Smart Agriculture, also known as Digital Agriculture, has emerged as an
essential paradigm in today’s agricultural landscape. The rapid development of this
field is fueled by the growth and application of Agricultural Informatics, which
significantly enhances various agricultural practices. These practices span from crop
and seed cultivation to plant and vegetable farming, livestock management, and postharvest activities.
Advanced Agricultural Information Systems (AIsS) deploy effective methodologies
and cutting-edge technologies to optimize cultivation processes, aiming to improve
productivity and efficiency. These Agroinformatics technologies are specifically
designed to support more commercially intensive agricultural operations and streamline
the management of large-scale systems. Agro Information Systems incorporate diverse
components of Information Technology (IT), such as databases, networks, web
technologies, software solutions, and multimedia systems, all of which contribute to a
more connected and data-driven agricultural environment.
With the rapid evolution of IT, new technologies such as cloud computing, data
analytics, big data, the Internet of Things (IoT), and Blockchain are becoming
increasingly vital in modern agriculture. Among these, Blockchain technology is
revolutionizing agriculture by enabling faster, more secure, and highly efficient
systems for agricultural development. Blockchain applications in agriculture ensure
transparency, traceability, and security in various processes, from farm-to-fork supply
chains to smart contract-based transactions.
In this context, the integration of Blockchain and Machine Learning (ML) technologies
plays a pivotal role in shaping Agriculture 4.0. By combining Blockchain's secure and
decentralized nature with ML’s predictive analytics and data-driven decision-making capabilities, these technologies offer unprecedented opportunities for improving
farming practices. This paper explores the current applications of Blockchain and
Machine Learning in agriculture, focusing on their potential and prospects in
transforming the industry. Furthermore, it delves into how blockchain and Machine
learning-based agrosystems can foster sustainable agricultural practices, supporting the
future of farming by enhancing productivity, reducing waste, and promoting
environmental stewardship.
Keywords: Agro ICT, Agriculture 4.0, Agro informatics, Digital agriculture, ML, Machine learning applications, Sustainable development.
