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Welcome to the Ash Cloud , I'm Ash Sweeting. Cow feed efficiency is the key driver of farm profitability.
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Yet, despite the importance of this to environmental sustainability and a farm profitability perspective, it remains one of the biggest gray areas and least known areas of livestock production.
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Today I'm joined by Matt Wilson from West Virginia University, who has spent his career studying how efficiently can help turn grass into food.
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Matt, thank you very much for joining me today.
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Good luck, glad to be here.
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So the work you're doing on, I guess, you know, understanding the inputs into livestock production and how that impacts the viability and profitability of the farmers and ranchers you're working with, as well as their sustainability and environmental climate footprint.
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Can you please elaborate and share share with me what you're focusing on in that space?
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Sure.
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Um, so the work I've been doing the last number of years uh has started and revolved around work at our central performance test.
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So we've got a bull test in the eastern portion of the state.
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And in 2003, uh we installed uh what at the time was a gross-safe feed intake system so that we could start to collect data on individual feed intake in animals that were in that performance test, and then research animals that we put through that facility as well.
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So that happened in 2003.
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We were actually the very first central performance test in the US to have an intake system.
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We installed that in August of 2003.
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Uh, Monty Curley at the University of Missouri had installed a research system in April of that year.
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So we were really kind of at the leading edge of individual intake systems uh at the time.
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And the focus very quickly turned to trying to uh not only measure the traits that we would normally measure in a bull test, but to also uh determine individual feed efficiency for those animals.
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Uh we use residual feed intake as the measure of feed efficiency.
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There are a couple different ways out there that people use.
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The advantage to that is it focuses mostly on maintenance energy efficiency, uh, less on uh growth efficiency.
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And so it gets at the the huge, you know, the the preponderant um energy demand of the animal is for maintenance.
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And so that was really what we were focused on.
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And then in 2019, we added to that system the ability to get uh uh individual body weights on animals when they went to water by installing inpin weighing nodes, and uh uh when we did that, we convinced GrowSafe, which is now Viteli, to add meters to the waterers that we used as an attractant for those inpin scales and uh integrated that water intake information into the system as well.
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And so for the last uh six and a half, seven years, we've been collecting individual daily feed intake, water intake, and weight data on animals.
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And my focus these recent years has really been about taking that wealth of data.
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We'll uh evaluate between 600 and 900 animals a year in that system, and taking that wealth of daily data and trying to use it to build sort of machine learning or AI-based approaches to determine intakes of grazing animals.
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And there's a huge need in the industry to have tools that could work at scale and accurately measure uh dry matter intake of grazing animals.
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Um, you know, until the tool we developed, a lot of that was based on uh equations in the nutrient requirements of beef cattle manual.
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That's the equations are based largely on dry lot data.
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Um, and we took the time and the effort, and it was a significant effort in time and both in the field and in the laboratory for the graduate students to go through and and do a lot of ground truth data collection by using inert markers of animals who are grazing out on pasture to calculate individual intakes.
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And so we've built a tool that allows us with daily body weight and daily water intake, and then we uh scrape publicly available data from the nearest NOAA station and meta data about the animals we're evaluating and are able to determine individual dry matter intakes.
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And so that's been a huge benefit to get that kind of data, accurate data about animals that are actually grazing in the field.
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And for for people who uh who are not animal scientists, um, you know, the why why is this so important?
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Well, it's critical because as we talk about footprints of the beef industry, whether that's uh carbon footprints or water footprints or ecological footprints, uh there's about 90 million beef cattle in the U.S.
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Um about 12% of them are in a feedlot for the final stage of their production.
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Um, but the majority of them, you know, the other 88% are grazing on pastures or feeding uh harvested forages.
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And so knowing what those animals are actually doing is important, uh, especially as we think about things like greenhouse gas emissions as an example.
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So the methane that uh an animal um adds to the environment, mostly through um the rumination process, uh they it's about, you know, the book says it's about 23 grams per kilogram of dry matter intake uh for animals that are eating a forage-based diet, about 10 to 13 grams per kilogram of dry matter intake for animals that are in the feedlot.
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And so the grazing animal produces about twice as much methane per kilogram of dry matter intake.
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Um, and it's where 88% of the animals are.
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And you know, the US it's 88% around the globe.
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Uh the numbers of animals that are fed in a feedlot is even lower, and so you know, the the overwhelming number of ruminants around the globe are in some sort of pastoral grassland system.
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Um, and the one of the features of that is that's where their their methane intensity is the greatest.
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And so understanding what's really going on there is critical for us then to identify animals that are more efficient in resource utilization and to make improvements then in those footprints and you know of a variety of types in those animals because that kind of change, genetic change in their resource utilization is permanent and additive, where you know, feed additives that might reduce out some of those outputs and shift some of that carbon to energetics of the animal, uh those really only work in situations where you're formulating a ration and delivering it to the animal.
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A lot of great stuff there, but to take a little step back um in terms of going through some of the things you said, you mentioned the maintenance requirement and the growth requirement.
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So any animal, depending on its size and its genetics and a bunch of things, will take a certain amount of energy just to stay alive for its normal metabolic functions before it actually grows and produces any food, be that beef or meat or or milk.
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And so if you have an animal that does is only being fed at maintenance, you're keeping that animal alive, but you're not actually producing any food.
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So it's um its impact, the the relative uh merit of of what it's creating for society in terms of food and the cost of that in terms of economics as well as environmental impact, um, it's not creating any value, but it's still got a significant cost.
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So that's a big part of why this efficiency is important.
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And and I frequently think about this a bit like a bit like cars or vehicles.
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And if you've got a if you've got 10 gallons or what 40 odd litres of of fuel, you can stick that into an efficient vehicle and drive um you know three or four hundred kilometres, or you could stick it into a very inefficient vehicle, create much more pollution and and not get very far.
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So it it's uh energetics is is a similar concept um in that regard.
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Is that is that how you see it as well?
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Does that make sense?
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Absolutely.
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So, you know, uh a big the what we feed animals is really their fuel.
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It is really an equivalent to the the liquid fuels we would use in a vehicle.
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And so uh I actually have a a slide I often show in presentations I give where we had two bulls that were in our one of our performance tests um that were uh very similar in genetics.
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So they had the same uh sire, they were born to have sib cows, uh born just a day apart from each other.
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And in our performance tests, they gained the same rate of gain, but one of those animals ate 50% more than the other for no additional performance.
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And if you put that difference on an annual scale, it was uh almost uh 7,000 pounds of additional uh feed intake for no additional performance.
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You know, it was like the difference between a car from the 70s with a carburetor and a car from the uh 2020s with fuel injection.
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Um, it's just that different.
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And the reason we focus on the efficiency of maintenance is because you're right.
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That's it's but depending on the life stage of that animal, it's 75 to 90 percent of their energy daily is used just to just in maintenance.
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Uh, it's why if I go to the gym for 15 minutes, I don't lose much weight because most of the calories I take in are used just to keep me alive.
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And in order to burn excess calories, that the number of calories I need to burn is tremendous because it's really a small increment that is sort of extra activity above basal metabolic rate.
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So on those that trial you mentioned, um you said about 7,000 pounds or about 3,000 kilos or three tons, um, just the difference in feed costs.
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And if you put a fairly conservative value of $200 a ton on that um on the feed cost, um, you're looking at $600 difference for exactly the same amount of growth and productivity, and that's on a single animal.
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And if you go back to the 90 um odd million animals across the country and you've got that much variation, you know, there's a lot of money slipping through the the fingers of a lot of a lot of producers um because of that inefficiency.
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Absolutely, and you know, if you make the wrong decision, those animals are often in the herd for 10 productive years if it's a cow, and you know, if you make that wrong choice, it's six hundred dollars a year, but it's for that entire lifetime, and so you know, in our in the beef industry, those animals are around for a long time, and so these decisions have have long consequences, and we are just starting, you know, it's only been for the last 20 years that we've had tools to really be able to um really uh at scale and in a reasonable way get at individual intakes, and so it it has the potential to be a real boost for the industry.
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In fact, a couple of years ago, I was at NCBA and I was on a I had a grant project at that time to try and help understand producers' decision-making process, particularly for replacement females.
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And one of the questions we would ask them is, you know, how much do your females eat?
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How much how do you assess input costs in deciding which females to keep?
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And they said, Well, we don't have a tool that does that, and so we don't pay attention to it, but you know, they with one simple decision, you know, a lot of the metrics can look the same, but that one simple decision could cost them six hundred dollars a year for you know 10 years.
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That's a lot of investment that has gone in the wrong direction.
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It doesn't have any payoff, and so it's uh it has tremendous potential as we start to go from the laboratory to the field to help producers find ways to become much more resource efficient in their operations and much like any other industry, look for places where there's costs that can be contained to improve profitability and therefore sustainability.
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So what I guess what I'm thinking is is you know the scenario if if we understand this, manage for it and and and and so and and have solutions that the animals are efficient and what that may look like, and I guess if we don't manage it, um and what that would look like.
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Is that something you've you've worked through um in terms of what those two scenarios would look like?
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Well, you know, if if we're not evaluating and managing it, we're gonna uh stay where we are.
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And if you look at something like the poultry industry, where they've had the ability to measure feed efficiency for a long time uh and put significant pressure on it, they've dramatically improved uh feed efficiency and and they know that improving feed conversion ratio, which is the the metric they use to measure feed efficiency by one thousandth of a point, it means millions of dollars for their industry.
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And we just have not put the kind of pressure we could on that in the beef industry.
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Um, but we're the tools are coming uh that that they've either come recently or are coming to allow producers to pay attention to that and have real impact on their selection decisions and what that means for the sustainability of their operation.
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And you know, we've been talking about feed efficiency, but the other thing, since we measure individual water intake as well, you know, water use efficiency is another thing that that has an impact, uh, particularly in those parts of the country where water resources are limited, which you know you think of things west of the Mississippi as kind of a uh boundary.
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Um and water is a much more important deal than it is here in the Mid-Atlantic region.
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Um, and I have a similar data slide that you know two bulls in the same test that had similar levels of performance, um, but the one that drank the most and drank the least, if you annualize their difference in water intake, it was 1,500 gallons.
