Predicting soil N mineralization: Relevance of organic matter fractions and soil properties |
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Authors: | Gerard H. Ros Marjoleine C. Hanegraaf Willem H. van Riemsdijk |
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Affiliation: | a Wageningen University, Department of Soil Quality, P.O. Box 47, NL-6700 AA Wageningen, The Netherlands b Nutriënten Management Instituut, NMI B.V., P.O. Box 250, NL-6700 AG Wageningen, The Netherlands |
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Abstract: | Distinct extractable organic matter (EOM) fractions have been used to assess the capacity of soils to supply nitrogen (N). However, substantial uncertainty exists on their role in the N cycle and their functional dependency on soil properties. We therefore examined the variation in mineralizable N and its relationship with EOM fractions, soil physical and chemical properties across 98 agricultural soils with contrasting inherent properties and management histories. Mineralizable N was determined by aerobic incubation at 20 °C and optimum moisture content for 20 weeks. We used multivariate statistical modelling to account for multi-collinearity, an issue generally overlooked in studies evaluating the predictive value of EOM fractions. Mineralization of N was primarily related to the size of OM pools and fractions present; they explained 78% of the variation in mineralizable N whereas other soil variables could explain maximally 8%. Both total and extractable OM expressed the same soil characteristic from a mineralization perspective; they were positively related to mineralizable N and explained a similar percentage of the variation in mineralizable N. Inclusion of mineralizable N in fertilizer recommendation systems should be based on at least one OM variable. The most appropriate EOM fraction can only be identified when the underlying mechanisms are known; regression techniques are not suitable for this purpose. Combination of single EOM fractions is not likely to improve the prediction of mineralizable N due to high multi-collinearity. Inclusion of texture-related soil variables or variables reflecting soil organic matter quality may be neglected due to their limited power to improve the prediction of mineralizable N. |
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Keywords: | Mineralizable nitrogen Multivariate analysis Soil organic matter Soil properties Extractable organic nitrogen |
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