By combining short laboratory incubations with rapid chemical tests and key soil properties, the research offers a faster, more precise way to estimate soil nitrogen supply.
Soils supply more nitrogen to rice crops than fertilizer alone, yet this contribution is rarely measured accurately. Rice accounts for about one-third of China’s grain production, and soil-derived nitrogen provides over half of the nitrogen accumulated in rice plants through microbial mineralization of organic matter. Quantifying this process is critical for guiding fertilizer application. However, fertilizer-omission field trials are strongly influenced by weather, irrigation, and external nitrogen inputs, while long-term laboratory incubations are labor-intensive and unsuitable for routine use. Although short-term incubations and rapid chemical extractions provide faster alternatives, their reliability across contrasting paddy soil regions is uncertain. Large regional differences in soil pH, texture, and organic matter quality therefore challenge universal prediction methods, underscoring the need for region-specific frameworks to estimate soil nitrogen supply more accurately and efficiently.
A study (DOI: 10.48130/nc-0025-0014) published in Nitrogen Cycling on 13 January 2026 by Xu Zhao’s team, Chinese Academy of Sciences, demonstrates that understanding how soils differ—not just how much nitrogen they contain—is key to smarter, region-specific nitrogen management in rice production.
Using a combination of controlled anaerobic incubations, rapid chemical extraction assays, and multivariate statistical analyses, this study systematically evaluated nitrogen mineralization (Nm) dynamics in paddy soils from two major rice-growing regions in China—the Yangtze River Delta (YRD) and Northeast China (NC). Soils were characterized for physicochemical properties and incubated for up to 112 days to quantify long-term Nm potential, while correlations between short-term and long-term mineralization were assessed to identify minimum representative incubation durations. In parallel, multiple rapid extraction methods (NaHCO₃, cold water, and hot water) were applied to estimate labile organic nitrogen pools, and structural equation modeling and regression analyses were used to identify key soil controls and develop predictive models for long-term Nm and mineralization efficiency (Nmr). The results revealed pronounced regional contrasts. YRD soils, despite having lower total nitrogen, organic carbon, C/N ratio, and cation exchange capacity than NC soils, showed substantially higher early-stage Nm rates and a 29.4% greater long-term mineralization potential, with nearly 85% of total Nm occurring within the first two weeks. Correspondingly, the shortest incubation period reliably representing long-term Nm was only 7 days for YRD soils, compared with 14 days for NC soils. Rapid extraction tests further indicated that YRD soils contained larger pools of labile, hydrolysable nitrogen, with UV-absorbing fractions (Na260) emerging as the strongest predictors of long-term Nm, whereas hot-water–extractable nitrogen (HWN) was more informative in NC soils. Across both regions, soil pH exerted the most consistent and dominant control on Nm and Nmr, though its influence interacted with texture, cation exchange capacity, and labile nitrogen fractions in a site-specific manner. By integrating short-term incubation data, rapid extraction indices, and soil properties, region-specific multivariate models explained up to 75% of the variation in long-term Nm after cross-validation, demonstrating that tailored, soil-type–specific frameworks substantially improve the prediction of soil nitrogen supply in paddy systems.
These findings help explain why rice systems in Northeast China achieve higher nitrogen-use efficiency with lower fertilizer inputs than those in the Yangtze River Delta, despite similar yields. The new models provide a practical framework for estimating soil nitrogen supply more quickly and accurately, allowing fertilizer recommendations to be tailored to local soil conditions. This approach could help reduce excessive nitrogen use, lower production costs, and mitigate environmental impacts such as nitrogen runoff and greenhouse gas emissions.
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References
DOI
10.48130/nc-0025-0014
Original Souce URL
https://doi.org/10.48130/nc-0025-0014
Funding information
This work was supported by the Natural Science Foundation of Jiangsu Province (Grant No. BK20241700), the National Natural Science Foundation of China (Grant No. 32402694), the Youth Innovation Promotion Association of the Chinese Academy of Sciences (Grant No. Y201956), Young Elite Scientists Sponsorship Program by CAST (Grant No. 2023QNRC001), Frontier Project from the Institute of Soil Science, Chinese Academy of Sciences (Grant No. ISSASIP2406), and the National Key Research and Development Program of China (Grant No. 2017YFD200104).
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