Research for animal welfare and environmental health
Concepts of livestock farming should incorporate the three pillars of sustainability: environment, society and economy. While there is a growing desire in society for improved animal welfare and enhanced environmental protection, the need for economic survival on the part of farmers must be taken into account at the same time. This requires innovative processes to find their way into practice.
We therefore focus our application-oriented basic research in animal husbandry in line with the One Health approach on improving animal welfare, on husbandry environment, animal and environmental protection as well as on the competitivity of agriculture. Our goals are: objective animal welfare standards, flexible and regionally adapted concepts to solve environmental conflicts, a transparent animal husbandry, consumer acceptance and regional added value.
Our research in this program area is particularly concerned with digital methods for monitoring animal welfare, housing climate and emissions, as well as the evaluation of animal housing systems, especially in open-ventilated and novel housing systems. We develop fundamental knowledge on the generation and dispersion of gaseous emissions and pathogen-laden particles as well as on the ways to minimize the risk of spreading multi-resistant pathogens.
The ATB boundary layer wind tunnel offers extensive possibilities for the investigation of airflow and dispersion processes around agricultural buildings as well as airflow and ventilation processes within the buildings. The detailed understanding at process level feeds into modeling approaches with the goal of estimating emissions from new housing systems and finding opportunities for low emissions in animal-friendly housing.
We consider animal husbandry as a part of circular agricultural systems and integrate our research into the holistic, bioeconomic concept of the Leibniz Innovation Farm, which is currently being established in Groß Kreutz.
Digital monitoring of animal welfare
We develop and test the use of non-invasive sensors for the animal-specific recording of stress and health. In this context, we analyze animal-individual indicators such as activity, respiration rate, body temperature and performance together with stable climatic parameters in different animal species and husbandry systems, increasingly by using data science, artificial intelligence and sensor fusion. Our aim is to develop automated decision support and control units based on animal-related indicators. Early warning systems are to support farmers in sustainably improving animal health and welfare.
Barn climate and emissions

We are developing algorithms to efficiently measure, characterize, and model the dynamics of pollutants that are harmful to the environment, climate, and/or health, and to mitigate infection and antimicrobial resistance (AMR). Within our three-pillar model, we combine measurements in different real-world husbandry systems with physical and mathematical modeling to form an overall system. The solutions developed here are intended to strengthen the resilience of farms and contribute to energy efficiency, moving away from fossil raw materials and reducing emissions.
Containing infections and antibiotic resistance

Our research follows the One Health approach and aims at prevention and control measures against the spread of zoonoses, infectious diseases and antibiotic resistance in the livestock sector. For example, we are investigating the influence of feed additives and improved hygiene measures in pig farming, the effectiveness of different farm manure treatments and parameter variations on the reduction of AMR bacteria in poultry farming, and are developing an early warning model for mastitis in dairy farming.
Assessment of animal husbandry systems
Our objective for a sustainable livestock production is to close material cycles, to improve nitrogen efficiency, to reduce GHG emissions and to develop individual, regional and flexible concepts for circular agriculture and food systems. To do this, we use methods of modeling, systems analysis, and multi-criteria evaluation, including quantification of trade-offs and synergies. The results are fed into operational decision support systems and proposals for stock improvement as well as into emission models for the analysis of country-specific scenarios and inventories. We also collaborate closely with international bodies at IPCC, UNECE and FAO in this area.
