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Predicting Flowering of Rhizome Johnsongrass (Sorghum halepense) Populations Using a Temperature-dependent Model

Published online by Cambridge University Press:  12 June 2017

David L. Holshouser
Affiliation:
Dep. Agron., Northeast Res. & Ext. Cen., University of Nebraska, Concord, NE 68728
James M. Chandler
Affiliation:
Dep. Soil & Crop Sci., Texas Agric. Exp. Stn., College Station, TX 77843

Abstract

Research was conducted to formulate a temperature-dependent population-level model for rhizome johnsongrass flowering. A nonlinear poikilotherm rate equation was used to describe development as a function of temperature and a temperature-independent Weibull function was used to distribute development times for the population. Johnsongrass flowering data were collected under constant temperature conditions to parameterize the poikilotherm rate equation and Weibull function. Coupling the poikilotherm rate equation with the Weibull function resulted in a population level temperature-dependent model. The model was validated against independent field data sets. The model accurately predicted rhizome johnsongrass flowering from plants emerging in the spring. The model performed poorly for plants emerging in summer. Adjustments to the high-temperature inhibition parameter of the poikilotherm rate equation improved model performance in the summer without affecting spring predictions.

Type
Weed Biology and Ecology
Copyright
Copyright © 1996 by the Weed Science Society of America 

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