Integrated evaluation of physical, chemical and biological properties of agricultural soil

A variety of microbiological soil tests were evaluated as indicators of soil quality and as predictors of fertility. Methods for evalutation of microbiological tests together with physical and chemical indicators were also studied. Prior to the actual evaluation of the microbiological soil tests, a strategy to select soils as different as possible with respect to their physical and chemical characteristics was developed. As sampling was not possible during the whole year, the effects of frozen and cold storage on the microbiological analyses used in the studies were also evaluated. The variations and relations of physical, chemical, and biological data were studied within a single field, and between fields from all over Sweden. Principal component analysis (PCA) was used for integrated evaluation of the data. The between field variations were also related to a fertility index achieved from a pot-experiment. The ability of a combination of soil quality index data to predict C- and N-yield in ryegrass was tested with multivariate regression techniques. Standard laboratory analyses were employed for texture, pH, available nutrients, and organic matter content. The microbiological variables assessed were basal respiration rate, substrate induced respiration (SIR), N-mineralization, potential ammonium oxidation, potential denitrification and phosphatase activity. The analysis of NIR-spectra provided a fast and cost-effective tool for the selection of samples representative of a large area. Frozen storage for 13 month of samples from annually frozen sites did not affect the microbial biomass or activity in any decisive way. The soil properties within fields varied as much as between fields. This has to be considered when choosing sampling strategy. tool for the integrated evaluation of soil quality data. The relation between factors regulating the microbial population and its degradation of the organic matter within fields and between fields was similar. However, there were a number of additional influencing factors between fields. It was therefore recommended to use separate models for different districts. As much of the influence of physical and chemical soil properties could be better reflected by microbial activities, microbial indicators were shown to be potential integral indicators of soil quality.