To the team of the program area
Research projects
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The collaborative project InnoRind (here: funding phase 2) brings together the expertise of twelve project partners across Germany, including universities, colleges, research institutes, chambers of agriculture and the a…
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Naturally ventilated pig barns with outdoor exercise yards (NVPBOYs) are receiving increasing attention worldwide. The air exchange between outside and inside a NVPBOY is poorly understood which prevents estimation of em…
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The frequency of occurrence of antimicrobial resistances (AMR) in livestock is an important aspect for their spread in the environment and exposure to humans and other animals. The ERA-NET project ENVIRE (Interventions t…
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Within the framework of HorseWatch, the influence of the horse breed and training conditions, the age at the beginning of use and the husbandry system on the health, behaviour and well-being of horses used very early in …
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The DairyMix project aims to support the transformation of farming structures towards higher levels of diversity by growing more crops in succession or in parallel. This improves the circular flow of carbon and nutrients…
More projects within the program area
Publications of the program
- Schumacher, B.; Stinner, W.; Strach, K.; Amon, T. (2023): Entwicklung und Test einer Methodik zur Langzeitmessung von Methanemissionen aus Gülle. Biogas Journal. (2): p. 76-85. 1.0
- Behrens, W.; Kolte, B.; Junker, V.; Frentrup, M.; Dolsdorf, C.; Börger, M.; Jaleta, M.; Kabelitz, T.; Amon, T.; Werner, D.; Nübel, U. (2023): Bacterial genome sequencing tracks housefly-associated dispersal of fluoroquinolone- and cephalosporin-resistant Escherichia coli from a pig farm. Environmental Microbiology. : p. 0. 1.0
- Wang, X.; Cao, M.; Hu, F.; Yi, Q.; Amon, T.; Janke, D.; Xie, T.; Zhang, G.; Wang, K. (2022): Effect of fans placement on the indoor thermal environment of typical tunnel ventilated multi-floor pig buildings using numerical simulation. Agriculture. (6): p. 891. Online: https://doi.org/10.3390/agriculture12060891 1.0
- Hempel, S.; Janke, D.; Losand, B.; Zeyer, K.; Zähner, M.; Mohn, J.; Amon, T.; Schrade, S. (2022): Comparison of methane emission patterns from dairy housings with solid and slatted floors at two locations. Agronomy. (2): p. 381. Online: https://doi.org/10.3390/agronomy12020381 1.0
- Hilgert, J.; Amon, B.; Amon, T.; Belek, V.; Dragoni, F.; Ammon, C.; Cárdenas, A.; Petersen, S.; Herrmann, C. (2022): Methane emissions from livestock slurry: effects of storage temperature and changes in chemical composition. Sustainability. (16): p. 9934. Online: https://doi.org/10.3390/su14169934 1.0
- Wei, S.; Chadwick, D.; Amon, B.; Dong, H. (2022): Comparison of nitrogen losses from different manure treatment and application management systems in China. Journal of Environmental Management. (März): p. 114430. Online: https://doi.org/10.1016/j.jenvman.2022.114430 1.0
- Kraft, M.; Bernhardt, H.; Brunsch, R.; Büscher, W.; Colangelo, E.; Graf, H.; Marquering, J.; Tapken, H.; Toppel, K.; Westerkamp, C.; Ziron, M. (2022): Can Livestock Farming Benefit from Industry 4.0 Technology? Evidence from Recent Study. Applied Sciences. (24): p. 12844. Online: https://doi.org/10.3390/app122412844 1.0
- Lv, Y.; Yao, H.; Li, A.; Yi, Q.; Janke, D.; Amon, T.; DS Quoie Jr, G.; Shen, X.; Long, Z. (2022): Comparison of simulation methods for dynamic internal air distribution in naturally ventilated livestock buildings. Computers and Electronics in Agriculture. : p. 107427. Online: https://doi.org/10.1016/j.compag.2022.107427 1.0
- D´Urso, P.; Arcidiacono, C.; Valenti, F.; Janke, D.; Cascone, G. (2022): Measuring ammonia concentrations by an infrared photo-acoustic multi-gas analyser in an open dairy barn: repetitions planning strategy. Computers and Electronics in Agriculture. (Januar): p. 107509. Online: https://doi.org/10.1016/j.compag.2022.107509 1.0
- Schulte, H.; Ammon, C.; Hagenkamp-Korth, F.; Hartung, E. (2022): Investigating the time-dependent dose-response relationship of ammonia emissions reduction through the application of a urease inhibitor in pig fattening houses. Biosystems Engineering. (October): p. 45-61. Online: https://doi.org/10.1016/j.biosystemseng.2022.07.008 1.0
More publications of the program area