AIMS & SCOPE
Big Data in Agriculture publishes high-quality research, reviews, and case studies that advance the understanding and application of data-intensive methods in agricultural sciences. The journal aims to provide an international forum for disseminating cutting-edge developments that leverage big data, artificial intelligence, and advanced analytics to address challenges in food production, sustainability, and global food security.
Scope of the Journal
  • Precision agriculture and smart farming technologies.
  • Applications of machine learning, AI, and predictive analytics in crop, soil, and livestock systems.
  • Remote sensing, GIS, and sensor networks for agricultural monitoring.
  • Big data approaches to climate change adaptation, risk assessment, and resource optimization.
  • Integration of genomic, phenomic, and bioinformatics data for crop and animal improvement.
  • Data-driven supply chain management, market analysis, and food security forecasting.
  • Ethical, policy, and socio-economic implications of big data in agriculture.
By fostering interdisciplinary exchange among agronomists, data scientists, environmental researchers, and policymakers, the journal supports the development of innovative, data-driven solutions for resilient and sustainable agricultural systems.