Prediction of available nitrogen response to organic material application using soil carbon content in agricultural soils of Japan

This study aims to examine the potential of using soil total carbon (TC) to predict changes in available nitrogen (AvN) by applying organic materials, with a rapid estimation method, while also evaluating the effects of soil temperature, soil type, and organic material type. Surface soil samples were collected from 16 paddy field sites (55 treatment plots) and 15 upland field sites (49 treatment plots) across Japan. Differences in AvN (ΔAvN) and TC (ΔTC) between plots where organic material was applied and those where chemical fertilizer was used were calculated, and the relationship between the two was assessed. Simple linear regression analysis yielded the following equations, indicating that ΔAvN following organic material application can be primarily explained by ΔTC: for paddy fields, ΔAvN (mg kg−1) = 4.27 × ΔTC (g kg−1) + 5.79 (R2 = 0.544, p < 0.0001); for upland fields, ΔAvN (mg kg−1) = 1.60 × ΔTC (g kg−1) + 0.20 (R2 = 0.677, p < 0.0001). Furthermore, ANCOVA analysis revealed that ΔAvN in both paddy and upland fields are primarily explained by ΔTC, regardless of soil temperature, soil type, or organic material type. Therefore, ΔTC can be a reliable indicator of ΔAvN, and given the wide geographic range and diverse organic materials included, the observed ΔAvN–ΔTC relationship is broadly applicable. In upland fields, it was suggested that adding soil temperature as a variable could improve prediction accuracy. The absence of correlation in Andosol paddy fields (p = 0.27) may be due to N dynamics under reducing conditions and the high C retention capacity of Andosols, making ΔAvN difficult to explain by ΔTC alone. To clarify why the effect of organic material type was not significant in both paddy and upland fields according to ANCOVA (p > 0.05), a promising approach is to analyze not only the C/N ratio but also N mineralization characteristics of the applied materials. In addition, examining the ΔAvN–ΔTC relationship immediately after the start of organic material application is important. These improvements will contribute to building a robust model for predicting long-term changes in AvN using TC variations.