Blockchain and Big Data Analytics in Agriculture: A Review of Digital Innovations

Abstract

In order to solve difficult issues in food and agriculture, information systems and big data analytics (BDA) are becoming more and more important. A lot of big data is used in retail and food distribution, but not enough in production, decision-making, or durability. In order to combine various data types, including sensor data, satellite images, and weather forecasts, BDA uses cutting-edge methods like machine learning and artificial intelligence. It then seeks out actionable data that can be applied to enhance agriculture, food processing, and preservation. In order to fully realize the potential of big data in transforming the future of food, the review suggested that future research should focus on interdisciplinary collaboration, addressing ethical considerations, and developing robust data governance frameworks – the ethical and regulatory frameworks need to keep up with technological advancements. This systematic review outlines recent advancements and emphasizes trends, challenges, and aspects that require further investigation regarding the use of BDA in the agri-food industry. It emphasizes how BDA can enhance quality assurance, precision farming, supply chain efficiency, and sustainable food systems. The primary challenges involve the sharing of data across systems, infrastructure problems, privacy issues, and differences in the pace at which stakeholders embrace technologies.