Zibeline International invites researchers, academicians, and practitioners to submit original manuscripts for consideration in this scholarly journal. The journal welcomes research papers, review articles, reports, and other relevant manuscript types covering interdisciplinary areas related to data-driven and intelligent agricultural systems.
Aims and Scope
Big Data in Agriculture (BDA) focuses on the application of big data analytics, artificial intelligence, machine learning, and digital technologies in agricultural systems. The journal covers topics including agricultural data mining, smart and precision agriculture, IoT and sensor-based farming, remote sensing and GIS applications, decision support systems, climate and yield prediction models, farm management analytics, sustainable data-driven agriculture, and interdisciplinary innovations that integrate agriculture with data science and information technology.
BDA is supported by an eminent group of editors and reviewers comprising distinguished scholars with extensive academic and research publications. The Editorial Board oversees a stringent, multi-level peer-review process, including manuscript evaluation, reviewer selection, assessment of reviewers’ comments, and final editorial decisions to ensure high scholarly standards.