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Use of a biophysical simulation model (DairyMod) to represent tall fescue pasture growth in Argentina
Resumen
Tall fescue pastures have an increasing potential to be used worldwide. The purpose of this study was to test the ability and flexibility of the model DairyMod to represent herbage mass accumulation (HMA) of tall fescue pastures from Argentina under several environmental conditions, including different seasons, fertilizer nitrogen levels and irrigation. Species‐specific responses were obtained by customizing particular parameters (i.e. number of living
[ver mas...]
Tall fescue pastures have an increasing potential to be used worldwide. The purpose of this study was to test the ability and flexibility of the model DairyMod to represent herbage mass accumulation (HMA) of tall fescue pastures from Argentina under several environmental conditions, including different seasons, fertilizer nitrogen levels and irrigation. Species‐specific responses were obtained by customizing particular parameters (i.e. number of living leaves per tiller, leaf appearance interval, optimum plant N concentration and the response of leaf gross photosynthesis to temperature). Additionally, a simulation experiment to compare the model assumption that optimum N concentration stays constant through HMA with the application of a reference critical N dilution curve verified for temperate forage grasses (N% = 4·8 HMA−0·32) was conducted. Application of DairyMod simulated with reasonable accuracy the HMA of tall fescue pastures under a wide range of climatic and management conditions; however, the model tended to underestimate HMA where pastures grew under high N availability. The use of a reference critical N curve substantially improved this bias, indicating that a further analysis on the N issue of the model is necessary. Results from this study provide support for further evaluations of the model under other scenarios and conditions. An upgrade of the model to improve simulation of N nutrition is suggested to enhance its performance to predict growth dynamics at high N availabilities as well as its value to address the effectiveness of N‐management practices.
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Autor
Berger, Horacio;
Machado, Claudio F.;
Agnusdei, Monica Graciela;
Cullen, Brendan R.;
Fuente
Grass and Forage Science 69 (3) : 441-453 (September 2014)
Fecha
2014-09
Editorial
Wiley
ISSN
0142-5242
1365-2494
1365-2494
Formato
pdf
Tipo de documento
artículo
Palabras Claves
Derechos de acceso
Restringido
Excepto donde se diga explicitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)