植物体征数字化获取技术及其在设施蔬菜精准管理中的应用OA

With the continuous advancement of smart agriculture and the digital transformation of protected vegetable production,digital acquisition of plant phenotypic traits has evolved from individual sensing techniques into a core technological foundation supporting precision management.At its core,this approach leverages multidimensional sensing and information processing technologies to achieve non-destructive,continuous and quantifiable characterization of plant morphological structure,physiological status,functional activity and stress responses.Grounded in the precise sensing requirements of protected vegetable production,this review systematically outlines the sensing architectures,signal mechanisms and representative characterization technologies.It summarizes the latest advances in water management,nutrient diagnosis,pest and disease early warning,growth monitoring and quality evaluation.Particular emphasis is placed on integrated application models,such as autonomous regulation in intelligent greenhouses for tomato production,along with their significant yield and efficiency benefits.The analysis demonstrates that digital plant phenotyping is driving a paradigm shift in protected vegetable production from traditional environment-parameter-dependent management toward a precision management model centered on crop feedback.Nevertheless,practical constraints remain in data standardization,engineering adaptability and closed-loop execution.Future efforts should focus on multimodal fusion representation,low-cost edge deployment,mechanism-data dual-driven modeling,and cloud-edge collaborative decision-making to support the transition of protected vegetable production from experience-driven to data-driven practices.