article · Agriculture
Agriculture 5.0 marks an evolution in precision crop management, integrating artificial intelligence, machine learning, robotics, and big data analytics to enhance productivity and support global food security. A wide range of emerging tools underpins this shift, including collaborative robots, digital twins, the Internet of Things, blockchain, cloud computing, 6G communication networks, and quantum technologies. These innovations alter how crop growth is monitored, perceived, and managed. Real-world applications of machine learning and deep learning demonstrate practical capabilities in crop monitoring, supported by smart sensors and autonomous systems. While these technologies offer substantial potential to establish sustainable and data-driven farming systems that reduce environmental damage, widespread adoption requires addressing key challenges. Realising the full scope of modern digital farming depends on multidisciplinary collaboration, regional adaptation of systems, and continuous advances in artificial intelligence and agricultural robotics.
Rising populations and environmental pressures require farming systems to produce higher yields with fewer resources. Integrating artificial intelligence, robotics, and advanced sensors enables precise crop management that minimises environmental harm while boosting output. Understanding these technologies helps researchers, technology providers, and agricultural managers identify the tools needed to modernise food production systems and strengthen global food security.
The technologies support precision crop management, automated monitoring, and digital decision-making for commercial growers, agribusinesses, and agritech developers. Maturity spans across a broad spectrum: machine learning, IoT sensors, and deep learning for crop monitoring are already applied and tested in real-world case studies, while advanced elements like 6G, digital twins, and quantum technologies remain at an early, frontier stage of exploration.
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Agriculture 5.0 (Ag5.0) represents a groundbreaking shift in agricultural practices, addressing the global food security challenge by integrating cutting-edge technologies such as artificial intelligence (AI), machine learning (ML), robotics, and big data analytics. To adopt the transition to Ag5.0, this paper comprehensively reviews the role of AI, machine learning (ML) and other emerging technologies to overcome current and future crop management challenges. Crop management has progressed significantly from early agricultural methods to the advanced capabilities of Ag5.0, marking a notable leap in precision agriculture. Emerging technologies such as collaborative robots, 6G, digital twins, the Internet of Things (IoT), blockchain, cloud computing, and quantum technologies are central to this evolution. The paper also highlights how machine learning and modern agricultural tools are improving the way we perceive, analyze, and manage crop growth. Additionally, it explores real-world case studies showcasing the application of machine learning and deep learning in crop monitoring. Innovations in smart sensors, AI-based robotics, and advanced communication systems are driving the next phase of agricultural digitalization and decision-making. The paper addresses the opportunities and challenges that come with adopting Ag5.0, emphasizing the transformative potential of these technologies in improving agricultural productivity and tackling global food security issues. Finally, as Agriculture 5.0 is the future of agriculture, we highlight future trends and research needs such as multidisciplinary approaches, regional adaptation, and advancements in AI and robotics. Ag5.0 represents a paradigm shift towards precision crop management, fostering sustainable, data-driven farming systems that optimize productivity while minimizing environmental impact.
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DOI: 10.3390/agriculture15060582
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