Background: In precision agriculture, rapid, non-destructive, cost-effective and convenient soil analysis techniques are needed for soil management, crop quality control using fertilizer, manure and compost, and variable-rate input for soil variability in a field. Visible and near-infrared spectroscopy is an effective measurement method for estimating multiple soil properties at once. Methods: The experimental site is a commercial paddy field in lbaraki Prefectural Government, Japan. The experiment was conducted on 5 fields (6.4ha) after harvesting for development of multiple local calibration models (MLCM). To develop MLCM, soil samples were collected a total of 100 soil samples from the corresponding scanning positions of Vis-NIR data using Tractor-mounted soil analysing system (SAS). Partial least-squares regression coupled with leave-one-out cross-validation method were used to establish the relationship between Vis-NIR underground soil reflectance spectra captured by SAS and MLCM were obtained through soil analysis. To develop MLCM, the Unscrambler V9.8 software was used. We show coefficient of determination (R2) and residual prediction deviation (RPD). Results: We obtained MLCM based on Vis-NIR underground soil reflectance spectra collected using SAS. The investigated soil properties were moisture content, soil organic matter, pH, electrical conductivity, cation exchange capacity, total carbon, ammonium nitrogen, hot water exchangeable nitrogen, nitrate nitrogen, total nitrogen, exchangeable potassium, exchangeable calcium, exchangeable magnesium, hot water soluble soil boron, soluble copper, exchangeable manganese, soluble zinc, available phosphate, C/N ratio, MgO/K20 ratio, CaO/MgO ratio, lime saturation degree, base saturation degree, phosphate absorption coefficient, exchange acidity, free iron oxide, sodium oxide, available silicate, bulk density, sand, silt and clay. The accuracy of MLCM on leave-one-out cross-validation method was obtained R2 from 0.70 to 0.92 and RPD form 1.81 to 3.61. Discussion & conclusion: To get good local calibration model of Exchange acidity, sodium oxide and soluble zinc require addition of new sample data and reanalysis.