stand out as a paragon of high-end security and compliance [01:21.960 --> 01:28.960] because the FedRAMP moderate authorisation, which Kiteworks has held since 2017 through [01:28.960 --> 01:32.840] the Department of Defence is not just a badge of honour. It's actually a testament to their [01:32.840 --> 01:39.600] unwavering commitment to robust security protocols. So Kiteworks is FedAMP moderate authorised, [01:39.600 --> 01:45.880] which eases the pain to CMMC compliance, offering a significant advantage to customers in terms [01:45.880 --> 01:50.640] of time, effort and financial resources. So that is why I've partnered with them. So [01:50.640 --> 01:55.640] if you're interested in stepping to the future of secure managed file transfer with Kiteworks, [01:55.640 --> 02:01.640] visit kiteworks.com to get started. That's kiteworks.com to get started today. But now [02:01.640 --> 02:07.080] it's time to get today's guest on. Buckle up and hold on tight as I beam your ears all the [02:07.080 --> 02:14.360] way to the US where Teddy is waiting to explore the digital transformation in agriculture. [02:14.360 --> 02:19.000] So a massive warm welcome to the show. Can you tell everyone listening a little about [02:19.000 --> 02:25.080] who you are and what you do? Sure. My name is Teddy Pecali. I'm the Chief Technology Officer [02:25.080 --> 02:32.000] here at Land of Lakes. Land of Lakes is a farm-to-fork cooperative based out of Minneapolis, Minnesota [02:32.000 --> 02:37.680] or just outside of Minneapolis. I've been in this role for about five years and my role [02:37.680 --> 02:42.920] really is about running our technology organisation, helping with digital transformation and looking [02:42.920 --> 02:48.040] after the security of our organisation. Well, a huge welcome to the show. One of the things [02:48.040 --> 02:53.240] I try and do here every single day is get people thinking differently about technology and these [02:53.240 --> 02:58.680] impacts on our lives, our world, our work and everything in between. I think when most people [02:58.680 --> 03:04.120] think about technology, they don't automatically associate innovations in agriculture or tech's [03:04.120 --> 03:09.800] role in form to fork. So can you tell me a little bit more about the transformative technologies [03:09.800 --> 03:15.000] currently being implemented at Land of Lakes and how they're actually revolutionising traditional [03:15.000 --> 03:20.520] farming practices? Yeah, absolutely. And there's lots of exciting things going on. So I'm really [03:20.520 --> 03:25.640] happy to dive into this. And I think we'll have a really fun discussion. So let's just kind of quickly [03:25.640 --> 03:30.920] 30 seconds start on the structure of the company. That way you sort of understand all the entities. [03:30.920 --> 03:35.720] And then we talk about the technologies that we're implementing. So we have about four divisions in [03:35.720 --> 03:41.000] our organisation, starts with our Windfield United business. That's a wholesale distribution [03:41.000 --> 03:47.000] business where we buy seed, crop protection and plant nutrition products from large manufacturers [03:47.000 --> 03:55.000] like a buyer, singenta, Corteva. And then we sell those products to our retailers, which are locally [03:55.000 --> 04:01.480] owned and operated retailers in rural communities here in the United States. So anywhere in the Midwest, [04:01.480 --> 04:08.280] the West, the South, and those retailers then sell those products along with other services [04:08.280 --> 04:15.160] to row crop farmers, predominantly corn, soybeans, wheat, etc. So our job there is as a wholesale [04:15.160 --> 04:20.120] distributors to get the best rates for our retailers for these products and the farmers that are part [04:20.120 --> 04:26.280] of the system. But really we add a lot of intelligence in the process, how to best utilize the products [04:26.280 --> 04:31.160] that we're buying that are going to go into the ground. How do we use technology to better implement [04:32.120 --> 04:36.440] some of these capabilities that are, you know, like a lot of technologies goes into these products [04:36.440 --> 04:40.920] themselves. But how do you get the best out of it on the farm? So that we'll talk a little more [04:40.920 --> 04:46.680] about that. But that's our crop inputs business. Then we get into animal nutrition. And the brand [04:46.680 --> 04:51.800] is a Purina brand Purina. There's a Nestle Purina as well that's dog and cat, but we do every other [04:51.800 --> 04:59.240] species in North America. So think horses, chickens, cattle, cows, goats, you name the animal other [04:59.320 --> 05:04.120] than dog and cat, we have the feed for it. So we're a basic manufacturer in that space where we [05:04.120 --> 05:11.800] formulate the feed and then we sell that to either retailers or we sell it to big box companies like [05:11.800 --> 05:16.840] tractor supply, but then sell it to consumers. So there's a little bit of ag business there, [05:16.840 --> 05:22.440] especially when you talk about producers that have a lot of animals, but also a consumer business [05:22.440 --> 05:27.240] where it could be just one or two animals that you have, you know, in the farm or on even at home. [05:27.240 --> 05:33.400] And so an interesting business there and one that's a lot of fun. Then we have our dairy business [05:33.400 --> 05:38.680] that most folks with no land of lakes for is the butter. So that goes back to the roots of this [05:38.680 --> 05:44.200] organization where we buy the milk from dairy producers, we turn that into butter and cheese [05:44.200 --> 05:48.760] and other derivative products. And then we sell that to food retailers and then you would find [05:48.760 --> 05:53.160] that in the grocery store. So that's, you know, things that most people would recognize a land of [05:53.160 --> 05:59.240] lakes named for. And then our last business is a sustainability based business. So it's looking [05:59.240 --> 06:04.920] across the our businesses and how we implement sustainability in our four walls. But also how [06:04.920 --> 06:09.560] do we look at sustainability for the farmers on a part of our system, their retailers, and really [06:09.560 --> 06:15.880] coming up with interesting practices that would then revolutionize the way