A virtual spreader to overcome experimental limits : Example of use to deepen the meaning of the transverse coefficient of variation
Résumé
A virtual spreader was modelled by combining the use of theoretical motion equations and statistical distributions of input parameters. These parameters were deduced from experimental measurements using a custom-made spreader, an imaging system, a particle impact recording device and a rotating test bench. Using this model, each spread pattern was computed using a random selection of values following the statistical distribution of each input parameter. Using simulations, we quantified how the CV value was affected by application rates and measurement protocols whatever spreader settings. Simulations showed the CV value and its measurement variability increased when the application rate decreased. The CV value also increased when the collection tray surface (used for spreader tests) decreased. The model was also used to analyse the CV value of blended fertilisers.
