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- Author or Editor: Laurent Gauthier x
To achieve high yield and better quality of soilless greenhouse tomato, it is necessary to keep the nutrient concentrations in the root environment at the target levels. Dynamic control of the nutrient solution composition can be used for this purpose. We developed a computer program that dynamically adjusts nutrient solution compositions based on various climatic and agronomic characteristics. The program integrates nutrient uptake and crop transpiration models and is part of a general-purpose greenhouse management and control software system developed at Laval University (GX). The architecture of the system and some simulation results comparing the effect of various control scenarios on the evolution of the composition of nutrient solutions are presented.
In soilless culture, the buffering capacity of the root environment for nutrients is low. This, combined with fluctuations of climatic factors and changes in nutrient uptake rates, can lead to nutrient imbalances. In order to achieve high yield and better quality, it is necessary to keep the nutrient concentrations in the root environment at the target levels. This requires frequent analysis and adjustments to the nutrient solution. Currently, leaching of the growing media or renewal of the nutrient solution is commonly used to avoid accumulation or depletion of nutrient in the root environment. However, this practice lowers the efficiency of fertilizers and can lead to the contamination of the ground water. One way to remedy to this problem is through the use of nutrients uptake models to track the composition of the nutrient solutions. The objective of this study was to develop such models. Such models can be used to maintain balanced nutrient solutions for longer periods. This can lead to reduced leaching and improved fertilizer use efficiency. Macronutrient (N, P, K, Ca, and Mg) uptake models were developed for tomato plants grown in an NFT system using data collected from experiments conducted in the Laval Univ. greenhouses. Analysis of the experimental results showed that the main factors affecting nutrients uptakes are light and transpiration.
A software system (SAGE) was built for on-farm decision support. The objective was to provide a framework for constructing and deploying knowledge-based decision support in the areas of integrated pest management, fertilization, and field operations. The framework is open by design and includes a generic model of an agro-ecosystem as well as various mechanisms allowing for the continued growth in scope and function of the software. The SAGE system is designed to provide a number of building blocks and predefined decision-support strategies that can be adapted to specific needs and situations. It operates on a personal computer and is based on the use of an objectoriented technology for software construction and operation. A prototype of the system has been built and is being used to build commodity-specific decision-support modules.
Transpiration and water uptake play an important role in the growth of horticultural crops, such as tomatoes. Water uptake ensures the transport of nutrients. However, the transpiration rate is affected by the humidity level in the greenhouse. High levels of humidity restrict transpiration and lead to fungal diseases resulting in yield losses. Under northern latitudes, using more airtight structures combined with high levels of artificial lighting increase the humidity level inside the greenhouses. To decrease humidity, growers have to dehumidify by ventilating and heating at the same time, leading to increased energy consumption. However, to our knowledge, the literature does not report on the energy consumption needed to dehumidify. To evaluate this energy consumption, we used a greenhouse simulation model of heat and mass exchanges integrated into a general greenhouse control and management software system (GX). Evapotranspiration, condensation on the cladding, and infiltration and ventilation rates were taken into account for the water balance. Based on 1 year of climatic data, three sets of simulation were realized: 1) no dehumidification; 2) standard dehumidification by ventilation and heating; 3) dehumidification with heat exchangers. Results indicate that for an acceptable level of humidity within a greenhouse tomato crop (vapor pressure deficit >5 kPa), the energy consumptions with standard dehumidification and with heat exchangers are 25% and 15% higher, respectively, than without dehumidification. These results are being used to establish recommendations for the management of humidity under northern latitudes.
Experiments were conducted in four independently controlled greenhouses. The purpose of these experiments was to measure the effect of humidity on transpiration and yields. Four different humidity treatments were evaluated: 1) high night and high day humidity levels (vapor pressure deficits <0.4 kPa), 2) high night and low day humidity levels (VPD >0.8 kPa), 3) high night and low day humidity levels, and 4) variable greenhouse humidity to maintain a set hourly transpiration rate. Transpiration rates were measured in the four greenhouses at 15-min intervals from Nov. 1993 to May 1994. Results show that high humidity reduces the hourly and daily transpiration levels significantly and has an impact on crop yields. Results also show that it is possible to regulate crop transpiration by calculating the transpiration rate for a set of VPD and solar radiation levels.
In greenhouses, computerized climate control systems can be used to dynamically and automatically regulate climatic and environmental parameters. To support such a mode of operation, a crop growth model that was developed for greenhouse tomato plants (TOMGRO) was chosen. The model describes the phenological development and increase in dry weight of various organs from planting till maturity under variable environmental conditions. The assimilate partitioning is based on sink strength. A FORTRAN version of TOMGRO was converted to the Smalltalk object-oriented programming environment. This model was integrated into GX, a dynamic climate management software system that was developed at Laval Univ. GX defines a general architecture that may accommodate different decision-making modules based on mathematical models and rule bases. The TOMGRO model is being used to evaluate different production scenarios and will be used to calculate and predict crop growth rates, development, and yields. The model can be used to perform real-time and seasonal cost–benefit analysis and for the dynamic optimization of greenhouse climatic parameters.
