- O. Körner (1)
- Anna Petropoulou (1)
- M.N. Pons (1)
- I. Righini (1)
- R. Sconcini-Sessa (1)
- G. Straten van (1)
- H.F. Zwart de (1)
Autonomous Greenhouse Challenge, First Edition (2018)
Hemming, S. ; Zwart, H.F. de; Elings, A. ; Righini, I. ; Petropoulou, Anna - \ 2019
climate set points - crop management - cucumber - greenhouse climate - harvest - irrigation - outside weather - pruning - resource consumption
The dataset contains data on greenhouse climate, irrigation, outside weather, greenhouse climate set points, harvest and crop management, resource consumption. Data were collected during a 4-month cucumber production (cv. Hi Power) in 6 glasshouse compartments (96 m2), located in Bleiswijk (The Netherlands). The dataset contains raw and processed data. Raw data were collected via climate measuring boxes, climate and irrigation process computer, manual registrations, outside weather station. The dataset was produced during the first edition of Autonomous Greenhouse Challenge, an international competition aiming at using Artificial Intelligence algorithms for the remote control of greenhouse horticulture production. Five international teams consisting of scientists, professionals and students participated in this experiment. The teams' names are: iGrow, deep_greens, AiCU, Sonoma, Croperators. They developed AI algorithms to remotely determine the Climate control set points and they additionally sent instructions for the crop pruning strategy. They had to realize the highest yield with minimal use of resources (e.g. water, CO2). The achievements in AI-controlled compartments were compared with a reference compartment, operated manually by three Dutch commercial growers (named Reference).
Dealing with bio- and ecological complexity, Challenges and Opportunities
Carson, E. ; Feng, D.D. ; Pons, M.N. ; Sconcini-Sessa, R. ; Straten, G. van - \ 2006
Annual Reviews in Control 30 (2006)1. - ISSN 1367-5788 - p. 91 - 101.
positron-emission-tomography - systems biology - greenhouse climate - management - expression - networks - dynamics - design - models
The complexities of the dynamic processes and their control associated with biological and ecological systems offer many challenges for the control engineer. Over the past decades the application of dynamic modelling and control has aided understanding of their complexities. At the same time using such complex systems as test-beds for new control methods has highlighted their limitations (e.g. in relation to system identification) and has thus acted as a catalyst for methodological advance. This paper continues the theme of exploring opportunities and achievements in applying modelling and control in the bio- and ecological domains.
Temperature integration and process-based humidity control in chrysanthemum
Körner, O. ; Challa, H. - \ 2004
Computers and Electronics in Agriculture 43 (2004)1. - ISSN 0168-1699 - p. 1 - 22.
grandiflorum ramat. kitamura - dendranthema x grandiflorum - greenhouse climate - air humidity - growth - morifolium - model - microclimate - irradiance - quality
Simulations in the authors’ previous studies have shown that a modified temperature integration regime with a 6-day averaging period and increased set-point flexibility was able to reduce annual energy consumption by up to 9% as compared to a regular temperature integration regime. The commonly applied fixed set-point for relative humidity (RH) of 80–85% strongly reduced the potential for energy saving with this regime. Therefore, a more flexible humidity control regime was developed. Simulations indicated that yearly energy consumption could be reduced by 18% as compared to a fixed set-point of 80% RH. By combining the two regimes (temperature integration and humidity control), it was predicted that the energy saving would be even greater. To test this prediction, the combined regimes were applied in two experiments with cut-flower chrysanthemum crops investigating the effect on plant development and growth. Different temperature bandwidths for temperature integration (±2, ±4, ±6 and ±8 °C) were also compared within the joint regime. Crop development was only delayed with the ±8 °C temperature bandwidth. The best regime with respect to plant development, growth, quality and energy saving (±6 °C temperature bandwidth) was compared in a spring experiment with a climate regime used in commercial practice. Energy consumption was 23.5% less with the joint regime. No negative consequences of high humidity were observed, but there was a strong increase in the dry weight of all plant organs. Total plant dry weight was 39% higher than in the regular regime. It can be concluded that energy saving and crop yield increase can be achieved simultaneously, although the dynamic temperature control has to be adjusted to the chrysanthemum developmental stage. The combined dynamic climate regime forms a promising basis for future climate controllers and is easily extendable to other greenhouse crops.