How to Choose the Right New Technology for Your Dairy Farm
Aidan Connolly and Jeffrey Bewley
August 30, 2021
It is increasingly clear that technology is the future of dairy, but the number of options to choose from can be overwhelming. Cow wearables (IOT), machine learning and augmented reality based technologies, camera vision and feeding and milking robotics are just some of the technologies that a dairy farmer can choose from. However, thinking about and deciding on technology is not the only thing a dairy farmer has on their plate. Money should be spent wisely. And whether the dollars are spent on technology, more cows, a new barn, a new mixer, etc, it all must be economical and relevant.
Which Questions to Ask? To separate the wheat from the chaff, it is time to look again at technologies and how they might best fit from a performance and profitability perspective. The decision to invest all comes down to matching the technology to the issue you want to address on your farm. A piece of technology may look very cool and exciting and may overshadow what you can really do with the information. Managing expectations and asking the right questions are key. There is no piece of technology that is going to turn an unprofitable dairy into a profitable one overnight; incremental changes are what we will see.
A dairy farmer should take time to ask: Is a certain technology addressing what I am asking for, does it do it well, what can it measure and can it do more in the future? These types of questions are often new for a dairy farmer, compared to asking questions about what to expect from a new type of ration for example (e.g. effects on milk production or somatic cell count). Besides important questions around costs of the technology per animal, additional hardware costs, possibilities to integrate with other systems and a FMS, available support and training and data use and ownership, the key question remains: What is the issue at the farm level that we are trying to address? The answer should drive the process of finding the right technology to invest in. New technology can’t just be a gadget on the farm.
Different Decision Levels Technology can increase profitability and performance on cow, group and/or farm levels. The decision level should match the technology. Before the use of technology, monitoring an individual cow’s health has been difficult, time consuming and cost intensive. However, the use of sensors and wearable technologies allows farmers to monitor individual cows for breeding and health. And there is no shortage of companies producing this type of technology. So if the farmer wants to mainly address identification of individual sick cows (e.g. monitoring ketosis), then wearables do what they promise. But IOT sensors have challenges, often referred to as the ‘hassle factor’. It involves finding people (scarce labor) to manage the sensors on the cows, or when they break or fall off Overall, sensors have been a game changer on farms, but they require different investments and management styles that in itself is challenging.
Large dairies tend to focus more on group / herd level and are often eager to invest in technologies that focus on management of feeding costs and feeding process. Then technologies based on camera vision such as that of Cainthus uses the feed from cameras stationed throughout the barn and machine learning software. Cainthus alerts the farmers when feed is low in the bunk, when push-ups have not happened. Camera vision also provides valuable pen level information on lying time and other behavioral indicators such as cow comfort and productive time. Another promising area of technology that gives information on individual cows as well as group level are the in-line sensors / milk meters that measure milk fat, protein, somatic cell counts, progesterone, antibiotics and other relevant components at every milking. An increasing number of companies are active in this field, such as SomaDetect and Labby. The milk-based sensors provide relevant information to optimize production, animal health (mastitis) programmes, breeding and more.
Fully Utilizing the Data Defining the issue you want to solve and selecting the best technology to do so is the first step. Efficient use of the equipment is next. An automatic feed pusher for example, working with the technology, can be pretty straightforward. The main goal here is to automate certain manual tasks, not so much to gather data. But for more complicated (data) devices such as sensors or cameras, it can be more challenging. If farmers can’t interpret the data coming from the sensors and cameras, and use it to take actions, then the data is useless. Artificial intelligence and machine learning models can sort through data, highlighting the parts that are of actionable use to the farmer. It also allows producers to analyze the data that sensors and other hardware technologies collect.
More and more technologies are focused on providing these actionable insights on a desktop or mobile dashboard, and often also show recommendations on what to do.
Frequently of course farm workers don’t avail of all the options and functionalities technology offers (but for example what percentage of functionality of Excel do you use yourself?) but this will change in the future, when future dairy farmers will better understand the value of this data and the technology companies continue to simplify and deliver interfaces that make it easier to understand.. Nutritionists, veterinarians and farm consultants can also play a bigger role shere.
Small Progress is Also a Win Dairy farmers are in a constant battle where to invest their money, and as long as the risks of being in dairy farming don’t change, this battle will not change. Choosing the right technology for your farm drills down to what you want to target on your farm. Do you want to reduce the cases of ketosis in your herd, do you want to reduce feed costs, reduce manual labor, or do you want to optimize your first age of breeding? The main issue to solve determines what the first type of technology should be. Sensors, artificial intelligence/machine learning, camera vision and other technologies provide individual data for each cow or generate valuable group level insights, allowing farmers to improve.
It is important to not hold on to too high standards. Progress is not always from 0 to 100, but rather from 0 to 20 for starters. Small improvements can already make a big difference. For example, a producer with 4000 cows is spending $1 million a month on feed. Why not start with a simple goal to get 1 Lb more of that expensive feed into each cow, or waste a 1 Lb less feed per cow at the end of the day? Given that up to 60% of the cost of producing milk is represented by the feed, small improvements, aided by technology, can result in significant gains in productivity and farm profitability.