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Um, and again, you start amplifying that by the number of animals, even in a population, and in those parts of the country where producers haul water to animals, um, you know, it's not just the volume of the water, which is a critical resource, but it's the time and labor and fuel associated with hauling all that extra water around.
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And so there's just tremendous opportunity in the beef industry that didn't exist 25 years ago to really uh collect data about phenotypes that can make a huge difference in the profitability of operations and start to use that data to improve both individual producer operations and um the efficiency of the industry uh broadly read.
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And what's what's needed to accelerate uh progress?
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Because you know, you know, adding on to what you've just said, if you you know, beef prices are going up, there's a shortage of cows packing, how the packers are closing down because they can't get enough animals coming through, um global demand for protein is is is continuing to rise as and the the in impacts of our of our livestock production systems are in continuing to um be politically volatile and also have have significant impacts on the environment.
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So having having systems where we can produce more food with fewer resources, um with less waste, so there's there's greater profits for those people who are doing the work and and and that's their livelihood, and also a lower climate impact, there's there's no losers in in that scenario.
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Um it's a win for everyone.
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So what do we need or what's needed to accelerate progress uh in this space?
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I think the biggest thing is is you know the the ability to move technology from the research space to the industry large rent.
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So uh right now in West Virginia, we've taken our technology, and for the last three years, we've conducted a grazing performance test for our heifers and use that information to try and identify uh the most efficient in the group, taking that kind of approach uh and spreading it across the country so it's available, especially at a time that everybody talks about the tremendous need to um grow the cowherd.
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Um, now the the data about harvest suggests that people aren't retaining heifers at the rate we really need them to, but it's an opportune time from a uh at least a potential to grow that heifer crop and regrow the cow herd with a very, very different um footprint that's much smaller than it has been in the past, that could rapidly have a positive impact on the industry because addressing those that you know we the shortage in females that exist today, if we could bring in uh sort of the next generation of females at 10 or 15% more efficient than the average of the current herd, that would have long-term impact on the beef industry, uh, reducing footprints and and increasing the potential for profitability on farms.
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So you mentioned like I I back to the uh the the motor vehicle analogies because I think they're quite useful.
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Uh you've got, you know, you're driving down the down the freeway, and there's one car that is particularly polluting, and you know, there's smoke coming out of it, and there's there are hundreds and hundreds of other cars, but that that one car that's really, really bad uh has a disproportionate impact on the pollution of all the cars.
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And if you just get rid of that one car, then the whole freeway and the air, it doesn't make it perfect, it doesn't turn it into wilderness, but it certainly has a disproportionate effect.
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And and those top most inefficient animals, um, are they similar to that highly polluting car?
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Yeah, and the yeah, I I have a conversation that I think is what you're getting at with my farm manager all the time.
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He says, you know, if we could just get rid of the bottom 25%, uh it you know, it would it would raise the average efficiency tremendously.
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I tell him that, you know, in my animal genetics class that was selecting the top 75%, but either way, it it gets you to the same place.
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It you know, we could make a huge leap forward.
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Uh uh the analogy I use when I'm talking to classes is the car analogy.
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And so when I was when I turned 16, uh my parents gave me the opportunity.
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To buy their old Pontiac Catalina station wagon uh built in 1977, and it got six and a half, seven miles a gallon.
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Um, and you know, just the the cost that was invested in fuel over the lifetime of that vehicle, I could have uh bought several vehicles that were you know had an efficiency like we have today.
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My my son, when he turned 16, ended up with a Toyota RAV 4 that gets 30 miles a gallon.
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I mean, it's just that that's that's a tremendous difference in what it takes to move that down the road.
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And I think that's really where there's a huge opportunity.
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Um, in class, we always tell students in animal science that 70% of their variable cost of production is feed cost.
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Um, it's sometimes hard to really capture that value in animals that graze because it's it's sometimes hard to put a value on pasture forage, um, but um it's still a real cost.
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And so, you know, at a time that margins are thin, even though prices are high, um the the ability to increase stocking density on the same acreage or maintain a stocking rate on a smaller acreage really has the potential to make a difference.
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When when the Grow Safe tool first became available, there was a producer that got on board out in the West and he went from stocking 19 cow calf pairs per section to 38 cow calf pairs per section just by focusing on efficiency.
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Now, there was a tremendous focus on efficiency, and and anytime you focus on one trait, that means you take away some focus from other traits, but you know, it's that kind of improvement that's possible, and it's something we haven't put a lot of pressure on.
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Unlike the poultry and swine industries that that have had these kinds of records for a long time, we've we've often evaluated groups of animals and assumed they're they're all reflective of the average.
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And what I can tell you is when you get individual data about a group of animals in a pen, uh, very few of them are average.
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They're often either way out on one end, that's seven miles per gallon car, or they're at the other end and they're a 30 mile per gallon car.
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And selecting those efficient animals just is a you know, you have to still consider performance and fertility and and production.
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But if you have information about efficiency as well, and you can put that into your uh matrix of selection, all of a sudden you can say, okay, well, for these two animals that are similar otherwise, I want to take the one that does it for less inputs.
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And they come in all different shapes and sizes, right?
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Some people think, oh, well, if they're efficient, they're probably small animals that eat a little bit.
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And what I can tell you is every set of data I look at for a group of animals, there are efficient animals throughout the intake spectrum and throughout the weight spectrum.
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And so there are large animals that are very efficient.
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There are also small animals that eat little but do it inefficiently.
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And so at the end of the day, you can't just find them by just looking at the animals.
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You gotta have data uh about individual performance, and it's really, you know, the one of the things that that I think will come to the industry in time is we'll get away from trying to manage averages and we'll get better at managing individuals.
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Because even if you've got that inefficient vehicle, you can do things about how you manage that vehicle and use that vehicle and drive that vehicle that makes best use of whatever type of performance it has.
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So I think there's a lot of potential out there.
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You mentioned um having the tools to actually get the data so you can you know make these decisions and evaluate them, which is obviously critical, but you also said that that's an area that um tools are emerging and it's it's being addressed.
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What other areas need additional energy focus investment?
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Um, is there policy issues?
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Is there is there market signals?
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Are there are there other areas that we need to also focus above and beyond the the development of the technology?
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I mean, I think the the market signals and the conversations that you have with um thought leaders at places like uh NCBA and others, you know, there's this tremendous need to try to grow the cowherd.
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Um, it is the the although it's leading to high prices for parts of the market, those high prices are causing uh um undesirable consequences in other parts of the industry.
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And so, you know, if there was if there was incentive to grow the cow herd, to retain heifers, and and if that can be done, especially to using tools that would allow us to grow the cow herd by retaining heifers that were of um improved uh potential for the industry, uh, it's a that would be a boon.
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And uh, and you know, there's discussion about how do you incentivize that in a world where uh heifer going to the feedlot is just worth so much, it's hard for a producer to want to retain that animal as part of the breeding herd.
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And so I think that is probably one of our biggest things.
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Um, that you know, what are the what are the incentives that that would lead the industry to really increase the number of heifers that were retained so that we could grow the cow herd, uh especially in a world where you know, with New World Screwworm uh moving north, we've limited or stopped importation of cattle from Mexico, and so that's having impacts on the price of beef in the retail case at grocery stores in the US.
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And so there are there are other factors outside of sort of our normal production system um traits that are having impacts on prices that really get at what is the cost of protein to consumers in the marketplace.
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And that's you know, anything we can do to uh drive those prices down is helpful for you know people meeting their dietary requirements, as having the capacity to uh uh adequately feed particularly fragile populations.
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I mean, there's just a whole host of uh uh downstream uh impacts that would happen if we could uh start to um grow the cow herd and do that in a way that that addresses the demand that is out there with supply that is needed.
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We've focused uh almost exclusively so far on on the United States, but you know, cows being cows, um, they're not that different here than they are across the rest of the globe.
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Um, there are there's there's more animals in feed yards here than anywhere else.
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So those percentages out on pasture is even higher when you start looking at Latin America and Asia and Africa and Europe and Australia.
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So where where do you see the work that you're doing translating more broadly globally?
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I think it it varies with a lot of those different places and kind of where they are in their beef cattle industry journey.
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So some of those places, um, you know, I think of Brazil or Australia, uh the selection of animals to perform at a high level in those um countries is um it's similar, I would say, to ours.
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I've not been to those places, but in in what I read and conversations I have with people, they're much closer to ours.
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There are also places where you know live animal is the primary determinant.
00:30:41.200 --> 00:30:51.279
And so there's because there hasn't been a lot of selection pressure on you know productivity or efficiency, uh, there's tremendous opportunity.
00:30:51.279 --> 00:31:05.839
I think there's a need to be sensitive to you know the cattle that perform in Central Africa are have a different genetic base than cattle that perform uh you know in the northern reaches of Canada and Russia.
00:31:05.839 --> 00:31:43.279
And so, you know, it it needs to be place-based, but I think there's huge opportunity for aspects of precision livestock farming and and you know, US, Europe, Australia, Brazil, those kinds of places will adopt technology the fastest, but sort of older generation but still recently developed technologies could have a tremendous impact uh in in places where there hasn't been as much advancement of uh the industry for the genetics that exist in those places.
00:31:43.279 --> 00:31:52.480
And so it's a it's something I think that there's a tremendous opportunity globally for us to take the land that's available.
00:31:52.480 --> 00:32:02.079
And the reality is, is across the globe, the greatest proportion of agricultural land is grasslands.
00:32:02.079 --> 00:32:33.359
We often think of, or at least my perception of the common thought is you know, you talk about agriculture and people think about row crops and tilable land, uh, but the reality is the greatest proportion of land globally is grassland that can be used for grazing, where ruminants are are well suited to convert those uh grasses into that are mostly carbohydrate into high-quality protein for human consumption.
00:32:33.359 --> 00:32:45.519
Um, and so I think there's just tremendous need to um look for ways to transfer technology uh at an appropriate stage.
00:32:45.519 --> 00:33:02.000
You know, um maybe here individual animal performance testing is is the key, but maybe in some places just knowing better what performance metrics are uh would be helpful in identifying animals that could do more with less.
00:33:02.000 --> 00:33:04.160
I think at the end of the day, that's the real key.
00:33:04.160 --> 00:33:08.480
We're not we've got no more land that's going to become agricultural land.
