Evaluation of Agricultural Production Systems Simulator as yield predictor of Panicum virgatum and Miscanthus x giganteus in several US environments

• Autores: Ojeda, Jonathan Jesus; Volenec, Jeffrey J.; Brouder, Sylvie M.; Caviglia, Octavio; Agnusdei, Monica Graciela
• Año de publicación: 2017
• Idioma: inglés
• Tipo de recurso: artículo
• Fuente: Global change biology Bioenergy 9 (4) : 796–816. (April 2017)
• Materia: Panicum Virgatum; Miscanthus; Sistemas de Explotación; Rendimiento; Técnicas de Predicción; Modelos de Simulación; Bioenergía; Biomasa; Farming Systems; Yields; Forecasting; Simulation Models; Bioenergy; Biomass; Estados Unidos; Switchgrass; Agricultural Production Systems Simulator; APSIM
• Institución: Instituto Nacional de Tecnología Agropecuaria

Simulation models for perennial energy crops such as switchgrass (Panicum virgatum L.) and Miscanthus (Miscanthus x giganteus) can be useful tools to design management strategies for biomass productivity improvement in US environments. The Agricultural Production Systems Simulator (APSIM) is a biophysical model with the potential to simulate the growth of perennial crops. APSIM crop modules do not exist for switchgrass and Miscanthus, however, re-parameterization of existing APSIM modules could be used to simulate the growth of these perennials. Our aim was to evaluate the ability of APSIM to predict the dry matter (DM) yield of switchgrass and Miscanthus at several US locations. The Lucerne (for switchgrass) and Sugarcane (for Miscanthus) APSIM modules were calibrated using data from four locations in Indiana. A sensitivity analysis informed the relative impact of changes in plant and soil parameters of APSIM Lucerne and APSIM Sugarcane modules. An independent dataset of switchgrass and Miscanthus DM yields from several US environments was used to validate these re-parameterized APSIM modules. The re-parameterized modules simulated DM yields of switchgrass [0.95 for CCC (concordance correlation coefficient) and 0 for SB (bias of the simulation from the measurement)] and Miscanthus (0.65 and 0% for CCC and SB, respectively) accurately at most locations with the exception of switchgrass at southern US sites (0.01 for CCC and 2% for SB). Therefore, the APSIM model is a promising tool for simulating DM yields for switchgrass and Miscanthus while accounting for environmental variability. Given our study was strictly based on APSIM calibrations at Indiana locations, additional research using more extensive calibration data may enhance APSIM robustness.
EEA Paraná
Fil: Ojeda, Jonathan Jesus. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Volenec, Jeffrey J. Purdue University. Department of Agronomy; Estados Unidos
Fil: Brouder, Sylvie M. Purdue University. Department of Agronomy; Estados Unidos
Fil: Caviglia, Octavio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Ecología Forestal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina
Fil: Agnusdei, Monica Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina