Data and Modelling

1. Mission

The overall research group mission is to deliver high-impact research and research-based teaching that advance sustainable animal housing, health and management systems. We aim to develop and maintain a strong research group for data and modelling, integrating large-scale databases, computer vision and sensor technology, and artificial intelligence to support data-based decision-making in animal production.  As part of the Vetstat cluster, we contribute to the veterinary contingency and ensure that our research is communicated internationally and in Denmark to farmers, veterinarians, and stakeholders.

2. Vision

Our vision is to be an internationally recognized research group in data and modeling focused on livestock systems, enabling sustainable, welfare-oriented, and prudent-antimicrobial animal production. By transforming complex data into actionable knowledge, we aim to improve animal health and welfare, enhance production efficiency and contribute to the overall quality of life for both animals and humans

3. Focus Areas / Priorities / Objectives

To strengthen our scientific impact and societal relevance, our activities are organized into four core pillars:

Current focus areas:

    i) Data Systems, Surveillance, and Veterinary Contingency

• VetStat-based research on antimicrobial usage (AMU)
• Risk assessment of antimicrobial resistance (AMR)
• Identification of risk factors and development of alternatives to AMU
• Contribution to national veterinary contingency systems
  
  ii) Precision Livestock Farming and Artificial Intelligence

• Sensor-based monitoring (video, audio, and environmental data)
• Machine learning for early detection of health and welfare changes
• Behavior modelling and automated classification systems
• Development of predictive and decision-support tools for farmers
  
  iii) Animal Systems, Housing, and Environment

• Design and optimization of animal housing systems
• Climate and environmental conditions in and around livestock production
• Integration of animal health, welfare, and productivity
  
  iv) Sustainable and Regenerative Livestock Systems

• Development of sustainability indicators and data-driven assessments
• Use of public and farm-level data to evaluate system performance
• Advancing regenerative livestock production approaches
• Supporting the transition towards sustainable dairy and livestock systems

Across all pillars, we apply advanced statistical modelling, machine learning, and data integration methods to transform complex datasets into actionable insights. 

4. Future priorities:

Strengthen our leadership in VetStat-based AMU and AMR research, reinforcing our role in veterinary contingency and policy support

Expand the use of real-time sensor data and adaptive models to enable early detection and prediction of changes in animal health, welfare, and productivity

Develop integrated decision-support systems that assist farmers in making sustainable and evidence-based management decisions

Further position the group at the forefront of AI-driven livestock research and digital agriculture

Leverage public and large-scale datasets to advance sustainability assessments and explore new models for dairy and livestock production systems

4. Research Strengths / Comparative advantage

The Data & Modelling group combines strong interdisciplinary expertise in animal nutrition, antimicrobial usage and resistance, health monitoring and surveillance, disease modelling, animal housing, statistical methods and machine-learning/AI-based approaches using these expertises as the fundamental tools behind the work with big data. Quantitative Methods are applied in Herd Management, Precision Livestock Farming, Machine-learning methods for monitoring and classifying animal behavior, health and welfare.  The group possesses distinctive scientific expertise in areas like Climate and environmental conditions in and around animal housing, Animal and Sustainability, Development of Regenerative Livestock Systems, and Vetstat-based research.   

Our key comparative advantages: 

• Unique access to large-scale, longitudinal datasets such as Vetstat and Commercial Sensor Data (images, rumination, activities);
• Strong integration of data science, animal science, and applied livestock systems
• Direct engagement with policy, veterinary contingency and industry stakeholders
• Ability to translate complex data into operational tools and actionable knowledge 

This combination enables us to deliver both high scientific impact and tangible contributions to sustainable livestock production.