00:33:08.480 --> 00:33:14.799
We've got good quality agricultural land that's being removed from production all the time all over the globe.
00:33:14.799 --> 00:33:32.799
And so, how do we try to do more with less as populations continue to grow, uh population populations continue to move up in uh from sort of third world conditions to second and first world conditions?
00:33:32.799 --> 00:33:40.559
Um, you know, the a lot of things we worry about in third world countries are dietary, right?
00:33:40.559 --> 00:33:55.920
There's an awful lot of preventable uh disease and suffering that occurs just because of malnutrition, which is sometimes undernutrition, sometimes it's just not uh the the right blend of nutrition.
00:33:55.920 --> 00:34:07.440
And so there's tremendous opportunity for animal agriculture to upcycle poor quality um feedstuffs into high-quality uh protein for human consumption.
00:34:07.440 --> 00:34:24.559
And I think there's uh an a it's reasonable that those of us that are at the leading edge of that find ways to take things that are applicable uh to populations and apply them in their in their culturally appropriate ways.
00:34:25.760 --> 00:34:40.800
I think it's probably also worth adding that somewhere in the order of one and a half billion people globally rely on livestock and livestock production for their livelihoods, which is probably bigger than any other single industry.
00:34:40.800 --> 00:35:12.400
And those millions of square miles or square kilometers of land that are uh used for livestock production, if we as humans or as societies want to impact that land, the the most powerful um avenue to do that is through those people that are currently the custodians of that land, which are the the herders, the farmers, the ranchers, uh the pastoralists, wherever you know that happens to be in the world.
00:35:12.960 --> 00:35:13.519
Absolutely.
00:35:13.519 --> 00:35:58.639
I think that's that's really critical, is that you know being able to uh help communities, villages, you know, whatever the the appropriate unit of of society is to be to attain a better standard of life for them and their families, um, for those that agriculture is their calling, uh finding ways to improve how they do it in their um systems is is a valuable to value to them and their family, just like any other industry that we can improve the productivity of has value for those that are involved in producing.
00:35:59.760 --> 00:36:16.079
You mentioned perception earlier on, and you know, perception is one of those things that's very very individual and personal, so I'm certainly not going to speak for humanity in this perspective because I I wouldn't be so bold.
00:36:16.079 --> 00:36:27.920
However, you know, frequently in conversations when people it comes up about the beef industry, the picture that people get are are the big feed yards.
00:36:27.920 --> 00:36:38.800
Um and you know, 12% in the US, much lower elsewhere in the world, and the grazing systems are where the animals are.
00:36:38.800 --> 00:36:48.960
Is is perception and people's perception a an issue that we need to spend more time and effort on.
00:36:48.960 --> 00:36:54.239
And if you think that is the case, where what do you think are the priorities there?
00:36:55.280 --> 00:36:58.000
It's something that I actually think a lot about.
00:36:58.000 --> 00:37:12.880
Um, you know, the message about what we actually do in agriculture to feed populations, you know, in the US, less than 2% of the population is engaged in agriculture in any way.
00:37:12.880 --> 00:37:20.639
Uh it's kind of funny you ask because just yesterday, one of my sons, he's a freshman in engineering at WVU now.
00:37:20.639 --> 00:37:38.159
Uh he sent me a reel from Instagram, and it was some guy talking about beef production around the world and the the what I think is an artificial dichotomy of grass-fed versus grain-fed.
00:37:38.159 --> 00:37:52.639
And he stated with great assurance that grass-fed cattle take 18 months to mature, and that corn-fed or grain-fed animals uh take six weeks.
00:37:52.639 --> 00:38:01.840
And my son, who's you know, only kind of partially paid attention over the years, says, Dad, we don't even wean the calves when they're six weeks old.
00:38:01.840 --> 00:38:21.519
Um, but it's just, you know, the there is all because there is so much information out there in a in a in a in our modern world, and and information literacy and information reality are huge struggles.
00:38:21.519 --> 00:38:31.599
And I think there's an opportunity for those of us that are involved in agriculture to do more to help people understand what really goes on.
00:38:31.599 --> 00:39:02.239
Um, I didn't come from an agricultural background, my my parents live in a city in Indianapolis, and so when I talk to them, I always try and, you know, I try to be as objective as possible, which I am a person that's engaged in the industry, and so I have a certain perspective sometimes, but trying to help them understand the realities of what does it take to feed you know eight billion people?
00:39:02.239 --> 00:39:03.280
Where are they?
00:39:03.280 --> 00:39:04.880
Where are the resources?
00:39:04.880 --> 00:39:06.159
How do we do that?
00:39:06.159 --> 00:39:16.400
How do we actually get from a calf on the farm or a lamb or a kid if it's a goat to an animal that's ready to harvest?
00:39:16.400 --> 00:39:17.679
What does that really look like?
00:39:17.679 --> 00:39:20.480
What are the the footprints of it?
00:39:20.480 --> 00:39:26.400
How do they compare to um other you know plant-based protein sources?
00:39:26.400 --> 00:39:41.679
Um, you know, there's a there's a whole um need for translation of what is sometimes very technical scientific information to general audience.
00:39:41.679 --> 00:39:55.440
Uh, when my boys were very young, uh they asked the the quote-unquote teachers at their daycare before they were in kindergarten, asked me to come and talk to the kids about animals.
00:39:55.440 --> 00:40:04.880
And so I came in, I put diapers on a couple of lambs and brought in some three or four-day-old chicks uh so they could have something to see.
00:40:04.880 --> 00:40:12.880
And it turned out a the word got out, and a bunch of moms came that day, too, which was a little odd to have all the moms present at daycare.
00:40:12.880 --> 00:40:19.119
Um, but there was a kid that showed up with a super deluxe hamburger on the front of his shirt.
00:40:19.119 --> 00:40:21.840
I didn't stage it, but it was perfect.
00:40:21.840 --> 00:40:27.280
So I I brought that kid up front and we just started the topic, you know, where's the bun come from?
00:40:27.280 --> 00:40:31.519
And then all the kids said the grocery store, those kinds of things.
00:40:31.519 --> 00:40:39.199
And we eventually got to that the bun comes from the farm, and the lettuce comes from the farm, the hamburger comes from the farm.
00:40:39.199 --> 00:40:46.480
Uh, and and so by the end, I said I got the kids, they they understood that when I said, Where's the food come from?
00:40:46.480 --> 00:40:47.760
They said it comes from the farm.
00:40:47.760 --> 00:40:51.519
And one of the mothers raised her hand and she said, But not candy.
00:40:51.519 --> 00:40:55.440
And I said, Actually, candy comes from the farm too.
00:40:55.440 --> 00:40:59.119
Um, and you know, I I oversimplified it.
00:40:59.119 --> 00:41:20.239
I didn't talk about wild-caught seafood, and you know, there are there are some non-farm food products, but you know, it's that notion that it all has to come from the farm, that it's it's a it's a huge complex, you know, the notion that there are there's something like three days supply of chicken in the US at any given time.
00:41:20.239 --> 00:41:25.199
And if we stopped producing and harvesting it, it would disappear like that.
00:41:25.199 --> 00:41:38.159
And people just don't think about what it takes, you know, what has to happen in some cases two years ago to get food on their plate, whether that's at home or in a restaurant or in an institution.
00:41:38.159 --> 00:41:52.320
Um, it's a it's a huge complex thing, and there's all kinds of pricing signals and other things that impact how the people that do that production make decisions about what they're going to produce.
00:41:52.320 --> 00:41:58.480
Um, and you know, those are stories that we just there's not enough general understanding of.
00:41:58.480 --> 00:42:16.480
And so, you know, I recognize there's there's a limit to how much I can do about it, but I take every opportunity I can to talk to general audiences and help them start to understand, you know, for something that we depend on daily, um, it's a big deal.
00:42:16.480 --> 00:42:36.880
Uh, I spent a little time as the associate dean for research here at WVU in the uh ag school, and I would talk to one of the vice presidents of research, and she would often talk about the great research that was happening in the physics department and the great research that was happening in the medical school.
00:42:36.880 --> 00:42:54.000
And over time I worked on her and and I pointed out, I said, you know, there that most of the world's population may never ever in their life see a doctor, but almost all the population has to eat.
00:42:54.000 --> 00:43:17.599
And it's just, you know, it's a it's a different calling to be a researcher in agriculture, it's a different calling for those people that work in production agriculture, um, and they don't get the credit and the thanks that they ought to, because especially in first world nations like the US, we've got so many choices that we don't know what to do about it.
00:43:17.599 --> 00:43:38.400
Uh and you know, uh the the thing maybe we shouldn't get into, but uh I'll mention it is that you know, no matter how efficient production is, uh the amount of food we waste is uh another side of the bigger uh agriculture food system uh uh continuum.
00:43:38.400 --> 00:43:46.320
And you know, in the US, 40 to 50 percent of the of the edible food that is produced is thrown out.
00:43:46.320 --> 00:43:59.119
Um and I spent some time trying to get uh anaerobic digestion or other tools for making better, making higher use of that organic waste.
00:43:59.119 --> 00:43:59.760
Uh ultimately.
00:43:59.760 --> 00:44:18.719
We were unsuccessful, but you would have conversations with people, and they just were completely unaware that most of that goes in a landfill and rots away and you know creates um detriment to the ecosystem by being rotting food.
00:44:18.719 --> 00:44:25.679
Um and and so there's a uh it's a there it's a big issue.
00:44:25.679 --> 00:44:33.119
Um and I think the we we worry about we don't worry about food because it's plentiful here.
00:44:33.119 --> 00:44:40.639
We focus in the US more on on excess calorie intake, and and it is a problem in the US.
00:44:40.639 --> 00:44:55.840
You know, obesity is is uh a real issue in the US, uh, but in most of the world, in the sort of average human, um, they've got insufficient calories, uh, or at least insufficiently balanced calories.
00:44:55.840 --> 00:45:00.559
And so it's a hard thing to to get people to wrap their mind around.
00:45:00.559 --> 00:45:04.239
Um, and understandably, but we need to talk more about it, no doubt.
00:45:04.639 --> 00:45:06.880
Think back to the animal side of things.
