抄録
The soil nitrogen cycle is a core biogeochemical process in farmland ecosystems, with microorganisms playing a crucial role in nitrogen transformation. With the rapid advancement of high-throughput sequencing technologies and big data analysis methods, researchers can now more accurately analyze the structure and dynamic changes of soil microbial communities, thereby exploring their functional mechanisms in nitrogen transformation. This study outlines the primary processes of nitrogen cycling in agricultural soils, with a focus on the roles of various microbial communities in nitrogen mineralization, nitrification, denitrification, and nitrogen fixation. By integrating high-throughput sequencing with multidimensional environmental data, the application of big data in monitoring microbial activity and constructing models of nitrogen cycling is explored. A nitrogen transformation model based on microbial activity, soil moisture, and organic matter variation is proposed to simulate and predict the effects of different management practices on soil nitrogen use efficiency. Furthermore, by incorporating big data mining and machine learning technologies, the study optimizes fertilizer and water management strategies, proposing precision fertilization and integrated water-nutrient management plans that aim to improve nitrogen use efficiency and promote environmental sustainability. This big data-driven, microbially mediated nitrogen transformation model reveals the dynamic mechanisms of soil nitrogen cycling and provides scientific and technological support for the future implementation of precision agriculture.
