Autonomous Greenhouse Challenge, Second Edition (2019)

The dataset contains data on outdoor and indoor greenhouse climate, irrigation, status of actuators, requested and realized climate setpoints, resource consumption, harvest, crop-related parameters, tomato quality, analysis of irrigation and drain samples and root-zone/slab information. Data were collected during a 6-month cherry tomato production (cv. Axiany) in 6 high-tech glasshouse compartments, located at the Wageningen Research Centre in Bleiswijk (The Netherlands). The dataset was produced during the second edition of Autonomous Greenhouse Challenge. This competition sees five international teams - consisting of scientists, professionals and students with multi-disciplinary expertise - challenging themselves in order to make a large step towards the Autonomous Greenhouse. The teams' names are: The Automators, AICU, IUA.CAAS, Digilog and Automatoes. The teams developed their own intelligent algorithms and used them to determine the set points for climate, irrigation and a number of cultivation-related parameters and control the production of cherry tomato crop remotely. The teams objective was to maximize net profit, by minimizing use of resources (e.g. water, nutrients, energy -heating and electricity- CO2) while optimizing income as a function of production and fruit quality. The achievements in AI-controlled compartments were compared with a reference compartment, operated manually by three Dutch commercial growers (named Reference). The dataset contains raw and processed data. Raw data were collected via climate measuring boxes and sensors, climate and irrigation process computer, weather station, manual registrations (performed by the greenhouse staff).

本数据集涵盖户外与室内温室气候、灌溉、执行器(actuators)状态、目标与实际气候设定点(setpoints)、资源消耗、收获产量、作物相关栽培参数、番茄品质、灌溉与排水样本分析，以及根区/基质块(root-zone/slab)相关信息。数据采集自位于荷兰布莱斯韦克（Bleiswijk）的瓦赫宁根研究中心(Wageningen Research Centre)的6个高科技温室单元(compartments)，采集周期为6个月，期间种植了樱桃番茄栽培品种'Axiany'。本数据集源自第二届自主温室挑战赛(Autonomous Greenhouse Challenge)。该赛事共有五支国际参赛队伍，成员涵盖具备多学科专业背景的科研人员、行业从业者与学生，旨在通过参赛向着自主温室的目标迈出实质性进展。参赛队伍分别为：The Automators、AICU、IUA.CAAS、Digilog及Automatoes。各队伍自主研发智能算法，以此确定气候、灌溉及多项栽培相关参数的设定点，并远程调控樱桃番茄的生产流程。参赛队伍的核心目标为最大化净利润：在最小化水资源、养分、能源（供暖与电力）及二氧化碳等资源消耗的同时，基于产量与果实品质优化营收。研究人员将AI调控温室单元的生产表现与由三名荷兰商业种植者手动运营的参考单元（命名为Reference）进行了对标对比。本数据集包含原始数据与处理后数据。原始数据通过气候测量箱与传感器、气候及灌溉过程计算机、气象站，以及温室工作人员手动记录的方式采集获取。