00:45:06.880 --> 00:45:16.239
When you think of pre-industrial revolution societies, you know, animals were that food recycling mechanism.
00:45:16.239 --> 00:45:28.320
Anything that wasn't eaten in the house was fed to some chickens or some swine or some sheep or goats or cows and converted back into something that was then was then edible.
00:45:28.320 --> 00:45:45.840
Um, plus you've got the nutrient cycling through their manure and through their dung going back into soils or vegetable gardens or or all those sorts of interactions and and that feedback loop has has been fairly dramatically severed in our modern societies.
00:45:46.239 --> 00:45:48.800
It it's it's been partially severed.
00:45:48.800 --> 00:46:24.719
Uh, you know, I one of the things I often I sometimes talk to people about is you know, if you think about food processing, there's a tremendous amount of food processing what we used to call byproduct, and sometimes we call it now co-product, but components of converting raw materials into further processed food stuff for consumption, that there are products there that that today the the the those things go into uh animal diets somewhere.
00:46:24.719 --> 00:46:57.519
Um, whether it's you know the the starting in the 90s when we started to make a lot of ethanol, there's there was all of a sudden all these waste products from that ethanol production, we call them distiller's grains, that there was a need at the time for in the 90s for research on how do those become good feedstuffs because just burying them or landfilling them was too costly or or not the right thing for those industries to do.
00:46:57.519 --> 00:47:22.960
And so um a lot of there's a lot of cakes and meals and other you know in animal agriculture, we talk about soybean meal as an ingredient all the time, and soybean meal is the waste product of soybean oil production, and you know, it's a fundamental component, particularly of monogastric diets, uh like pigs and poultry.
00:47:22.960 --> 00:47:37.840
And so there's still a lot of that that happens, um, but it's not it's not in a in a defined you know watershed level ecological circle, right?
00:47:37.840 --> 00:47:48.960
Those those things are moved across the country, and so the the co-products and the the things like manures and other things end up in disparate places.
00:47:48.960 --> 00:48:02.639
If you look at a map of nitrogen flow across the globe, there's this these huge arrows of nitrogen exiting the upper Midwest of the US, going to all kinds of places.
00:48:02.639 --> 00:48:08.480
It's not staying in a circular economy there uh in the upper Midwest.
00:48:08.480 --> 00:48:24.320
And you know, there's implications of that, you know, and um it's a it's a complex thing, and and I I often tell people that I like I don't like to talk about systems, I like to talk about complexes.
00:48:24.320 --> 00:48:26.400
It's like a big bowl of jello.
00:48:26.400 --> 00:48:58.079
And if you push it in one place, what you get is a reverberation of consequences, and so you know, if we sometimes try to come to simple solutions to a perceived problem without recognizing that adding or removing something from the complex doesn't just address that thing, but it then has these follow-on consequential reverberations to all kinds of other aspects.
00:48:58.079 --> 00:49:05.599
And so um it is it's it, you know, the the deeper you dig into it, the more complicated it gets.
00:49:05.599 --> 00:49:25.119
And so I sometimes have conversations with students, you know, I've had some of our classes, they hear about an issue and they say, well, you know, we should just not do this, or we should just not do that, and then you start thinking about, well, you know, here's here's what other activities depend on, you know, step one.
00:49:25.119 --> 00:49:27.519
And you don't often think about that.
00:49:27.519 --> 00:49:43.039
And so you know, if you change this operation, it will impact other places, and sometimes those impacts are as detrimental or or more detrimental than the problem you're trying to solve.
00:49:43.039 --> 00:50:27.360
And so, you know, helping young people as they grow and develop to recognize that interrelation of food and agriculture, and then the food and agriculture with larger things in the world, um, and both the sort of biological processes that are impacted, and then you layer on top of that policy, um, and sometimes well-meant policy, but that has just um tremendously constraining consequences that then then then lead to other unintended and sometimes not recognized for some period of time consequences.
00:50:27.360 --> 00:50:31.360
And so it's a there's a lot to to do.
00:50:31.360 --> 00:50:55.119
There's real opportunities to improve things, and you know, circling back to your comment early on, you know, improving the efficiency of the beef industry or animal agriculture uh more largely, um it has win-win uh consequences, and it's sometimes hard to find those things that are a win that lead to another win.
00:50:55.119 --> 00:51:22.000
Um, and so I think it's important that that um that that be part of education, be part of communication, and it's something that agriculture has historically not done a good job of telling its story, especially as fewer and fewer people were involved in it, because it was no longer that diversified operation that had some cows, some pigs, some chickens, and the slop went out in the yard.
00:51:22.559 --> 00:51:44.800
Well, that's that's a hundred percent why I invited you on today to discuss this, because the work you're doing across that feed efficiency side of things is is you know such an opportunity to create that that win for farmers and ranchers, that win for food productivity and food security, and also that win for the environment and climate.
00:51:44.800 --> 00:51:48.320
And they're they're few and far between far between.
00:51:48.320 --> 00:51:59.280
When we find them, we need to we need to make sure that they're they're um you know lifted to the top and and and put on the agenda and discussed um so they don't slip through the cracks.
00:51:59.599 --> 00:52:01.199
Yep, I agree 100%.
00:52:02.000 --> 00:52:08.079
So uh before we go, is there anything else that you'd like to add that we haven't uh already discussed?
00:52:10.719 --> 00:52:15.360
Um I mean I think we've we've covered an awful lot of ground.
00:52:15.360 --> 00:52:23.039
Um, you know, I think the the biggest thing is is you know how do we do a better job in our industry?
00:52:23.039 --> 00:52:49.599
How do we do a better job of communicating what we do for the globe from our industry and helping people, especially outside of agriculture specifically, or science generally, understand you know what it what is really happening, what could happen, uh, and how to make good policy.
00:52:49.599 --> 00:52:56.960
Because at the end of the day, all of these things, the the hardest part of them is the human dimensions piece.
00:52:56.960 --> 00:52:58.079
I'm convinced of that.
00:52:58.079 --> 00:53:05.599
I mean, I can I can tell students to study for class, um, and and getting them to do it is the hard part.
00:53:05.599 --> 00:53:16.000
I can talk to producers about uh changing management practices for their own for the the financial benefit of their operation, but getting them to do it's hard.
00:53:16.000 --> 00:53:17.519
And and that's the real part.
00:53:17.519 --> 00:53:30.719
And I, you know, I'm not a uh uh anthropologist or sociologist or psychologist, but I have over the my years come to realize that human dimension piece is the hardest part of all this.
00:53:32.719 --> 00:53:35.519
Matt, thank you so very much for joining me today.
00:53:35.519 --> 00:53:37.599
Sure, thanks for having me.
00:53:37.599 --> 00:53:39.920
Thank you for listening to the AshCloud.
00:53:39.920 --> 00:53:53.840
Please subscribe to AshCloud if you've enjoyed this podcast, where I will continue to discuss food sustainability with guests to bring a deep understanding of the environmental, political, and cultural challenges facing our society and creative ideas on how to address them.
00:00:07.280 --> 00:00:19.440
Welcome to the Ash Cloud , I'm Ash Sweeting. Cow feed efficiency is the key driver of farm profitability.
00:00:20.480 --> 00:00:34.399
Yet, despite the importance of this to environmental sustainability and a farm profitability perspective, it remains one of the biggest gray areas and least known areas of livestock production.
00:00:34.399 --> 00:00:44.159
Today I'm joined by Matt Wilson from West Virginia University, who has spent his career studying how efficiently can help turn grass into food.
00:00:44.159 --> 00:00:46.960
Matt, thank you very much for joining me today.
00:00:46.960 --> 00:00:49.439
Good luck, glad to be here.
00:00:49.439 --> 00:01:09.120
So the work you're doing on, I guess, you know, understanding the inputs into livestock production and how that impacts the viability and profitability of the farmers and ranchers you're working with, as well as their sustainability and environmental climate footprint.
00:01:09.120 --> 00:01:15.920
Can you please elaborate and share share with me what you're focusing on in that space?
00:01:16.879 --> 00:01:17.439
Sure.
00:01:17.439 --> 00:01:26.000
Um, so the work I've been doing the last number of years uh has started and revolved around work at our central performance test.
00:01:26.000 --> 00:01:29.200
So we've got a bull test in the eastern portion of the state.
00:01:29.200 --> 00:01:48.799
And in 2003, uh we installed uh what at the time was a gross-safe feed intake system so that we could start to collect data on individual feed intake in animals that were in that performance test, and then research animals that we put through that facility as well.
00:01:48.799 --> 00:01:51.200
So that happened in 2003.
00:01:51.200 --> 00:01:57.200
We were actually the very first central performance test in the US to have an intake system.
00:01:57.200 --> 00:02:00.239
We installed that in August of 2003.
00:02:00.239 --> 00:02:05.760
Uh, Monty Curley at the University of Missouri had installed a research system in April of that year.
00:02:05.760 --> 00:02:13.199
So we were really kind of at the leading edge of individual intake systems uh at the time.
00:02:13.199 --> 00:02:30.080
And the focus very quickly turned to trying to uh not only measure the traits that we would normally measure in a bull test, but to also uh determine individual feed efficiency for those animals.
00:02:30.080 --> 00:02:34.960
Uh we use residual feed intake as the measure of feed efficiency.
00:02:34.960 --> 00:02:37.680
There are a couple different ways out there that people use.
00:02:37.680 --> 00:02:46.639
The advantage to that is it focuses mostly on maintenance energy efficiency, uh, less on uh growth efficiency.
00:02:46.639 --> 00:02:55.280
And so it gets at the the huge, you know, the the preponderant um energy demand of the animal is for maintenance.
00:02:55.280 --> 00:02:57.599
And so that was really what we were focused on.
00:02:57.599 --> 00:03:28.080
And then in 2019, we added to that system the ability to get uh uh individual body weights on animals when they went to water by installing inpin weighing nodes, and uh uh when we did that, we convinced GrowSafe, which is now Viteli, to add meters to the waterers that we used as an attractant for those inpin scales and uh integrated that water intake information into the system as well.
00:03:28.080 --> 00:03:40.159
And so for the last uh six and a half, seven years, we've been collecting individual daily feed intake, water intake, and weight data on animals.
