Abstract: The lack of detailed maps of spatial distribution of soil units is a frequent constraint in decision-making processes, hydrological modeling, and productive assessment of an area. In this work, the Digital Soil Mapping (DSM) technique was applied, and Principal Component Analysis (PCA) was used to obtain the spatial distribution of dominant soil units in a watershed. The study area was the Mixteco watershed, which covers an area of 655 903 ha, of the Mexican state of Oaxaca. For DSM, topographic, hydrological, climatic and geological environmental covariables were used. The environmental covariables with greater impact on the spatial distribution of soil units, in order of importance, were geological, topographic and climatic. Digital classification was based on 142 randomly distributed training areas and 60 sites for validation of results. In the watershed, according to the FAO (2014) WRB Classification System, the following soil groups were identified satisfactorily (76.67% for overall accuracy and 71.20% for the kappa index): Cambisols (35.8%), Fluvisols (7.16%), Leptosols (48.25%), Regosols (8.00%) and Vertisols 0.79%). DSM satisfactorily determined the spatial distribution of soil units in the watershed and identified the most influential environmental covariables.

Resumen: La escasez de mapas con una distribución detallada de las unidades de suelo representa una limitante frecuente para la toma de decisiones, el modelado hidrológico y determinación del potencial productivo de un área. En este trabajo se aplicó la técnica de Mapeo Digital de Suelos (MDS), a través del Análisis de Componentes Principales (ACP), para obtener la distribución espacial de las unidades de suelo. El área de estudio corresponde a la cuenca del río Mixteco, con una superficie de 655 903 ha, que se ubica en el estado de Oaxaca. Para el MDS se emplearon covariables ambientales del tipo topográficas, hidrológicas, climáticas y geológicas. Las covariables ambientales de mayor impacto, en la distribución espacial de las unidades de suelo, en orden de importancia fueron las geológicas, topográficas y climáticas. La clasificación digital se basó en 142 áreas de entrenamiento y 60 sitios para la validación de resultados, distribuidos aleatoriamente. En la cuenca, de acuerdo al Sistema de Clasificación WRB de la FAO (2014), a través del MDS se identificaron de manera satisfactoria (precisión global de 76.67% y un Índice Kappa de 71.20) los siguientes grupos de suelos Cambisoles (35.8%), Fluvisoles (7.16%), Leptosoles (48.25%), Regosoles (8.00%) y Vertisoles (0.79%). El MDS determinó satisfactoriamente la distribución espacial de las unidades de suelo en la cuenca e identificó las covariables ambientales de mayor influencia.

Abstract This research analyzes the influence of existing social relations within a group of 22 producers of rambutan (Nephelium lappaceum) of Soconusco, Chiapas in 2014. The joint actions were analyzed related to improving the marketing of their product. Building scale relational links was used for collective work composed identification levels, contribution, collaboration, cooperation and partnership. Through the analysis of social networks (ARS) the number of relationships, and the density indicators and index for each level of centralization were identified. The results indicate a significant decline in relations present (47, 24, 11, 6, 3) in ascending order of the assessed levels; the higher the ratio, the lower their number. The lowest densities were reported in collaboration levels (1.6%), cooperation (0.09%) and association (0.07%). a strong social dislocation is observed mainly attributable to previous organizational experiences, individualism, and different visions of productive activity. a scenario of mistrust and poor commitment among members that negatively influences the collective enterprises is observed. It is concluded that it is necessary to take actions that promote greater social articulation, confidence and organizational culture among producers, before or on par with commercial integration initiatives.

Resumen La presente investigación analiza la influencia de las relaciones sociales existentes al interior de un grupo de 22 productores de rambután (Nephelium lappaceum) del Soconusco, Chiapas en 2014. Se analizaron las acciones conjuntas relacionadas con la mejora de la comercialización de su producto. Se empleó la escala de construcción de vínculos relacionales para el trabajo colectivo integrada por los niveles de identificación, aportación, colaboración, cooperación y asociación. A través del análisis de redes sociales (ARS) se identificaron el número de relaciones, y los indicadores de densidad e índice de centralización por cada nivel. Los resultados indican una disminución considerable en las relaciones presentes (47, 24, 11, 6, 3) en orden ascendente de los niveles evaluados; a mayor nivel de relación, menor número de éstas. Las densidades más bajas se reportaron en los niveles de colaboración (1.6%), cooperación (0.09%) y asociación (0.07%). Se observa una fuerte desarticulación social atribuible principalmente a experiencias organizativas previas, individualismo, y visiones diferentes de la actividad productiva. Se observa un escenario de desconfianza y deficiente compromiso entre los miembros que influye negativamente en los emprendimientos colectivos. Se concluye que es necesario realizar acciones que promuevan una mayor articulación social, confianza y cultura organizacional entre los productores, previo o a la par de iniciativas de integación comercial.

A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES) has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.