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Modeling Distributions of Crop and Weed Seed Germination Time

Published online by Cambridge University Press:  12 June 2017

David C. Bridges ,
Hsin-I Wu ,
Peter J. H. Sharpe  and
James M. Chandler
David C. Bridges
Affiliation:
Dep. Agron., Univ. Georgia, Griffin, GA 30223–1797;
Hsin-I Wu
Affiliation:
Biosystems Res. Group, Industrial Eng. Dep., Texas A&M Univ., College Station, TX 77843
Peter J. H. Sharpe
Affiliation:
Biosystems Res. Group, Industrial Eng. Dep., Texas A&M Univ., College Station, TX 77843
James M. Chandler
Affiliation:
Dep. Soil and Crop Sci., Texas Agric. Exp. Stn., College Station, TX 77843. TAES J. No. TA23651
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Abstract

Research was conducted to determine the utility of a single, temperature-independent Weibull function for describing cumulative seed germination under several temperature regimes with 14 sets of weed and crop seed germination data. A modified cumulative Weibull function was derived to distribute germination times for individuals within the population and distributed the occurrence of germination given ample sample size and appropriate sample interval. The descriptive and predictive attributes of the stochastic model component are well suited for incorporation into seed germination models and are likely applicable to models to predict distribution of times for other developmental processes of plants.

Keywords

Simulationcomputer modelstochastic germination modelcumulative Weibull function
Type
Special Topics
Information
Weed Science , Volume 37 , Issue 5 , September 1989 , pp. 724 - 729
Copyright
Copyright © 1989 by the Weed Science Society of America 

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References

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