ReviewJournal of animal science and technology2025
The vision of big data recirculation for smart livestock farming in South Korea.
Review in Journal of animal science and technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Generative artificial intelligence in animal genomics for smart agriculture: Applications, challenges, and future prospects.Veterinary and animal science · 2026Review
- From machine learning to digital twin integration for livestock production and research.Frontiers in veterinary science · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A smart livestock farm is a livestock farm where information and communication technology systems are used. Based on the measured data, these systems can make decisions regarding all processes, including stocking, breeding, shipping, and evaluation. The data generated from smart livestock farms have increased the complexity and diversity of phenotypes. Fused data that integrate environmental and phenotypic information from smart livestock farms with genetic data are valuable for detailed applications in breeding and specifications, as they help understand complex and organic phenotypes and environments. However, their effectiveness is limited by restrictions on data sharing and non-standardized formats. This limitation leads to other restrictions against researchers, such as restrictions on the range of projects, the supply of new technologies or farm species, and policy development or application restrictions. Therefore, promoting a recirculating environment to increase productivity, developing climate-adapted livestock, and implementing policies are necessary. We discuss the smart livestock farm from the perspective of '
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.