we go do farming as an [06:15.880 --> 06:20.120] example. And we can generate carbon credits and then we sell those carbon credits to downstream [06:20.120 --> 06:25.960] players, etc, etc. And when I say farm to fork, we're all connected. So you think about the seed [06:25.960 --> 06:33.480] at the beginning that's sold, that gets into the ground, it's grown, it turns, you know, into a crop. [06:33.480 --> 06:39.160] We harvest it. When you look at our animal business, corn and soybeans are like the main ingredients [06:39.160 --> 06:43.800] creating a feeding formulation for any type of animal. And so in the number one species we serve [06:43.880 --> 06:50.840] in Purina is cows and dairy cows particularly. And so you think of our owners or our members, [06:51.480 --> 06:56.680] some of those cows are their cows, and then they produce butter and cheese, our milk, and then we [06:56.680 --> 07:00.840] turn it into butter and cheese and you find out the store. So when we talk about the whole spectrum [07:00.840 --> 07:06.520] from the time in which the seed went into the ground to you and I consuming a product at the store, [07:06.520 --> 07:11.160] we sort of have the whole gamut end to end. And then obviously we all do all that with a lot [07:11.160 --> 07:15.160] of sustainability practices along the way. So that's a little bit of our business, right? [07:15.160 --> 07:19.400] And as I kind of described each one of them, we talk a little bit about some of the technology, [07:19.400 --> 07:23.800] right? How do you, when you buy seed and you plant it into the ground, how can you use technology [07:23.800 --> 07:28.280] to help you make a better decision and get away from intuition? And there's a lot more things we [07:28.280 --> 07:33.560] do there to help you in season while the crop is growing, we make decisions around attrition of [07:33.560 --> 07:39.560] the plant itself. And even what time, when is a good time to harvest it, etc, etc. [07:40.440 --> 07:46.120] On the animal nutrition side, we'll use technology to help you manage the animals that are on the [07:46.120 --> 07:53.160] farm. We'll help you manage the gut microbiome of your horses, if that's what you have. And we use [07:53.160 --> 07:57.000] technology to be able to help with that. And then on the dairy production side, obviously, [07:57.000 --> 08:01.640] there's a lot of technology we work on with a lot of our retailers. But even our dairy producers, [08:01.640 --> 08:06.040] how do we help them monitor the cows that are in their barns? How do we make the most as far as [08:06.040 --> 08:10.760] getting the best quality of their cows? What should they be fed, which ties back to our feed [08:10.760 --> 08:14.840] business? And then when we look at our sustainability business, when it's connected end to end, [08:14.840 --> 08:19.320] it's all about technology, capturing all the data points along the way, understanding what [08:19.320 --> 08:24.680] practices we're using today, and optimizing and changing our practices to be able to leverage [08:24.680 --> 08:30.840] better sustainability, a practice to put it to be put in place. And then our technology tracks [08:30.840 --> 08:35.640] all of that. And then when we sell the credit downstream, obviously, that's all done through a [08:35.640 --> 08:40.840] technology transaction. So that's how our technology gets involved a little bit around [08:40.840 --> 08:43.800] all of it, right? And we touch all the different pieces there. [08:44.680 --> 08:50.520] It's incredibly cool what you're doing here. And if we scroll down our LinkedIn news feeds at [08:50.520 --> 08:56.760] the moment, it's full of stories around AI and data analytics. And even from a consumer tech [08:56.760 --> 09:01.560] point of view, anyone following the events in Vegas this week for CES, they're all going [09:01.640 --> 09:07.640] to be seeing things around AI everywhere and data analytics, etc. So to drill into some of the [09:07.640 --> 09:13.960] work that you're doing here, I'm curious, how is AI being utilized to assist farmers in and [09:13.960 --> 09:19.400] ultimately making them, helping them make more informed decisions regarding things like soil, [09:19.400 --> 09:24.760] seed placement, and also what impact what results have you noticed is having on [09:24.760 --> 09:29.160] prop yields and sustainability, because it's you're solving real problems here. And I'd love [09:29.160 --> 09:34.440] to expand on this. Yes, absolutely, Neil. And that's a I love that question. It's almost [09:36.040 --> 09:41.240] this is why I have passion talking about, right? And we give an AI, I mean, it's an artificial [09:41.240 --> 09:45.240] intelligence becoming almost synonymous with just using technology these days, right? Everything has [09:45.240 --> 09:49.720] AI in it. And we've been doing it for quite some time, particularly around the predictive side of [09:49.720 --> 09:54.040] things. So in that crop inputs business that I mentioned earlier, where we buy the seed and I [09:54.040 --> 09:58.920] say we have a lot of knowledge that we help farmers make decisions every day, right? So if we kind of [09:59.240 --> 10:04.040] double click on that a little bit, part of what we do is we actually have these things called [10:04.040 --> 10:10.280] answer plots, they're research plots where we buy all the seed ahead of time before the [10:11.560 --> 10:15.480] before the seeds available the next season, we actually purchase it ahead of time and we plant [10:15.480 --> 10:21.240] it into all these plots that are all in there, there's about 115 of them and they're dispersed [10:21.240 --> 10:25.720] in all the areas where we do business. And when we put the seed into the ground, and then we [10:26.280 --> 10:31.800] also apply crop protection to it, we learned quite a bit about how that seed performs in a given soil [10:31.800 --> 10:37.640] type, how that seed performs in a given climate, how that seed performs given the type of practices [10:37.640 --> 10:43.240] that you may put in place around tillage, for example, and we capture all that data. And then [10:43.240 --> 10:49.960] what we do with that data is as now the products are available to farmers, that data is turned into [10:49.960 --> 10:55.400] more ways of which you can help a farmer make a best decision on their field. Now [10:55.480 --> 11:00.120] this is where the AI comes into place, right? So there's a lot of predictive types things [11:00.120 --> 11:05.640] where we go, look, for the area you're in for the topography, the soil, the climate, [11:05.640 --> 11:11.560] these are the seed profiles that best match sort of the, and give you the best potential on that [11:11.560 --> 11:16.760] field. But also here are the practices you need to follow around the season, that you can get the [11:16.760 --> 11:21.080] most out of it. However, we also know that the weather is very unpredictable and it changes as [11:21.160 --> 11:27.080] a season goes on. So we will use AI to be able to adjust some of the recommendation as the crops [11:27.080 --> 11:32.520] coming out of the ground. And so those are the types of ways. And there's a big, between the [11:32.520 --> 11:36.440] farmer and us, there's these retailers that are occupied and these retailers have these [11:37.000 --> 11:42.520] professionals called agronomists. And agronomists is like the all-knowing person that really can [11:42.520 --> 11:46.600] help the farmer make those decisions. Because some of that, yes, it could be very analytical in [11:46.600 --> 11:52.600] nature, but you need someone who's actually local that understands the environments that the [11:52.600 --> 11:57.400] plants are growing in that can give that best advice to that farmer. So we work a lot to put [11:57.400 --> 12:02.600] these technology tools and the AI in the hands of these agronomists that can then best help [12:02.600 --> 12:07.800] those farmers make those decisions, right? And some of the things we do, for example, [12:07.800 --> 12:12.120] just to get a little more tactical around the AI to the agronomist, there's this thing called [12:12.120 --> 12:16.840] the crop protection guide. So it's like almost like the Bible of crop protection, right? It looks [12:16.840 --> 12:22.520] into the book, right? It's this big and it's 400 pages. And if you want to know about what chemistry [12:22.520 --> 12:27.480] goes on, what field combined with what, at what rate, where's the area where you're not damaging [12:27.480 --> 12:33.480] the plant and you're kind of taking care of the diseases potentially or the pests that are [12:33.480 --> 12:37.480] infecting that plant, this is the book you use. And a lot of agronomists, I mean, this is like the [12:37.480 --> 12:42.760] thing they walk around with. And the one I have is very pristine and neat. And you know, [12:42.760 --> 12:47.080] but there's like, you know, beat up and has notes everywhere and everything else. So we're [12:47.080 --> 12:52.680] actually looking at generative AI to be able to digitize this book. I mean, we have a PDF version, [12:52.680 --> 12:57.160] but ironically, the PDF version is actually more complicated to use than the physical one, [12:57.160 --> 13:00.680] because the physical one you can quickly flip to where you need to go to, whereas digital [13:00.680 --> 13:04.600] becomes a little harder. And we've always struggled with that over the years. But now, [13:04.600 --> 13:11.000] with generative AI, we can almost make it a conversation between the agronomist and the [13:11.000 --> 13:15.480] crop protection guide, right? So you have a conversation, you ask it to have this situation going on, [13:15.480 --> 13:19.560] trying to put this much chemistry down, you know, what do I combine it with, what's the rate, [13:19.560 --> 13:24.440] and there's sort of this interactive conversation that happens with that recommendation at the end [13:24.440 --> 13:29.240] that the agronomist then gives to the farmer. So those are ways in which you're starting to use [13:29.240 --> 13:35.080] practically AI to be able to really take more of the guesswork out of what we used to do before, [13:35.080 --> 13:39.320] or just more of the tribal knowledge. Now, that's still very much required, but now we're using [13:40.280 --> 13:43.640] really AI to take you to the next level, which is really exciting. [13:44.440 --> 13:50.600] It really is. And of course, farming is about traditional industry. We've got families that have [13:50.600 --> 13:54.680] been running farms for hundreds and hundreds of years. I'm curious, what are the biggest [13:54.680 --> 13:59.640] challenges Lando Lakes faces in integrating advanced technologies into agriculture? [13:59.640 --> 14:05.160] Is there any resistance? Is there something else? And also what opportunities do these challenges [14:05.160 --> 14:10.440] maybe present to? Yeah, absolutely. So, you know, if we could kind of keep going on the example, [14:10.440 --> 14:16.760] we just gave so the animist is using the AI like this crop protection guide. We have a lot of [14:16.760 --> 14:21.240] predictive models that will tell us these seeds work well in this environment. This is what you [14:21.320 --> 14:27.320] should plant, et cetera. So those are all really, really neat technology platforms and capabilities [14:27.320 --> 14:31.720] that we didn't have before that are really taken to the next level. The other one that's really [14:31.720 --> 14:37.080] exciting is the sustainability side. So we could say things like, okay, I know you tilled the ground [14:38.360 --> 14:42.360] and but what if you didn't do tillage and what if what if you put cover crops at the edge of the [14:42.360 --> 14:47.800] field, especially when there's near a waterway and that will prevent the runoff, which means the [14:47.880 --> 14:51.800] chemistry that we're putting on actually goes into the ground and stays there and even the [14:51.800 --> 14:55.960] micronutrients and they're not running off into the stream, which by the way, farmers don't want [14:55.960 --> 15:00.040] that either. They don't want the pollution, but also that's investment they're putting into the [15:00.040 --> 15:05.480] field that just is literally washing away and they don't want that, right? The key is to take care [15:05.480 --> 15:09.720] of the problems you have on the field or make the plants stronger. So those are the types of [15:09.720 --> 15:14.040] things an agronomist would then help also help from a sustainability standpoint, right? By doing [15:14.040 --> 15:18.520] that, you're making the soil healthier, et cetera. But here's the challenge in on all of this. [15:19.240 --> 15:23.400] First of all, you