Developing techniques that are easily accessible to producers and extension agents would facilitate the assessment of pasture degradation in rural areas. The objective of this work was to evaluate the sensitivity of field-based indicators of soil quality at different levels of degraded pastures, validate these indicators with those determined in laboratory. Six areas were chosen: four areas of pastures in different gradients of degradation visually assessed (Degraded Pasture 1 -P 1 ; Degraded Pasture 2 -P 2 ; Degraded Pasture 3 -P 3 ; and Degraded Pasture 4 -P 4 ), in descending order of degradation; an area of Capoeira (natural vegetation of soil recovery); and a secondary Forest used as reference. The soil under all areas was an Ultisol clayey, and field determinations used were: soil coverage rate (Soil Cov. Rt ), depth of the root system (D RS ) and "A horizon" thickness. Laboratory determinations were: soil density, total porosity (Tp), macroporosity (Ma), microporosity (Mi), Ca , organic carbon (OC), base (BS) and aluminum saturation (AS). Also, the organic matter compartments such as particulate organic matter (POM), particulate organic carbon and carbon fraction associated with soil minerals were determined. Soil quality ranking were assigned to the different areas, and orthogonal contrasts were made to compare the stages of degradation. Subsequently, linear correlations were adjusted to test whether there were significant differences for the field and laboratory indicators among the areas of study. Soil quality ranking assigned represented the levels of degraded pasture visually observed in field, therefore allowing correlations with field indicators "A horizon" thickness (Rainy season r =0.71 and Dry season r =0.91) and D RS (Rainy season r =0.81 and dry season r =0.58). Similar correlations were found when the Soil Cov. Rt was used, where correlations were observed with the "A horizon" thickness (Rainy season r =0.61 and Dry season r =0.75) and D RS (Rainy season r=0.76 and Dry season r =0.84). The field and laboratory determinations showed statistical differences between study areas, indicating that they were sensitive to levels of degradation. Through field determinations, it was possible to separate four groups of degradation: reference (Forest), low degradation (P 4 and P 3 ), under recovery (Capoeira) and high degradation (P 1 and P 2 ). The easily determined field-based quality indicators showed significant correlations with the laboratory values: BS, AS, Ma and POM, especially on the 0-5 cm surface layer, showing small variation between sampling periods and indicating the possibility of using these indicators to differentiate levels of degraded pastures with good accuracy.