Precision Agriculture Technologies for Irrigation and Agricultural Mechanization: Adaptability to the Cuban Context
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Abstract
Agriculture faces the challenge of increasing productivity to ensure global food security while adapting to climate change and reducing its environmental impact. This review analyzes the state of the art in smart irrigation and precision mechanization technologies and assesses their potential adaptation to the Cuban context. The most recent evidence confirms that smart irrigation systems based on IoT and predictive algorithms achieve water savings of 30-50%. Precision mechanization, including variable rate technology (VRT) and autonomous agricultural robotics, reduces fertilizer use by 15-30% and herbicide use by up to 90%. Early pest detection systems based on computer vision and deep learning achieve accuracies exceeding 95%. Farm management information systems (FMIS) act as the integrating core of these systems. Adaptation to the Cuban context is possible, but faces challenges such as high costs, connectivity limitations, and an obsolete machinery fleet. However, the existing skilled human capital and political will offer significant opportunities. A three-phase, phased implementation strategy is proposed, prioritizing low-cost technologies, shared machinery models, the use of mobile phones as navigation assistants, and the development of local capabilities, beginning with systems that operate both offline and online. The integration of these technologies can be a strategic pathway to increase food sovereignty and the resilience of Cuban agriculture in the face of climate change, resource scarcity, and the need for greater productive efficiency.
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