A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Harvest time prediction of silage maize - model calibration, validation, and implementation in practical agriculture
Silage maize maturation, particularly the genotype dependent differences in maturation between ear and stover, are extensively discussed in Germany currently. Points of particular interest are the determination of the optimum harvest date and the possibilities to predict maturation. The aim of a current project therefore was to develop a tool for predicting contents of dry matter (DM) and starch. For this purpose the suitability of three models, two growing-degree day (GDD) approaches and the mechanistic MAISPROG model, was tested. Model calibration and validation, which was based on a multi-year, multi-site experiment, showed a generally satisfactory model fit. The consideration of radiation and soil water availability in MAISPROG improved the prediction accuracy substantially compared to the GDD models. In 2005, MAISPROG was implemented nationwide as a regional harvest time prognosis tool for practical use in agriculture.
Harvest time prediction of silage maize - model calibration, validation, and implementation in practical agriculture
Silage maize maturation, particularly the genotype dependent differences in maturation between ear and stover, are extensively discussed in Germany currently. Points of particular interest are the determination of the optimum harvest date and the possibilities to predict maturation. The aim of a current project therefore was to develop a tool for predicting contents of dry matter (DM) and starch. For this purpose the suitability of three models, two growing-degree day (GDD) approaches and the mechanistic MAISPROG model, was tested. Model calibration and validation, which was based on a multi-year, multi-site experiment, showed a generally satisfactory model fit. The consideration of radiation and soil water availability in MAISPROG improved the prediction accuracy substantially compared to the GDD models. In 2005, MAISPROG was implemented nationwide as a regional harvest time prognosis tool for practical use in agriculture.
Harvest time prediction of silage maize - model calibration, validation, and implementation in practical agriculture
Herrmann, A. (author) / Kornher, A. (author) / Höppner, Frank (author) / Greef, Jörg Michael (author) / Rath, J. (author) / Taube, F. (author)
2006-01-01
Audio file
Electronic Resource
English
Environmental Life Cycle Assessment of Silage Maize in Relation to Regenerative Agriculture
| DOAJ | 2024
Unwelcome harvest: Agriculture and pollution
| Elsevier | 1992
A Blighted Harvest: The World Bank and African Agriculture
| Online Contents | 1995