Comparing an empirical crop model with a functional structural plant model to account for individual variability

Abstract Individual variability generally exists in crop fields. It increases with an increase in plant population density, water or nutrient deficiency, or spatio-temporal irregularity, and often results in a reduction in yield. As individual variability exists in a community but is expressed through individuals, we studied it by applying two models, one at the stand level and the other at the individual level. The crop model PILOTE and the functional structural plant model (FSPM) GreenLab were applied to a field of maize ( Zea mays L.) to provide a numerical description of the crop at different levels. The delay and slower increase in LAI and in total dry matter at stand level compared to individual level, led us to hypothesize that uneven emergence could have an effect on variability. We derived a theoretical distribution of germination dates, which supported this hypothesis. In parallel, we used GreenLab to analyze possible sources of variability in accumulated biomass within a dynamic system, and to estimate possible parameters from experimental data. Using PILOTE and GreenLab, we successfully identified two typical types of individual variability in the maize field: variability in development over time and variability in competition for space during growth. Our method could be used in future research on the cause and influence of individual variability on performance, and to identify the link between an FSPM based on individual plants and a crop model at stand level.