00:03:40.159 --> 00:03:46.080
And my focus these recent years has really been about taking that wealth of data.
00:03:46.080 --> 00:04:07.280
We'll uh evaluate between 600 and 900 animals a year in that system, and taking that wealth of daily data and trying to use it to build sort of machine learning or AI-based approaches to determine intakes of grazing animals.
00:04:07.280 --> 00:04:18.560
And there's a huge need in the industry to have tools that could work at scale and accurately measure uh dry matter intake of grazing animals.
00:04:18.560 --> 00:04:30.000
Um, you know, until the tool we developed, a lot of that was based on uh equations in the nutrient requirements of beef cattle manual.
00:04:30.000 --> 00:04:34.079
That's the equations are based largely on dry lot data.
00:04:34.079 --> 00:04:55.199
Um, and we took the time and the effort, and it was a significant effort in time and both in the field and in the laboratory for the graduate students to go through and and do a lot of ground truth data collection by using inert markers of animals who are grazing out on pasture to calculate individual intakes.
00:04:55.199 --> 00:05:17.600
And so we've built a tool that allows us with daily body weight and daily water intake, and then we uh scrape publicly available data from the nearest NOAA station and meta data about the animals we're evaluating and are able to determine individual dry matter intakes.
00:05:17.600 --> 00:05:25.759
And so that's been a huge benefit to get that kind of data, accurate data about animals that are actually grazing in the field.
00:05:27.199 --> 00:05:37.279
And for for people who uh who are not animal scientists, um, you know, the why why is this so important?
00:05:38.319 --> 00:05:52.720
Well, it's critical because as we talk about footprints of the beef industry, whether that's uh carbon footprints or water footprints or ecological footprints, uh there's about 90 million beef cattle in the U.S.
00:05:52.720 --> 00:06:02.319
Um about 12% of them are in a feedlot for the final stage of their production.
00:06:02.319 --> 00:06:12.720
Um, but the majority of them, you know, the other 88% are grazing on pastures or feeding uh harvested forages.
00:06:12.720 --> 00:06:22.800
And so knowing what those animals are actually doing is important, uh, especially as we think about things like greenhouse gas emissions as an example.
00:06:22.800 --> 00:06:50.959
So the methane that uh an animal um adds to the environment, mostly through um the rumination process, uh they it's about, you know, the book says it's about 23 grams per kilogram of dry matter intake uh for animals that are eating a forage-based diet, about 10 to 13 grams per kilogram of dry matter intake for animals that are in the feedlot.
00:06:50.959 --> 00:06:59.120
And so the grazing animal produces about twice as much methane per kilogram of dry matter intake.
00:06:59.120 --> 00:07:02.000
Um, and it's where 88% of the animals are.
00:07:02.000 --> 00:07:05.680
And you know, the US it's 88% around the globe.
00:07:05.680 --> 00:07:23.920
Uh the numbers of animals that are fed in a feedlot is even lower, and so you know, the the overwhelming number of ruminants around the globe are in some sort of pastoral grassland system.
00:07:23.920 --> 00:07:31.199
Um, and the one of the features of that is that's where their their methane intensity is the greatest.
00:07:31.199 --> 00:08:14.160
And so understanding what's really going on there is critical for us then to identify animals that are more efficient in resource utilization and to make improvements then in those footprints and you know of a variety of types in those animals because that kind of change, genetic change in their resource utilization is permanent and additive, where you know, feed additives that might reduce out some of those outputs and shift some of that carbon to energetics of the animal, uh those really only work in situations where you're formulating a ration and delivering it to the animal.
00:08:16.079 --> 00:08:27.199
A lot of great stuff there, but to take a little step back um in terms of going through some of the things you said, you mentioned the maintenance requirement and the growth requirement.
00:08:27.199 --> 00:08:44.320
So any animal, depending on its size and its genetics and a bunch of things, will take a certain amount of energy just to stay alive for its normal metabolic functions before it actually grows and produces any food, be that beef or meat or or milk.
00:08:44.320 --> 00:08:52.799
And so if you have an animal that does is only being fed at maintenance, you're keeping that animal alive, but you're not actually producing any food.
00:08:52.799 --> 00:09:09.279
So it's um its impact, the the relative uh merit of of what it's creating for society in terms of food and the cost of that in terms of economics as well as environmental impact, um, it's not creating any value, but it's still got a significant cost.
00:09:09.279 --> 00:09:13.919
So that's a big part of why this efficiency is important.
00:09:13.919 --> 00:09:20.720
And and I frequently think about this a bit like a bit like cars or vehicles.
00:09:20.720 --> 00:09:42.320
And if you've got a if you've got 10 gallons or what 40 odd litres of of fuel, you can stick that into an efficient vehicle and drive um you know three or four hundred kilometres, or you could stick it into a very inefficient vehicle, create much more pollution and and not get very far.
00:09:42.320 --> 00:09:48.399
So it it's uh energetics is is a similar concept um in that regard.
00:09:48.399 --> 00:09:50.720
Is that is that how you see it as well?
00:09:50.720 --> 00:09:51.840
Does that make sense?
00:09:52.320 --> 00:09:52.960
Absolutely.
00:09:52.960 --> 00:09:58.080
So, you know, uh a big the what we feed animals is really their fuel.
00:09:58.080 --> 00:10:03.679
It is really an equivalent to the the liquid fuels we would use in a vehicle.
00:10:03.679 --> 00:10:17.600
And so uh I actually have a a slide I often show in presentations I give where we had two bulls that were in our one of our performance tests um that were uh very similar in genetics.
00:10:17.600 --> 00:10:25.360
So they had the same uh sire, they were born to have sib cows, uh born just a day apart from each other.
00:10:25.360 --> 00:10:36.559
And in our performance tests, they gained the same rate of gain, but one of those animals ate 50% more than the other for no additional performance.
00:10:36.559 --> 00:10:49.840
And if you put that difference on an annual scale, it was uh almost uh 7,000 pounds of additional uh feed intake for no additional performance.
00:10:49.840 --> 00:10:59.440
You know, it was like the difference between a car from the 70s with a carburetor and a car from the uh 2020s with fuel injection.
00:10:59.440 --> 00:11:00.960
Um, it's just that different.
00:11:00.960 --> 00:11:05.360
And the reason we focus on the efficiency of maintenance is because you're right.
00:11:05.360 --> 00:11:17.519
That's it's but depending on the life stage of that animal, it's 75 to 90 percent of their energy daily is used just to just in maintenance.
00:11:17.519 --> 00:11:27.440
Uh, it's why if I go to the gym for 15 minutes, I don't lose much weight because most of the calories I take in are used just to keep me alive.
00:11:27.440 --> 00:11:42.799
And in order to burn excess calories, that the number of calories I need to burn is tremendous because it's really a small increment that is sort of extra activity above basal metabolic rate.
00:11:43.200 --> 00:11:55.120
So on those that trial you mentioned, um you said about 7,000 pounds or about 3,000 kilos or three tons, um, just the difference in feed costs.
00:11:55.120 --> 00:12:14.799
And if you put a fairly conservative value of $200 a ton on that um on the feed cost, um, you're looking at $600 difference for exactly the same amount of growth and productivity, and that's on a single animal.
00:12:14.799 --> 00:12:29.759
And if you go back to the 90 um odd million animals across the country and you've got that much variation, you know, there's a lot of money slipping through the the fingers of a lot of a lot of producers um because of that inefficiency.
00:12:30.159 --> 00:13:19.919
Absolutely, and you know, if you make the wrong decision, those animals are often in the herd for 10 productive years if it's a cow, and you know, if you make that wrong choice, it's six hundred dollars a year, but it's for that entire lifetime, and so you know, in our in the beef industry, those animals are around for a long time, and so these decisions have have long consequences, and we are just starting, you know, it's only been for the last 20 years that we've had tools to really be able to um really uh at scale and in a reasonable way get at individual intakes, and so it it has the potential to be a real boost for the industry.
00:13:19.919 --> 00:13:33.919
In fact, a couple of years ago, I was at NCBA and I was on a I had a grant project at that time to try and help understand producers' decision-making process, particularly for replacement females.
00:13:33.919 --> 00:13:38.240
And one of the questions we would ask them is, you know, how much do your females eat?
00:13:38.240 --> 00:13:44.879
How much how do you assess input costs in deciding which females to keep?
00:13:44.879 --> 00:14:00.159
And they said, Well, we don't have a tool that does that, and so we don't pay attention to it, but you know, they with one simple decision, you know, a lot of the metrics can look the same, but that one simple decision could cost them six hundred dollars a year for you know 10 years.
00:14:00.159 --> 00:14:04.720
That's a lot of investment that has gone in the wrong direction.
00:14:04.720 --> 00:14:32.320
It doesn't have any payoff, and so it's uh it has tremendous potential as we start to go from the laboratory to the field to help producers find ways to become much more resource efficient in their operations and much like any other industry, look for places where there's costs that can be contained to improve profitability and therefore sustainability.
00:14:33.840 --> 00:14:56.799
So what I guess what I'm thinking is is you know the scenario if if we understand this, manage for it and and and and so and and have solutions that the animals are efficient and what that may look like, and I guess if we don't manage it, um and what that would look like.
00:14:56.799 --> 00:15:03.120
Is that something you've you've worked through um in terms of what those two scenarios would look like?
00:15:04.080 --> 00:15:09.279
Well, you know, if if we're not evaluating and managing it, we're gonna uh stay where we are.
00:15:09.279 --> 00:15:38.480
And if you look at something like the poultry industry, where they've had the ability to measure feed efficiency for a long time uh and put significant pressure on it, they've dramatically improved uh feed efficiency and and they know that improving feed conversion ratio, which is the the metric they use to measure feed efficiency by one thousandth of a point, it means millions of dollars for their industry.
00:15:38.480 --> 00:15:44.159
And we just have not put the kind of pressure we could on that in the beef industry.
00:15:44.159 --> 00:16:00.639
Um, but we're the tools are coming uh that that they've either come recently or are coming to allow producers to pay attention to that and have real impact on their selection decisions and what that means for the sustainability of their operation.
