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Digital twin technology, a sophisticated multi-scale and multi-physical methodology, facilitates the real-time synchronization and high-fidelity data exchange and integration between the physical and informational realms. Owing to its immense potential in real-time monitoring, predictive analytics, and decision optimization, this transformative technology has begun to see preliminary applications in the management of agricultural production processes, offering unprecedented opportunities for enhancing efficiency and productivity. To elucidate the current application landscape and future trajectory of digital twin technology in agricultural management, various application instances across diverse production settings, including arable fields, orchards, greenhouses, livestock farming, and agricultural machinery were enumerated and scrutinized. Following this, five-dimensional model of digital twins in agricultural processes was delved, offering an in-depth analysis of pivotal technologies such as data acquisition, virtual-scenario construction, cyber-physical interaction, and data analytics. Ultimately, informed by the evaluation of current applications and critical technologies, the developmental trends of digital twin technology in the intelligent management of agricultural production were posited. Through the comprehensive discourse and analysis, it aimed to furnish valuable insights for the advancement and deployment of digital twin technology in the intelligent control of agricultural production processes, paving the way for a more sustainable and efficient agricultural future. Based on the analysis of current applications and key technologies, the development trend of digital twins applied to intelligent control in agricultural production is: It is essential to move beyond the application framework of a single scenario and stage, and realize digital twin and intelligent control services for the entire agricultural production process.