• Vetstat based research on antimicrobial usage (AMU), risk assessment of antimicrobial resistance, risk factors for high AMU, alternatives to AMU (https://dkvet.dk/forskning/udvalgte-projekter/vetstat-klyngen/)
• Veterinary contingency tasks
• Quantitative Methods in Herd Management, Precision Livestock Farming, Machine-learning methods for image recognition
• Modelling animal behavior
• Climate and environmental conditions in and around animal housing
• Design of animal housing
• Animal health and welfare
• Animal and Sustainability
• Development of Regenerative Livestock Systems

1. Crone CM, Rasmussen AP, Larsen C, Williams AR, Eskildsen MH, Christensen EMH, de Knegt LV, Amdi C. and Madsen JG, 2025. Effect of Benzoic Acid supplementation on growth performance and early development of gastrointestinal tract function and immune system in artificially reared suckling piglets. Livestock Science, Volume 294. Doi: https://doi.org/10.1016/j.livsci.2025.105655
2. Rydal, M.P., Lyderik, K.K., Andersen, A.B. et al., 2025. Outbreaks of post-weaning diarrhea caused by ETEC F4 are strongly associated with CHCF1 genotype in Danish pigs. Sci Rep 15, 41748 (2025). https://doi.org/10.1038/s41598-025-26829-w
3. Neves, A. L. A., Pfeiffer, M. A., Dhakal, R., Woudstra, S., Krömker, V., & Vieira, R. A. M., 2025. Effects of Fat Supplementation on Growth Performance and Blood Biochemical Parameters in Dairy Calves During Pre- and Post-Weaning Phases. Dairy 2026, Vol. 7, 7(1), 1. https://doi.org/10.3390/DAIRY7010001
4. Jensen, DB, 2025. Predicting footpad lesion scores of Dutch broiler flocks using routinely collected data. Smart Agricultural Technology.
5. Jensen, DB, 2025. Comparison of strategies for automatic video-based detection of piling behavior in laying hens. Smart Agricultural Technology:
6. Stivanin, C.B.S, Vizzotto E.F, Bettencourt AF, Guadagnin AR, Aires JF, Machado FS, Campos MM, Tomich TR, Pereira LGR, Fischer V. Water intake and drinking behaviour in Holstein, Gyr and Girolando-F1 cows presenting high body condition score during the transition period. Arch Anim Nutr. 2025 Jun-Dec;79(3-6):248-266. doi: https://doi.org/10.1080/1745039X.2025.2586092.
7. da Silva, D. V., Benhami, V. M. L., Moreira, E. D. A., De Paula, V. R., Tomich, T. R., Silva, D. A. L., & Pereira, L. G. R. (2025). Biologically based net energy allocation procedures can improve carbon footprint analysis in milk production systems. The International Journal of Life Cycle Assessment, 30(2), 668–681. https://doi.org/10.1007/s11367-025-02435-w
8. Jensen, DB, 2025. Evaluation and comparison of pre-trained convolutional neural networks for detecting Equine pain face. Equine Veterinary Education, under review.

