Precision Livestock Farming and Innovative Temperature Management: Integrated Data, Omics, and Technology Solutions for Mitigating Thermal Stress in Intensive Livestock Systems
Precision Livestock Farming and Innovative Temperature Management: Integrated Data, Omics, and Technology Solutions for Mitigating Thermal Stress in Intensive Livestock Systems
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About this Research Topic
Submission deadlines
Manuscript Extension Submission Deadline 1 August 2026
Modern livestock production faces the dual challenge of maximizing productivity while ensuring animal welfare and sustainability. Temperature stress, especially heat stress intensified by climate change, poses a significant threat to both animal well-being and farm efficiency. Traditional management methods often struggle to keep animals within their thermoneutral zone under increasingly variable and extreme climate conditions, leading to negative welfare, productivity, and environmental outcomes. In this context, innovative strategies that blend advanced management practices, precision genetic solutions, and technological interventions are urgently needed.
The goal of this Research Topic is to highlight and accelerate the adoption of advanced, data-driven approaches for mitigating temperature stress in livestock farming. We seek contributions that examine the trade-offs and synergies among housing strategies (such as stocking density), environmental controls, and cutting-edge technologies—including smart climate systems, PLF (Precision Livestock Farming) sensors, and automated monitoring devices. By focusing on integrating real-time physiological, behavioral, genetic, and environmental data, this Topic aims to demonstrate how precision solutions and adaptive management can safeguard animal welfare, improve farm resiliency, and align with sustainability objectives in the face of climate change. Ultimately, we aim to build a foundation for comprehensive, ethical, and sustainable livestock management.
This Special Issue welcomes submissions focused on the following areas:
- PLF Technologies for Heat Stress Management: Sensor-based monitoring systems, automated interventions (e.g., targeted cooling), and precision feeding strategies to combat heat stress.
- Data Analytics & Predictive Modeling: Using machine learning and AI to analyze complex datasets and predict heat stress risk, optimize management practices, and improve animal welfare outcomes.
- 'Omics' and Heat Tolerance: Exploring the genetic and physiological mechanisms of thermotolerance, utilizing genomics, proteomics, and other 'omics' approaches to identify resilient breeds and develop targeted interventions.
- Novel Biomarkers for Heat Stress Detection: Identifying and validating biomarkers that can provide early and accurate indicators of heat stress in livestock.
- Nutritional Interventions for Enhanced Resilience: Investigating the role of targeted nutrition in enhancing animal thermotolerance and mitigating the negative effects of heat stress.
- Ethical Considerations and Practical Implementation: Exploring the ethical implications of PLF technologies and addressing the challenges of implementing these systems in diverse farming contexts.
- dentification of, and description of emerging technologies to address thermal challenges
- AI models to develop precision livestock solutions for climate control in livestock farming
- Breeding for more heat tolerant animals (Genotype by Environment interaction )
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This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
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FAIR² DATA Direct Submission
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Methods
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This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.