The livestock industry is gearing up for its turn in the innovation saddle as more startups like Performance Livestock Analytics tap corporate partners like Wilbur-Ellis to pick up the pace
Innovation is changing virtually every segment of food production. There are intricate algorithms assessing mountains of data coming from row crop operations in the Midwest, newly discovered microbes spawning bio-based fertilizers, gene editing that can improve the nutritional profile of crops, hyperspectral scanners helping food distributors achieve better food safety standards, and iPad POS systems optimizing the restaurant experience.
One place where technology has been less apt to spread like wildfire is livestock production, including beef, dairy, and other segments of the supply chain that puts meat and milk products on our plates.
When it comes to digitalization, the industry is just getting started according to Dane Kuper, founder and CEO of precision animal agtech startup Performance Livestock Analytics (PLA). The company just announced an undisclosed investment from ag retailer and feed supplier Wilbur-Ellis’ venture capital arm Cavallo Ventures. Wilbur-Ellis will tap the Iowa-based startup’s Performance Beef analytics tool and other technologies to help optimize production.
“It’s an investment first and foremost, but it’s also a partnership discovery process. Wilbur-Ellis has a lot of the same customers we are serving, providing products and feed to those farms, dealer networks, and distribution products. We are serving those same customers from a data management standpoint. When we look at the stakeholders involved in raising livestock, everyone has an interest in helping those farmers to produce in the best way possible,” Kuper told AgFunderNews.
After spending five years with Climate Corp as regional sales manager after Monsanto acquired the startup, Kuper set his sights on the livestock industry. He saw firsthand how the row crop production underwent a digital revolution after big data swept the industry.
“Livestock is one of the last industries where you will see true digitization hit. We have seen every other industry go through a digital revolution,” Kuper explains. “You’re starting to see an acceleration of animal agtech in a big way and you will see it even further. We are really where the row crop industry was when we were starting Climate Corp in 2011.”
What is PLA?
PLA’s Performance Beef tool is a cloud-based platform that aims to help producers optimize key aspects of their operations including nutrition and animal health, by monitoring the measurement, analysis, and reporting of financial and operational data to achieve better feed management. Feed is one of the most expensive inputs in a beef cattle operation, making most producers eager to see whether they’re spending more than they need to, or whether their feed of choice is giving them the gains they’re seeking.
There are roughly 1,100 producers currently using the subscription-based software service by Kuper’s account.
“We just launched a partnership with Elanco to focus on how we can help our customers use certain products like vaccinations in a more precise way to achieve higher outcomes. The platform can make suggestions on different vaccination protocols and tell the user what the vaccination window is. It can also track any retreatment and tell them what protocol they can use if they miss the treatment window.”
What’s the Hitch in the Industry’s Giddy-Up?
Technology has not been completely absent in animal agriculture. Wyoming recently tapped blockchain to help its ranchers get better prices for premium beef products and Cargill helped create a remote control herding robot to improve worker safety in feedlots. Dairies have been an anomaly in the industry’s otherwise lagging focus on technology, creating futuristic rotating milking parlors and data management systems to track feed intake and milk supply. More recently, dairy innovators have started dabbling with wearable devices – think FitBit’s for cows – and new categories of healthcare products.
At FoodBytes! NYC last year, animal health and antibiotic-use reduction technologies dominated, including SomaDetect which uses deep learning and AI to provide real-time, automated analysis of milk quality without any addition of chemicals or consumables. There’s even been a government-backed initiative in California to reduce the state’s dairy-related livestock emissions by constructing a pipeline to transport biogas produced in on-farm digesters.
But compared to other spaces and segments of the food chain one has to wonder why livestock is entering its digital chrysalis later in time. After all, there are an awful lot of cows roaming the Earth with nearly 32 million head of beef cattle in the US according to the 2017 Census of Agriculture.
Consider also the fact that the number of beef cattle operations has increased in the five year period between the 2012 and 2017 Census, with 1,140 new operations in business. Overall, beef cattle production takes place on about one-third of US farms.