00:16:00.639 --> 00:16:24.159
And you know, we've been talking about feed efficiency, but the other thing, since we measure individual water intake as well, you know, water use efficiency is another thing that that has an impact, uh, particularly in those parts of the country where water resources are limited, which you know you think of things west of the Mississippi as kind of a uh boundary.
00:16:24.159 --> 00:16:29.679
Um and water is a much more important deal than it is here in the Mid-Atlantic region.
00:16:29.679 --> 00:16:48.399
Um, and I have a similar data slide that you know two bulls in the same test that had similar levels of performance, um, but the one that drank the most and drank the least, if you annualize their difference in water intake, it was 1,500 gallons.
00:16:48.399 --> 00:17:12.319
Um, and again, you start amplifying that by the number of animals, even in a population, and in those parts of the country where producers haul water to animals, um, you know, it's not just the volume of the water, which is a critical resource, but it's the time and labor and fuel associated with hauling all that extra water around.
00:17:12.319 --> 00:17:41.359
And so there's just tremendous opportunity in the beef industry that didn't exist 25 years ago to really uh collect data about phenotypes that can make a huge difference in the profitability of operations and start to use that data to improve both individual producer operations and um the efficiency of the industry uh broadly read.
00:17:42.480 --> 00:17:48.960
And what's what's needed to accelerate uh progress?
00:17:48.960 --> 00:18:21.759
Because you know, you know, adding on to what you've just said, if you you know, beef prices are going up, there's a shortage of cows packing, how the packers are closing down because they can't get enough animals coming through, um global demand for protein is is is continuing to rise as and the the in impacts of our of our livestock production systems are in continuing to um be politically volatile and also have have significant impacts on the environment.
00:18:21.759 --> 00:18:42.720
So having having systems where we can produce more food with fewer resources, um with less waste, so there's there's greater profits for those people who are doing the work and and and that's their livelihood, and also a lower climate impact, there's there's no losers in in that scenario.
00:18:42.720 --> 00:18:44.720
Um it's a win for everyone.
00:18:44.720 --> 00:18:51.839
So what do we need or what's needed to accelerate progress uh in this space?
00:18:52.480 --> 00:19:05.039
I think the biggest thing is is you know the the ability to move technology from the research space to the industry large rent.
00:19:05.039 --> 00:19:34.400
So uh right now in West Virginia, we've taken our technology, and for the last three years, we've conducted a grazing performance test for our heifers and use that information to try and identify uh the most efficient in the group, taking that kind of approach uh and spreading it across the country so it's available, especially at a time that everybody talks about the tremendous need to um grow the cowherd.
00:19:34.400 --> 00:20:34.079
Um, now the the data about harvest suggests that people aren't retaining heifers at the rate we really need them to, but it's an opportune time from a uh at least a potential to grow that heifer crop and regrow the cow herd with a very, very different um footprint that's much smaller than it has been in the past, that could rapidly have a positive impact on the industry because addressing those that you know we the shortage in females that exist today, if we could bring in uh sort of the next generation of females at 10 or 15% more efficient than the average of the current herd, that would have long-term impact on the beef industry, uh, reducing footprints and and increasing the potential for profitability on farms.
00:20:36.079 --> 00:20:43.759
So you mentioned like I I back to the uh the the motor vehicle analogies because I think they're quite useful.
00:20:43.759 --> 00:21:04.799
Uh you've got, you know, you're driving down the down the freeway, and there's one car that is particularly polluting, and you know, there's smoke coming out of it, and there's there are hundreds and hundreds of other cars, but that that one car that's really, really bad uh has a disproportionate impact on the pollution of all the cars.
00:21:04.799 --> 00:21:15.359
And if you just get rid of that one car, then the whole freeway and the air, it doesn't make it perfect, it doesn't turn it into wilderness, but it certainly has a disproportionate effect.
00:21:15.359 --> 00:21:23.039
And and those top most inefficient animals, um, are they similar to that highly polluting car?
00:21:24.160 --> 00:21:31.039
Yeah, and the yeah, I I have a conversation that I think is what you're getting at with my farm manager all the time.
00:21:31.039 --> 00:21:38.880
He says, you know, if we could just get rid of the bottom 25%, uh it you know, it would it would raise the average efficiency tremendously.
00:21:38.880 --> 00:21:47.279
I tell him that, you know, in my animal genetics class that was selecting the top 75%, but either way, it it gets you to the same place.
00:21:47.279 --> 00:21:50.240
It you know, we could make a huge leap forward.
00:21:50.240 --> 00:21:54.720
Uh uh the analogy I use when I'm talking to classes is the car analogy.
00:21:54.720 --> 00:21:59.759
And so when I was when I turned 16, uh my parents gave me the opportunity.
00:21:59.759 --> 00:22:08.880
To buy their old Pontiac Catalina station wagon uh built in 1977, and it got six and a half, seven miles a gallon.
00:22:08.880 --> 00:22:23.920
Um, and you know, just the the cost that was invested in fuel over the lifetime of that vehicle, I could have uh bought several vehicles that were you know had an efficiency like we have today.
00:22:23.920 --> 00:22:30.720
My my son, when he turned 16, ended up with a Toyota RAV 4 that gets 30 miles a gallon.
00:22:30.720 --> 00:22:37.599
I mean, it's just that that's that's a tremendous difference in what it takes to move that down the road.
00:22:37.599 --> 00:22:41.279
And I think that's really where there's a huge opportunity.
00:22:41.279 --> 00:22:49.839
Um, in class, we always tell students in animal science that 70% of their variable cost of production is feed cost.
00:22:49.839 --> 00:23:05.599
Um, it's sometimes hard to really capture that value in animals that graze because it's it's sometimes hard to put a value on pasture forage, um, but um it's still a real cost.
00:23:05.599 --> 00:23:26.079
And so, you know, at a time that margins are thin, even though prices are high, um the the ability to increase stocking density on the same acreage or maintain a stocking rate on a smaller acreage really has the potential to make a difference.
00:23:26.079 --> 00:23:44.480
When when the Grow Safe tool first became available, there was a producer that got on board out in the West and he went from stocking 19 cow calf pairs per section to 38 cow calf pairs per section just by focusing on efficiency.
00:23:44.480 --> 00:24:02.400
Now, there was a tremendous focus on efficiency, and and anytime you focus on one trait, that means you take away some focus from other traits, but you know, it's that kind of improvement that's possible, and it's something we haven't put a lot of pressure on.
00:24:02.400 --> 00:24:15.519
Unlike the poultry and swine industries that that have had these kinds of records for a long time, we've we've often evaluated groups of animals and assumed they're they're all reflective of the average.
00:24:15.519 --> 00:24:24.240
And what I can tell you is when you get individual data about a group of animals in a pen, uh, very few of them are average.
00:24:24.240 --> 00:24:34.720
They're often either way out on one end, that's seven miles per gallon car, or they're at the other end and they're a 30 mile per gallon car.
00:24:34.720 --> 00:24:45.599
And selecting those efficient animals just is a you know, you have to still consider performance and fertility and and production.
00:24:45.599 --> 00:25:01.839
But if you have information about efficiency as well, and you can put that into your uh matrix of selection, all of a sudden you can say, okay, well, for these two animals that are similar otherwise, I want to take the one that does it for less inputs.
00:25:01.839 --> 00:25:04.880
And they come in all different shapes and sizes, right?
00:25:04.880 --> 00:25:12.640
Some people think, oh, well, if they're efficient, they're probably small animals that eat a little bit.
00:25:12.640 --> 00:25:24.640
And what I can tell you is every set of data I look at for a group of animals, there are efficient animals throughout the intake spectrum and throughout the weight spectrum.
00:25:24.640 --> 00:25:28.079
And so there are large animals that are very efficient.
00:25:28.079 --> 00:25:32.480
There are also small animals that eat little but do it inefficiently.
00:25:32.480 --> 00:25:38.960
And so at the end of the day, you can't just find them by just looking at the animals.
00:25:38.960 --> 00:25:54.640
You gotta have data uh about individual performance, and it's really, you know, the one of the things that that I think will come to the industry in time is we'll get away from trying to manage averages and we'll get better at managing individuals.
00:25:54.640 --> 00:26:09.759
Because even if you've got that inefficient vehicle, you can do things about how you manage that vehicle and use that vehicle and drive that vehicle that makes best use of whatever type of performance it has.
00:26:09.759 --> 00:26:13.119
So I think there's a lot of potential out there.
00:26:14.880 --> 00:26:31.359
You mentioned um having the tools to actually get the data so you can you know make these decisions and evaluate them, which is obviously critical, but you also said that that's an area that um tools are emerging and it's it's being addressed.
00:26:31.359 --> 00:26:39.359
What other areas need additional energy focus investment?
00:26:39.359 --> 00:26:41.440
Um, is there policy issues?
00:26:41.440 --> 00:26:45.119
Is there is there market signals?
00:26:45.119 --> 00:26:51.839
Are there are there other areas that we need to also focus above and beyond the the development of the technology?
00:26:52.640 --> 00:27:09.359
I mean, I think the the market signals and the conversations that you have with um thought leaders at places like uh NCBA and others, you know, there's this tremendous need to try to grow the cowherd.
00:27:09.359 --> 00:27:23.119
Um, it is the the although it's leading to high prices for parts of the market, those high prices are causing uh um undesirable consequences in other parts of the industry.
00:27:23.119 --> 00:27:48.160
And so, you know, if there was if there was incentive to grow the cow herd, to retain heifers, and and if that can be done, especially to using tools that would allow us to grow the cow herd by retaining heifers that were of um improved uh potential for the industry, uh, it's a that would be a boon.
00:27:48.160 --> 00:28:01.680
And uh, and you know, there's discussion about how do you incentivize that in a world where uh heifer going to the feedlot is just worth so much, it's hard for a producer to want to retain that animal as part of the breeding herd.
00:28:01.680 --> 00:28:04.799
And so I think that is probably one of our biggest things.
00:28:04.799 --> 00:28:36.240
Um, that you know, what are the what are the incentives that that would lead the industry to really increase the number of heifers that were retained so that we could grow the cow herd, uh especially in a world where you know, with New World Screwworm uh moving north, we've limited or stopped importation of cattle from Mexico, and so that's having impacts on the price of beef in the retail case at grocery stores in the US.
