The Role of Artificial Intelligence in Agricultural Development - Nana Parulava; Helmut Caspary (Modern Scientific Method, 2025)
Environmental pollution represents one of the most significant global challenges of the 21st century. Agriculture, as a vitally important sector, not only experiences the negative impacts of environmental degradation but can also be one of its causes when traditional, intensive methods are used. Specifically, agriculture is responsible for approximately 18% of global greenhouse gas emissions, 70% of freshwater usage, and about 33% of the world’s agricultural land is degraded. Modern technologies, especially artificial intelligence, offer innovative solutions for developing more sustainable and environmentally friendly agriculture. Modern agriculture increasingly suffers from a shortage of qualified labor, which creates significant obstacles to the sector’s effective development. The outflow of the younger generation from rural areas and the physically demanding working conditions exacerbate this problem, making it necessary to implement automation of agricultural processes. Traditional methods based on manual labor are often inefficient, characterized by low productivity and high risk, which significantly hinders the full realization of agricultural potential. In this context, the integration of artificial intelligence into automated systems offers a revolutionary approach to overcoming existing challenges. Robots and autonomous systems equipped with artificial intelligence can perform routine and labor-intensive tasks (such as sowing, harvesting, weed control) with high precision and efficiency. Additionally, real-time data analysis and decision-making by artificial intelligence enable the optimization of automated processes and more rational use of resources, which ultimately contributes to increasing agricultural productivity and sustainability. For example, the automation of modern irrigation systems, which often use artificial intelligence algorithms to analyze soil moisture, weather forecasts, and plant needs, significantly reduces the need for human resources in managing irrigation processes. Automated systems ensure more efficient use of water resources, prevent excessive watering or drying out, which positively affects both yield and the environment. There are numerous studies confirming the effectiveness of using artificial intelligence to optimize irrigation systems. These studies show that artificial intelligence models can significantly improve water use efficiency and reduce irrigation costs. For instance, a study published in the journal "Agricultural Water Management" shows that using artificial intelligence models can reduce water usage by up to 30% and increase yields. This study used machine learning algorithms to analyze soil moisture, weather, and crop requirement data to optimize irrigation schedules. There are also studies where artificial intelligence is used to monitor irrigation systems, detecting water leakage and other problems, which in turn reduces costs and improper water usage. In another study conducted by the University of California, researchers developed an artificial intelligence system that uses sensors and satellite images to assess irrigation needs in real-time. Results showed that this system was able to reduce water usage by 25% while maintaining yield. These studies demonstrate that artificial intelligence models can significantly improve water use efficiency and reduce irrigation costs. The purpose of this article is to explore the potential of artificial intelligence in developing sustainable fruit farming, with a special emphasis on optimizing organic product production using automated irrigation systems and other intelligent agro-technologies. This article also considers sharing international experience in implementing artificial intelligence in agriculture. The article discusses Germany’s approach to AI implementation in agriculture, specifically in fruit farming.