Thursday, December 15, 2022

Automating feeding to improve dairy cow health

Dairy cows sometimes suffer negative energy balance because their rations are short of what they need for good health, but automating feeding systems could resolve that issue.

Patty Kedzierski, a PhD candidate in the Department of Animal Biosciences at the University of Guelph, is handling data collection and research for solutions under supervision by Dr. John Cant.


“Current dairy cattle feeding practices can cause a negative energy balance (NEB), resulting in adverse effects on the cow’s health and productivity,” she said. “Automated technologies could  . . . target the individual needs of each cow.”


Kedzierski said most farms feed their cattle a total mixed ration (TMR), meaning all cows are fed the same diet based on a cow representative of the top percentile of the herd. Cows have varying nutritional and metabolic needs, so feeding a TMR can result in a large proportion of the herd being over- or underfed.


“During early lactation, if the energy intake provided by the TMR is insufficient for milk synthesis, cows experience a negative energy balance,” she said. “Negative energy balance leaves cows more susceptible to disease and reduced productivity, which can be costly for milk producers.”


Data will be collected from various sensors, including a 3-D camera and an emission monitoring system. 


These automated technologies will measure daily dry matter intake, milk yield, body weight, body condition score and respiratory gas exchange of oxygen, carbon dioxide and methane. 


Kedzierski anticipates that automated data collection may help to reduce negative energy balance during early lactation. She says implementing individualized feeding plans could help optimize productivity, lower feed costs, minimize nutrient excretion and curb disease.


“In the future, I hope to be able to integrate all of these technologies onto a singular platform,” she said. “Doing so would make it easier to implement individualized care practices on farm and would thus reduce NEB and its associated costs.”