Digitalization for Healthy and Environmentally Friendly Management of Dairy Cattle

Visual observation is still the gold standard for precise recordings of animal behavior. Unfortunately, it is also time and labor intensive. Wearable sensors can be a more practical way to collect behavioral data over longer periods of time. Steeneveld et al. (2015) concluded that labor reduction is an important reason for investing in sensor systems for dairy cows. Farmers need easy to handle, early warning systems to reduce workload and observation time, especially under practical conditions. Fortunately, more and more sensor systems to measure physiological and behavioral data exist on the market (Ding et al., 2022; Hoffmann et al., 2022; Mylostyvyi et al., 2024). For example, Precision Livestock Farming (PLF) is technology that assists in detecting animals under specific conditions such as disease or stress (Wrzecińska et al., 2023) by real-time monitoring of herds using sensors (Aquilani et al., 2022).

Until recently, a sensor was defined as a device that measures a physiological or behavioural parameter related to the health of an individual cow and allows automated on-farm detection of changes in this condition (Steeneveld & Hogeveen, 2015). However, the sensor itself is only the first step within the sensor system. The second step is to use the sensor data in an algorithm that provides information about the health of individual cows (Fig. 1). At this stage, the sensor data can be combined with non-sensor data relating to the cow’s history. The algorithm provides information about the health of the cow by detecting changes in the sensor data. The third step uses this information in a decision support model (using economic and other information).

Figure 1. Use of sensors in PLF systems

Other studies also recommend the use of accelerometers to record rumination and additional behaviours in dairy cows, describing them as the most commonly used motion sensors (Vanrell et al., 2018). Triaxial accelerometers were used by Capuzzello et al. (2023), to analyze the proportion of time spent ruminating in rumen-fistulated cows, using a bolus placed in the reticulum and a neck collar as well as ultrasound and auscultation as traditional methods to determine reticuloruminal contractility. However, it was clear that most of the sensors only monitored one or two behaviors, for example rumination and feeding time or only lying time. Rectal temperature (RT) and respiratory rate (RR) may be important clinical predictors of animal health. Therefore, it is concluded that further research is needed for different approaches to refine the detection algorithm and combine RT and RR with other production and behavioral variables to obtain a system with high sensitivity and specificity of disease detection.

This work was made possible by the professional cooperation between Ukrainian and German scientists. The main idea and technical side of the project belongs to Dr. Gundula Hoffmann, who is leading the working group Digital Monitoring of Animal Welfare at the Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) in Potsdam, Germany.

The objective of the project is to examine digital technologies in agriculture and analyze how they can be used to promote animal welfare. Many digital agricultural technologies are already practical or in advanced development, but widespread application is yet to come. While individual technologies of digital agriculture are already being used on a larger scale (e.g. milking robots), innovative applications (such as tracking systems for monitoring animal behavior) are still rather uncommon in agricultural practice. During the project, we will focus mainly on the possible practical use of digitalization on farms for animal-specific monitoring of animal welfare. We will evaluate how the data (from sensors and from farmers) and digitalization can be used to improve animal health, welfare and therefore, the productivity and food quality.

The continuous improvement of livestock farming and the implementation of efficient production methods in compliance with animal welfare and environmental protection criteria is a common task and goal of the project. The project deals with the use of digitalization to promote fair, healthy and environmentally friendly husbandry of dairy cattle (taking into account the goals of the “European Green Deal”). The aim is to evaluate innovative solutions that will sustainably improve the dairy cattle sector in Ukraine. With the help of digitalization technologies, we want to improve the health of dairy cows and thereby increase animal welfare and the quality of the milk produced. By using smart sensors to monitor health and climate parameters, diseases can be detected early and acted upon accordingly.

Author: Dr. Roman Mylostyvyi

Scientific supervisor of the project

Use of digitalization for a healthy and environment-friendly management of dairy cattle

Dnipro State Agrarian and Economic University

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