ReviewAnimals : an open access journal from MDPI2020
Transforming the Adaptation Physiology of Farm Animals through Sensors.
Review in Animals : an open access journal from MDPI, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 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
30 citing papers in PubMed.
- A Multi-Object Tracking Method for Dairy Cows in Intensive Farming Scenarios.Animals : an open access journal from MDPI · 2026Article
- 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
- Big data and artificial intelligence in animal nutrition: a new era of precision feeding.Tropical animal health and production · 2026Review
- A Supervised Deep Learning Model Was Developed to Classify Nelore Cattle (Animals : an open access journal from MDPI · 2026Article
- From Sensors to Sustainability: Integrating Welfare, Management, and Climate Resilience in Small Ruminant Farm Systems.Animals : an open access journal from MDPI · 2025Review
- Application of Machine Learning Models for the Early Detection of Metritis in Dairy Cows Based on Physiological, Behavioural and Milk Quality Indicators.Animals : an open access journal from MDPI · 2025Article
- AdapTree: Data-Driven Approach to Assessing Plant Stress Through the AI-Sensor Synergy.Sensors (Basel, Switzerland) · 2025Article
- Instance segmentation and automated pig posture recognition for smart health management.Journal of animal science and technology · 2025Article
- Integrating multi-modal data fusion approaches for analysis of dairy cattle vocalizations.Frontiers in veterinary science · 2025Article
- RGB-based machine vision for enhanced pig disease symptoms monitoring and health management: a review.Journal of animal science and technology · 2025Review
- Applications of Artificial Intelligence for Heat Stress Management in Ruminant Livestock.Sensors (Basel, Switzerland) · 2024Review
- Computer-Vision-Based Sensing Technologies for Livestock Body Dimension Measurement: A Survey.Sensors (Basel, Switzerland) · 2024Review
- Human-computer interactions with farm animals-enhancing welfare through precision livestock farming and artificial intelligence.Frontiers in veterinary science · 2024Article
- Estimation of gestating sows' welfare status based on machine learning methods and behavioral data.Scientific reports · 2023Article
- Artificial Intelligence and Sensor Technologies in Dairy Livestock Export: Charting a Digital Transformation.Sensors (Basel, Switzerland) · 2023Review
- Passive radio frequency identification and video tracking for the determination of location and movement of broilers.Poultry science · 2023Article
- Innovations in Cattle Farming: Application of Innovative Technologies and Sensors in the Diagnosis of Diseases.Animals : an open access journal from MDPI · 2023Review
- The autumn activity patterns and time budgets of Forest musk deer (Veterinary research forum : an international quarterly journal · 2023Article
- Measuring Comfort Behaviours in Laying Hens Using Deep-Learning Tools.Animals : an open access journal from MDPI · 2022Article
- Point-of-Care Diagnostics for Farm Animal Diseases: From Biosensors to Integrated Lab-on-Chip Devices.Biosensors · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite recent scientific advancements, there is a gap in the use of technology to measure signals, behaviors, and processes of adaptation physiology of farm animals. Sensors present exciting opportunities for sustained, real-time, non-intrusive measurement of farm animal behavioral, mental, and physiological parameters with the integration of nanotechnology and instrumentation. This paper critically reviews the sensing technology and sensor data-based models used to explore biological systems such as animal behavior, energy metabolism, epidemiology, immunity, health, and animal reproduction. The use of sensor technology to assess physiological parameters can provide tremendous benefits and tools to overcome and minimize production losses while making positive contributions to animal welfare. Of course, sensor technology is not free from challenges; these devices are at times highly sensitive and prone to damage from dirt, dust, sunlight, color, fur, feathers, and environmental forces. Rural farmers unfamiliar with the technologies must be convinced and taught to use sensor-based technologies in farming and livestock management. While there is no doubt that demand will grow for non-invasive sensor-based technologies that require minimum contact with animals and can provide remote access to data, their true success lies in the acceptance of these technologies by the livestock industry.
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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.