Soils provide a broad set of vital ecosystem services and sustains the production of food and fibers, balancing the ecosystem. Thus, from the perspective of soil quality, it is defined as an ability to balance within the ecosystem to sustain biological productivity, promoting the health of plants and animals, being evaluated by traditional indicators as physical, chemical and biological indicators, so the present work aims to estimate the soil quality index using multivariate models using soil biological attributes and validation with growth variables of the bioindicator plant. The study was developed in the agricultural area in P. Prudente, SP, the points collected were georeferenced, collections in depth of 0 -20 cm, microbiological analysis, microbial carbon and nitrogen biomass, dehydrogenase, respiration and microbial coefficient, having a bioindicator plant curly lettuce (Lucy Brown) as a validator of the soil. The results were discovered using the PCA model for the identification of autos vectors and autos values, grouping and identifying their collinearities, linear regression, r-pearson validation and cluster heuristic analysis. The microbial attributes and the bioindicator plant discriminated the agricultural areas evaluated with establishment and validation of SQI. The metabolic coefficient and N of the microbial biomass dissipation of the highest covariance values by multivariate analysis. The reforestation area with native species (SQI0.782%) and the livestock crop integration system (SQI0.765%) were evaluated as areas with better soil quality
Microbial carbon and nitrogen cycling responses to drought and temperature in differently managed mountain grasslands