00:28:36.240 --> 00:28:52.240
And so there are there are other factors outside of sort of our normal production system um traits that are having impacts on prices that really get at what is the cost of protein to consumers in the marketplace.
00:28:52.240 --> 00:29:10.480
And that's you know, anything we can do to uh drive those prices down is helpful for you know people meeting their dietary requirements, as having the capacity to uh uh adequately feed particularly fragile populations.
00:29:10.480 --> 00:29:26.799
I mean, there's just a whole host of uh uh downstream uh impacts that would happen if we could uh start to um grow the cow herd and do that in a way that that addresses the demand that is out there with supply that is needed.
00:29:28.079 --> 00:29:42.240
We've focused uh almost exclusively so far on on the United States, but you know, cows being cows, um, they're not that different here than they are across the rest of the globe.
00:29:42.240 --> 00:29:46.720
Um, there are there's there's more animals in feed yards here than anywhere else.
00:29:46.720 --> 00:29:54.000
So those percentages out on pasture is even higher when you start looking at Latin America and Asia and Africa and Europe and Australia.
00:29:54.000 --> 00:30:02.079
So where where do you see the work that you're doing translating more broadly globally?
00:30:03.119 --> 00:30:12.000
I think it it varies with a lot of those different places and kind of where they are in their beef cattle industry journey.
00:30:12.000 --> 00:30:27.599
So some of those places, um, you know, I think of Brazil or Australia, uh the selection of animals to perform at a high level in those um countries is um it's similar, I would say, to ours.
00:30:27.599 --> 00:30:34.240
I've not been to those places, but in in what I read and conversations I have with people, they're much closer to ours.
00:30:34.240 --> 00:30:41.200
There are also places where you know live animal is the primary determinant.
00:30:41.200 --> 00:30:51.279
And so there's because there hasn't been a lot of selection pressure on you know productivity or efficiency, uh, there's tremendous opportunity.
00:30:51.279 --> 00:31:05.839
I think there's a need to be sensitive to you know the cattle that perform in Central Africa are have a different genetic base than cattle that perform uh you know in the northern reaches of Canada and Russia.
00:31:05.839 --> 00:31:43.279
And so, you know, it it needs to be place-based, but I think there's huge opportunity for aspects of precision livestock farming and and you know, US, Europe, Australia, Brazil, those kinds of places will adopt technology the fastest, but sort of older generation but still recently developed technologies could have a tremendous impact uh in in places where there hasn't been as much advancement of uh the industry for the genetics that exist in those places.
00:31:43.279 --> 00:31:52.480
And so it's a it's something I think that there's a tremendous opportunity globally for us to take the land that's available.
00:31:52.480 --> 00:32:02.079
And the reality is, is across the globe, the greatest proportion of agricultural land is grasslands.
00:32:02.079 --> 00:32:33.359
We often think of, or at least my perception of the common thought is you know, you talk about agriculture and people think about row crops and tilable land, uh, but the reality is the greatest proportion of land globally is grassland that can be used for grazing, where ruminants are are well suited to convert those uh grasses into that are mostly carbohydrate into high-quality protein for human consumption.
00:32:33.359 --> 00:32:45.519
Um, and so I think there's just tremendous need to um look for ways to transfer technology uh at an appropriate stage.
00:32:45.519 --> 00:33:02.000
You know, um maybe here individual animal performance testing is is the key, but maybe in some places just knowing better what performance metrics are uh would be helpful in identifying animals that could do more with less.
00:33:02.000 --> 00:33:04.160
I think at the end of the day, that's the real key.
00:33:04.160 --> 00:33:08.480
We're not we've got no more land that's going to become agricultural land.
00:33:08.480 --> 00:33:14.799
We've got good quality agricultural land that's being removed from production all the time all over the globe.
00:33:14.799 --> 00:33:32.799
And so, how do we try to do more with less as populations continue to grow, uh population populations continue to move up in uh from sort of third world conditions to second and first world conditions?
00:33:32.799 --> 00:33:40.559
Um, you know, the a lot of things we worry about in third world countries are dietary, right?
00:33:40.559 --> 00:33:55.920
There's an awful lot of preventable uh disease and suffering that occurs just because of malnutrition, which is sometimes undernutrition, sometimes it's just not uh the the right blend of nutrition.
00:33:55.920 --> 00:34:07.440
And so there's tremendous opportunity for animal agriculture to upcycle poor quality um feedstuffs into high-quality uh protein for human consumption.
00:34:07.440 --> 00:34:24.559
And I think there's uh an a it's reasonable that those of us that are at the leading edge of that find ways to take things that are applicable uh to populations and apply them in their in their culturally appropriate ways.
00:34:25.760 --> 00:34:40.800
I think it's probably also worth adding that somewhere in the order of one and a half billion people globally rely on livestock and livestock production for their livelihoods, which is probably bigger than any other single industry.
00:34:40.800 --> 00:35:12.400
And those millions of square miles or square kilometers of land that are uh used for livestock production, if we as humans or as societies want to impact that land, the the most powerful um avenue to do that is through those people that are currently the custodians of that land, which are the the herders, the farmers, the ranchers, uh the pastoralists, wherever you know that happens to be in the world.
00:35:12.960 --> 00:35:13.519
Absolutely.
00:35:13.519 --> 00:35:58.639
I think that's that's really critical, is that you know being able to uh help communities, villages, you know, whatever the the appropriate unit of of society is to be to attain a better standard of life for them and their families, um, for those that agriculture is their calling, uh finding ways to improve how they do it in their um systems is is a valuable to value to them and their family, just like any other industry that we can improve the productivity of has value for those that are involved in producing.
00:35:59.760 --> 00:36:16.079
You mentioned perception earlier on, and you know, perception is one of those things that's very very individual and personal, so I'm certainly not going to speak for humanity in this perspective because I I wouldn't be so bold.
00:36:16.079 --> 00:36:27.920
However, you know, frequently in conversations when people it comes up about the beef industry, the picture that people get are are the big feed yards.
00:36:27.920 --> 00:36:38.800
Um and you know, 12% in the US, much lower elsewhere in the world, and the grazing systems are where the animals are.
00:36:38.800 --> 00:36:48.960
Is is perception and people's perception a an issue that we need to spend more time and effort on.
00:36:48.960 --> 00:36:54.239
And if you think that is the case, where what do you think are the priorities there?
00:36:55.280 --> 00:36:58.000
It's something that I actually think a lot about.
00:36:58.000 --> 00:37:12.880
Um, you know, the message about what we actually do in agriculture to feed populations, you know, in the US, less than 2% of the population is engaged in agriculture in any way.
00:37:12.880 --> 00:37:20.639
Uh it's kind of funny you ask because just yesterday, one of my sons, he's a freshman in engineering at WVU now.
00:37:20.639 --> 00:37:38.159
Uh he sent me a reel from Instagram, and it was some guy talking about beef production around the world and the the what I think is an artificial dichotomy of grass-fed versus grain-fed.
00:37:38.159 --> 00:37:52.639
And he stated with great assurance that grass-fed cattle take 18 months to mature, and that corn-fed or grain-fed animals uh take six weeks.
00:37:52.639 --> 00:38:01.840
And my son, who's you know, only kind of partially paid attention over the years, says, Dad, we don't even wean the calves when they're six weeks old.
00:38:01.840 --> 00:38:21.519
Um, but it's just, you know, the there is all because there is so much information out there in a in a in a in our modern world, and and information literacy and information reality are huge struggles.
00:38:21.519 --> 00:38:31.599
And I think there's an opportunity for those of us that are involved in agriculture to do more to help people understand what really goes on.
00:38:31.599 --> 00:39:02.239
Um, I didn't come from an agricultural background, my my parents live in a city in Indianapolis, and so when I talk to them, I always try and, you know, I try to be as objective as possible, which I am a person that's engaged in the industry, and so I have a certain perspective sometimes, but trying to help them understand the realities of what does it take to feed you know eight billion people?
00:39:02.239 --> 00:39:03.280
Where are they?
00:39:03.280 --> 00:39:04.880
Where are the resources?
00:39:04.880 --> 00:39:06.159
How do we do that?
00:39:06.159 --> 00:39:16.400
How do we actually get from a calf on the farm or a lamb or a kid if it's a goat to an animal that's ready to harvest?
00:39:16.400 --> 00:39:17.679
What does that really look like?
00:39:17.679 --> 00:39:20.480
What are the the footprints of it?
00:39:20.480 --> 00:39:26.400
How do they compare to um other you know plant-based protein sources?
00:39:26.400 --> 00:39:41.679
Um, you know, there's a there's a whole um need for translation of what is sometimes very technical scientific information to general audience.
00:39:41.679 --> 00:39:55.440
Uh, when my boys were very young, uh they asked the the quote-unquote teachers at their daycare before they were in kindergarten, asked me to come and talk to the kids about animals.
00:39:55.440 --> 00:40:04.880
And so I came in, I put diapers on a couple of lambs and brought in some three or four-day-old chicks uh so they could have something to see.
00:40:04.880 --> 00:40:12.880
And it turned out a the word got out, and a bunch of moms came that day, too, which was a little odd to have all the moms present at daycare.
00:40:12.880 --> 00:40:19.119
Um, but there was a kid that showed up with a super deluxe hamburger on the front of his shirt.
00:40:19.119 --> 00:40:21.840
I didn't stage it, but it was perfect.
00:40:21.840 --> 00:40:27.280
So I I brought that kid up front and we just started the topic, you know, where's the bun come from?
00:40:27.280 --> 00:40:31.519
And then all the kids said the grocery store, those kinds of things.
00:40:31.519 --> 00:40:39.199
And we eventually got to that the bun comes from the farm, and the lettuce comes from the farm, the hamburger comes from the farm.
00:40:39.199 --> 00:40:46.480
Uh, and and so by the end, I said I got the kids, they they understood that when I said, Where's the food come from?
00:40:46.480 --> 00:40:47.760
They said it comes from the farm.
00:40:47.760 --> 00:40:51.519
And one of the mothers raised her hand and she said, But not candy.
00:40:51.519 --> 00:40:55.440
And I said, Actually, candy comes from the farm too.
00:40:55.440 --> 00:40:59.119
Um, and you know, I I oversimplified it.