A dynamic management strategy for supplemental lighting in greenhouses was developed. It makes use of a plant growth model and of a rule-based decisionmaking protocol within the framework of a generic greenhouse climate management software system. The model, an adapted version of SUCROS87, tracks plant growth and predicts dry weight production based on measured or estimated values of light intensity, temperature, and CO2 concentration. A set of logical predicates (rules) implements the strategy's behavior. Optimization of lamp use was conducted as a function of economic criteria that enable a comparison between the additional income associated with yield increases due to supplemental lighting and incurred cost increases. Although the model is not perfectly reliable in its predictions, the system can be used to simulate the effect of changes to economic parameters on the decisions of the management strategy. The dynamic strategy described here differs from conventional supplemental lighting scenarios in the sense that it increases the length of the period of supplemental lighting when the daily solar light integral is low, and reduces or eliminates the use of supplemental lighting when the weather forecast predicts that the daily solar light integral will exceed plant requirements.
Tomato plants were grown in peat bags in greenhouse to examine the effects of variation of the nutrient solution electrical conductivity (EC) and substrate water potential (Ψsub) on photosynthesis in leaves, fruits, stem, and petioles. EC of the nutrient solution delivered to peat bags varied between 1 to 4 dS·m–1 with Ψsub of either –5 kPa or –9 kPa as the setpoint for starting the irrigation. The EC variation was adjusted by a computer system according to potential evapotranspiration. Gross photosynthetic capacity (PC) decreased as the leaf age developed. PC in the 10th, 15th and 18th leaves from the top was only 76%, 37%, and 18% of PC in the 5th leaf, respectively. However, low quantum use efficiency (QUE) was only observed in the 18th leaf and low dark respiration (RD) was only in 15th and 18th leaves. Net photosynthesis (PN) was only observed in young fruits (≈10 g FW) or young petioles and no PN was observed in large fruits (50 g or more FW) and stems. Both PC and RD were lower in older fruits and petioles or in the lower part of the stem compared to the younger ones or upper parts. EC variation increased PC, QUE, and RD in most parts. Low Ψsub increased RD in most parts and decreased PC in fruits, stem, and petioles. It is suggested that EC variation increased plant physiological activity of tomato and low Ψsub increased carbon consumption, although it was not severe enough to depress leaf PC.
Tomato plants were grown in peatmoss-based substrate and supplied with nutrient solution of high (4.5 mS·cm–1) or low (2.3 mS·cm–1) electrical conductivity (EC) under high (95%) or low (55% of capillary capacity) substrate water content (SWC) to examine the effects of high EC and low SWC on growth and physiology. Salts were allowed to accumulate in the substrate for 7 weeks. Both high EC and low SWC significantly decreased dry matter production (DMP) and fruit yield (FY). Fruit harvest index was lower in high EC- or low SWC-treated plants. Decrease in marketable FY was attributed to both the decrease in total FY and the increase in small and abnormal (cracked and rot) fruits. Both high EC and low SWC decreased photosynthesis (PN) and leaf water potential (ΨL). However, chlorophyll content and respiration were increased by high EC under both high and low SWC. Water consumption based on both whole plant and unit of leaf area was decreased by high EC and low SWC. ΨL and transpiration were depressed by high EC and low SWC, especially at midday. There was a significant positive correlation between fruit yield and water consumption. The effects of high EC and low SWC were additive on most of the variables. Decreases in ΨL might ultimately account for water consumption reduction, PN depression, and FY decrease.
In Quebec, the carrot Cercospora blight represents a major foliar disease. In carrot fields, it causes reductions in yields of up to 30%. The evolution of this disease can be predicted by considering the meteorological and biological parameters and by using expert knowledge. Disease management can be enhanced through the use of a computerized decision support system (DDS). The objectives of the project were: 1) to define a conceptual framework for the operation of a carrot protection module, 2) to integrate a model of Cercospora blight evolution within the framework, 3) to integrate and structure the information needed for the consultation of the DSS, and 5) to validate the recommendations of the module. The various components (knowledge base, database, simulation model) constitute an extension to an existing framework used for agricultural production management (SAGE). The latter is built using an object-oriented programming language (Smalltalk) and an object-oriented database management system. A fully operational version of the system was developed and will be tested during the summer of 1995. The developed system combines a Cercospora blight model and a set of rules that convey the expert's knowledge. These rules were formulated based on interviews with the expert. The nature and organization of the rules will be presented as well as a critical evaluation of the methodology and tools used to build the system.