Modelación matemática de la calidad fisicoquímica y sensorial del fruto de tomate (Solanum lycopersicum)

Fruit quality is a complex issue defined as a sophisticated chain of biological processes (Genard et al., 2007). These processes (transpiration, respiration, photosynthesis) involve exchanges between the fruit and its environment. Quantitative integration of these processes to monitor fruit?s behavior is a task involving physiological modeling. Nowadays, the interest in mathematical modeling about the quality changes during fruit maturation has been increased (Wegehenkel and Mirschel, 2005). It is possible through simulation to evaluate the quality of final products in order to satisfy quality consumer demands and to adjust or improve the decision making related to harvest dates and product commercialization. Adequate models should be mechanistic enough to give a representative description of physiological processes and explain variations in quality traits. Recently, models have become more accurate and better able to predict the outcome of complex issues such as genotype-environment interactions. Furthermore, efforts have been made to define fruit quality and integrating it with crop growth models. These models are based on accurate descriptions of early stages of growth, including fresh fruit mass, dry matter content and concentration of sugars. Nevertheless, most of models do not include variables related to quality traits such as flavor and aroma. GC-O techniques could provide important information in order to establish correlations among physicochemical and sensory attributes. Including this information in mathematical models can lead to a wider comprehension of the metabolism-environment interaction and their influence on quality attributes. Precision agriculture offers the possibility to control environment with the purpose of enhance physicochemical and sensory characteristics in crops.