03144naa a2200277 a 450000100080000000500110000800800410001902400520006010000130011224501740012526000090029930000100030852023140031865000110263265000120264365300240265565300130267965300180269265300140271070000210272470000160274570000240276170000210278570000180280677300420282421242452020-08-10       2020    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.1016/j.agsy.2020.1029172DOI1 aBOSI, C.  aAPSIM-Tropical PasturebA model for simulating perennial tropical grass growth and its parameterisation for palisade grass (Brachiaria brizantha).h[electronic resource]  c2020  a14 p.  aTropical grasses are used as forage, to produce energy from biomass, for land restoration and carbon sequestration, among other applications. Many modelling approaches have been employed to simulate tropical grasses growth, but these have several limitations that must be solved by adapting them or creating new models. This study aimed to develop a tropical pasture model in the Agricultural Production Systems Simulator (APSIM) modelling framework, and to parameterise it to simulate Brachiaria brizantha ?BRS Piatã? growth, under grazing and cut-and-carry management. For this, three field experiments were conducted in the South-east of Brazil where pasture growth was measured in a cut-and-carry system, with irrigated and rainfed treatments, and in a rainfed grazing system. Model evaluation was performed through precision and accuracy indices and simulation errors. Under cut-and-carry management, forage productivity was estimated with R2 values from 0.89 to 0.94, Willmott agreement indices between 0.97 and 0.98, and Nash-Sutcliffe Efficiency values of 0.88 to up to 0.92. This demonstrates the capacity of the APSIM-Tropical Pasture model to simulate tropical pastures. Simulation of phenology, early growth after sowing, partitioning and senescence during flowering, and reallocation and retranslocation of plant dry matter and nitrogen were important aspects for this capacity. Then, APSIM-Tropical Pasture can be used to simulate tropical pastures, but several requirements for further improvements have been identified, such as to improve the simulations of flowering for palisade grass, N effects on pasture yield, reallocation and retranslocation processes. Under grazing management, forage productivity was estimated with R2 = 0.80, Willmott agreement index of 0.91, and Nash-Sutcliffe Efficiency value of 0.62. Despite these reasonable results, simulations presented problems, since does not take into account the effect of grazing animals on pastures. This indicates that, in its current form, APSIM-Tropical Pasture is not able to simulate pastures under grazing effectively. However, this simulation of grazed system was important to identify main modelling constraints and direct future research to improve knowledge of processes and interactions needed for pasture model development.  aForage  aGrazing  aBRS Piatã cultivar  aC4 grass  aCut and carry  aModelling1 aSENTELHAS, P. C.1 aHUTH, N. I.1 aPEZZOPANE, J. R. M.1 aANDREUCCI, M. P.1 aSANTOS, P. M.  tAgricultural Systemsgn. 184, 102917.