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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 Journalarrow_drop_down
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 . 2021 . Peer-reviewed
License: Wiley Online Library User Agreement
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Improving the CROPGRO Perennial Forage Model for simulating growth and biomass partitioning of guineagrass

Authors: Henrique B. Brunetti; Kenneth J. Boote; Patricia M. Santos; José R. M. Pezzopane; Carlos G. S. Pedreira; Márcio A. S. Lara; Leonardo S. B. Moreno; +1 Authors

Improving the CROPGRO Perennial Forage Model for simulating growth and biomass partitioning of guineagrass

Abstract

AbstractTropical forage grasses are used for several applications including grazing, silage, and biofuels; with harvesting at varying phenological stages. Mechanistic simulation models can be powerful tools to assist with planning and decision making of pasture utilization strategies. The objective of this study was to improve and evaluate the ability of the Cropping System Model‐CROPGRO‐Perennial Forage model (CSM‐CROPGRO‐PFM) to simulate growth and biomass partitioning of two guineagrass [Panicum maximum Jacq. syn. Megathyrsus maximus (Jacq.) BK Simon & SWL Jacobs] cultivars, Tanzânia and Mombaça. Data from two experiments with contrasting harvest management and field conditions were used. Model parameters were modified, targeting improvement in d‐statistic and root mean square error (RMSE) for aboveground, leaf, stem biomass, leaf area index (LAI), and leaf proportion of aboveground biomass. Major improvement in model performance was achieved by modifying the vegetative partitioning parameters between leaf and stem through increasing partitioning to leaf during early regrowth while increasing it to stem during late regrowth. Modifications were made to parameters affecting leaf and stem senescence, leaf photosynthesis, and leaf area expansion sensitivity to cool weather. The RMSE values decreased from 2,261 to 1,768 kg ha−1 for aboveground biomass, from 1,620 to 874 kg ha−1 for stem biomass, from 11.41 to 7.27% for leaf percentage, from 1.91 to 1.68 for LAI, but increased slightly for leaf biomass. The d‐statistic computed over all these variables increased from .86 to .93. The improved model performance for both short and long harvest cycles will facilitate further applications for diverse forage crops utilization strategies.

Country
Brazil
Keywords

Soil organic carbon, PFM, Perennial Forage Model, RMSE, Root mean square error, LAI, Specific leaf area, Leaf area index, SOC, SLA

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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!
9
Top 10%
Average
Top 10%
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