Nutrition models may help producers to reduce impact on environment
Nutritional modeling systems developed in the Department of Animal Science at Texas A&M University have helped participating Texas feedlot operators keep feed costs in check and produce beef more profitably. Now, these models have the potential to be applied to help reduce greenhouse emissions, according to researchers.
Luis Tedeschi, Texas A&M AgriLife Research nutritionist and associate professor in the Department of Animal Science, has extensively studied decision support systems, specifically nutritional modeling. While a doctoral student at Cornell University, Tedeschi worked with Danny Fox in developing the Cornell Net Carbohydrate and Protein System model for evaluating herd nutrition and nutrient excretion.
At Texas A&M, Tedeschi built upon that work in developing the Cattle Value Discovery System, or CVDS, which helps feedyards sort animals into homogenous groups so that a higher percentage reach a desired level of grade on the day the pen is marketed.
“Usually when feedlots receive animals, they group them in pens by weight,” he said. “We changed the paradigm to grouping them according to CVDS-predicted days to reach the target U.S. Department of Agriculture quality grade, usually USDA low choice.”
Also, nutritionists have typically formulated cattle rations that often contained excess nutrients to ensure that growth rate was maximized, which often increased nutrient excretion and contributed to adverse effects on water and air quality, Tedeschi said.
The Large Ruminant Nutrition System, LRNS, is a computer model that estimates beef and dairy cattle nutrient requirements and supply under specific conditions of animal type, climatic conditions, management and physiochemical composition of available feeds. This model uses the same computational engine of the Cornell Net Carbohydrate and Protein system, Tedeschi said.
The CVDS modeling system is used by Performance Cattle Company and Micro Beef Technologies, among others. When used in combination with the LRNS, the CVDS creates a complete ration for each animal and predicts a day to reach the target USDA grade. An RFID (radio frequency identification)ear tag system monitors which lots of animals receive a certain kind and amount of feed ration.
“It’s a very complete model for nutrition,” Tedeschi said. “In addition to improving performance and profitability while reducing environmental impact, these models help producers and consultants understand nutrient requirements and feed utilization in beef, sheep and goats.”
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