A Comprehensive Strategy for Tomato Cultivation Utilizing Precision Agriculture Techniques

Abstract

Tomato cultivation in the Mediterranean region is challenged by numerous factors, including water scarcity, soil degradation, pest and disease pressures, and climate change. Socioeconomic factors, including farmers' aging, demographic issues, and limited access to advanced agricultural technologies, exacerbate these challenges. This paper explores Precision Agriculture (PA) technologies to improve the sustainability and productivity in tomato farming. PA techniques, such as remote and proximal sensing, including hyperspectral imaging, provide real-time monitoring on crop health status, soil conditions, and moisture content levels, enabling farmers to optimize critical management practices regarding irrigation, fertilization, and pest control. Integrating artificial intelligence (AI) and machine learning (ML) with hyperspectral imaging enhances early crop disease detection, reduces the extensive application of pesticide use. Furthermore, advancements in automated harvesting technologies, including robotic systems equipped with sophisticated visual recognition and end-effector mechanisms, offer promising solutions to labor-intensive harvesting processes. This paper presents a comprehensive review of these technologies, highlighting their applications, contribution, and potential impacts on improving the efficiency and sustainability of tomato cultivation in the Mediterranean region. Through the adoption of these innovative approaches, higher yield, better resource management practices, and reduced production costs are expected.