Abstract:
Lodging lowers the productivity of sugarcane through a reduction in radiation use efficiency and stalkdamage. However, there are few reports of experiments specifically designed to quantify effects of lodg-ing in sugarcane. Efforts to model onset and progression of lodging, and the impact on crop productivity,have not been attempted. The objectives of this paper were to quantify effects of lodging on sugarcaneand to develop modeling capability in terms of predicting lodging onset, progression and impact. Fieldexperiments with irrigated ratoon crops were conducted at Pongola, South Africa. In one treatment thecane in each plot was allowed to grow through bamboo frames that prevented lodging. In the othertreatment, the cane was not supported and could lodge at any stage. The degree of lodging was capturedweekly by a rating that ranged from 1 to 9, where 1 = fully erect cane and 9 = completely lodged cane.At harvest estimated recoverable crystal percent (ERC %) of stalks and yield (cane and ERC) was mea-sured for each plot. Lodging resulted in decreased ERC yields of up to 20.6%. An algorithm for simulatinglodging when aboveground biomass (including rainfall and irrigation water retained on it) exceeds avariety-specific threshold, and which also considers wind speed and soil water content, was evaluatedfor predicting the extent and impact of lodging in the Pongola experiments, as well as for four deficitirrigation treatments of a field experiment conducted in Komatipoort, South Africa. The study showedthat the onset of lodging was simulated reasonably well for various soil/crop/atmospheric conditions,while the extent of lodging at harvest was simulated very accurately for all crops. Simulated lodging wasprimarily driven by crop size and lodging events were triggered by rainfall that added weight to the aerialmass of the crop, and reduced the anchoring ability of the soil through saturation of the top soil. Moreaccurate simulation of lodging, and its impacts on yield, will improve the accuracy of yield predictionsby crop models, increasing their value in applications such as crop forecasting, climate change studiesand exploring crop improvement and management options.
