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).本数据集涵盖室外与室内温室气候、灌溉工况、执行器（actuators）状态、预设与实际气候设定值、资源消耗、收获量、作物相关参数、番茄品质、灌溉与排水样本分析以及根区/栽培基质块（root-zone/slab）相关信息。数据采集自位于荷兰布莱斯维克（Bleiswijk）的瓦赫宁根研究中心（Wageningen Research Centre）的6个高科技温室隔间，采集周期为6个月的樱桃番茄（栽培品种：Axiany）种植全过程。本数据集源自第二届自主温室挑战赛（Autonomous Greenhouse Challenge），该赛事邀请5支具备多学科专业背景的国际团队参赛——团队成员涵盖科研人员、行业从业者与学生——旨在推动自主温室技术实现跨越式发展。参赛队伍分别为：The Automators、AICU、IUA.CAAS、Digilog与Automatoes。各团队自主开发智能算法，以此确定气候、灌溉及多项种植相关参数的设定值，并远程管控樱桃番茄的种植生产。各团队的优化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）、CO₂等资源消耗的同时，根据产量与果实品质优化收益。AI管控隔间的种植成果，将与由三名荷兰商业种植者手动操作的参考隔间（命名为Reference）进行对比。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、气候与灌溉过程计算机、气象站以及温室工作人员的手动记录采集获得。