Simulating guinea grass production: empirical and mechanistic approaches

Araujo, Leandro C., Santos, Patricia M., Rodriguez, Daniel, Pezzopane, Jose Ricardo M., Oliveira, Patricia P. A. and Cruz, Pedro G. (2013) Simulating guinea grass production: empirical and mechanistic approaches. Agronomy Journal, 105 1: 61-69. doi:10.2134/agronj2012.0245


Author Araujo, Leandro C.
Santos, Patricia M.
Rodriguez, Daniel
Pezzopane, Jose Ricardo M.
Oliveira, Patricia P. A.
Cruz, Pedro G.
Title Simulating guinea grass production: empirical and mechanistic approaches
Journal name Agronomy Journal   Check publisher's open access policy
ISSN 0002-1962
1435-0645
Publication date 2013-01
Sub-type Article (original research)
DOI 10.2134/agronj2012.0245
Volume 105
Issue 1
Start page 61
End page 69
Total pages 9
Place of publication Madison, WI, United States
Publisher American Society of Agronomy
Collection year 2014
Language eng
Abstract Tropical grasses are economically important for cattle production in Brazil, and accurate simulation models for tropical pastures can benefi t forage researchers and farm managers by improving tropical forage production systems. Th is research calibrated and validated four modeling approaches of contrasting complexity to simulate mass production of Mombaça Guinea grass (Panicum maximum Jacq.). Th e models included three empirical agro-climatic models (i.e., using cumulative degree days, photothermal units, and a climatic growth index) and a biophysical simulation model, Agricultural Production Systems Simulator (APSIM)- Growth. Data sets for calibration and independent validation included frequent records of aboveground dry matter production during the 2005-2006 and 2010-2011 growing seasons from three trials. All models performed well during calibration (R2 = 0.78-0.86; coeffi cient of variation = 26-32.1%). During model validation, the R2 varied between 0.69 and 0.78, the agreement index was between 0.88 and 0.93, the coeffi cient of variation between 37.6 and 50.2%, and the mean bias error was between 6 and 470 kg ha-1. Even though all models were in agreement between simulated and observed results, APSIM-Growth was able to simulate Guinea grass production across broader climatic, soil, and management (e.g., N fertilization) conditions.
Keyword Brazil
Tropical grass
Guinea grass
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Alliance for Agriculture and Food Innovation
Official 2014 Collection
 
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