have to have there's an enormous amount of data required. So I talked about the data [15:23.400 --> 15:30.440] we capture by planting in our research plots. I talked about maybe some of the data that farmers [15:30.440 --> 15:34.920] have from their equipment, for example. But a lot of them are have equipment that the most [15:34.920 --> 15:39.480] sophisticated, the newest equipment will have the most sophisticated software that captures really [15:39.480 --> 15:45.560] good data. But if you have, and most farmers have a variety of equipment that ranges from one [15:45.560 --> 15:50.440] year old to 20 years old, and the 20 year old piece of equipment is not capturing the data [15:50.440 --> 15:55.400] that the new one is. And so, but because they have a mix, now we're having to figure out how to [15:55.400 --> 16:01.160] stitch that together because, yeah, we have our insight, but how do you localize it to that field? [16:01.160 --> 16:06.200] Now you need information about that field to really take it to the next level. And that's a [16:06.200 --> 16:11.480] challenge, gathering that data, normalizing it, preparing in such an, you know, like is you talk [16:11.480 --> 16:15.720] more about artificial intelligence, all as good as the data you've got, right? And how well organized [16:15.720 --> 16:21.400] that is, the harder it is to organize, the bigger a challenge it becomes. So that may be a barrier [16:21.400 --> 16:28.040] to be able to kind of take it to the next level. Another thing we struggle with is also on the [16:28.040 --> 16:32.760] adoption side. And I don't mean because farmers don't want to, they love it. I mean, farmers are [16:32.760 --> 16:37.880] the most entrepreneurial set of individuals. I have a lot of them. They do farm, but they also [16:37.880 --> 16:42.920] have these side hustles and side businesses they've always got going on. I love how our dairy producers, [16:42.920 --> 16:48.120] for example, will milk cows, but they also have an ice cream business on the side that they run [16:48.120 --> 16:53.320] and think of that nature, right, which is, which is exciting. But the problem is, there's a lot [16:53.320 --> 16:58.040] happening in a short period of time, especially when you're planting as an example, you may have a [16:58.120 --> 17:03.400] very short window between the last rain and the next rain. And you're not even really sure about [17:03.400 --> 17:06.920] when you talk about the next rain, that would mean you have certainty when it's going to rain on [17:06.920 --> 17:12.440] that field on a given data given time. And that's not exactly all that predictable. But you do know [17:12.440 --> 17:16.840] that in general, maybe you have three or four days, maybe eight, if you're lucky, where it's going [17:16.840 --> 17:22.360] to be dry, and that is the time to plant. And when that happens, sometimes you have a plan for a [17:22.360 --> 17:26.680] field. I'm going to put this much seed on this ground at this density, and I'm going to leverage [17:26.680 --> 17:31.000] the maximum amount of the soil, except the plan doesn't go that way, because it was supposed to [17:31.000 --> 17:36.040] rain eight days from now, but actually rain tomorrow. So I was going to go to field number three, [17:36.040 --> 17:39.880] and now I'm going to field number seven, I am not going to reconfigure the equipment with a new [17:39.880 --> 17:44.520] prescription and a new seed in the back. So I'm just going to do whatever I need to do, [17:45.080 --> 17:49.720] you know, like for today. And so all the best plans go out the door when it starts [17:49.720 --> 17:53.160] doing it every single day, because it's like the mother nature just didn't cooperate with you [17:53.240 --> 17:58.040] that time. So that's where, you know, you may have these awesome tools you want to put in place, [17:58.040 --> 18:01.880] but when rubber comes, you know, push comes to shove at that moment, you're just, you know, [18:01.880 --> 18:05.640] you just kind of do what you need to do. And so you've got to get better at doing predictive [18:05.640 --> 18:10.200] type stuff. And so that way it just becomes normally just a normal way we do things, [18:10.200 --> 18:12.760] and now make it an obstacle to be able to use the technology. [18:14.280 --> 18:18.280] And before you came on the podcast today, I was doing a little research on you guys, [18:18.360 --> 18:24.520] I was reading about the Windfield United Innovation Center and its role in advancing agricultural [18:24.520 --> 18:29.400] technology. Can you expand on that? And maybe tell the listeners a little bit more about how [18:29.400 --> 18:34.680] the unique facilities like the wind tunnel and drone technology also could contribute into this [18:34.680 --> 18:40.840] advancement too. Oh, Lee, that's this is where we're trying to get better and better at modeling [18:40.840 --> 18:44.280] what happens on a field. Because like I said, I told you just talked about the challenge of [18:44.360 --> 18:49.640] gathering the data, what happens when, you know, sort of like things just happen on the fly. [18:50.200 --> 18:55.800] So the way we try to minimize that, by trying to recreate what happens on a field in our facilities [18:55.800 --> 19:02.520] and in our plots. So when the Windfield Innovation Center is one of those facilities, [19:02.520 --> 19:06.200] where we have a couple of things happening there, which if you ever get a chance to come on, [19:06.200 --> 19:10.360] I would love to take you through it. It's a really fun experience. But we have what's called [19:10.360 --> 19:15.160] the Wind Tunnel as an example. So it's this huge machine that really try to mimic wind [19:15.160 --> 19:21.640] conditions on a field. Right? So we send wind through it like at different velocities. And then [19:21.640 --> 19:27.480] now we use and we have a nozzle that would spray water and maybe a crop protection application with [19:27.480 --> 19:33.640] that wind. And then we try to see if you add an adjuvant that makes the droplet thicker, for [19:33.640 --> 19:38.200] example, what kind of impact it has of certain winds with a certain nozzle type. And we do this [19:38.200 --> 19:42.360] in a variety of combinations. That way we know if you apply the following chemistry [19:43.000 --> 19:48.920] at the following wind speed, at the following