=Paper=
{{Paper
|id=Vol-3293/paper56
|storemode=property
|title=Animal-specific Heat Stress in Dairy Cattle - Abstract
|pdfUrl=https://ceur-ws.org/Vol-3293/paper56.pdf
|volume=Vol-3293
|authors=Sophia Sauter,Isabella Lorenzini,Sarah Hertle,Bernhard Haidn
|dblpUrl=https://dblp.org/rec/conf/haicta/SauterLHH22
}}
==Animal-specific Heat Stress in Dairy Cattle - Abstract==
<pdf width="1500px">https://ceur-ws.org/Vol-3293/paper56.pdf</pdf>
<pre>
Animal-specific Heat Stress in Dairy Cattle - Abstract
Sophia Sauter 1, Isabella Lorenzini 1, Sarah Hertle 1 and Bernhard Haidn 1
1
    Bavarian State Research Center, Prof.-Dürrwaechter-Platz 2, Poing, 85586, Germany


                 Summary
                 Due to climate change, the associated increase in temperatures and simultaneously high milk
                 yields, dairy cows are increasingly exposed to heat-related stress situations. High metabolic
                 performance of high-performance animals additionally shifts their thermoneutral zone to lower
                 temperatures. Often only climatic parameters such as the temperature-humidity index are used
                 to assess the heat stress in dairy cattle.
                 Different studies additionally use animal-specific parameters for an earlier detection of heat
                 stress. Geischeder, 2017 identified the physiological parameters respiratory rate and body
                 temperature as suitable indicators for individual animal heat load. In another study, the
                 behavioural parameters rumination and locomotor activity showed a correlation with heat load
                 (Heinicke et al. 2020).
                 For the detection of heat stress in dairy cattle, animal-specific parameters recorded via sensor
                 systems (automatic milking system, weighing troughs, pedometers and boli) on one
                 experimental farm will be used in the first step to identify suitable behavioural and
                 physiological parameters. The respiratory rate, which is recorded by visual animal observation
                 of focus animals, serves as a reference value. For the prediction model, data from different
                 sources were combined. The identification data of 12 focus animals (age, lactation status,
                 lactation number, breed) were combined with data from pedometers (ENGS Dairy Solutions),
                 that are used to record locomotor activity, lying and feeding behavior. The rumen boli
                 (SmaxTec) continuously record locomotor activity, rumination activity, body temperature, and
                 drinking cycles. Likewise, the barn climate and environmental data were recorded by a weather
                 station. Furthermore, animal-specific feed intake can be recorded at this experimental farm via
                 weighing troughs.
                 Visual recording of respiration rate was performed on 3 days each in July and September 2021.
                 Breathing rate was counted once per hour for 15 seconds in all focal animals, using lateral flank
                 movement. These data are then extrapolated to 1 minute. This results in one value per hour per
                 focal animal. A further data collection will take place in 2022, starting in June 2022 until the
                 end of August 2022. All recorded parameters will be compiled in a database to form a complete
                 data set and analysed with the statistics program Rstudio to find relevant parameters that
                 individually change during heat stress. First results are expected in summer 2022. In addition,
                 the data collected by the various sensor systems will be used to create prediction models for
                 recognizing individual animal heat load. These models will essentially incorporate behavioral,
                 physiological and environmental data.

                 Keywords 1
                 Animal-specific sensor, heat stress, dairy cattle

                 Acknowledgements
                 The project is supported by funds of the Federal Ministry of Food and Agriculture (BMEL)
                 based on a decision of the Parliament of the Federal Republic of Germany. The Federal Office
                 for Agriculture and Food (BLE) provides coordinating support for digitalisation in agriculture
                 as funding organisation.



Proceedings of HAICTA 2022, September 22–25, 2022, Athens, Greece
EMAIL: SophiaAnna-Maria.Sauter@lfl.bayern.de (A. 1); Isabella.Lorenzini@lfl.bayern.de (A. 2); Sarah.Hertle@lfl.bayern.de (A. 3);
Bernhard.Haidn@lfl.bayern.de (A. 4)
              ©️ 2022 Copyright for this paper by its authors.
              Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
              CEUR Workshop Proceedings (CEUR-WS.org)




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