外文摘要：This article delves into the intricate details of a robust machine learning analysis that was conducted on a plethora of environmental data, including precipitation, temperature, soil moisture, and vegetation index data, in three distinct regions of Turkey, namely the Aegean, Southeastern Anatolia, and the Mediterranean. The core objective of this scientific inquiry is to shed light on the quintessential determinants that wield a profound influence on agricultural productivity, with an explicit focus on the soil's moisture, temperature fluctuations, and precipitation patterns. It is of paramount importance to fathom the intricacies and multifarious dimensions of these pivotal determinants to enrich our understanding of the entangled dynamics between the ecosystem and crop cultivation. The intricate nature of soil's moisture is a multifaceted interplay, encompassing water availability and the delicate interconnectedness between precipitation, soil structure, and vegetative growth, which can instigate a series of biological and chemical reactions. Furthermore, the study underscores the significance of monitoring the normalized difference vegetation index (NDVI) as a critical indicator of vegetation growth and yield. The outcomes of this study are truly fascinating and highlight the enormous potential of AI-powered tools, which incorporate advanced machine learning and deep learning models, in elevating and optimizing crop management practices, thereby leading to heightened crop productivity and profitability while promoting sustainability. The revolutionary discoveries made in this study underscore the tremendous potential of artificial intelligence (AI) technologies to propel and elevate the agricultural forecasting and management processes, resulting in a more sustainable, productive, and efficient agricultural industry that bestows substantial environmental, social, and economic advantages.
外文关键词：precision agriculture;machine learning;Aegean;Southeastern Anatolia;Mediterranean;CPC leaky bucket model
作者：Altan, M Uzunoz;Nabatov, E
作者单位：Yildiz Tech Univ;Newcastle Univ
期刊名称：INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
期刊影响因子：0.0
出版年份：2024
出版刊次：21（10）
原文传递申请：江苏省科技资源（工程技术文献）统筹服务平台