Soil fertility assessment is a key for sustainable planning of a particular area. Thus, the present study was conducted to assess the soil fertility status of the Regional Agricultural Research Station, Parwanipur, Bara, Nepal. The study area is situated at the latitude 27°4’40.9’’N and longitude 84°56’9.85”E at 75masl altitude. Altogether 76 soil samples were collected based on the variability of land at 0-20 cm depth. The texture, pH, OM, total N, available P2O5, K2O, Ca, Mg, S, B, Fe, Zn, Cu and Mn content in the samples were determined following standard analytical methods. Arc-GIS 10.1 was used for soil fertility mapping. The soil structure was angular blocky, and varied between grayish brown (10YR 5/2) and dark grayish brown (10YR 4/2) in color. The sand, silt and clay content were 24.41±0.59%, 54.57±0.44% and 21.03±0.32%, respectively and categorized as silt loam and loam in texture. The soil was moderately acidic in pH (5.67±0.09), low in organic matter (0.74±0.04%) and available Sulphur (0.8± 0.1 ppm). The total nitrogen (0.06±0.001%), available boron (0.59±0.08ppm) and available zinc (0.51±0.05ppm) were low. Furthermore, available potassium (50.26±2.95ppm), available calcium (1674.6±46.3ppm) and available magnesium (175.43± 8.93ppm) were medium. Moreover, available copper (1.36±0.06 ppm) and available manganese (16.52±1.12 ppm) were high, while, available phosphorus (77.55±6.65 ppm) and available iron (85.88±7.05 ppm) were found high. It is expected that the present study would help to guide practices required for sustainable soil fertility management and developing future agricultural research strategy in the farm.

Although algorithms are well developed to predict soil organic carbon (SOC), selecting appropriate covariates to improve prediction accuracy is an ongoing challenge. Terrain attributes and remote sensing data are the most common covariates for SOC prediction. This study tested the predictive performance of nine different combinations of topographic variables and multi-season remotely sensed data to improve the prediction of SOC in the cultivated lands of a middle mountain catchment of Nepal. The random forest method was used to predict SOC contents, and the quantile regression forest for quantifying the prediction uncertainty. Prediction of SOC contents was improved when remote sensing data of multiple seasons were used together with the terrain variables. Remote sensing data of multiple seasons capture the dynamic conditions of surface soils more effectively than using an image of a single season. It is concluded that the use of remote sensing images of multiple seasons instead of a snapshot of a single period may be more effective for improving the prediction of SOC in a digital soil mapping framework. However, an image with the right timing of cropping season can provide comparable results if a parsimonious model is preferred.

Soil fertility evaluation of an area or region is most basic decision making tool for the sustainable soil nutrient management. In order to evaluate the soil fertility status of the Regional Agricultural Research Station (RARS), Tarahara, Susari, Nepal. Using soil sampling auger 81 soil samples (0-20 cm) were collected based on the variability of land. The collected samples were analyzed for their texture, structure, colour, pH, OM, N, P 2 O 5 , K 2 O, Ca, Mg, S, B, Fe, Zn, Cu and Mn status. The Arc-GIS 10.1 software was used for the preparation of soil fertility maps. The soil structure was granular to sub-angular blocky and varied between brown- dark grayish brown and dark gray in colour. The sand, silt and clay content were 30.32±1.4%, 48.92±0.89% and 20.76±0.92%, respectively and categorized as loam, clay loam, sandy loam, silt loam and silty clay loam in texture. The soil was moderately acidic in pH (5.98±0.08). The available sulphur (2.15±0.21 ppm), available boron (0.08±0.01 ppm) and available zinc (0.35±0.03 ppm) status were very low, whereas extractable magnesium (44.33±6.03 ppm) showed low status. Similarly, organic matter (2.80±0.07%), total nitrogen (0.09±0.004 %), extractable calcium (1827.90±45.80 ppm) and available copper (1.15±0.04 ppm) were medium in content. The available phosphorus (39.77±5.27 ppm), extractable potassium (134.12±4.91 ppm), and available manganese (18.15±1.15 ppm) exhibits high status, while available iron (244.7±19.70 ppm) was very high. The fertilizer recommendation can be done based on determined soil fertility status to economize crop production. Furthermore, research farm should develop future research strategy accordance with the prepared soil data base.