00:40:59.119 --> 00:41:20.239
I didn't talk about wild-caught seafood, and you know, there are there are some non-farm food products, but you know, it's that notion that it all has to come from the farm, that it's it's a it's a huge complex, you know, the notion that there are there's something like three days supply of chicken in the US at any given time.
00:41:20.239 --> 00:41:25.199
And if we stopped producing and harvesting it, it would disappear like that.
00:41:25.199 --> 00:41:38.159
And people just don't think about what it takes, you know, what has to happen in some cases two years ago to get food on their plate, whether that's at home or in a restaurant or in an institution.
00:41:38.159 --> 00:41:52.320
Um, it's a it's a huge complex thing, and there's all kinds of pricing signals and other things that impact how the people that do that production make decisions about what they're going to produce.
00:41:52.320 --> 00:41:58.480
Um, and you know, those are stories that we just there's not enough general understanding of.
00:41:58.480 --> 00:42:16.480
And so, you know, I recognize there's there's a limit to how much I can do about it, but I take every opportunity I can to talk to general audiences and help them start to understand, you know, for something that we depend on daily, um, it's a big deal.
00:42:16.480 --> 00:42:36.880
Uh, I spent a little time as the associate dean for research here at WVU in the uh ag school, and I would talk to one of the vice presidents of research, and she would often talk about the great research that was happening in the physics department and the great research that was happening in the medical school.
00:42:36.880 --> 00:42:54.000
And over time I worked on her and and I pointed out, I said, you know, there that most of the world's population may never ever in their life see a doctor, but almost all the population has to eat.
00:42:54.000 --> 00:43:17.599
And it's just, you know, it's a it's a different calling to be a researcher in agriculture, it's a different calling for those people that work in production agriculture, um, and they don't get the credit and the thanks that they ought to, because especially in first world nations like the US, we've got so many choices that we don't know what to do about it.
00:43:17.599 --> 00:43:38.400
Uh and you know, uh the the thing maybe we shouldn't get into, but uh I'll mention it is that you know, no matter how efficient production is, uh the amount of food we waste is uh another side of the bigger uh agriculture food system uh uh continuum.
00:43:38.400 --> 00:43:46.320
And you know, in the US, 40 to 50 percent of the of the edible food that is produced is thrown out.
00:43:46.320 --> 00:43:59.119
Um and I spent some time trying to get uh anaerobic digestion or other tools for making better, making higher use of that organic waste.
00:43:59.119 --> 00:43:59.760
Uh ultimately.
00:43:59.760 --> 00:44:18.719
We were unsuccessful, but you would have conversations with people, and they just were completely unaware that most of that goes in a landfill and rots away and you know creates um detriment to the ecosystem by being rotting food.
00:44:18.719 --> 00:44:25.679
Um and and so there's a uh it's a there it's a big issue.
00:44:25.679 --> 00:44:33.119
Um and I think the we we worry about we don't worry about food because it's plentiful here.
00:44:33.119 --> 00:44:40.639
We focus in the US more on on excess calorie intake, and and it is a problem in the US.
00:44:40.639 --> 00:44:55.840
You know, obesity is is uh a real issue in the US, uh, but in most of the world, in the sort of average human, um, they've got insufficient calories, uh, or at least insufficiently balanced calories.
00:44:55.840 --> 00:45:00.559
And so it's a hard thing to to get people to wrap their mind around.
00:45:00.559 --> 00:45:04.239
Um, and understandably, but we need to talk more about it, no doubt.
00:45:04.639 --> 00:45:06.880
Think back to the animal side of things.
00:45:06.880 --> 00:45:16.239
When you think of pre-industrial revolution societies, you know, animals were that food recycling mechanism.
00:45:16.239 --> 00:45:28.320
Anything that wasn't eaten in the house was fed to some chickens or some swine or some sheep or goats or cows and converted back into something that was then was then edible.
00:45:28.320 --> 00:45:45.840
Um, plus you've got the nutrient cycling through their manure and through their dung going back into soils or vegetable gardens or or all those sorts of interactions and and that feedback loop has has been fairly dramatically severed in our modern societies.
00:45:46.239 --> 00:45:48.800
It it's it's been partially severed.
00:45:48.800 --> 00:46:24.719
Uh, you know, I one of the things I often I sometimes talk to people about is you know, if you think about food processing, there's a tremendous amount of food processing what we used to call byproduct, and sometimes we call it now co-product, but components of converting raw materials into further processed food stuff for consumption, that there are products there that that today the the the those things go into uh animal diets somewhere.
00:46:24.719 --> 00:46:57.519
Um, whether it's you know the the starting in the 90s when we started to make a lot of ethanol, there's there was all of a sudden all these waste products from that ethanol production, we call them distiller's grains, that there was a need at the time for in the 90s for research on how do those become good feedstuffs because just burying them or landfilling them was too costly or or not the right thing for those industries to do.
00:46:57.519 --> 00:47:22.960
And so um a lot of there's a lot of cakes and meals and other you know in animal agriculture, we talk about soybean meal as an ingredient all the time, and soybean meal is the waste product of soybean oil production, and you know, it's a fundamental component, particularly of monogastric diets, uh like pigs and poultry.
00:47:22.960 --> 00:47:37.840
And so there's still a lot of that that happens, um, but it's not it's not in a in a defined you know watershed level ecological circle, right?
00:47:37.840 --> 00:47:48.960
Those those things are moved across the country, and so the the co-products and the the things like manures and other things end up in disparate places.
00:47:48.960 --> 00:48:02.639
If you look at a map of nitrogen flow across the globe, there's this these huge arrows of nitrogen exiting the upper Midwest of the US, going to all kinds of places.
00:48:02.639 --> 00:48:08.480
It's not staying in a circular economy there uh in the upper Midwest.
00:48:08.480 --> 00:48:24.320
And you know, there's implications of that, you know, and um it's a it's a complex thing, and and I I often tell people that I like I don't like to talk about systems, I like to talk about complexes.
00:48:24.320 --> 00:48:26.400
It's like a big bowl of jello.
00:48:26.400 --> 00:48:58.079
And if you push it in one place, what you get is a reverberation of consequences, and so you know, if we sometimes try to come to simple solutions to a perceived problem without recognizing that adding or removing something from the complex doesn't just address that thing, but it then has these follow-on consequential reverberations to all kinds of other aspects.
00:48:58.079 --> 00:49:05.599
And so um it is it's it, you know, the the deeper you dig into it, the more complicated it gets.
00:49:05.599 --> 00:49:25.119
And so I sometimes have conversations with students, you know, I've had some of our classes, they hear about an issue and they say, well, you know, we should just not do this, or we should just not do that, and then you start thinking about, well, you know, here's here's what other activities depend on, you know, step one.
00:49:25.119 --> 00:49:27.519
And you don't often think about that.
00:49:27.519 --> 00:49:43.039
And so you know, if you change this operation, it will impact other places, and sometimes those impacts are as detrimental or or more detrimental than the problem you're trying to solve.
00:49:43.039 --> 00:50:27.360
And so, you know, helping young people as they grow and develop to recognize that interrelation of food and agriculture, and then the food and agriculture with larger things in the world, um, and both the sort of biological processes that are impacted, and then you layer on top of that policy, um, and sometimes well-meant policy, but that has just um tremendously constraining consequences that then then then lead to other unintended and sometimes not recognized for some period of time consequences.
00:50:27.360 --> 00:50:31.360
And so it's a there's a lot to to do.
00:50:31.360 --> 00:50:55.119
There's real opportunities to improve things, and you know, circling back to your comment early on, you know, improving the efficiency of the beef industry or animal agriculture uh more largely, um it has win-win uh consequences, and it's sometimes hard to find those things that are a win that lead to another win.
00:50:55.119 --> 00:51:22.000
Um, and so I think it's important that that um that that be part of education, be part of communication, and it's something that agriculture has historically not done a good job of telling its story, especially as fewer and fewer people were involved in it, because it was no longer that diversified operation that had some cows, some pigs, some chickens, and the slop went out in the yard.
00:51:22.559 --> 00:51:44.800
Well, that's that's a hundred percent why I invited you on today to discuss this, because the work you're doing across that feed efficiency side of things is is you know such an opportunity to create that that win for farmers and ranchers, that win for food productivity and food security, and also that win for the environment and climate.
00:51:44.800 --> 00:51:48.320
And they're they're few and far between far between.
00:51:48.320 --> 00:51:59.280
When we find them, we need to we need to make sure that they're they're um you know lifted to the top and and and put on the agenda and discussed um so they don't slip through the cracks.
00:51:59.599 --> 00:52:01.199
Yep, I agree 100%.
00:52:02.000 --> 00:52:08.079
So uh before we go, is there anything else that you'd like to add that we haven't uh already discussed?
00:52:10.719 --> 00:52:15.360
Um I mean I think we've we've covered an awful lot of ground.
00:52:15.360 --> 00:52:23.039
Um, you know, I think the the biggest thing is is you know how do we do a better job in our industry?
00:52:23.039 --> 00:52:49.599
How do we do a better job of communicating what we do for the globe from our industry and helping people, especially outside of agriculture specifically, or science generally, understand you know what it what is really happening, what could happen, uh, and how to make good policy.
00:52:49.599 --> 00:52:56.960
Because at the end of the day, all of these things, the the hardest part of them is the human dimensions piece.
00:52:56.960 --> 00:52:58.079
I'm convinced of that.
00:52:58.079 --> 00:53:05.599
I mean, I can I can tell students to study for class, um, and and getting them to do it is the hard part.
00:53:05.599 --> 00:53:16.000
I can talk to producers about uh changing management practices for their own for the the financial benefit of their operation, but getting them to do it's hard.
00:53:16.000 --> 00:53:17.519
And and that's the real part.
00:53:17.519 --> 00:53:30.719
And I, you know, I'm not a uh uh anthropologist or sociologist or psychologist, but I have over the my years come to realize that human dimension piece is the hardest part of all this.
00:53:32.719 --> 00:53:35.519
Matt, thank you so very much for joining me today.
00:53:35.519 --> 00:53:37.599
Sure, thanks for having me.
00:53:37.599 --> 00:53:39.920
Thank you for listening to the AshCloud.
00:53:39.920 --> 00:53:53.840
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