Modelos matemáticos para el manejo del riego y nutrición del cultivo de tomate (Lycopersicon esculentum Mill.) en invernadero.

The tomato is the most important vegetable worldwide. In Mexico, 70% of the cultivated area under protected conditions corresponds to tomato crop. It is important to have an effective management in intensive agriculture. In order to do so, it is important to understand the factors that determine the production potential of crops. Water use is the most important factor in determining the performance, the second one is mineral nutrition. It is convenient to use techniques such as mathematical modeling, in order to design strategies that allow for efficient management of water and nutrients in the tomato crop. Two crop cycles of tomato were developed during the years 2011 and 2012 in order to generate the information needed to calibrate and validate a dynamic growth model. Four plants per week were removed to determine fresh and dry weights of different tomato organs. In order to know the relationship between the different organs of tomato plant correlation analysis and regression were performed between them. The obtained data was used to generate different growth curves for plant structures. The daily water consumption was also measured to determine evapotranspiration and transpiration. Multiple regression equations were fitted to estimate daily evapotranspiration and transpiration. Through instrumentation, several climatic variables were measured. Mineral analyzes where performed during crop development to determine the contents of N, P, K, Ca, Mg and S in the various organs of the plant. With this information, regression equations were generated to mimic the mineral content in plants. Regression models were included in the dynamic model in order to dynamically simulate changes in mineral concentration over time. It was found that the tomato crop provided an exponential growth phase from transplanting until flowering, and a linear growth phase after flowering. It was shown that a strong correlation exists between the fresh and dry weights of different plant organs (P ≤ 0.01), and at different stages of growth (P ≤ 0.01). Regarding water consumption by tomato plants, regression equations were generated and they presented adjusted R2 index values greater than 0.90 for both estimated transpiration to estimated evapotranspiration. Regarding the modeling of tomato growth, the results showed that the model adequately simulates weight of leaves and fruit weight (EF> 0.95 and Index> 0.95). On the other hand, output for harvested leaves and harvested fruits, the simulation was less accurate (EF <0.90 and Index <0.90). Meanwhile, the simulation of the concentration of minerals was adequate for S, N, P, K, since both the EF index and the index showed values higher than 0.95. Simulation of Ca and Mg concentration showed EF values of 0.75 and 0.89 respectively. Information presented in this work is useful for irrigation management and nutrition, both considered as major factors in greenhouse tomato crop. Using the obtained multiple regression models is possible to estimate water needs of tomato plants under greenhouse conditions from simple variables. The dynamic modeling of tomato growth and mineral concentration is used for crop management planning and to design more suitable nutrition strategies.