Match Made in Metadata

Match Made in Metadata

K-State’s Beef Cattle Institute uses big data to reflect real-time research.

Story and photos by Audrey Hambright

Innovators in data analytics continue to step up in a big way – but it’s not where you might think.

The Beef Cattle Institute (BCI) at Kansas State University has a strong history in representing producer and food animal veterinary needs alike, but has recently taken on the likeness to a start-up company in Silicon Valley.

How so? It’s using big data to reflect real-time research.

Collecting behind the scenes to get ahead

Under the supervision of Dr. David Amrine, BCI research director, the BCI has created a large operational database through strong collaborations with consulting veterinarians and feedyards. The data represents approximately 55 feedyards across the United States or 2.5 million head of cattle on feed.

That’s 2.5 million head of cattle for which the BCI is receiving daily updates. To put that into perspective, the USDA reported United States feedlots with capacity of 1,000 or more head totaled 12 million head on Jan. 1, 2021.

“It’s a dynamically updated system,” Dr. Amrine says. “The treatments, the new cattle that come in and cattle that leave from that previous day are all uploaded nightly into our data warehouse. Now we have the latest information.”

This gives BCI faculty and students conducting research real-time access to information gathering from a digital “data warehouse.” One of the keys to this system is the ability to keep all data confidential and anonymous prior to analysis. Information gained from this system is valuable to the industry because findings are based on real-world information; yet, data are never associated with any individual operation.

A custom-built system

Even though the data is collected overnight, developing the infrastructure and background took a bit longer, as it was essentially built from the ground up, using only a branded web service as the platform.

The system needed to accept both nightly exports from the participating feedyards, then upload that information into the database. Capabilities were expanded during this process, including the ability for the system to upload “clean” data, or data that was not duplicated.

“One of the other challenges with the design and implementation of the system is that the format of information coming from the feedlots is not all the same,” Dr. Amrine says. “This adds to the complexity of the system.”

Prior to attending veterinary school at Kansas State University, Dr. Amrine worked as a programmer/analyst for several years. During veterinary school he realized he didn’t want to go into traditional clinical practice, but instead found a way to combine his programming and data skills with veterinary medicine. He worked as a data scientist for Adams Land & Cattle in Nebraska for a few years after receiving his Ph.D. in applied epidemiology at K-State. However, it was ultimately the potential to use data contained in the warehouse for advancing predictive analytics research related to the health and performance of beef cattle that attracted Dr. Amrine to the research position at the BCI.

“Research using predictive analytics has exploded in the past 10 years – especially in human health and food production – however, the uptake and application to the beef cattle industry has lagged behind,” Dr. Amrine says.

He added that large amounts of data are typically needed to accurately explore and apply predictive analytics in the beef cattle industry, and that it has been difficult to accumulate these data.

“The data warehouse we have developed has taken us several steps further in the ability to have large datasets available to accurately train and develop machine learning models that can hopefully be applied towards some of the industry’s largest challenges,” he says.

According to Dr. Brad White, director of the BCI, Dr. Amrine’s combination of experience has proved to be extremely valuable.

“David has unique experiences from both the perspective of a veterinarian and a data scientist which allows him to create methods of analysis which provide practical insights for cattle producers,” Dr. White says.

How is the data being used?

Dr. White is certain this technology creates the ability to make data-based decisions which can contribute to moving the animal health industry forward.

“We see this as a place that we can generate new knowledge from existing data,” he says. “Long term, we see opportunities in creating new tools with the data which allow us to better predict health production performance outcomes which would facilitate owners, managers and veterinarians making better decisions. That’s our end game. We believe we can provide novel information and tools to producers that will allow them to make good decisions and add value to their operations.”

Student researchers at the BCI are already making use of this anonymized, secure data. Blaine Johnson, Hector Rojas, Lilli Heinen and Kristin Smith are each working on projects that affect the success of modern-day feedyards.

Blaine, who is currently working towards a Ph.D. in epidemiology, is utilizing the operational data available to him to improve the understanding of factors associated with heart disease in feedlot cattle. Previous research has identified individual risk factors such as, respiratory disease, placement period, risk of BRD and sex associated with right heart failure in fed cattle, however cohort level demographics were not analyzed. Blaine’s work has identified relevant risk factors and some of his work has been presented at the American Association of Bovine Practitioners and Academy of Veterinary Consultants meetings. His study is sponsored by the American Angus Foundation.

Dr. David Amirine studies a new set of feedlot data from the data warehouse.

BCI graduate students Blaine Johnson, Kristen Smith, Hector Rojas and Lilli Heinen.

Hector, a master’s student in veterinary biomedical science, is focusing his efforts on bovine respiratory disease (BRD). Hector is specifically using the data to evaluate environmental aspects that influence BRD risk, such as stocking rate, pen density and amount of bunk space, just to name a few. This study is part of a USDA grant in collaboration with Texas A&M University and Mississippi State University.

Lilli, a student pursuing her Ph.D. while simultaneously attending veterinary school, has started working on a project with Dr. Phillip Lancaster, nutritionist at the BCI. Dr. Lancaster and Lilli are exploring potential relationships between changes in feeding patterns and the risk of adverse animal health events during the feeding phase. Kristin is also a Ph.D. student in epidemiology, and is evaluating factors associated with cattle that died from BRD during the mid and late feeding periods. Her study began last fall and is sponsored by the Foundation for Food and Agriculture Research.

To stay up to date on the results of these studies, visit www. beefcattlinstitute.org to subscribe to its weekly newsletter.