14TSB_ATC_IR_Optimising Big Data to Drive Sustainable Agricultural Intensification

该项目将解决目前阻碍可持续集约化(SI)的主要农艺/土壤挑战。英国园艺部门目前的浪费和田地损失水平是不可持续的，主要是由于与土壤退化有关的限制和不适当的作物管理方法。该项目的重点是在可持续土壤管理的基础上最大限度地减少浪费和田地损失。土壤是粮食生产的基础，因为它们支持作物生产，而对于种植者来说，土壤是他们的主要商业资产。我们将通过创建一个连贯的农业信息学数据集来推动园艺和耕地生产系统的SI，该数据集涵盖了土豆、谷物、油籽、甜菜、葱、根和甘蓝的全面轮作，具有前所未有的分辨率和规模(5-10年的数据覆盖20,000公顷)。我们将使用农业信息学特有的方法，包括识别和描述作物生产和作物利用的环境和农学驱动因素的数据挖掘和计算技术，如贝叶斯信念网络、神经网络和随机森林，以确定一个领域的历史和流行背景如何影响其当前状态、性能和未来效用(SI)，并阐明如何将土壤健康的度量标准用于系统监测、管理和改进。实现这一项目的数据框架已经通过“土壤换生命”(SFL)系统建立起来，这是一个现有的公司规模的土壤信息管理系统，以上述“农业信息学”方法为基础。SFL系统允许整理土壤物理化学和生物参数、“土壤健康”的具体指标、作物、品种、农学、气象、水和经济数据，所有这些都用于支持一套相关的分析和数据挖掘工具。该项目将开发移动应用程序和相关的网络数据服务，部署这些应用程序，为田间种植者提供对SFL数据库的同步、地理参考访问。种植者将能够参考统一的数据基础上的地块，逐个田地，无论是历史的还是当代的经营。还将提供农业信息学分析工具的总结结果。因此，来自被判定为环境相似的地理位置的成果将被提供给人们，突出所采取的行动和成果--允许种植者之间的知识转移。该项目将对这一“大数据”进行深入的分析和探索，提供强有力的科学证据来支持SI，并在田间、农场和企业规模上保持土壤健康。该项目将起到催化剂的作用，改变英国农业企业目前在本地生成和存储的“大数据”的组合方式，并对其进行关键的、充分的利用。

This project will address key agronomic/soil related challenges currently impeding sustainable intensification (SI). Current levels of wastage and field losses across the UK horticultural sector are not sustainable and are largely attributed to soil degradation-related constraints and inappropriate crop management approaches. This project will focus on minimising wastage and field losses as underpinned by sustainable soil management. Soils are the foundation of food production as they support crop production, and for growers, soil is their primary business asset.We will drive SI in horticultural and arable production systems by creating a coherent agri-informatics data set covering a comprehensive range of rotations derived from potato, cereals, oil seeds, sugarbeet, alliums, roots and brassica's of unprecedented resolution and scale (5-10 years' worth of data covering >20,000 ha). We will use methods particular to agri-informatics, which consist of data-mining and computational techniques that identify and describe the environmental and agronomic drivers of crop production and crop utilization such as Bayesian belief networks, neural networks, and random forests to determine how the history and prevailing context of a field influences its current state, performance and potential for future utility (SI), and elucidate how metrics of soil health can be used for system monitoring, management and improvement. The data framework to realise this project is already established via the 'Soil-for-Life' (SfL) system an existing company scale Soil Information Management System underpinned by the aforementioned 'agri-informatics' approaches. The SfL system permits the collation of soil physico-chemical and biological parameters, specific indicators of 'soil health', crop, varietal, agronomic, meteorological, water and economic data, all deployed to support the suite of related analytical and data mining tools. This project will develop mobile applications and related web data services which will be deployed to provide growers in the field with synchronous, geo-referenced access to the SfL databank. Growers will be able to consult the harmonised data holdings on a parcel basis, field by field, both for historical and contemporary operations. Summary results from the agri-informatics analytical tools will also be provided. Thus outcomes from geographic locations judged to be similar environmentally will be made accessible, highlighting actions taken and outcomes - allowing for knowledge transfer between growers. This project will allow an in-depth analysis and exploration of this 'big data', providing robust scientific evidence to support SI and to maintain soil health at a field, farm and enterprise scale. This project will act as a catalyst for a step-change in the way that 'big data' currently generated and stored locally by UK Agri-businesses is combined and critically, fully utilised.