Typology of exogenous organic matters based on chemical and biochemical composition to predict potential nitrogen mineralization

• Published in: Bioresource technology Vol. 101; no. 1; pp. 157 - 164
• Main Authors: Lashermes, G., Nicolardot, B., Parnaudeau, V., Thuriès, L., Chaussod, R., Guillotin, M.L., Linères, M., Mary, B., Metzger, L., Morvan, T., Tricaud, A., Villette, C., Houot, S.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.01.2010; [New York, NY]: Elsevier Ltd; Elsevier
• Subjects: agricultural soils; agricultural wastes; Algorithms; Biochemical fractionation; Biological and medical sciences; Biotechnology; chemical composition; Computer Simulation; Exogenous organic matter; food wastes; Fundamental and applied biological sciences. Psychology; Hierarchical classification; kitchen waste; Life Sciences; mineralization; Minerals - analysis; Minerals - chemistry; Models, Chemical; N mineralization; nitrogen; Nitrogen - analysis; Nitrogen - chemistry; nutrient availability; Organic Chemicals - analysis; Organic Chemicals - chemistry; organic matter; soil nutrients; soil organic matter; Typology; EOM; Hierarchical classification; N91; MFA; CEL; LIG; N mineralization; Biochemical fractionation; N14; HEM; SOL; C o; Exogenous organic matter; HC; Typology; N o; Exogenous; Fractionation; Organic matter; Biochemical analysis; Prediction; Biochemistry; Nitrogen; Nitrogen cycle; Mineralization; typology; exogenous organic matter; n mineralization; biochemical fractionation; hierarchical classification
• ISSN: 0960-8524; 1873-2976
• DOI: 10.1016/j.biortech.2009.08.025

Our aim was to develop a typology predicting potential N availability of exogenous organic matters (EOMs) in soil based on their chemical characteristics. A database of 273 EOMs was constructed including analytical data of biochemical fractionation, organic C and N, and results of N mineralization during incubation of soil–EOM mixtures in controlled conditions. Multiple factor analysis and hierarchical classification were performed to gather EOMs with similar composition and N mineralization behavior. A typology was then defined using composition criteria to predict potential N mineralization. Six classes of EOM potential N mineralization in soil were defined, from high potential N mineralization to risk of inducing N immobilization in soil after application. These classes were defined on the basis of EOM organic N content and soluble, cellulose-, and lignin-like fractions. A decision tree based on these variables was constructed in order to easily attribute any EOM to 1 of the 6 classes.