Search

Plant height has a deep influence on the productivity of many crops, as it involves susceptibility to lodging, crop–weed competition, and the achievement of favorable harvest index. Nevertheless, modellers have practically ignored related ecophysiological processes, especially those modulated by management practices. The aim of this study was to analyze and model the processes involved with the effects of management on rice (Oryza sativaL.) elongation. Data were collected in two greenhouse experiments (2010–2011) where three factors (floodwater level, N fertilization, sowing density) were arranged in a split‐plot design with three replicates. The model proposed demonstrated its suitability in reproducing both the dynamics involved with tissue elongation in the different phenological phases and the effects of submergence and N luxury consumption on elongation rates. Relative root mean square error (RRMSE) ranged between 4.23 and 12.41% for different treatments and years. The inclusion of algorithms for the impact of agronomic practices on plant height in cropping system models would increase their suitability for scenario analyses and for in silico ideotyping studies, owing to the great interest shown by geneticists in related traits. Moreover, this study—performed with students of a Cropping Systems MS course—demonstrated once more the power of modeling within educational activities. In this case, models were not the subject of the teaching but tools for analyzing processes and formalizing new knowledge.