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Chemical Composition of Crop Biomass Impacts Its Decomposition
Author(s) -
Johnson Jane M.-F.,
Barbour Nancy W.,
Weyers Sharon Lachnicht
Publication year - 2007
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2005.0419
Subject(s) - lignin , decomposition , hemicellulose , panicum virgatum , chemistry , agronomy , chemical composition , moisture , botany , horticulture , biology , bioenergy , biofuel , microbiology and biotechnology , organic chemistry
Understanding the interaction between plant components and their subsequent decomposition provides insights on how plant quality differences may influence C sequestration within a given management system. Our hypothesis was that decomposition is a function of biochemical composition when all other variables are constant (e.g., particle size, temperature and moisture). Recognizing the challenges of reconciling laboratory and field studies, this study examined the decomposition dynamics of five selected crops with varying composition under controlled temperature and moisture regimes. Residue materials were partitioned into leaf, stem, and root organs to give a clearer indication of compositional control on decomposition. Plant quality varied among species (alfalfa [ Medicago sativa L.], corn [ Zea mays L.], cuphea [ Cuphea viscosissima Jacq. · Cuphea lanceolata W.T. Aiton], soybean [ Glycine max (L.) Merr.] and switchgrass [Panicum virgatum L.]). A two‐component litter decomposition model was used to describe decomposition observed during 498 d. Stepwise multivariate regression indicated initial N concentration, starch, total lignin, and acid‐insoluble ash (AI ash) were the four best predictors ( r 2 = 0.83) of the rate of active component decomposition ( k a ); however, initial composition poorly predicted the rate of passive decomposition ( k p ). The best four‐component model ( r 2 = 0.43) identified by stepwise multiple regression for k p included AI ash, hemicellulose, N concentration, and C/N ratio. Rate constants are a function of the incubation period, thus making direct comparison among separate experiments difficult. Chemical recalcitrance appears to slow root decomposition; such chemical recalcitrance to decay may partially explain why roots have been found to contribute more C to the SOC pool than surface residues.