Validation of a Tomato Crop Simulator for Mediterranean Greenhouses G. Dimokas and C. Kittas University of Thessaly, School of Agricultural Science, Department of Agriculture Crop Production & Rural Environment, Fytokou Str, 38446, N. Ionia Magnesias, Greece, e-mail: ckittas@uth.gr M. Tchamitchian Écodéveloppement, I.N.R.A., DomaineSaint-Paul, Site Agroparc, Avignon Cedex 9, 84914, France, e-mail: arm@avignon.inra.fr ISHS International Workshop on Greenhouse Environmental Control and Crop Production in Semi-Arid Regions October 20-24, 2008, Tucson, Arizona, USA Abstract The aim of this work is the validation of the adaptation of the TOMGRO tomato crop simulation to short term cropping technique and to Greek conditions. Indeed, a current practice in plastic greenhouses in the Mediterranean regions is to stop the development of the plant after 7 trusses by topping, which is the removal of the terminal bud of the plant. Experiments were carried out in the farm of the University of Thessaly in the region of Volos, during the autumn and winter period of 2007. Crop development, growth and greenhouse climate were measured. The modified TOMGRO has been calibrated over the winter 2005 data and validation occurred on the winter 2007. A good agreement has been observed between the measured and simulated plant development indicators, biomass and fruit production during validation process. Finally, a satisfactory agreement has been obtained for the plant leaf area which is classically one of the weak points of TOMGRO. On the basis of these results, we conclude that this adaptation of TOMGRO simulates properly short term tomato crops under greenhouses and therefore can be used in decision support to help growers operate the greenhouse. Inputs of the Biological Model Air Temperature Relative Humidity Solar Radiation CO2 Concentration Integration of hourly variables for daily temperature calculation Daily initialization RESULTS The degree of agreement between the measured and the simulated values is similar for the different development indicators as can be seen on figure 1, which shows the evolution of the number of nodes and set leaves. It can also be seen that simulated and measured values of the number of nodes and set leaves have the same slope during the increasing period. The increase stops at the same time for the measured and simulated values, when the topping of the plants occurs and the total number then remains stable. A satisfactory agreement was also observed for total leaf area (figure 2a) which is properly simulated both during the period where new leaves appear and increase in size, and during the period where the leaf area decrease due to leaf removal. Figure 2b presents the evolution of the number of trusses. The simulated values increase later than the measured one during the first 50 days of the experiment. After that date, a good agreement between measured and simulated values can be observed. DISCUSSION Comparisons of validation results with field data for tomato development, fruit and biomass production showed strong reliability and suitability of the modified simulator to the local cultivation practice. The results obtained a good ability to simulate the development of a topped short-cycle crop, especially for the number of nodes, the number of leaves (figures 1), which could be expected granted the results obtained on longer cycles and on different cultivars by Jones et al. (1991) and Dayan et al. (1993a, b). The number of trusses is quantitatively correct, but the simulated truss appearance date can differ from the observed date, either preceding or following it (figure 2b). In the results presented by Jones et al. (1991) and Dayan et al. (1993a, b) it can be noticed that although the plant development is a continuous process without limit, the leaf area becomes more or less constant after about 100 days after transplanting, because deleafing compensates for the apparition of new leaves. Amount of carbohydrates for the pool Growth respiration Maintenance respiration Confirm the weather data from Climate Model Biological Model Rate of development for each organ Number of organs Gross photosynthesis Organs development rate Hourly “Loop” Calculation the percentage of the appearance Age class for each organ Daily “Loop” Ratio source / sink Demand for assimilates for each organ Validation LACEC, Laboratory of Agricultural Constructions & Environmental Control CONCLUSIONS The results described here show that this modified version of TOMGRO simulates properly short term Mediterranean greenhouse tomatoes. The validation of the simulator, even with small differences between measured and simulated values, gives the opportunity to use it for the estimation of tomato’s crop development and production on short term cultivations. The modification of the model and the ending of the crop development in a specific time horizon, are making the biological simulator a useful tool for the growers of the Mediterranean who follow a specific schedule for crops rotation. The number of green fruits that are remaining on the plant is the necessary information for the growers in order to schedule the crop that will follow tomato plants in theirs crop rotation plan. The connection of the biological simulator with a climate simulator will give the opportunity for optimization of the producing process. Optimization methods have scarcely been used on agricultural problems (Garcia, 1999). Optimization, method can be applied for greenhouse climate and crop production simultaneously in order to succeed the best strategy according to growers needs. The optimization method allows searching for the best management strategy in a range of possible future climates to which the greenhouse may be submitted. This will help growers in the strategic management of crop and climate, in order to achieve the best benefit of the production according to their time schedule. Fig. 1(a) Number of nodes, during the experimental period. (─) simulated values, (□) measured values Fig. 3(a) Plant dry weight, during the experimental period. (─) simulated values, (□) measured values Fig. 3(b) Total fruits dry weight, during the experimental period. (─) simulated values, (□) measured values Fig. 1(b) Number of set leaves, during the experimental period. (─) simulated values, (□) measured values ACKNOWLEDGEMENTS This paper is part of the 03ED526 research project, implemented within the framework of the “Reinforcement Program of Human Research Manpower” (PENED) and co-financed by National and Community Funds (25% from the Greek Ministry of Development-General Secretariat of Research and Technology and 75% from E.U.-European Social Fund). Fig. 2(a) Total leaf area of the plant (m2/plant), during the experimental period. (─) simulated values, (□) measured values Fig. 4(a), (b) Green versus mature fruit dry weight, during the experimental period. (─) simulated values, (□) measured values