Tomato is the second vegetable crop consumed in Colombia. Important productive zones are located in Cundinamarca, Boyaca, Antioquia, Valle, and Santander, with the area about 11,304 ha. Different types of producers apply different farming systems and conditions of management and commercialization. Due to the necessity to characterize the circumstances of these production systems in a precise form during the first semester of 2008, primary information was taken in producer farms, participative diagnostics were realized including farmers and technicians, and secondary information was obtained from several sources in order to realize this characterization. The information was analyzed by multivariate analysis in its procedures, principal components, cluster analysis, and discriminate analysis. The cluster analysis showed that 8 principal components explained 75% of whole variance between the analyzed systems. We determined that exist 8 productive clusters that grouped in whole 38 farm types with 100 cultivated lots. Discriminate analysis confirmed that 6 clusters exist. We determined that, for Cundinamarca and Boyaca, there are 6 existing productive systems, which were described in their physical, biotic, economic and socio-cultural components. INTRODUCTION Agriculture systems today may be described as goal-oriented manipulations of ecosystems for human gains (Ohlander et al., 1999). A system is a set of interactive components. The physical systems in contrast with the abstract or conceptual systems are no-random organized accumulations of matter and energy in space and time that have subsystems and interactive and interrelated components. The position of the components and subsystems give the structural properties to the system, while the changes in matter, energy and information represent their functional properties (Hart, 1986). For the goals of this article, a system of agricultural production is defined as the set of physical, biotic, economic, and socio-cultural components that are in permanent interaction to generate products and resources. These components interact and form sets with characteristics of structure and function and that can be defined as subsystems (Miranda et al., 2000). Several authors have undertaken studies that try to characterize productive systems and establish typologies of producers to implement projects of investigation and extension (Kaminsky, 1980; Miranda, 1986; Calvo and Icaza, 1986; Gil and Caballero, 1986; Ortiz et al., 1986) with a view to achieve the agricultural development in different countries and regions. In Colombia in the last decade, several authors (Duarte et al., 1999; Rios et al., 1999; Miranda et al., 2000; Miranda, 2004) have developed studies of characterization and typification of productive agricultural systems at different hierarchic levels in order to implement projects of investigation closest to the circumstances of the farmers and stockbreeders in several producing zones of Colombia. In general, the methodology used by the different investigators and compiled by the International network of Methodologies of Investigation in Systems of Production (RIMISP) (Escobar and Berdegue, 1990) has been focused on the use of some skills multichanged for the identification of homologous Proc. IS on Tomato in the Tropics Eds.: G. Fischer et al. Acta Hort. 821, ISHS 2009 36 individuals. In Colombia, the production of tomato is common in almost all the zones; nevertheless, it concentrates principally in the departments of Cundinamarca, Norte de Santander, Valle de Cauca, Boyaca, Huila, Antioquia, Risaralda, and Caldas. At present the country produces 376,645 t of tomato in approximately 11,304 ha, of which 30%, are under the greenhouse (Asohofrucol, 2007; Frutas and Hortalizas, 2008). The goal of this work was to identify, characterize and typify the productive systems with emphasis on table tomato existing in the producing zones of the departments of Cundinamarca and Boyaca (Colombia) by means of the employment of statistical techniques of multivariate analysis in order to define typologies of producers, who permit to implement the process of investigation and extension in this culture according to the circumstances of the producers. MATERIALS AND METHODS Definition of the Study Zone The research was done in the producing zones of the department of Cundinamarca in the municipalities Fomeque and Caqueza (zone 1: 4°19’28.3’’N and 74°22’28’’W) Fusagasuga (zone 2: 5°41’10.7’’N and 73°29’55.4’’W) and the department of Boyaca in Villa de Leyva, Sachica, Raquira, Sutamarchan and Santa Sofia (zone 3: 5°23’32’’N and 73°21’35’’W). Biophysical and Socio-Economical Characterization of the Studied Zone For this characterization, there was obtained information of the different components of the system (Table 1) according to the following: physical component: cartographic data available (similar format or digital format) of soil (samples of soil for characterization), relief, drainages, topography, use of soil; biotic component: identification and characterization of the species, hybrids or existing varieties of table tomato in the chosen zones and the information available about the current systems of farming; economic component: determination of the economic management of productive system; socio-cultural component: determination of the social and cultural circumstances that surround the systems of production and define them in direct or indirect way. Study Variables The variables with major coefficients of change NN, NP, PMC, AMC, NS, LR and CMC were useful for the achievement of the analysis of multiple correspondences preserving the definition of every variable adopted from the beginning of the study (Table 1). Statistical Analysis of the Information This analysis included several steps: a) selection of properties that behave as variables (under the criterion of coefficient of high variation), b) factorial analysis of components to reduce the dimensions of the variables, c) analysis of conglomerates using the principal components as classificatory variables, and d) determination of the types of systems of production and discriminate analysis to verify the certainty of the classification. For the classification, the algorithm of Ward was chosen for being hierarchic and of agglomerative type. Additionally, a factorial analysis of correspondence was realized with the methodology proposed by Duranton and Lecoq (1980). RESULTS AND DISCUSSION The analysis of the attributes of variables showed that the quantitative variables presented different coefficients of change and levels of significance (Table 1) and, for this reason, had the highest weight in the shape of the conglomerates. The variables of qualitative type were used in the description of typologies of the system found. Table 2 shows the percentage contribution of every principal component to the