Avances en la inteligencia artificial para incrementar el rendimiento en los cultivos

Abstract

This research analyzes the progress in the application of artificial intelligence (AI) to increase crop yields, addressing fundamental challenges such as resource optimization and early recognition of pests and diseases. The research was carried out through a systematic analysis of scientific publications disseminated in the last five years, focusing on machine learning models that consider climatic aspects, soil type and specific crop requirements to recommend the optimal amount of resources to be applied in each area of the field. Big data analysis and automation techniques were employed, highlighting the use of advanced tools such as sensors, drones and intelligent irrigation systems that allow continuous monitoring and more accurate decision making. The results show that the integration of AI platforms in precision agriculture has significantly improved crop effectiveness and productivity. The importance of this research lies in demonstrating how the adoption of AI technologies not only increases crop yields, but also contributes to the environmental sustainability and economic development of the agricultural sector. These findings underscore the need to foster the implementation of AI-based solutions to address present, current and future challenges in agriculture, ensuring efficient and sustainable food production.

Keywords: Artificial Intelligence, Big Data, Automation, Precision agriculture, Agricultural sustainability.