农作物表型组大数据工厂成套技术装备研究综述

Review of Integrated Technology and Equipment System for Crop Phenomics Big Data Factory

摘要:

面向作物表型组大数据获取解析、作物种质资源表型鉴定等亟需高效率、智能化和低成本技术、装备及系统的问题，在系统梳理分析国内外农作物高通量表型平台相关技术产品研究现状的基础上，通过组织多学科的协同技术攻关，突破了作物表型组大数据高通量获取和智能化解析中的关键技术难题，设计了具有自主知识产权的轻小敏捷型多传感器阵列、通用化成像单元和适用于多生境的固定式、移动式高通量表型平台装备，以及配套算法和软件平台，构建了农作物表型组大数据工厂成套技术装备体系。该体系由大田和设施作物高通量自主作业表型平台、室内器官和显微表型平台、大田和设施环境自动化种植管控设备、作物模型系统、数字孪生智慧管控平台和大数据计算服务中心等构成，可实现多生境、自动化、高通量、高效率、高精度的多源作物表型-环境数据协同采集，涵盖农作物群体、个体、器官和显微多重尺度，能够重建农林作物的三维形态结构并精准解析株型、产品、品质、抗性等表型组指标，是发展数字育种和智慧栽培的新一代信息化基础设施。农作物表型组大数据工厂技术装备体系创新了作物表型组大数据的产生、处理和服务模式，可为作物表型组理论技术的发展、基于AI for Science 的平台化科研和工厂化的作物种质资源表型鉴定等提供体系化的技术装备支撑。

Abstract:

The rapid development of crop phenomics demands high-efficiency, intelligent, and cost-effective technologies and systems for large-scale data acquisition and analysis, as well as for germplasm phenotyping. To address these challenges, multidisciplinary innovations was integrated to overcome key technical bottlenecks in high-throughput data acquisition and intelligent traits extraction for crop phenomics. A suite of proprietary technologies was developed, including lightweight and agile multi-sensor arrays, universal imaging box, and both fixed and mobile high-throughput phenotyping platforms adaptable to diverse environments, together with corresponding algorithms and software systems. These developments culminate in the Crop Phenomics Big Data Factory (CPBDF). CPBDF is a comprehensive technology and equipment framework that conceptualizes farmlands, greenhouses, and growth chambers as “factories”, where phenotyping platforms function as “production lines”, and the output is high-quality phenomics big data. The system integrated field-based and facility-based autonomous phenotyping platforms, organ- and microscopy-level phenotyping systems, automated cultivation control devices, crop modeling systems, a digital-twin intelligent management platform, and a big data computing center. It enabled automated, multi-source, and multi-scale data acquisition with high throughput, precision, and integration, supporting three-dimensional reconstruction and quantitative phenotypic analysis across crop populations, individuals, organs, and microstructures. The proposed framework established a paradigm for the production, processing, and application of crop phenomics big data. It provided foundational infrastructure for digital breeding and smart cultivation, and served as a key enabler for AI for Science-driven research platforms and factory-style germplasm phenotyping.