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Ciencia del suelo
versión On-line ISSN 1850-2067
Resumen
ROJAS, JULIETA MARIANA; ROLDAN, MARÍA FLORENCIA y GUEVARA, GRACIELA SUSANA. INFLUENCIA DE ROTACIONES EN LA CALIDAD DEL SUELO EN LA ZONA CENTRAL DEL CHACO Y SU RELACIÓN CON LA PRODUCCIÓN DE ALGODÓN. Cienc. suelo [online]. 2015, vol.33, n.2. ISSN 1850-2067.
Crop rotation has been widely recommended to improve soil quality (SQ). The objective of this study was to analyze the influence of a 5- year cycle of rotation on SQ evaluating in an integrated way through multivariate analysis the parameters pH, electrical conductivity (EC), total organic carbon (TOC), particulate organic carbon (POC), organic carbon associated to the mineral fraction (AOC), total nitrogen (Nt), phosphorus (P) and bulk density (Bd); and to evaluate test crop (cotton) yields in relationship to the set of parameters. It was hypothesized that: a) rotation influence SQ evaluated through a set of parameters and b) cotton yields as test crop can be associated with one or more indicators of SQ. Composite samples at 0-10 and 10-20 cm in experimental plots of the EEA INTA Sáenz Peña (Chaco, Argentina) were taken. Three rotations were analyzed: maximum coverage (greater presence of grasses and crops per year), continuous cotton (almost monoculture) and minimum coverage, by principal component analysis (PCA), for each depth. Soil parameters were considered as active variables and cotton yield as a supplementary variable. The parameters that defined the main differences were P, EC and POC, multivariate analysis was a useful tool to select them. Cotton yields were more closely associated with TOC, AOC and POC. The rotation with greater coverage, and the presence and frequency of grasses differed from others because of their EC values and P content on the surface and POC in the subsurface. A major contribution of residues by this rotation could have influenced POC and EC; the highest P extraction by corn and soybeans caused lower levels of this element.
Palabras clave : Soil quality, Principal component analysis, Particulate organic carbon, Cotton.