Submitted to: Journal of Soil Biology and Biochemistry
Publication Type: Peer reviewed journal
Publication Acceptance Date: 5/21/1997
Publication Date: N/A
Citation: Interpretive Summary: Crop residue decomposition models are significant components of soil erosion models because of the protective action of residues on the soil surface. Modeling of crop residue decomposition requires information on the rate of mass loss from crops. This type of information is usually collected from experiments where the residues are allowed to decompose in the field or in the laboratory over a long period of time. This study evaluated a method (substrate-induced respiration) for predicting residue decomposition coefficients after a short period of exposure to the field environment. The procedure needed to be modified with the additional data collected in this study. A new prediction equation was developed that appeared to work well with the short term data. The new equation has the potential to reduce labor and time needed to develop crop residue decomposition coefficients.
Technical Abstract: Modeling of crop residue decomposition for nutrient cycling and effectiveness of residues to control soil erosion requires information on crop specific decomposition coefficients (k). Respiration on decomposing residues reflects the activity of the microbial community and should give an indication of the residue decomposition rate. A method for estimating k kusing substrate-induced respiration (SIR) on plant residues was evaluated. Basal respiration, total SIR, fungal SIR, and bacterial SIR were measured on five crop residues monthly for one year. Mass loss from the residue were used to determine k for a single exponential decay function. Predictions of k from SIR using the equation proposed by Neely et al. (1991) were not adequate for all five crops. A new equation (-k=-6.07* 10**-4 + 6.23*10**-6) was determined using the previously published data and data from the current study. Improved estimations of k were made from SIR at the 60 day sampling with the new equation. Predicting k from SIR could greatly reduce the labor and time involved in evaluating decomposition differences between residues.