What is precision agriculture? UGA expert explains drones, AI and the future of ag tech: täielik transkriptsioon

WEBVTT 00:00:00.390 --> 00:00:10.949 Welcome to Cultivating Curiosity, where we get down and dirty with the experts on all the ways science and agriculture touch our lives, from what we eat to how we live. 00:00:10.949 --> 00:00:12.359 I'm Jordan Powers. 00:00:12.359 --> 00:00:18.149 And I'm Emily Cabrera. We're from the University of Georgia's College of Agricultural and Environmental Sciences. 00:00:19.829 --> 00:00:20.010 [chime] 00:00:20.000 --> 00:00:32.719 We are on the UGA Tifton campus today with Luan Oliveira, assistant professor in the CAES Department of Horticulture and precision agriculture specialist for UGA Extension. Luan, thank you for joining us today. 00:00:32.719 --> 00:00:33.409 Thank you. 00:00:33.409 --> 00:00:36.409 In a nutshell, what is precision agriculture? 00:00:36.409 --> 00:01:44.525 So, precision ag is a small piece of what we call digital ag. Precision ag is a management strategy that helps us on better manage the variability of our fields. So think of a football stadium, you think that that beautiful green lawn, like that green turf, is uniform, but no, there's a lot of science there to actually apply the proper fertilizers to where it needs the most, so all that color is uniform, so that's precision ag. You put your nutrients or your fertilizer, your chemicals where they need to be. Digital ag is something broader, and that's where we get into robotics. So digital ag is the integration of precision ag, which is the management strategy, IoT, internet of things, and computer communication. So, if you see an autonomous tractor running on a field that's more digital ag than precision ag, because that tractor might not be doing the variable nutrient application that we need the management strategy that I just told you guys, so that's it. 00:01:44.739 --> 00:01:49.659 What opportunities does precision ag open for recent grads in this area? 00:01:49.810 --> 00:02:54.370 When you think of people that has an agriculture background versus the people that has an AI background, it's easier for a person to learn the coding, the AI piece, than that guy that knows a lot about AI to learn about plant physiology. So I think that that's where the opportunity is, is recent grads to study classes related to AI, related to precision agriculture, so they can pursue these jobs in big tech companies, where they can apply their knowledge in agriculture, but also apply the knowledge that they gain on artificial intelligence and technology in general. I've heard from big tech companies like Microsoft, when I was at the World Agritech Summit, that this is one of the most valuable backgrounds, where people have the plant backgrounds, like the physiology, weeds, production, nutrient management, but they also have the coding, the AI background as well. 00:02:54.580 --> 00:03:07.469 Ag tech and precision agriculture have become buzzwords, and we're even starting to hear more about AI in ag, but can we actually break that down for folks that aren't familiar with production agriculture? What do these technologies actually look like in the field? 00:03:07.599 --> 00:03:28.629 There's a way to break it down, and the way is prior talking about AI, what AI means, right? Artificial intelligence is basically the capacity of a computer to mimic human intelligence, so that's what we call artificial. So when you get a common or a conventional implement, I would say sprayer, because that's where AI is most applicable now. 00:03:28.629 --> 00:04:18.444 If you got a sprayer and you put a computer there with electro hydraulic systems like nozzles, and then you train that AI to understand what the weeds are, so it's basically you give thousands of examples to that computer and then say, hey, computer, next time you see a weed, you open that nozzle on the top of that weed. So I think that there's a short way to break it down. So it's using computers that mimic human intelligence to enhance the capacity of those implements, because the way it has been done is that, hey, I'm going to spray, so I spray the whole field, places where there are weeds and places where there are not weeds there. When we use AI to identify exactly where those weeds are, we can do something called spot spraying. So, we spray these spots that we actually need. 00:04:18.444 --> 00:04:40.269 So, in a story that we published last year, and we'll link to that in the show notes. You said something that I think is really beautiful. You said, quote, 'The adoption of these technologies is creating a sustainable ecosystem, not only environmentally speaking, but also socially and economically.' You talked a little bit about this with spot spraying versus spraying an entire field, but can you expand a little bit on this three-pronged benefit? 00:04:40.329 --> 00:05:55.495 Yes, so think of sustainability not only as an environment but as a holistic approach. If a grower adopts a technology that, instead of paying for a whole tank of herbicide, for example, some of these technologies, they're proven to reduce that amount by sixty percent. So if you spend that amount of chemicals, like if you're a big enough grower that spend that amount of chemicals for the entire season, and then you cut your costs in 60% already, it's not that money going back to your pocket, but it's money that you did not spend, and then that goes to the environment as well, because you sprayed 60% less chemicals inside of that field that money that the grower didn't spend can be applied to somewhere else, that's where the social sustainability goes, because that money stays in the community, and then that's the social, so that money was not spent, that money can be directed to somewhere else, which is other label-related activities. So if we do a quick math, if a farmer spends a million dollars in labor per year, and we could save 100,000 on chemicals, that's 10% back to that labor workforce. 00:05:55.495 --> 00:05:58.764 Absolutely, it's this cycle that we can kind