Conference oral presentations

1. Pereira, L.G.R. "What Is the Right Way to Produce? Leveraging Data Science to Guide Us". CPH Cattle seminar. 14th of April 2026, Copenhagen, Denmark.
2. Pereira, L.G.R, Knegt, L.V. Pfeiffer MA, Woudstra S, , Associations between bulk tank somatic cell count and multidimensional on-farm animal welfare scores in Brazilian dairy herds.) 2026 ADSA Annual Meeting, Milwaukee, WI. USA.
3. Lyderik KK, de Knegt LV, Kruse AB, Alban L. Qualitative Insights on Antimicrobial Prescription Practices in Danish Pig Production: Understanding Danish pig veterinarians’ perceptions through interviews - A Pilot study. 15th SafePork Conference, October 6-8, 2025. Rennes, France.
4. Lyderik KK, de Knegt LV, Kruse AB., 2025. Ongoing projects about analysis of antimicrobial use in pigs. Seminar on research in antimicrobial use based on VetStat and other data sources. November 24, 2025. Copenhagen, Denmark
5. Lyderik, KK. 2025. Effects of increased number of daily meals on ileal digestibility of calcium and phosphorus in sows. ISEP
6. Jensen, DB, 2025. AI for Animal Science: Comparative Analysis of Pre-Trained CNNs for Classifying Equine Pain Faces
7. Kruse, AB, Dahl, J., de Knegt LV, Alban, L. Consequences of phasing out medical zinc oxide on antimicrobial use, vaccination and productivity in Danish weaner herds. 15th SafePork Conference, October 6-8, 2025. Rennes, France
8. Pereira, LG.R. Keynote Speaker at the 2nd SIMBOVCERRADO – International Symposium on Sustainability of Dairy and Beef Cattle Farming in the Cerrado, 2025. (Symposium). Sustainable production in dairy farming in the Cerrado Biome: Soil and climate conditions, biodiversity, and levels of intensification. Campo Grande – Brazil.
9. Pereira, LG.R. Keynote Speaker at the 3rd RTC Technical Journey, 2025. (Conference)
   Milk of the future for consumers of the future. Gramado, Brazil
10. Pereira, LG.R. Keynote Speaker at the IV SINPEL – National Uflaleite Symposium on Dairy Cattle Farming, 2025. (Symposium). The regenerative awakening in milk production: balance, integration, and biodiversity for a sustainable future. Lavras, Brazil
11. Pereira, LG.R. Keynote Speaker at the Low-Carbon Milk Production Seminar, 2025. (Seminar), Low-Carbon Milk and the Future We Want. Brasília, Brazil.
12. Pereira, LG.R. Keynote Speaker at the 20th State Milk Forum, 2025. (Conference)
    Milk carbon footprint: current knowledge and opportunities. Nao me toque, Brazil.
13. Pereira, LGR. Speaker at Schothorst Feed Research seminar. Beyond Milk: Pathways to Regenerative and Integrated Dairy Production. Netherlands, 2025.

Conference posters

1. Pereira, L.G.R. Energy balance, methane production, and blood metabolites of calves with anaplasmosis. 2026 ADSA Annual Meeting, Milwaukee, WI. USA.
2. Lyderik KK, Kruse AB, Alban L, de Knegt LV., 2025. Validating and monitoring antimicrobial use in Danish pig production using VetStat data and time-series models. SVEPM Conference 2025, March 26-28. Berlin, Germany.
3. Pfeiffer MA, Woudstra S, Teixeira VA, de Knegt LV, de Souza GM, Tomich TR, Campos MM, Pereira LGR. Evaluating Sensor-Derived Rumination and Activity Data for Monitoring Pre-Weaning Dairy Calf: A Correlation Study with Traditional Metrics. The 76th EAAP Annual Meeting, August 25-29, 2025. Innsbruck, Austria.
4. de Knegt LV, Kruse AB, Alban L., 2025. Preliminary assessment of the veterinary and human risk of antimicrobial resistance due to the increased use of neomycin in Danish pigs. The15th SafePork Conference, October 6-8, 2025. Rennes, France.
5. Lyderik, KK, 2025. The number of daily meals for sows has only marginal influence on plasma metabolites and the gut microbiome. ISEP
6. Jensen, DB, 2025. Automatic monitoring of piling behavior in laying hens using convolutional neural networks. PhD sommerskole i Lleida
7. Abstract submitted to SVEPM 2026: Jensen DB, Veldhuis AV, Santman-Berends I, Vrieze E, Bastiaansen T, de Knegt LV. Early detection of calf disease from automated milk feeder data using dynamic linear models and random forests.
8. Correia Cairo, F., Pereira, L. G. R., Panetto, J. C. C., Machado, M. A., Tomich, T. R., Campos, M. M., & Barbosa da Silva, M. V. G. (2025, September). Enteric methane dilution effects achieved with the genetic enhancement of Girolando cattle raised in tropical weather. Poster presented at the 76th Annual Meeting of the European Federation of Animal Science (EAAP), Innsbruck, Austria.
9. Correia Cairo, F., Campos, M. M., Coelho, S. G., Tomich, T. R., Samarini Machado, F., Sacramento, J. P., & Pereira, L. G. R. (2025, September). Characterizing residual feed intake in Girolando cattle across growth and lactation phases. Poster presented at the 76th Annual Meeting of the European Federation of Animal Science (EAAP), Innsbruck, Austria.