DairyNZ explores the potential of digital technology to support animal wellbeing and the overall health of farm systems.
The-future-of-farm-tech
Farmers can use the Grazing Heat Load Index (GHLI) to predict heat stress and make informed decisions about managing heat load during hot summer days. Photo: Inside Dairy

DairyNZ explores the potential of digital technology to support animal wellbeing and the overall health of farm systems.

Contributors: Jenny Jago, DairyNZ principal scientist, programme lead; Kirsty Verhoek, DairyNZ senior scientist; Paul Edwards, DairyNZ senior scientist and Charlotte Reed, DairyNZ scientist

As farms generate more data than ever before, the challenge is figuring out how to use it effectively and unlock its potential. Meanwhile, interest from customers and consumers worldwide is growing, particularly in how their food is produced and the quality of life of the animals involved.

Between 2020 and 2024, DairyNZ worked alongside AgResearch and Fonterra on the New Zealand Bioeconomy in a Digital Age (NZBIDA) programme. This initiative explored how farmers could leverage digital technologies and data to improve farm management and enhance animal care.

There were several elements, including some initial background work led by Fonterra, to uncover what customers were seeking from a cow wellbeing perspective. Further work explored the range of available technologies and their wellbeing-related measurements, with a strong emphasis on wearable devices.

The three main projects focused on understanding cow wellbeing via digital technology, measuring and predicting heat stress in NZ dairy cows, and the potential for wearable data to aid in pasture management.

Proof of concept: Using wearable data for pasture management

Farmers in New Zealand are increasingly investing in wearable technology, with nearly one million cows now equipped with various devices. The data is typically used for monitoring individual animals to identify heat or health events, but we wanted to investigate what other insights could be generated from the data.

Initially we collaborated with a group of farmers and sector stakeholders to determine the focus of the research, which highlighted a desire to aid grazing management. Specifically, could animal sensor data give an indication of feed availability?

We carried out a controlled grazing experiment, dividing cows wearing five sensors  across four herds (see Figure 1). These herds were given different amounts of pasture, from 80% to 120% of their estimated requirements, to see if these differences could be reflected in changes in the sensor data.

The data from the sensors was compared to measures such as pre-grazing pasture mass and post-grazing residual, which showed correlations, particularly with rumination time. Novel ‘cow’ behaviours calculated from animal location data, like how far the cows travelled and how close they were to their herd mates, were also good at explaining pasture mass.

Overall, the study demonstrated the potential of using animal sensors for grazing management, which could save time, reduce costs and alleviate the mental load on farmers. However, it’s still in the early stages and more research is needed to see how useful it is and how it can be applied in different farming situations.

We’ve shared the initial findings with the companies whose technologies were used in the experiment. The next step would be for commercial companies to invest in further research and development in this area.

Screenshot 2025 01 29 at 122637%20PM
Figure 1: Experimental design (4x 5-day allocation periods).

Measuring and predicting heat stress in New Zealand dairy cows

Heat stress occurs when cows have more heat load than they can release it leads to discomfort and lower milk production. All dairy regions in New Zealand get hot enough to cause heat stress during summer.

The most common global measure for heat stress is the temperature humidity index (THI), which is relevant for situations where cows are housed indoors. But it is less applicable to our NZ pastoral systems since our cows are outdoors, exposed to the elements. A specific grazing heat load index (GHLI) had been developed to assess heat stress in pasture-based cows, incorporating factors like air temperature, solar radiation and wind speed.

Within the NZBIDA programme, we sought to strengthen the GHLI, which was initially developed using a Waikato dataset. Data was collected from 600 cows across seven farms, measuring weather variables such as temperature, humidity, solar radiation and wind speed, alongside animal-based indicators like respiration rate, panting and rumen temperature.

By including data from many locations, we have strengthened the GHLI. However, it is still challenging to predict heat stress in conditions such as high wind speed. As part of our future research focus, we hope to explore alternative modelling techniques that could help enhance the GHLI, providing farmers with a more accurate forecasting tool.

We know that animals vary in their susceptibility to heat stress, and sensor or wearable technology is helping us gain a deeper understanding of these differences.

​In addition, if we can forecast specific days and times when animals are most at risk, it will enable farmers to take a more strategic approach to reducing heat load. For example, if we discovered that only 20% of the herd need shade under certain conditions, we wouldn’t have to provide shade for the entire herd in those situations.

We found that the GHLI is a valuable tool for assessing heat stress risks in outdoor animals, helping farmers make informed decisions on managing heat stress effectively. The next round of research will delve deeper into opportunities for mitigating heat and becoming more strategic with mitigations.

The next steps: building a ‘connected’ farm

The Connected Farm project is exploring how integrating various data sources could support farm management. As part of this, we’ve developed a proof-of-concept dashboard that consolidates information about both the cow and her environment. Our two partner farms in Waikato and Canterbury are currently testing the dashboard and collaborating with us to refine the concept.

The dashboard brings together learnings from across the programme.  It was developed alongside farmers to determine the necessary data inputs, frequency and resolution needed to support on-farm decisions.

For example, it displays forecasted heat stress risk alongside details on water systems and paddock conditions, such as cover and shade availability, helping farmers better manage heat stress events. Actual weather data is shown alongside cow behaviour, allowing farmers to see how their herd responds to environmental conditions.

A key focus is also understanding cows’ daily experiences. To achieve this, data from various sources is compiled into a “time budget”, providing insight into how cows spend their time and what factors influence their behaviour.

So far, the project has shown there is value in combining different data streams.  However, building trust and confidence in the data is essential for effective use, and this takes time. As the Connected Farm project moves into the new season, our team and partner farms will continue exploring how to fully harness the potential of digital technology to support on-farm decisions.

This story first appeared in Inside Dairy, the official publication of DairyNZ.

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