Impact of crop rotation and crop residue management on soil organic matter content

Introduction In Flanders, as in many European countries, organic matter decline in agricultural soils is a major problem and farmers are encouraged to improve their soil organic matter management. In this context, the Soil Service of Belgium developed the “Cslim” (Csmart) application, based on the Roth-C model. This application allows farmers to predict the organic carbon evolution in their fields, taking into account field history, soil type, initial C-content and future crop rotations. Literature data are used to estimate C inputs from crop residues as well as their decomposable/resistant plant material (DPM/RPM) ratios. However, several observations made in arable fields indicated that predictions made by the application didn’t always correspond to reality. Objectives In this research the organic matter input from 5 important arable crops in Flanders as well as their DPM/RPM ratios were investigated in order to improve the predictive power of the Cslim application. Materials and Methods Crop residues from maize, sugar beets, winter wheat, potatoes and peas were harvested in arable fields in the loam region of south-east Flanders. The residues were weighed, dried, grinded and analysed. The residues were then mixed with soil samples with known organic matter content, in quantities corresponding to field conditions, and incubated in controlled laboratory conditions. During incubation, CO2-production was measured weekly in order to determine organic matter decomposition. DPM/RPM ratios of the plant residues were derived from the mineralisation curves. Finally, Cslim simulations using the newly derived C inputs and DPM/RPM ratios were compared to simulations with the old values from literature, for different crop combinations. Results and conclusion The amounts of crop residues measured in the fields were significantly higher than the figures given in literature and used in the Cslim application. On the other hand, the measured decomposition rates and the derived DPM/RPM ratios of the plant residues were comparable to the data found in literature. Therefore it was concluded that the Cslim application could be significantly improved using more realistic amounts of crop residues. If farmers can indicate the expected average yields of the crops in each simulation, a good estimation of the crop residues can be made.