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Modeling weed emergence as influenced by burial depth using the Fermi-Dirac distribution function

Published online by Cambridge University Press:  12 June 2017

Hsin-I Wu
Affiliation:
Center for Biosystems Modeling, Industrial Engineering Department, Texas A&M University, College Station, TX 77843-2474
James M. Chandler
Affiliation:
Department of Soil and Crop Sciences, Texas Agricultural Experiment Station, Texas A&M University, College Station, TX 77843-2474
Scott A. Senseman
Affiliation:
Department of Soil and Crop Sciences, Texas Agricultural Experiment Station, Texas A&M University, College Station, TX 77843-2474

Abstract

Research was conducted to determine the suitability of the Fermi-Dirac distribution function for modeling the seedling emergence of downy brome, johnsongrass, and round-leaved mallow, as influenced by burial depth. Six sets of previously published emergence data were used to formulate the model and test its adequacy. Two independent johnsongrass emergence data sets were used to validate the model. Constant temperature growth chamber studies were conducted to evaluate the effects of temperature and moisture on the model parameters. The Fermi-Dirac distribution function was found to adequately describe the seedling emergence of downy brome, johnsongrass, and round-leaved mallow as indicated by a good visual data fit, narrow confidence intervals for the model parameters, and regression analysis of observed vs. modeled data. Although this function is a model used in physical science, its parameters can be related to abiotic factors such as soil texture, temperature, and moisture.

Type
Weed Biology and Ecology
Copyright
Copyright © 1997 by the Weed Science Society of America 

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