speed of the tractor itself. And, you know, with [19:48.920 --> 19:53.320] these types of equipment like the nozzle, this is what this is what you can expect to get as a [19:53.320 --> 19:57.960] result. So we capture that data and that's information that's available, particularly to a farmer when [19:57.960 --> 20:03.000] they're in the cab doing this type of work, right? And that could be readily used that way. We have [20:03.000 --> 20:09.160] these chambers there that can mimic the conditions of like South Dakota, for example, [20:09.160 --> 20:15.400] and a hot July day, as well as another chamber could be mimicking the conditions of Indiana [20:15.400 --> 20:22.040] on a spring cool day. And we put the different seeds growing in these chambers. And then we attack [20:22.040 --> 20:27.480] them with different diseases and pests, the same one, but two different conditions. And how does the [20:27.480 --> 20:32.520] plant react to those conditions? So we try to mimic sort of what happens on the outside, [20:32.600 --> 20:36.840] but in a very controlled environment on the inside. And then we can see, okay, what [20:36.840 --> 20:41.720] things could you do to make sure that that plant is not heavily impacted by it? So that's another [20:41.720 --> 20:46.440] piece that's in the innovation center. And then we also have a phenotyping center where [20:46.440 --> 20:51.240] we actually it's a greenhouse and we grow the plants and we try to grow the best possible plant [20:51.240 --> 20:56.280] there. But that's also where we know the answer plots that I mentioned earlier that are outdoors [20:56.280 --> 21:01.800] that are in different geographies. We actually try to get the same different plants in the same [21:01.800 --> 21:07.800] spot with the same type of temperature, paying pressure, and same sunlight as an example, [21:07.800 --> 21:12.200] and see how they perform. So we could actually do that indoors as well, and we capture that [21:12.200 --> 21:18.600] information. So these are the data sets that we gather that we learn about plants and how they [21:18.600 --> 21:23.080] behave and how they react. And then we have that available to that make available to those [21:23.080 --> 21:27.400] agronomists and farmers that can make the decisions on the fly combined with their local data. [21:28.360 --> 21:35.000] I love that. And another huge topic in farming right now is sustainable farming practices. [21:35.000 --> 21:41.480] There's a huge focus on it. So how are Lando Lakes promoting sustainable farming practices [21:41.480 --> 21:47.480] through technology? And what are they, again, tangible impacts on resource usage and environmental [21:47.480 --> 21:51.880] preservation? Anything you can share around that too? Absolutely. I mean, this is core, [21:52.840 --> 21:58.760] sustainable farming is just good farming, right? I mean, that is, and every farmer, [21:59.720 --> 22:03.960] when you start talking to them, that's what they want. I mean, number one thing, as any farmer, [22:03.960 --> 22:08.280] particularly a generational farmer, they want to leave the land in better conditions that they [22:08.280 --> 22:13.480] found, which means the soil has to be healthier every year, right? So you start with the soil in one [22:13.480 --> 22:19.640] condition, the following year. Well, you finish your work that one year, and then you need to [22:19.720 --> 22:23.080] leave the soil in a better condition than when you start it so that the next year, [22:23.080 --> 22:27.720] you have a better year. If you ask a farmer, do you want that? It's a result, and it's not even a [22:27.720 --> 22:34.040] question, really. Everyone that needs to be that way, right? So now, what do we do to make sure that [22:34.040 --> 22:39.400] that that happens? So what we need to do is really understand the characteristics of that soil, [22:39.400 --> 22:44.040] that field itself, the topography of that field. And now this is where we talk about [22:44.040 --> 22:48.920] practices like tillage, practices like cover crops. And these are the types of things that we [22:48.920 --> 22:53.720] start to explain to farmers, although there may be a little bit of an increase in cost and maybe a [22:53.720 --> 22:58.760] change in practice required to be able to put these things into place. At the end of the day, [22:59.320 --> 23:05.320] we try to make sure that from a financial perspective, they're not upside down. In fact, [23:05.320 --> 23:10.680] in a lot of cases, if they do things right and they put the right pieces of the puzzle together, [23:10.680 --> 23:15.240] they may end up in a situation where they're just as profitable as using a conventional method [23:15.240 --> 23:20.680] or even more profitable if they go about this way while keeping the soil in a really good spot. [23:20.680 --> 23:26.120] So, and now we need a lot of data, and that's that our Chutera business works with farmers [23:26.120 --> 23:31.400] to collect even additional data, that local data at the field level. So we can crunch out a lot of [23:31.400 --> 23:36.040] what-if type scenarios, and this is where we use the AI, to be able to say, what if you did a cover [23:36.040 --> 23:40.840] crop on this edge of the field? What if you change the tilling practices on all your fields? [23:41.400 --> 23:45.400] What if you went to strip dill instead? What if you added a pond in the middle of the field that [23:45.400 --> 23:50.840] make a difference in how your field performs? And so these are the things we help them do. And then [23:50.840 --> 23:57.160] at the end, we also tell them, but by photosynthesis, the plants themselves will absorb carbon [23:57.800 --> 24:03.160] out of the atmosphere and then sequester it into the soil. And the job here is to keep [24:03.160 --> 24:08.840] that carbon intact in the soil itself. And if you do that, then you really sequester in carbon, [24:08.840 --> 24:12.680] and despite the fact they're using tractors and other things that emit carbon, at the end of the [24:12.680 --> 24:16.920] day, you could be carbon negative, not only carbon neutral, but carbon negative on that field, [24:16.920 --> 24:21.560] which means you're extracting more carbon in the atmosphere than you're putting out. And if that's [24:21.560 --> 24:28.840] the case, you can actually monetize that carbon credit and sell