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Net nitrogen mineralization enhanced with the addition of nitrogen-rich particulate organic matter.

St. Luce, M., Whalen, J.K., Ziadi, N., and Zebarth, B.J. (2016). "Net nitrogen mineralization enhanced with the addition of nitrogen-rich particulate organic matter.", Geoderma, 262, pp. 112-118. doi : 10.1016/j.geoderma.2015.08.017  Access to full text


Particulate organic matter (POM) is a labile fraction of soil organic matter (SOM) that can contribute to nitrogen (N) mineralization. We added native and non-native POM to soils with contrasting properties and assessed net N mineralization during a 28 days incubation study. Soils (0–15 cm depth) for this study were a clay soil with a 3-year history of corn (Zea mays L.), a loam soil with a 2-year history of alfalfa (Medicago sativa L.) and sandy–loam and silty–clay–loam soils that were cropped in the previous 5 years with a corn-soybean (Glycine max L.) — corn–forage–forage [45% alfalfa + 55% timothy (Phleum pratense L.)] and corn–soybean–forage–forage–forage rotation, respectively. The POM was separated by size fractionation (> 53 μm) from coarsely sieved (> 6 mm) soil. The N concentration in POM followed the order loam > silty–clay–loam > clay > sandy–loam, whereas the acid unhydrolyzable fraction, a proxy for the lignin concentration, was the reverse. Compared to soil only, addition of N-rich POM from the loam soil increased net N mineralization in the clay soil and gave similar net N mineralization in the other soils, while addition of N-poor POM from the sandy–loam soil resulted in lower net N mineralization in the loam and silty–clay–loam soils. Multiple stepwise regression analysis showed that net N mineralized due to POM addition was related to the N concentration in the POM (partial R2 = 0.54) and the initial soil mineral N concentration (partial R2 = 0.33), suggesting that N mineralized from POM was related more to POM chemical composition than soil properties. We propose that information on POM chemistry in conjunction with soil mineral N concentration and texture could be useful for constructing N mineralization prediction models to improve N fertilizer management in agricultural soils.

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