Advances in Emerging Digital Technologies for Sustainable Agriculture: Applications and Future Perspectives

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Abstract

Sustainable agriculture is under increasing pressure due to climate variability, resource scarcity, and the need to reduce environmental impacts without compromising productivity. This study aimed to systematically analyze recent advances in emerging digital technologies applied to sustainable agriculture. The PRISMA protocol was applied to Scopus and Web of Science, considering publications from 2020 to 2025, which were analyzed using RStudio 4.5.10 and VOSviewer 1.6.20, resulting in 101 relevant articles. The findings indicate that multisensor monitoring and precision agriculture enable high-resolution characterization of soil–crop variability, supporting site-specific irrigation, fertilization, and phytosanitary management. Likewise, machine learning-based predictive models improve decision-making by forecasting yield, water stress, nutrient deficiencies, and disease outbreaks. In addition, edge computing and autonomous systems enhance operational efficiency and reduce labor dependency. Blockchain strengthens transparency and sustainability certification through secure traceability, while digital twins optimize management strategies through prior simulation. Despite these advances, limitations remain, including platform fragmentation, limited interoperability, uneven adoption among smallholders, and challenges in model generalization across heterogeneous agroecosystems. Therefore, further progress toward integrated and interoperable digital ecosystems is recommended

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