@article{LIU2026, 
author = {Yingying LIU and Jirui GONG and Xiaofei GAO},
title = {Comparative calibration of soil organic carbon determination methods for different land use types},
year = {2026},
journal = {Experimental Technology and Management},
volume = {43},
number = {10},
pages = {43-49},
keywords = {soil organic carbon, pretreatment method, silver cup method, centrifugation method, land use type},
url = {https://www.sciopen.com/article/10.16791/j.cnki.sjg.2026.10.006},
doi = {10.16791/j.cnki.sjg.2026.10.006},
abstract = {ObjectiveAs soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems, its precise determination provides crucial technical support for assessing soil quality, calculating the potential of terrestrial carbon sinks, and promoting low-carbon agriculture. In recent years, elemental analysis has become the mainstream method for detecting SOC content; however, the pretreatment step for removing inorganic carbon directly affects measurement accuracy. The silver cup and centrifugation methods are two widely used and relatively stable pretreatment approaches. However, existing studies mostly focus on standard soil compounds, neglecting the influence of key factors such as land use types, soil-forming environments, and soil matrix compositions. This narrowness makes it difficult to provide method selection references for the efficient and precise detection of large quantities of various soil types. Therefore, this study selected soils from four typical land use types—agricultural land, grassland, urban green space, and sandy wasteland—to systematically explore their impact on measurement results obtained using the two pretreatment methods, thereby providing a scientific basis and technical support for the efficient and precise detection of organic carbon in different soil types.MethodsThe study used a VELP CN802 carbon-nitrogen analyzer to determine the SOC content based on the Dumas dry combustion method. After strictly verifying the instrument’s precision and accuracy, the accuracy and reproducibility of the silver cup and centrifugation methods were evaluated using standard soil compounds. Subsequently, 39 soil samples from multiple provinces (regions), including Heilongjiang, Jilin, Inner Mongolia, and Shaanxi, were selected. For each sample, three replicates were prepared using the same pretreatment methods, and each sample was measured three times consecutively. The average SOC content of each sample was calculated based on the mean of nine measurements, and the relative difference between the values from the two pretreatment methods was compared to assess inter-method consistency and variance.ResultsThe results showed that both pretreatment methods had good stability. The silver cup method had higher accuracy, while the centrifugation method was low-cost and convenient for batch operations. Land use types significantly affected assessment consistency by altering the SOC content, component characteristics, and the inorganic carbon state. The relative difference generally followed the order agricultural land < urban green space < grassland < sandy wasteland, and it was significantly positively correlated with soil pH. The conversion equation (y = 1.0191x + 0.0374, R2 = 0.9995) based on the data obtained could effectively and correctly measure the centrifugation method data, reducing the relative error to 0.04%–5.15%, meeting industry standards and achieving a balance between detection cost and accuracy.ConclusionsThis study provides referential methods for the large-scale, efficient, and precise determination of SOC in different land use types. However, due to the limited number and coverage of samples, the influence of microscopic factors such as soil texture and SOC components could not be deeply analyzed. Thus, the generalizability of the conclusions and correction models needs verification. In the future, sample type and spatial coverage can be expanded, and deviation mechanisms can be analyzed in combination with microscopic techniques to build a multi-method optimization system and a universal correction database, providing a more reliable technical basis for the precise detection of SOC content.}
}