ArticleScientific reports2021
Combining expert knowledge and machine-learning to classify herd types in livestock systems.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 47 citations in OpenAlex.
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- Evolution of the Swiss pork production systems and logistics: the impact on infectious disease resilience.Scientific reports · 2025Article
- Estimating sectoral livestock biomass and stock value using data from national diseases eradication programs: a case study based on the Irish cattle herd from 2011 to 2021.Frontiers in veterinary science · 2025Article
- Improved cattle farm classification: leveraging machine learning and linked national datasets.Frontiers in veterinary science · 2025Article
- An epidemiological investigation into the reasons for high bovine tuberculosis incidence in cattle herds of the Burren, Ireland, prior to 2020.Irish veterinary journal · 2024Article
- Use of conjoint analysis to weight biosecurity practices on pasture-based dairy farms to develop a novel audit tool-BioscoreDairy.Frontiers in veterinary science · 2024Article
- A Literature Review of Modeling Approaches Applied to Data Collected in Automatic Milking Systems.Animals : an open access journal from MDPI · 2023Review
- A Cloud Enabled Crop Recommendation Platform for Machine Learning-Driven Precision Farming.Sensors (Basel, Switzerland) · 2022Article
- Modelling transmission of Mycobacterium avium subspecies paratuberculosis between Irish dairy cattle herds.Veterinary research · 2022Article
- The Irish cattle population structured by enterprise type: overview, trade & trends.Irish veterinary journal · 2022Article
- Perspectives of digital agriculture in diverse types of livestock supply chain systems. Making sense of uses and benefits.Frontiers in veterinary science · 2022Article
- Prediction of Maize Phenotypic Traits With Genomic and Environmental Predictors Using Gradient Boosting Frameworks.Frontiers in plant science · 2021Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A detailed understanding of herd types is needed for animal disease control and surveillance activities, to inform epidemiological study design and interpretation, and to guide effective policy decision-making. In this paper, we present a new approach to classify herd types in livestock systems by combining expert knowledge and a machine-learning algorithm called self-organising-maps (SOMs). This approach is applied to the cattle sector in Ireland, where a detailed understanding of herd types can assist with on-going discussions on control and surveillance for endemic cattle diseases. To our knowledge, this is the first time that the SOM algorithm has been used to differentiate livestock systems. In compliance with European Union (EU) requirements, relevant data in the Irish livestock register includes the birth, movements and disposal of each individual bovine, and also the sex and breed of each bovine and its dam. In total, 17 herd types were identified in Ireland using 9 variables. We provide a data-driven classification tree using decisions derived from the Irish livestock registration data. Because of the visual capabilities of the SOM algorithm, the interpretation of results is relatively straightforward and we believe our approach, with adaptation, can be used to classify herd type in any other livestock system.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.