Barbara Rodrigues
As research scientist and manager of the Grazingland Animal Nutrition Laboratory, GAN Lab, Barbara Rodrigues, Ph.D., merges her passion for animal science and environmental stewardship to develop actionable insights for ranchers and livestock managers to enhance the sustainability and efficiency of livestock production systems
“As our global population continues to grow, the demand for animal products increases, posing significant challenges for natural resource management and environmental sustainability,” Rodrigues said. “I am motivated by the need to find solutions that not only improve animal nutrition and production but also minimize the environmental impact of livestock operations.”
In addition to research, Rodrigues oversees the daily activities of the lab, conducting dietary diagnostic analysis of fecal samples using fecal near-infrared reflectance spectroscopy, FNIRS, and applying these findings to the Nutritional Balance Analyzer, NUTBAL, software package to generate reports that assist ranchers in optimizing their nutritional and grazing management decisions.
“Dr. Rodrigues has been a critical component to the reinvigoration of the Grazingland Animal Nutrition Laboratory,” said Bill Fox, Ph.D., director of the Center for Natural Resource Information Technology and Texas A&M AgriLife Extension Service range specialist. “She provides leadership in updating of all the technological components of FNIRS applications and is currently working on groundbreaking efforts to use near-infrared spectroscopy for estimating methane production of livestock.”
Rodrigues said methane production from the enteric fermentation of ruminants is a source of greenhouse gas emissions in the U.S. agricultural sector. Because of this, livestock operations are often criticized for their environmental impact.
However, she said those assessments can sometimes be based on incomplete or inconsistent information.
“While various techniques and methodologies exist for measuring enteric methane emissions, many are tailored for specific research purposes and are not feasible for use on commercial farms,” she said. “These methods are often costly, time-consuming and require specialized equipment that is not readily accessible to most producers.”
Rodrigues said the GAN Lab has been using FNIRS to predict grazing livestock diet quality since 1995. The lab’s latest project drew from a comprehensive U.S. dataset of approximately 30,000 fecal samples. Rodrigues selected a subset representing beef cattle grazing in the Gulf Coast region of Texas from 2016 to 2019, and applied published equations to this data, which were presented at the 2024 annual meeting of the American Society of Animal Science in Canada.
Rodrigues said the FNIRS/Nutbal technique has shown promise in providing valuable inputs for established methane calibrations.
“Our research project aims to validate these predictions against methane reference methods to ensure accuracy and reliability,” she said. “By integrating FNIRS technology, we aim to develop a rapid, cost-effective and non-invasive approach to estimate methane production from livestock. This technique could improve how methane emissions are monitored, providing real-time data that producers can use to make informed decisions.”
The lab recently secured $2 million in grant funding to continue studying the use of FNIRS in the methane project. Additionally, Rodrigues and the lab team are working to strengthen international near-infrared reflectance collaborations, including partnerships with her home country of Brazil.
Rodrigues said the GAN Lab is also focused on expanding FNIR diet quality equations to newer near-infrared reflectance instruments and technology, as well as implementing field-portable NIRS applications to measure soil characteristics and constituents.
“Ultimately, our goal is to equip producers with the tools and knowledge to optimize forage resource management, reduce methane emissions and enhance the overall sustainability of grazing animal agriculture,” Rodrigues said. “By providing a practical and accessible method for methane estimation, we hope to empower producers to implement strategies that minimize the environmental impact of their operations while improving the productivity and health of their herds.”
