Editor’s note: The following was written by Martin Mangual, Madonna Benjamin and David Thompson with Michigan State University Extension for the university’s website Dec. 20.
Farmers understand “running to where the trouble is,” and new technology with promising results can help.
Precision farming technologies, which employ sensors to help manage farm operations, are at an early stage of adoption in livestock production. Recent advances in cost, quality of equipment, machine learning/cloud-based systems, and the fact that skilled farm labor is becoming harder to find are all factors that have generated additional interest from livestock producers.
One feature most precision livestock farming capabilities share is the ability to operate continually without regular human intervention. This allows farm staff to monitor individual animals and focus on activities such as administering treatments or assisting in maternity instead of routine tasks like pen watching.
Factors driving interest/demand for precision livestock farming include:
- Increasing global demand for animal protein.
- Labor shortage (managers, trained animal handlers).
- Need for lower input costs to maintain farm profits.
- Expanding farmer awareness of precision livestock farming and its benefits.
- Public demand to lower antibiotic use in food animals.
- Public demand to improve animal welfare.
- Public demand to lower carbon footprint of livestock.
- Public demand for greater transparency in food production.
- Advances in sensor and cloud-based technologies.
Reviewed in this article are various precision livestock farming technologies and their perceived impact on livestock health and farm labor for dairy and swine farms.
Feeding animals optimally to achieve their genetic potential, along with labor, are the costliest daily inputs on farms. Automatic calf feeding systems exemplify an established precision livestock farming technology. Automatic calf feeding systems seamlessly allow producers to maximize animal performance and fine-tune individualized feeding plans for calves as they develop and grow.
Many auto-feeders are equipped with scales that allow the operator to track a calf’s growth. This technology also allows a proactive approach to disease identification and prevention.
A Minnesota study showed that sick calves change their meal intervals and drinking speed, among other feeding behaviors, before they show clinical signs. A Michigan farmer using this technology noted that it helps identify calves that might need extra attention sooner, preventing small issues from significantly impacting the calf program.
Implementing automatic calf feeding systems, for example, might alleviate the need for two hours of time to wash and sanitize buckets and redirect employees’ time to added-value procedures like processing calves in a timely way or observing calves more closely.
Other precision livestock farming technology that increase the observation of susceptibility, or early stages of disease, include sensors to track rumination activity using sounds or rumen motion. It has been shown that changes in rumination time or patterns can identify animals that are decreasing intake or showing other physiological changes.
In a recent study, cows with metritis were identified by the aid of sensors measuring rumination.
Lameness has a negative impact on animal performance and is a major welfare concern for both the swine and dairy industries. Identifying lame animals accurately and early requires both trained labor and facilities that provide a clear view for scoring.
However, when using precision livestock farming sensors, a computer can be trained to recognize, with high reliability, the gait patterns of livestock experiencing lameness. To do this, computers receiving video images collected over time quantify movement patterns and identify abnormal movements that reflect potential lameness. This allows employees to spend less time scoring animal movement and prioritize time to treat affected animals.
In dairy studies, multiple research groups are exploring the reliability of accelerometers, barn cameras, pressure plates, or a combination of these technologies.
Some automatic milking systems use a balance system to measure leg load of a cow while she is standing in the milking robot unit, then analyze the data to identify animals showing signs of potential lameness.
Another area where precision livestock farming technologies can impact labor input is estrus detection. Automating this process could save operation labor costs by decreasing the time it takes to complete this task in both swine and dairy herds.
For large-group gestation systems, this can supplement a breeding technician’s observations. Companies such as Ro-Main use sensors to capture sow behaviors associated with estrus, such as time standing in the presence of a boar, to predict the best timing for insemination. Research has shown that when this technology was complemented by worker supervision, farrowing rate improved.
In dairy cattle, precision livestock farming sensors, including activity monitors, pressure sensors, camera systems and lasers, have been used to measure walking, mounting and standing activity to determine estrus behavior. These approaches show promise as they not only reduce investment of employees’ time but also are non-invasive processes that reduce animal handling.