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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Agronomy Journal
Article . 2013 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
UQ eSpace
Article . 2013
Data sources: UQ eSpace
UQ eSpace
Article . 2013
Data sources: UQ eSpace
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Simulating Guinea Grass Production: Empirical and Mechanistic Approaches

Authors: Araujo, Leandro C.; Santos, Patricia M.; Rodriguez, Daniel; Pezzopane, Jose Ricardo M.; Oliveira, Patricia P. A.; Cruz, Pedro G.;

Simulating Guinea Grass Production: Empirical and Mechanistic Approaches

Abstract

Tropical grasses are economically important for cattle production in Brazil, and accurate simulation models for tropical pastures can benefit forage researchers and farm managers by improving tropical forage production systems. This research calibrated and validated four modeling approaches of contrasting complexity to simulate mass production of Mombaça Guinea grass (Panicum maximum Jacq.). The 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; coefficient 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 coefficient 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.

Country
Australia
Keywords

Tropical grass, 1102 Agronomy and Crop Science, Guinea grass, Brazil

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Top 10%
Top 10%
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