Critical Insights in Agriculture

Emerging Technologies for Modelling, Monitoring and Mitigating Agricultural GHG Emissions

Focus of the Special Issue

• This issue explores the innovative application of emerging technologies—such as AI-driven models, sensor networks, and precision agriculture tools—to quantify and reduce greenhouse gas (GHG) emissions from agricultural systems.
• The primary objective is to highlight novel methods and integrated approaches to better monitor, model, and mitigate emissions of methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2).
• Research is sought across diverse production environments, including cropping, livestock, and integrated agricultural systems.
• The collection aims to bridge the gap between high-tech data analytics and scalable, just mitigation strategies by bringing together voices from academia, industry, and policy.

Key Themes and Topics

• AI and Machine Learning for Predictive Modelling: Development and validation of predictive models for CH4, N2O, and CO2 using big data approaches.
• Sensor-based Monitoring: Real-time or near-real-time monitoring technologies and deployment strategies for on-farm emissions.
• Digital Twins and Systems Integration: Use of simulation environments to evaluate technology interventions, policy shifts, or behavioral responses.
• Precision Agriculture: Case studies on site-specific management, radioisotopes, robotics, and decision-support tools in mitigating emissions.
• Data Infrastructures: Frameworks for harmonizing environmental and agronomic datasets for large-scale modeling or policy application.
• Policy and Governance: Analysis of regulatory frameworks, market incentives, and cross-sectoral collaboration to accelerate technological uptake.
• Socio-technical and Ethical Dimensions: Critical perspectives on equity, accessibility, and data governance within tech-driven transitions.

Contribution Types

• The issue welcomes interdisciplinary contributions, including:
  • Empirical research and modeling studies.
  • Technical reviews.
  • Critical policy analyses.
• Submissions are encouraged from diverse fields such as environmental science, ag-tech, systems engineering, AI, climate science, and agricultural policy.
• The editorial committee particularly encourages research reflecting interdisciplinary collaboration and diverse geographical contexts.