“Livestock is a slightly smaller industry than row crop production and probably more challenging in terms of how you solve tech issues. It also probably has more variables to deal with and higher demand in how they need to produce these products compared to row crops,” Kuper explains. “Meat is a higher value product globally and you are seeing meat consumption on the rise. And now the consumer wants a connected experience when it comes to how the product was produced.”
Without diminishing the complexity of growing crops like soybean, corn, and wheat, raising beef cattle is an entirely different rodeo due to the very fact that the commodity is a living, breathing, and walking animal with its own nutritional requirements and health needs. The simple task of determining exactly how many pounds of feed each animal consumed is impossible for many producers unless animals are separated and fed individual rations, an impractical and wildly inefficient endeavor. Each animal will also have its own health history as disease plagues some but not all of the herd and different stats on things like the number of months it takes to reach finishing weight.
And then there’s the cow-calf segment of beef cattle production in which cows are bred to produce a new crop of calves each year. Breeding, calving, and weaning records are an entirely new set of metrics to capture for each individual animal.
The answer may simply be that it will take the industry a little more time to wrap its head around the dizzying number of variables involved to find the best and most practical on-farm digital solutions. It also sheds light on PLA’s decision to focus on the feedlot segment of beef cattle production, with plans to explore digital solutions for cow-calf producers and other beef supply chain points down the road.
Despite the large population of beef cattle, however, the average herd size in 2017 for all US producers as 43.5 cows. This may shed light on why technology has been slower to infiltrate, as producers may not be able to justify spending money on a novel tech tool for 44 cows compared to the tens of thousands of acres that many row crop operations encompass. But cattle operations above the 50-head mark are on the rise, with the 100-499 cow category jumping 13% alone compared to 2012 and the 500-999 cow category increasing 7%.
According to Andrew Loder, president of Wilbur-Ellis’ nutrition division, keeping this variability in mind is a must for any new technologies targeting beef cattle production.
“There’s not an unlimited amount of money that customers have and the solution has to be accessible regardless of the size of the operation. If it’s only meant for the big operations then that’s a limited market,” Loder tells AgFunderNews. “Part of our vision is to be an innovative leader in the marketing and distribution of animal nutrition. We think agtech plays a role in coming up with those innovative solutions for our customers. If we want to be a leader, we have to be forward-thinking about what animal agtech can mean for us and our customers.”
Cavallo Ventures also recently invested in an insect protein company called Beta Hatch, a Seattle-based startup industrializing insect production for sustainable animal feed, marking Cavallo’s first investment in the feed industry. Although Wilbur-Ellis will continue to think about innovation in-house, Loder sees great advantages in seeking out cutting-edge startups.
“We recently hired someone to be our innovation leader, but we know we won’t come up with all the answers and that we can’t come up with a portfolio of products that can support our customers. So we want to do both internal innovation and external innovation with companies like PLA that can bring ideas. With Beta Hatch, there’s a great compliment for our pet food and aqua customers. We could generate that internally, or we could accelerate the idea and incubate the idea faster than doing it all in-house or them doing it all on their own,” Loder explains.
With alternative meat products like plant-based proteins and lab-grown meat moving from the limelight to the spotlight, there’s a good reason for the livestock industry to see whether technology can help better address consumers’ concerns and demands. For him, these novel products are an opportunity for the beef industry to evolve and provide more transparency around how products are being produced. It’s challenging the livestock industry about how they operate and their sustainability, Kuper says.
There may not be a silver bullet to cut through the debate on alternative proteins versus conventional beef, but corporate partnerships are a good start.
“For both investors and startups, my advice is the same when it comes to animal agtech. Align with companies in the space that already understand the market because that will result in better decisions and investments. Cavallo is very aligned with some other funds wanting to get in the space and like us to be partnering with them as they assess opportunities because we can tell them quickly if we think it can be applied in the market.”
Here’s where AI could make the biggest impact in the agrifoodtech sector