it, whether it's as a scope 3 [24:28.840 --> 24:34.920] in your industry and where downstream customers that are using your grain want to be able to [24:34.920 --> 24:40.440] offset their capabilities or what the products they produce, or whether it's a company that's [24:40.440 --> 24:46.680] outside of our industry that wants to then really buy an offset and buy a credit, you could do that [24:46.680 --> 24:50.760] as well, which then gets into even a better financial position. So therefore, at the end of [24:50.760 --> 24:57.160] the day, it's a win-win for a farm. Your upside, your financial situation is in a better spot, [24:57.160 --> 25:01.800] your soil is healthier, and your plants are also going to be in a better condition. [25:02.760 --> 25:08.040] And speaking of going forward, we're recording this podcast at the beginning of 2024, but if I [25:08.040 --> 25:13.560] was asking you to look a little further ahead, what emerging technologies or indeed innovations [25:13.560 --> 25:18.680] do you believe will have the most significant impact on the future of agriculture? You must be [25:19.240 --> 25:23.160] following so many different trends and so many emerging technologies, but is there anything [25:23.160 --> 25:28.280] that really stands out? Do you all exercise you at the moment? Yeah, I mean, I think we talked [25:28.360 --> 25:31.240] about artificial intelligence, but that's, I mean, that's such a big umbrella, right? [25:31.240 --> 25:35.080] Yeah, I would go a little bit deeper into that deep learning sign of things. [25:35.640 --> 25:40.040] Where, like I said, today, we're not exactly, we do a lot of predictive analytics, [25:40.040 --> 25:44.920] but we're not in a spot where we can actually model exactly what happens on the end of the year, [25:44.920 --> 25:49.400] if you tell me model exactly what happened on that field, we're not quite there yet. So I think [25:49.400 --> 25:54.280] this concept of modeling exactly what happened is going to be the next step, right? Because then [25:54.360 --> 25:58.120] you could do a lot of what if scenarios you can make quick decisions on the fly. [25:59.560 --> 26:02.920] You could even create, I mean, there's a lot of farming games out there today, but you could [26:02.920 --> 26:06.680] almost gamify it, right? And it could almost be a game of like, where do you want to make your [26:06.680 --> 26:11.000] bets and where you don't want to make your bets? And how do you adjust properly? I think that's [26:11.000 --> 26:16.520] going to be exciting. I think sensors are getting interesting, more and more sensors are getting [26:16.520 --> 26:20.200] deployed onto fields so you can capture more of that local data that I mentioned earlier. [26:20.200 --> 26:24.280] So this intelligent edge, not just a basic sensor, but is there some processing that can [26:24.280 --> 26:29.000] even happen at the edge itself that can give a better insight and to kind of how to make [26:29.000 --> 26:34.120] better decisions going forward? We didn't quite talk too much about drones, but I'm excited about [26:34.120 --> 26:38.920] drones went through this excitement at first. And then it was everybody loved flying them because [26:38.920 --> 26:43.320] they're such untoys. And then it was the minute you lost one, when the combine ran over it, [26:44.120 --> 26:48.840] when the battery ran out on the drone, that's the day go, you know what, this was a fad I'm [26:48.840 --> 26:54.920] done with it. We're beyond that now. And now we're starting to use drones to get better imagery, [26:54.920 --> 26:59.960] local imagery. Folks, are you starting to use drones to do applications themselves? So it's [26:59.960 --> 27:05.320] deep in the season, you know, even if you wanted to make a change, for example, or you wanted to go [27:06.680 --> 27:11.480] combat some disease, when the, for example, corn is too high, the equipment can get in there, [27:11.480 --> 27:16.600] right? It's just the plant is too high at that moment, but a drone can easily go and help rectify [27:16.680 --> 27:20.840] some of those problems. So that's another one that I think will get it more excited. And then all of [27:20.840 --> 27:27.880] it working together, you know, the sensors, the drones, the modeling, the, you know, satellite imagery, [27:27.880 --> 27:32.040] all that coming together, which is going to make us better at farming, right? And in a more [27:32.040 --> 27:37.160] sustainable way. So that's what's exciting for me. And obviously, the equipment is also another area [27:37.160 --> 27:41.000] that's getting more and more interesting and becoming more autonomous. They kind of run [27:41.000 --> 27:45.400] themselves now. And, you know, could you have multiple pieces of equipment running at the same [27:45.400 --> 27:49.480] time that will be a thing that will happen in the future as well? Do they need to be as big as they [27:49.480 --> 27:53.320] are today? They got bigger because we didn't have enough people to run them. But if they become [27:53.320 --> 27:57.560] more automated, can they actually be smaller and give more work done? That's also possibility. Like [27:57.560 --> 28:01.720] I said, like I mentioned earlier in the plant, you have such a short window, you know, if you could [28:01.720 --> 28:07.640] maximize that time and even do things at night, that could be super, super interesting going forward too. [28:08.440 --> 28:13.960] It really could. And another serious, but of course, as we recall this podcast, [28:13.960 --> 28:18.760] I've just a couple of days ago, there was a big news report on the global average temperature [28:18.760 --> 28:25.320] reaching the highest ever last year. So with that in mind, in what ways are lander lakes addressing [28:25.320 --> 28:30.120] the challenges posed by climate change, particularly in maintaining crop growth under [28:30.680 --> 28:35.560] increasing volatile weather condition? And that's the way you talk to a farmer. I mean, [28:35.560 --> 28:43.000] if you ask them, is the climate variable in your region, in your area? Is it more or less [28:43.080 --> 28:48.280] predictable than it was in the future? It would tell you that it is much more volatile now than [28:48.280 --> 28:54.280] it was in the past. Yeah, the little weather apps and everything else they've got, they can tell you [28:54.280 --> 28:59.080] like three, four, five, seven days out of best what's going on. But you're doing planning [28:59.720 --> 29:03.720] in January for what's going to happen in April. And then for a crop that's going to grow in August, [29:03.720 --> 29:07.320] and you've asked them, how's the prediction at that moment? It's like, well, I have no idea, [29:07.320 --> 29:12.680] right? And that's where there's a lot of variability there. So I think, you know, when we say, look, [29:12.680 --> 29:19.160] go back and get the soil healthier, sequester more carbon than you put out, right? I'm excited [29:19.160 --> 29:22.840] even to think about electrification of the equipment, because they could that would even help with less [29:24.120 --> 29:29.000] output of carbon into the atmosphere. Those are the ways in which farmers can really contribute [29:29.000 --> 29:36.840] to combating the increase in temperatures, right? On the dairy production side, same thing, a lot [29:36.840 --> 29:41.720] of farmers now are becoming, you know, they have, they manage their manure better, they cover their [29:41.720 --> 29:47.560] manure, they turn that through a digester into energy. They're, they're reducing big time. The [29:47.560 --> 29:53.480] methane that goes out into the atmosphere. So all in all, I mean, these are us as a cooperative, [29:53.480 --> 29:59.560] like being sort of the membership of our dairy producers of our ag retailers, it's our responsibility [29:59.560 --> 30:03.080] to go out and figure out what are these best practices? What are the things that make sense to [30:03.080 --> 30:08.520] you, educate you on what is possible and what the impact of it is, and then hopefully help you [30:08.600 --> 30:12.360] implement it. So that's why a lot of these technologies would put in place is to really help our members [30:13.320 --> 30:18.200] really change and go to the next slide. And of course, you can't do it all on your own, [30:18.200 --> 30:21.960] and I'm not sure if you're going to be able to share any names or anything here, but I'm curious, [30:21.960 --> 30:26.600] are there any key collaborations or partnerships that have been instrumental in [30:26.600 --> 30:31.960] Lando Lakes technological advancements across the agricultural landscape? And how are these [30:31.960 --> 30:37.240] partnerships and collaborations helping build and shape the future of farming? Yeah, you know, [30:37.240 --> 30:41.480] what's exciting is a lot of ag companies recognize that technology is crucial for what [30:41.480 --> 30:45.960] they need to do, right? And so from an equipment standpoint, I mean, you have John Deere, we work [30:45.960 --> 30:49.960] closely with that, particularly even on that spray tunnel piece that I mentioned earlier, [30:50.600 --> 30:55.880] we work with buyer quite a bit. I mean, we are buyers largest distributor. And so therefore, [30:55.880 --> 30:59.960] there's a lot of technology they put into the products they produce. And then our goal is how [30:59.960 --> 31:04.680] do we take that technology, combine it what we have and deliver at the local level. So we do a lot of [31:04.680 --> 31:09.400] work with them, same with Cortaba, same with Syngenta. So love working with those organizations [31:09.400 --> 31:13.400] and some of the technological advancements they're putting for BASF as another one. [31:14.280 --> 31:19.560] But I would say also, we've got tech partners that are helping us like Microsoft, right? And [31:19.560 --> 31:24.120] Microsoft's been an interesting partnership for us because they've said, look, we are not the main [31:24.120 --> 31:28.120] experts, we're not the subject matter experts in agriculture, but we certainly know tech, we know [31:28.120 --> 31:34.360] cloud, we know feeding edge computing. How can we make these services available to you? And then [31:35.240 --> 31:39.640] let's call it customization or adoption that we need for agriculture. And that's we've been [31:39.640 --> 31:43.240] working closely with them. And a lot of the platforms we're on, whether it's an archer terra [31:43.240 --> 31:50.680] business or our crop inputs business run on the Microsoft Azure platform, which is really exciting. [31:50.680 --> 31:57.000] And Microsoft was also the first purchaser of our carbon credits, right? So when we did offsets, [31:57.000 --> 32:00.520] one of the things they wanted to prove is if we invest in these technologies and companies use [32:00.600 --> 32:05.000] them, could we use that as a method to offset our carbon emissions and our carbon profile? [32:05.000 --> 32:09.160] And they were able to do that over the last two years. So that's been an exciting partnership [32:09.160 --> 32:13.560] with them. So yeah, so we've got different players that help us. Obviously, we're not, [32:13.560 --> 32:18.680] we are by no means doing this on our own. We try to use our mindset as one of collaboration. [32:18.680 --> 32:23.880] And there's folks that know their area of the business really well. We actually do more choreographing [32:23.880 --> 32:27.960] than developing. Yes, there are some areas we do some development on on just where we have [32:28.040 --> 32:32.440] deep expertise. But in general, is how do we put a solution together for our members, [32:32.440 --> 32:35.240] which are these data producers and ad retailers and put it in their hands? [32:36.600 --> 32:41.160] Wow, incredibly cool. I love chatting with you today. But before I let you go, it's time to have [32:41.160 --> 32:46.920] a little bit of fun with you now. I always like to ask my guests a more personal question. So I'm [32:46.920 --> 32:52.360] going to ask you if there's a book that is inspired, you will mean something to you or a song that we [32:52.360 --> 32:56.680] can add to our Spotify playlist. All I'm going to ask though is what would you like to leave [32:56.680 --> 33:02.520] everyone listening with at what? Yeah, the book that comes to mind for me, and it's been an impact [33:02.520 --> 33:07.000] for a book for many, many years. It's Tuesdays with Morrie, right? And it's interesting because [33:07.000 --> 33:13.400] that has nothing to do with tech. But you know what though, despite all the technology advancements, [33:13.400 --> 33:17.560] all of the artificial intelligence, a lot of crazy things we can do, even farming at the