La producción de mezcal es una actividad económica y social importante en el estado de Oaxaca. Con el objeto de conocer a los tipos de suelos donde se cultiva el maguey mezcalero, se realizó un estudio etnoedafológico en 2014 en La Soledad Salinas, San Pedro Quiatoni, Oaxaca. Las clases de tierras identificadas y caracterizadas por los productores se compararon con la clasificación científica de suelos utilizando a los sistemas WRB y taxonomía de suelos. Con la clasificación campesina o local se identificaron seis clases de tierras mientras que con la WRB se establecieron tres unidades con cinco calificadores grupo I y con la Taxonomía de Suelos dos órdenes y cinco Subgrupos. Se concluye que para estudios detallados, con el fin de generar recomendaciones a nivel parcelario la clasificación campesina de suelos genera resultados más precisos, con menor tiempo y costo que los realizados con procedimientos técnicos.
Changes in soil structure can be monitored in undisturbed soil samples through the micromorphometric analysis of thin sections. In this methodology, it is common that individual images (three to ten repetitions) are used and that they cannot be related in different scales between soil components; in addition, although a minimum study area is established, its representativeness in the soil components is unknown. The objective of this study was to quantify the soil constituent (pores, aggregates, and roots) and to compare the values obtained from individual images versus high-resolution mosaics from a complete thin section. Unaltered samples were collected in three soils with different clay contents (Entisols, Inceptisols, and Vertisols) and presence of maize roots in the same phenological development stage (physiological maturity). Three thin sections of each soil (5 × 7 cm × 30 μm 1865 mm 2) were prepared and sequential images of 11.1× 7.4 mm (63 in total) were obtained at 2× magnification using a petrographic microscope and plane polarized light (PPL). The high-resolution mosaics (2.6 µm píxel-1) at a colour depth 24 bits (8 bits × 3 bands in standard RGB) were built using space operators; subsequently, three, five and ten images were randomly selected. The individual images and the mosaics were transformed by principal component analysis in ArcGis® and soil constituents were delimited according to their variances values. The results indicate that individual images are recommended only to quantify porosity or in homogeneous systems in structure and color, but not in heterogeneous systems where the data obtained show high variability. Even when the results are similar to those calculated in the mosaics, the dispersion of the data is high (variance 5 times greater than the mean) and with little representation. In contrast, high-resolution mosaics offer the total quantification of the thin section and soil components can be grouped into classes or categories to observe intra or inter relations in the soil system. In addition, the soil components can be related to different scales, for example macroaggregates and roots.
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