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In heated greenhouses, large amounts of energy are used to optimize climate conditions (temperature, humidity). In conventional tomatoes production, the estimated annual energy consumption is 320 kWh m-2 in France, with large differences across regions, 400 kWh m-2 in Brittany and 240 kWh m-2 in the South (ADEME, 2007). In Switzerland, it varies between 245 and 500 kWh m-2 according to the regions. With increasing energy prices and environmental concerns, growers have to find solutions to reduce their energy use and to improve the energy efficiency. Several axes could be used to achieve this goals, one of them is climate management. Within the working group "Energy saving and neutral production" of the Cost Action FA 1105 "BioGreenhouse", a review on the potential for energy saving in heated greenhouse thanks to climate management was done. Basically, there are two ways to reduce energy consumption: related to temperature control and to humidity control. The energy saving potential of lowered day and night temperature set points, temperature integration (TI) and screen management will be presented in relation to the effects on production. In Switzerland, three trials from 2006 to 2008 in tomato crops showed that an energy saving potential of 15 to 30% could be achieved with TI compared to the standard temperature treatment. An energy saving between 23 and 30% with screens management based on external temperature and light intensity compared to a management according to the sunrise was obtained. To reduce energy consumption related to humidity control, dehumidification with heat recovery was studied. A traditional dehumidification (ventilation and heating) was compared with dehumidification with a heat pump in tomatoes crop. In 2013, 15% energy saving was achieved with the dehumidifier and in 2014 reached 25%. No difference in plant growth, yield and fruit quality was measured.

Earlier research has revealed that considerable energy savings can be achieved by maintaining an average temperature in the greenhouse in stead of maintaining rigid pre-defined temperature `blue-prints¿. A model based optimal control approach has proven to be a suitable framework to tackle these kind of control problems and it has been shown that these algorithms can be implemented on-line. But, when on-line optimal temperature control is considered, interesting questions arise, some of which are still unresolved. The issue tackled in this paper concerns the relation between the resolution of the control strategy (sample time) and energy savings of the control strategy. One would expect that an accurate and frequent anticipation to changing outdoor climate conditions might result in reduced energy consumption. It was indicated in the literature that a sample-time of 0.25 h or 1 hour should be sufficient, but these choices were hardly motivated. In this research, the relation between the control resolution and energy savings was quantitatively investigated using a dynamic greenhouse climate model and measurements of Dutch outdoor climate conditions containing high-frequency components. The results indicate that for an open-loop optimal control problem concerning the realization of an average temperature during a fixed period of one day using a minimum amount of energy with full a-priori knowledge of the outdoor weather, a resolution of the heating profile between half an hour and a hour suffices to produce accurate results in terms of energy conservation. These results were not much affected by parameter variations (heat capacity of the air, the solar heating efficiency) or opening and closing of thermal screens.

A solar greenhouse has been designed that maximizes solar energy use and minimizes fossil energy consumption. It is based on a conventional Venlo greenhouse extended with a heat pump, a heat exchanger, an aquifer and ventilation with heat recovery. The goal is to minimize fossil energy consumption, while maximizing crop dry weight, keeping temperature and humidity within certain limits and satisfying a temperature integral. To achieve this the aim is to implement a receding horizon optimal controller. This type of controller computes optimal closed loop controls based on a cost function and a greenhouse and crop model. In this paper simulations of a simplified version of this closed loop optimal control system are presented. It is found that the boiler use is reduced, thereby reducing fossil energy use. Gas use is decreased by 77% compared to a conventional greenhouse with optimal control.

National audience; The present study on soil-less tomato crops aims to evaluate and compare on contrasted genotypes the impact of temperature integration (TI) on plant growth and development as well as on fruit yield and quality. TI, taking advantage of plant plasticity regarding temperature, consists in modulating the set points for heating (lower during the night) and ventilation (higher during the day) keeping similar mean 24h temperature for plant development. Four variety-rootstock combinations of tomato plants were studied for two consecutive years (2010 and 2011). Two climate managements were compared: a temperature integration technique (TI) and a control (grower’s technique). In order to test the limit of TI system, TI application lasted longer in 2011 and with temperature settings colder compared to 2010. During the first year of experiment (2010), energy saving was about 22% during TI period. Yield was not modified, nor leaf growth. In 2011, TI led to an 8.6% energy saving compared to control. Yield significantly increased for Plaisance-Beaufort combination and was not affected in other variety-rootstock combinations. In conclusion, for both years TI increased energy use efficiency. Plant development rate was not significantly modified by TI. Leaf area slightly decreased (-11%). Fruit size and composition (sugars, acids, vitamin C) were not modified by TI. Carotenoids (specifically phytoene and lycopene) were improved by TI in particular for Plaisance-Beaufort; this might be related to the reduced leaf area that allowed more light to reach the fruit and consequently promoted carotenoid synthesis. Temperature integration appears as a profitable alternative to classic management of greenhouse climate.

