Artificial Intelligence in Colombian Agriculture. Colombian versus Global Perspectives
DOI:
https://doi.org/10.24054/cyta.v10i2.4254Keywords:
Artificial intelligence in agriculture, smart farming, Agricultural sustainability, Digital transformationAbstract
Artificial intelligence is no longer a futuristic aspiration; it is a tangible tool transforming agricultural production. Demographic growth and increasing food demand, together with environmental sustainability and climate change challenges, force the sector to evolve toward more efficient and resilient systems. International studies report that machine learning and other AI techniques improve agricultural productivity, reduce costs and enable the management of large volumes of data, although they face challenges related to data quality and availability, technological infrastructure and farmers skills. This review summarises major trends, applications, benefits and challenges of AI in agriculture worldwide. We analyse the adoption of technologies, from machine learning algorithms and deep neural networks to Internet of Things (IoT) tools and robotics, in areas such as early pest and disease detection, water and nutrient management, agricultural mapping, livestock farming and aquaculture. The worlds scientific production is contrasted with that from Colombia, revealing notable progress but also limited national output. Data on the selected articles (year, country, technology, sector and results) are synthesised, and charts illustrate the temporal, geographical and sectoral distribution of research. The findings are discussed in light of Colombias agricultural development agenda, and future research directions are proposed.
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