AI Algorithms in the Agrifood Industry: Application Potential in the Spanish Agrifood Context DOI Creative Commons
Javier Marcos Arévalo, Francisco Javier Flor Montalvo, Juan-Ignacio Latorre-Biel

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(4), P. 2096 - 2096

Published: Feb. 17, 2025

This research explores the prospective implementations of artificial intelligence (AI) algorithms within agrifood sector, focusing on Spanish context. AI methodologies, encompassing machine learning, deep and neural networks, are increasingly integrated into various sectors, including precision farming, crop yield forecasting, disease diagnosis, resource management. Utilizing a comprehensive bibliometric analysis scientific literature from 2020 to 2024, this outlines increasing incorporation in Spain identifies prevailing trends obstacles associated with it industry. The findings underscore extensive application remote sensing, water management, environmental sustainability. These areas particularly pertinent Spain’s diverse agricultural landscapes. Additionally, study conducts comparative between global outputs, highlighting its distinctive contributions unique challenges encountered sector. Despite considerable opportunities presented by these technologies, key limitations, need for enhanced digital infrastructure, improved data integration, increased accessibility smaller enterprises. paper also future pathways aimed at facilitating integration agriculture. It addresses cost-effective solutions, data-sharing frameworks, ethical societal implications inherent deployment.

Language: Английский

AI Algorithms in the Agrifood Industry: Application Potential in the Spanish Agrifood Context DOI Creative Commons
Javier Marcos Arévalo, Francisco Javier Flor Montalvo, Juan-Ignacio Latorre-Biel

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(4), P. 2096 - 2096

Published: Feb. 17, 2025

This research explores the prospective implementations of artificial intelligence (AI) algorithms within agrifood sector, focusing on Spanish context. AI methodologies, encompassing machine learning, deep and neural networks, are increasingly integrated into various sectors, including precision farming, crop yield forecasting, disease diagnosis, resource management. Utilizing a comprehensive bibliometric analysis scientific literature from 2020 to 2024, this outlines increasing incorporation in Spain identifies prevailing trends obstacles associated with it industry. The findings underscore extensive application remote sensing, water management, environmental sustainability. These areas particularly pertinent Spain’s diverse agricultural landscapes. Additionally, study conducts comparative between global outputs, highlighting its distinctive contributions unique challenges encountered sector. Despite considerable opportunities presented by these technologies, key limitations, need for enhanced digital infrastructure, improved data integration, increased accessibility smaller enterprises. paper also future pathways aimed at facilitating integration agriculture. It addresses cost-effective solutions, data-sharing frameworks, ethical societal implications inherent deployment.

Language: Английский

Citations

0