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BioStar: A simple crop model for the assessment of agricultural biomass potentials in Lower Saxony, Germany
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Datum
2010
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Shaker Verlag
Zusammenfassung
Crop models have found widespread acceptance in the field of crop breeding, applied agricultural research and optimisation of farming processes, to name just a few. Crop models have been in existence for about four decades now (Bouman et al., 1996) and refined insights into plant-physiological processes are added to new models as well as gained from the use of these models. The crop model presented in this paper had the development objective to be simple enough to be of utility to untrained e.g. non-research oriented users and still to process and produce input and output data at a complexity level which allows for adequate results as far as the prediction of biomass yields and water efficiency of chosen crops are concerned. The algorithms, of which the crop model BioSTAR is built, have been thoroughly researched from literature resources and fitted together to supply a biomass-calculation tool, requiring only a moderate amount of crop specific input data and the option for using the model on large spatial scales of 1:100000 – 1:200000, i.e. NUTS levels 2 and 3 (Nomenclature des unités territoriales statistiques) as well as environments with limited climate and soil information. Depending on the availability of input data, the model can calculate the biomass accumulation over the growing period for various cereals, maize, oilseed rape, sugar beet and sorghum. The algorithms of the model are programmed in the C++ programming language and a Java version for the implementation as a plug-in in the open source GIS-software Open Jump is in the planning phase. First modelling runs for Triticale and Maize on agricultural sites in southern Lower Saxony have rendered satisfactory results, with average overestimations of Triticale yields of less than 5% and 19% for Maize. The modelled results reflect a strong correlation (0,712) of yields with the availability of soil water and hence soil type and soil quality.