by Katie Navarra

Labor continues to top farmers’ lists of operational challenges. Finding reliable labor and affording wages without sacrificing cow health is a critical issue. Health sensor monitoring technologies are one option dairy farmers have for streamlining human labor while still providing critical care for their cows. Automated health monitoring tech and its place in dairy herd health management was the focus of a Cornell PRO-DAIRY webinar led by Julio Giordano, DVM, MS, Ph.D., a member of Cornell University’s Department of Animal Science.

“The cows wear neck tags (sensors) and they alert farm personnel when they are having a health issue,” Giordano said. “The sensors monitor rumination and physical activity and generate an index that is an indication of the cow’s health.”

For example, if a cow’s index is less than 86, that’s a sign someone should go check the cow and separate her from the herd for clinical examination and potentially treatment or an intervention to improve her health. Some farms run intensive monitoring programs which consist of looking at every cow daily for 10 to 20 days after freshening, whereas others observe more intermittently or for less time, Giordano explained. Combining neck sensor and daily milk weight data may help farms reduce manual labor and interventions with cows.

“The main idea is labor reduction and reduced cow manipulation,” he said. “Instead of checking many cows that may not need attention, personnel can focus on the few that truly need attention.”

This is also better for the cows, according to Giordano. Sorting cows into separate pens and restraining them for some time until the clinical examination and treatments are completed disrupts their time budgets, and in some cases may create some minor stress.

“Most cows that are healthy may not need that extra attention. Thus, the use of technology can help reduce the burden of checking cows using traditional methods that rely more on observation of all cows,” he said.

In a study funded by the New York Farm Viability Institute, Giordano and his research team tested the ability of some of the commercially available technologies to identify sick cows and the impact of using such tech on herd performance. The results showed that most of the cows needing attention were identified by the technology, although some human intervention was still needed. The results showed that there were no significant negative effects on herd performance for cows managed with the strategy that depended mostly on data from the devices used.

“The same percentage of cows left the herd through sale or death with the strategy using the technology as with the traditional method,” he said. “There was also no major difference in milk production within the first 150 days of milking and there was no significant difference in reproduction.”

Cost and return on investment are the big questions when farmers get ready to purchase any new technology. The preliminary results of Giordano’s study indicate that the economics depend on sensor lifespan and potential labor savings.

Lifespan is a major factor for the wearable sensors. When the sensors remain functional for about three years they may be economically viable only when parlor sensors for milk yield are already available or when the parlor cost per stall is less than $1,000.

When the wearable systems have a five-year lifespan, it is easier for them to break even, even at low labor costs when the amount of labor reduced by using the tech is significant (for example, reduced from four to two workers checking cows at a large dairy). Things look a lot better with a seven-year lifespan. The technology can break even for most scenarios of labor reduction and cost. However, a seven-year lifespan with minimum maintenance costs may not be observed for most commercially available systems.

“If a farm already has daily milk weight sensors, integrating wearable herd health monitoring systems is an additional tool that may help diagnose when something is wrong in some cows,” he said.

Based on his research and experience working with commercial farms, Giordano suggested some strategies for implementation to consider. One is to continue generating the daily cow checklist based on the farm’s current methods and use the technology as an aid to provide additional data to help with diagnosis. A second option is to build a daily cow checklist combining the farm’s traditional method and alerts or parameter data from the tech.

“The second option may help reduce the number of cows to evaluate each day and can help improve the diagnosis of sick cows,” he said.

A third option, which Giordano encouraged users to strive for, is to allow the technology to generate the daily list based on health alerts from the health monitoring system. That’s where farms will see the greatest benefit of the investment, he said. “However, the potential benefit depends on having a health monitoring system that can accurately identify cows with health disorders and at the same time not generate a lot of false alerts for cows that do not need attention,” Giordano noted.

Before buying a system, Giordano suggested working with a company that provides solid technical support services. Be sure that it will integrate with existing systems being used.

“These technologies are good in general and they are getting a lot better, but they are certainly not perfect and several issues remain,” he said. “Consider those systems that have been well validated through independent research and work with a company that offers good technical service post sale.”