Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 409079
Title Predicting soil N mineralization: Relevance of organic matter fractions and soil properties.
Author(s) Ros, G.H.; Hanegraaf, M.C.; Hoffland, E.; Riemsdijk, W.H. van
Source Soil Biology and Biochemistry 43 (2011)8. - ISSN 0038-0717 - p. 1714 - 1722.
DOI http://dx.doi.org/10.1016/j.soilbio.2011.04.017
Department(s) Chair Soil Chemistry and Chemical Soil Quality
Chair Soil Biology and Biological Soil Quality
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2011
Keyword(s) nitrogen mineralization - microbial biomass - chemical methods - grassland soils - forest soils - indexes - availability - carbon - respiration - temperature
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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