National audience; The present study on soilless tomato crops aims to evaluate and compare on contrasted genotypes the impact of temperature integration (TI) on plant growth and development as well as on fruit yield and quality. TI, taking advantage of plant plasticity towards temperature, consists in modulating the set points for heating (lower during the night) and ventilation (higher during the day) keeping similar mean 24 h temperature for plant development. Four cultivar-rootstock combinations of tomato plants were studied for two consecutive years (2010 and 2011). Two climate managements were compared: a temperature integration technique (TI) and a control (grower's technique). In order to test the limit of the TI system, TI application lasted longer in 2011 and with temperature settings colder compared to 2010. During the first year of experiment (2010), energy saving was about 22% during TI period. Yield was not modified, nor was leaf growth. In 2011, TI led to an 8.6% energy saving compared to control. Yield significantly increased for 'Plaisance'-'Beaufort' combination and was not affected in other cultivar-rootstock combinations. In conclusion, for both years TI increased energy use efficiency. Plant developmental rate was not significantly modified by TI. Leaf area slightly decreased (-11%). Fruit size and composition (sugars, acids, vitamin C) were not modified by TI. Carotenoids (specifically phytoene and lycopene) were improved by TI in particular for 'Plaisance'-'Beaufort'; this might be related to the reduced leaf area that allowed more light to reach the fruit and consequently promoted carotenoid synthesis. Temperature integration appears as a profitable alternative to classic management of greenhouse climate.

Like in most countries, in the Netherlands energy consumption is an increasing cost component. In cut flowers grown at a relatively low temperature, most of the energy is used for dehumidification. In Alstroemeria dehumidification is especially important to prevent the physiological disorder expressed as necrotic leaf tips. Research has been carried out showing that improved climate control can save 37% on heating, without a reduction on yield and even a quality, compared to a contemporary reference. Showing less necrotic leaf tips, the quality was better in the greenhouse with the energy saving strategy in December and January. This result was realized with a novel dehumidification system, a double thermal screen and temperature integration. When vapour pressure deficit was below 1.9 g/m3, outside air was blown under the canopy with an air distribution system for dehumidification. If necessary, this outside air was first heated to greenhouse temperature to prevent an inhomogeneous temperature distribution. The reference greenhouse, controlled at the same humidity set point, used a combination of slightly opening the thermal screen followed by slightly opening the vents to carry off moisture. Eventually, at a vapour pressure deficit of 1.5 g/m3 the temperature of the heating pipe was risen to lower the humidity. In the greenhouse with the energy saving concept no heating pipe for dehumidification was needed. The performance of the energy saving concept proved to be efficient.

At low light levels measured and in a dynamic greenhouse climate, crop photosynthesis does not match prediction by photosynthesis models. In order to address this problem, a greenhouse scale crop photosynthesis measuring system was designed to generate data that can be used to validate crop photosynthesis models. The system is based on net CO2 exchange of a crop and was tested with a full scale cut chrysanthemum crop including the canopy bed structure. The system was used to measure crop photosynthesis at different CO2 concentration levels (350 and 970 ¿mol mol¿1), different temperatures, various low-photosynthetic photon-flux densities (PPFD; 85 and 160 ¿mol m¿2 s¿1) and natural light conditions (0¿600 ¿mol m¿2 s¿1). The system consisted of two identical closed greenhouses (44 m2 floor area each) that were sealed against air infiltration and tested on the occurrence of air leakage and unwanted CO2 sources with the help of tracer gases. The CO2 was supplied by computer-controlled flow proportionally to the difference between set point and measured concentration. An error analysis was applied successfully to find the required system characteristics needed to meet the requirement of a maximum system error of 5% for net CO2 exchange measurements even at low photosynthesis levels. The description of the arrangement, calibration and testing of this system supports the design process of accurate large-scale crop photosynthesis measuring systems for use in crop photosynthesis research.

Theoretically, using information about crop growth would allow the extension of present greenhouse control strategies towards a truly economic optimal control strategy. A brief survey is given of developments in the scientific literature. A full solution would require to consider the long-term crop development as well as all relevant short-term dynamics of the crop, the greenhouse and the external weather. Obstacles for the acceptance of such solutions are briefly discussed. One of the key factors is the lack of reliable crop development models for the wide variety of crops encountered in practice, and the need to leave part of the decision freedom in the hands of the grower. An analysis is given of simplified approaches resulting from integrating the crop equations over a day or more. The temperature integral concept, a specific example of such approach, is gaining popularity, despite the fact that it lacks exploitation of knowledge about the fast crop responses. The discussion leads to the concept of separation of responsibilities, where the short-term effects, including photosynthesis and evapo-transpiration, are handled by an automated model-predictive optimal controller, while the long-term effects are left to the grower, with support from a flexible decision support system based on crop models whenever they become available.