core, [33:17.560 --> 33:21.480] it's just a relationship business. It's a relationship all in all around. We even take the [33:21.480 --> 33:25.800] work business out of it. Any of these farmers that I get to work with, whether the [33:25.800 --> 33:31.080] world crop farmers or dairy producers, building that relationship and seeing sort of how they [33:31.080 --> 33:37.880] look at life and how they approach things. And it's always, I mean, when you talk to a farmer or an [33:37.880 --> 33:43.080] ag retailer, we don't get into that business side of things so much deeper into that in our [33:43.080 --> 33:47.720] conversation. First, it's all about, hey, how are you doing? What's happened? Anything with your [33:47.720 --> 33:53.640] family? I'm really sort of getting to know you at the core. And if you establish that and we do [33:53.640 --> 33:58.600] like a good job of creating that connection, everything else just comes very easy after that, [33:58.600 --> 34:03.400] right? And it's and they trust you. And so this getting this element of trust is really important [34:03.400 --> 34:07.400] and living to the max. And that's kind of where I go back to the end of the day. I'm like, [34:07.400 --> 34:12.120] I know this is scary. It's a plunge for you a little bit to kind of this. But I'm like, you know what? [34:12.120 --> 34:16.680] Like, we shouldn't have any regrets. We should go do this and we don't get many chances to try. [34:16.680 --> 34:21.480] Why not now, right? And let's let's go head on. And so that book for me has always been very [34:21.560 --> 34:26.440] inspirational. It's the only book I've read three types. And actually, like, and every time I sort [34:26.440 --> 34:31.800] of forget some of the messages, I'll go back and read it again. Well, I'll get that added straight [34:31.800 --> 34:36.840] to Amazon wishlist so listeners can check that out. And for anybody that would just love to find [34:36.840 --> 34:42.440] out more information about you, Lando Lakes, the winds on all we talked about, and anything between [34:42.440 --> 34:47.240] maybe they want to see some videos, maybe just want to contact you or your team to find out more. [34:47.240 --> 34:51.240] Where would you like to point everyone listening? Yeah, so the best place for us to go is Lando [34:51.240 --> 34:57.080] Lakes Inc.com, right? So there's an I and C you put it after Lando Lakes. That would give you the [34:57.880 --> 35:03.320] full breadth of our organization, crop inputs, the animal nutrition, the tritera business, [35:03.320 --> 35:09.640] and our dairy business. However, Lando Lakes.com itself is also one of our domains. And that's [35:09.640 --> 35:14.360] particularly for our dairy business. If somebody's looking to cook something, particularly bake [35:14.440 --> 35:20.680] I would say I love baking. So cookies, cakes, any sort of recipe, really, it's a big recipe [35:20.680 --> 35:25.400] site where very well done. And we have a kitchen here where we test all those things. So everything [35:25.400 --> 35:30.600] that's on online, we've tested here. And people have said give it a thumbs up. So I would recommend [35:30.600 --> 35:34.840] going there as well. And learning more about our organization, it will be Lando Lakes Inc.com. [35:36.040 --> 35:40.120] Awesome. And if I ever do make it over there to come and see you in person, if there was a role [35:40.120 --> 35:45.880] for chief taster, I'm your guy. Okay. Well, have you yes. And then by the way, the same recipe, [35:45.880 --> 35:50.200] we have different ovens and different stores we use. So you can get to test the same thing a [35:50.200 --> 35:57.240] couple of times, which is not a bad deal. I'm just learning more from you today, especially [35:57.240 --> 36:02.360] around how you're leveraging technologies and innovation to reshape agriculture, and also [36:02.360 --> 36:07.160] ultimately secure that long term resilient and sustainable food system. And also love [36:07.160 --> 36:13.960] hearing about your partnerships, how you're using AI to equip farmers with tools to make better, [36:13.960 --> 36:18.920] more informed decisions about soil and seed placement. This week, I've been following so [36:18.920 --> 36:24.520] much of CES. And there were so many solutions looking for problems. It's just so refreshing [36:24.520 --> 36:29.480] to hear you leveraging technology to solve real world problems about the world a better place. So [36:29.480 --> 36:33.720] you are the perfect antidote to everything I've been following today. So thanks for sharing your [36:33.720 --> 36:38.040] story. Okay. Now, thank you, Neil. Thanks for having me. This has been exciting. And [36:38.040 --> 36:41.800] thank you for letting us share our story. I think it's clear that the intersection of [36:41.800 --> 36:48.040] technology and agriculture is more significant than ever from utilizing AI and machine learning [36:48.040 --> 36:54.520] for hyper local insights to embracing more sustainable farming practices through precision [36:54.520 --> 37:01.240] agriculture. And Landa Lakes is setting a new standard in the AgTech landscape and the journey [37:01.240 --> 37:06.520] of transforming agriculture with technology. It's not just about innovation, but also about [37:06.520 --> 37:12.920] overcoming challenges and fostering collaborations. But what are your thoughts on the role of technology [37:12.920 --> 37:18.600] in modern agriculture? How do you see these advancements impacting our food system in the future? [37:18.600 --> 37:22.920] This is not my area of expertise. And I know there will be many people listening who feel [37:22.920 --> 37:29.000] passionately about this space. So please, I invite you, yes, you to join the conversation and share your [37:29.000 --> 37:34.200] insights with me. Email me now tech blog right to outlook.com Twitter, LinkedIn, [37:34.200 --> 37:40.840] Instagram, just at Neil see Hughes. And I'll feature your thoughts on here too. But remember, [37:40.840 --> 37:46.600] the field of agriculture is growing, growing with technology and thriving in ways that we [37:46.600 --> 37:53.080] never imagine. So thank you for listening. And until next time, don't be a stranger. [37:59.000 --> 38:01.000] You Transcription results written to '/home/forge/transcribe2.sonicengage.com/releases/20240207164437' directory