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A closer look at wearable technology

As more and more farmers adopt wearables, new research aims to assess how they affect reproductive performance.

Inside Dairy

2 min read

The use of wearable technology (on-animal sensors) has significantly increased among farmers. In a 2023 survey, 18% of farmers reported using wearables, compared to 3% in 2018. This growth translates to more than 820,000 cows now equipped with devices.

Investing in these technologies requires a significant commitment, yet farmers have had limited independent, publicly available information on their potential impact on reproductive performance — an important factor they regularly consider in return calculations — until now.

The widespread adoption of wearables has generated enough data to evaluate reproductive performance before and after implementation, as well as compare it to herds without wearables for the same period.

To provide more clarity around this, we analysed herd reproductive records to see what, if any, changes occurred after adopting wearables.

The analysis used data from 141 wearable herds and 1,158 non-wearable herds. The “control” herds (those without wearables) were matched with the wearable herds based on location, herd size, production and calving dates to compare like with like as much as possible.

Records were filtered to include only the period from two years before to two years after wearable adoption (or, for non-wearable herds, the year they were matched with a wearable herd). This was due to the limited number of farms with data extending beyond two years.

After adopting wearables, farmers extended the duration of their artificial breeding (AB) period. Some transitioned to all-AB in the first year, eliminating any natural mating periods with bulls.

By the second year, most had shifted to all-AB, with the delay presumed to be while they built confidence in the technologies.

Herds using wearables had higher performance measures, such as 3-week submission rates (see Figure 1) and 6-week calving rates (see Figure 2), compared to those without wearables, both before and after adopting the technology.

With this in mind, companies marketing wearables should take care when discussing reproductive performance, ensuring that comparisons with industry averages don’t unintentionally suggest any differences are due to the adoption of wearables.

Wearable herds had lower non-return rates after adoption, likely because they had longer AB periods. However, after accounting for mating length, there was no significant difference (see Figure 3).

Notably, lower-performing herds showed no reproductive performance gains after adopting wearables, with results comparable to similar herds without them.

Farmers have had limited independent, publicly available information on the potential impact.

The research indicates that farmers who automated mating with wearables, potentially reducing labour or reliance on key staff, did so without compromising reproductive performance.

A longer artificial breeding period offers several potential benefits, including that the non-return rate is more likely an accurate indicator of conception rates, providing timely feedback to adjust mating plans rather than waiting until after scanning to assess bull performance. And all-AB systems can help produce higher-value calves.

In the future, wearable technologies could offer benefits beyond reproduction and individual animal management, such as improving grazing management or mitigating heat stress. Future outcomes may improve as farmers better understand how to use data from wearable systems effectively, for example, additional pregnancy diagnoses.

Given the lack of evidence for significant positive or negative impacts, it would be advisable for farmers considering wearable technologies not to place value on improved reproductive performance when assessing return on investment.

For more information on wearables and herd reproductive performance, check out dairynz.co.nz/wearables

The impact of wearables on reproductive performance

A study of self-selected herds that have adopted wearables relative to a matched reference group.

The adoption year was marked as Year 0, with any effects of wearables becoming apparent from Year 1 onward.

Inside Dairy May July 2025 Wearable Technology Graphs Figure1v2
Inside Dairy May July 2025 Wearable Technology Graphs Figure1v2
Inside Dairy May July 2025 Wearable Technology Graphs Figure2v2
Inside Dairy May July 2025 Wearable Technology Graphs Figure2v2
Inside Dairy May July 2025 Wearable Technology Graphs Figure3v2
Inside Dairy May July 2025 Wearable Technology Graphs Figure3v2

About the contributor

Paul Edwards
DairyNZ senior scientist

Other technical contributors

  • Callum Eastwood - DairyNZ
  • Sarah Bird - Massey University PhD student
  • Chris Burke - DairyNZ
  • Winston Maston - EpiVets

This article was originally published in Inside Dairy May-July 2025.

Additional links

Automated heat detection

/animal/reproduction-and-mating/automated-heat-detection/

Reducing Sprains and Strains

/research/science-projects/reducing-sprains-and-strains/

Milking Practices and Technology Use

/research/science-projects/milking-practices-and-technology-use/

Page last updated:

4 Jul 2025


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