ISHS Acta Horticulturae 563: International Conference on Environmental Problems Associated with Nitrogen Fertilisation of Field Grown Vegetable Crops
COMPUTER MODELS AS TOOLS FOR INTERPRETING FIELD EXPERIMENTAL DATA: CASE STUDIES ON THE MINERALISATION OF N FROM CROP RESIDUES AND THE RESPONSE OF LETTUCE TO N FERTILISER |
| Authors: | I.G. Burns, C.R. Rahn, G.D. Bending, M. Hardgrave, A. Lee |
| Keywords: | Crop residues, crop response, decomposition, fertiliser, lettuce, mineralisation, model, nitrogen, nitrate |
| Abstract:
Two case studies are presented to illustrate how different modelling approaches have been used to interpret data from field and glasshouse experiments in order to learn more about the underlying processes involved. The first study relates to the cycling of N in rotations and focuses on the role of crop residues as a N source. Experimental data is provided to illustrate differences in patterns of decomposition of residues from different crops. The release of N during this process is often assumed to be governed by the C:N ratio of the residue. This paper describes the use of a simple subroutine to show how the rate of mineralisation can be influenced by other chemical properties of the residues. A modified version of the HRI N response model (N_ABLE) incorporating this new subroutine has been shown to give much improved agreement with independent data on the availability of N to following crops. The second case study uses N_ABLE to examine the factors controlling the response of soil-grown glasshouse lettuce to N fertiliser. Tests showed that the original model (which was developed for field grown vegetables) underestimated lettuce growth at low fertiliser levels. Investigations suggested that this was due to a more rapid rate of root growth and to a more efficient conversion of N into dry matter than predicted by the original model, which were probably caused by the different environmental conditions in the glasshouse. Adjusting the model to allow for these effects greatly improved the accuracy of simulation. | |
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