Vegetation restoration is a critical strategy for addressing ecosystem degradation globally. However, understanding the specific impacts of land-use changes, particularly the conversion of farmland to forestland and grassland, on soil nutrients and microbial biomass in the Loess Plateau remains limited and requires further evaluation. Therefore, this study was conducted to explore how these conversions affect soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), and microbial biomass components under various land-use patterns. We studied the SOC, TN, TP, soil microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), microbial biomass phosphorus (MBP) content and their ratios under six land-use patterns (Farmland (FL), Abandoned cropland (ACL), Natural grassland (NG), Alfalfa grassland (Medicago sativa L. (MS)), Spruce forestland (Picea asperata Mast. (PA)) and Cypress forestland (Platycladus orientalis (L.) Franco (PO))). The conversion of FL to grassland and forestland significantly increased C:N and C:P by 9.82~64.12%, 10.57~126.05%, and 51.44~113.40%, 22.10~116.09%, respectively. The conversion of FL to ACL reduced the C:N and C:P by 5.34~13.57% and 1.51~7.55%, respectively. The conversion of FL to NG can increase soil N:P. The conversion of FL to grassland and forestland increased soil MBC, MBN, and MBP by −31.54~84.48%, −48.39~1533.93%, −46.55~173.85%, and −34.96~17.13%, 68.72~432.14%, −38.39~318.46%, respectively. However, the MBC, MBN, and MBP contents in the soil converted from FL to ACL varied from −28.21~11.95%, 11.17~531.25%, and −82.64~70.77%, respectively. Soil SOC, TN, TP, available potassium (AK), pH, and soil bulk density (BD) are the main factors causing microbial biomass differences. These results indicate that converting farmland into forestland and grassland can improve soil nutrient structure and increase soil microbial biomass and carbon accumulation. The results of this study provide theoretical support for the scientific management of regional land.

Pingliang City has a complex topography and diverse soil types. To realize the improvement of soil according to local conditions and the reasonable and sustainable use of soil resources, an evaluation of soil quality in Pingliang City was carried out, based on the soil distribution situation in Pingliang City, adopting a method combining fuzzy mathematics and cluster analysis of the main evaluation factors, such as soil organic matter, topsoil depth, soil erosion intensity, soil moisture regime, effective soil thickness, soil texture, soil profile structure, soil nutrient status and topographical parts, to carry out a comprehensive evaluation. A comprehensive evaluation of soil quality was conducted in seven counties under the jurisdiction of Pingliang City, and the evaluation results were compared and analyzed against the national standard, “Cultivated land quality grade”, to provide a basis for the selection of scientific soil improvement methods. The results of the arable land quality grades indicate that the quality of farmland in Pingliang City is divided into three to ten grades, and the average quality grade of farmland is 6.83, which is in the middle–lower level, and the overall grade distribution shows the characteristics of low in the middle and high in the east and west. The results of fuzzy mathematics combined with cluster analysis indicated the following trends in soil quality for the 12 soil genera: Chuan black gunny soil > yellow moist soil > sandy soil > silt soil > mulching helilu soil> loessal soil> loamy soil > slope loessal soil > arenosol > tillage leaching gray cinnamon soil > calcareous gray cinnamon soil > red clay soil. The results of the combination of fuzzy mathematics and clustering were significantly correlated with the results of the evaluation of the soil quality of arable land; the correlation coefficient was 0.884. This indicates that the method can accurately and objectively review the advantages and disadvantages of arable land soil and can be effectively applied to the evaluation of the soil quality of agricultural soils in other regions. It is a complement to the existing evaluation of the soil quality of arable land and at the same time provides a reference for the improvement of soil quality in agricultural regions.