抄録
Gene-environment interaction research is a core field in modern agricultural science, aiming to elucidate the complex relationships between genotypes and environmental factors (such as climate change, soil properties, and agricultural management practices) to provide theoretical guidance and technical support for crop adaptive breeding. This paper first reviews the fundamental theoretical framework of gene-environment interactions and analyzes the variability of gene expression under different environmental conditions and their physiological mechanisms. It then explores the application of big data and advanced technologies—such as high-throughput genomics, phenotypic data acquisition, environmental variable modeling, and machine learning methods—in gene-environment interaction research, particularly how these technologies enhance research efficiency, accuracy, and predictive capability. The paper further discusses the practical applications of gene-environment interactions in agriculture, emphasizing their contributions to improving crop environmental adaptability, stress resistance, and yield potential. The analysis of representative agricultural cases highlights the broad application prospects of gene-environment interactions in crop breeding and their profound impact on agricultural productivity and sustainability. Finally, the paper presents future research trends and challenges in this field, emphasizing the importance of interdisciplinary collaboration, data sharing, and the integration of intelligent technologies as key drivers of innovation. This paper aims to systematically summarize the theoretical and technological advancements in gene-environment interaction research, provide scientific insights for improving crop environmental adaptability, and propose new technological pathways and strategies for promoting sustainable agricultural development.
