ReviewAnimals : an open access journal from MDPI2024
Technological Tools and Artificial Intelligence in Estrus Detection of Sows-A Comprehensive Review.
Review in Animals : an open access journal from MDPI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 23 citations in OpenAlex.
- Precision phenotyping of reproductive events in dairy cattle under heat stress: epidemiological validity and implications for genetic improvement in tropical systems.Tropical animal health and production · 2026Review
- Delayed ovulation in cattle: Physiological mechanisms, diagnostic approaches, and reproductive management strategies.Veterinary world · 2026Article
- Toward Vision-Based Estrus Monitoring in Chongming White Goats: Behavioral Manifestations and Serum Hormone Correlations.Animals : an open access journal from MDPI · 2026Article
- A Conformer-Based Time-Frequency Decoupling Network for Pig Vocalization Behavior Classification.Animals : an open access journal from MDPI · 2026Article
- Characterising responses in group-housed pigs to Salmonella typhimurium infection through integrated computer vision-based behavioural monitoring and statistical analyses.Porcine health management · 2026Article
- Edge-AI Enabled Acoustic Monitoring and Spatial Localisation for Sow Oestrus Detection.Animals : an open access journal from MDPI · 2026Article
- Reproductive performance of a semi-automated insemination system technology in sows.Animal reproduction · 2026Article
- Sustainability and future outlook of the Philippine pig industry.Journal of advanced veterinary and animal research · 2025Article
- Association of relative expression of HSD11B-1 and HSD11B-2 with pregnancy status in sheep.BMC genomics · 2025Article
- Spatiotemporal Modeling and Intelligent Recognition of Sow Estrus Behavior for Precision Livestock Farming.Animals : an open access journal from MDPI · 2025Article
- Revolutionizing pig farming: Japan's technological innovations and environmental strategies for sustainability.Journal of advanced veterinary and animal research · 2025Article
- Integrated Convolution and Attention Enhancement-You Only Look Once: A Lightweight Model for False Estrus and Estrus Detection in Sows Using Small-Target Vulva Detection.Animals : an open access journal from MDPI · 2025Article
- A Review of the Monitoring Techniques Used to Detect Oestrus in Sows.Animals : an open access journal from MDPI · 2025Review
- Transformation toward precision large-scale operations for sustainable farming: A review based on China's pig industry.Journal of advanced veterinary and animal research · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In animal farming, timely estrus detection and prediction of the best moment for insemination is crucial. Traditional sow estrus detection depends on the expertise of a farm attendant which can be inconsistent, time-consuming, and labor-intensive. Attempts and trials in developing and implementing technological tools to detect estrus have been explored by researchers. The objective of this review is to assess the automatic methods of estrus recognition in operation for sows and point out their strong and weak points to assist in developing new and improved detection systems. Real-time methods using body and vulvar temperature, posture recognition, and activity measurements show higher precision. Incorporating artificial intelligence with multiple estrus-related parameters is expected to enhance accuracy. Further development of new systems relies mostly upon the improved algorithm and accurate data provided. Future systems should be designed to minimize the misclassification rate, so better detection is achieved.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.