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Predicting Emergence of 23 Summer Annual WeedSpecies

Published online by Cambridge University Press:  20 January 2017

Rodrigo Werle ,
Lowell D. Sandell ,
Douglas D. Buhler ,
Robert G. Hartzler  and
John L. Lindquist
Rodrigo Werle
Affiliation:
Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE 68583
Lowell D. Sandell*
Affiliation:
Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE 68583
Douglas D. Buhler
Affiliation:
Michigan State University, East Lansing, MI 48824
Robert G. Hartzler
Affiliation:
Iowa State University, Ames, IA 50011
John L. Lindquist
Affiliation:
Department of Agronomy and Horticulture, University of Nebraska–Lincoln, Lincoln, NE 68583
*
Corresponding author's E-mail: lsandell2@unl.edu
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Abstract

First- and second-year seedbank emergence of 23 summer annual weed speciescommon to U.S. corn production systems was studied. Field experiments wereconducted between 1996 and 1999 at the Iowa State University Johnson Farm inStory County, Iowa. In the fall of 1996 and again in 1997, 1,000 seeds formost species were planted in plastic crates. Seedling emergence was countedweekly for a 2-yr period following seed burial (starting in early spring).Soil temperature at 2 cm depth was estimated using soil temperature andmoisture model software (STM2). The Weibull function was fit tocumulative emergence (%) on cumulative thermal time (TT), hydrothermal time(HTT), and day of year (DOY). To identify optimum base temperature (Tbase) and base matric potential (ψbase) forcalculating TT or HTT, Tbase and ψbase values rangingfrom 2 to 17 C and −33 to −1,500 kPa, respectively, were evaluated for eachspecies. The search for the optimal model for each species was based on theAkaike's Information Criterion (AIC), whereas an extra penalty cost wasadded to HTT models. In general, fewer seedlings emerged during the firstyear of the first experimental run (approximately 18% across all species)than during the second experimental run (approximately 30%). However,second-year seedbank emergence was similar for both experimental runs(approximately 6%). Environmental effects may be the cause of differences intotal seedling emergence among years. Based on the AIC criterion, for 17species, the best fit of the model occurred using Tbase rangingfrom 2 to 15 C with four species also responding to ψbase = −750kPa. For six species, a simple model using DOY resulted in the best fit.Adding penalty costs to AIC calculation allowed us to compare TT and HTTwhen both models behaved similarly. Using a constant Tbase,species were plotted and classified as early-, middle-, and late-emergingspecies, resulting in a practical tool for forecasting time of emergence.The results of this research provide robust information on the prediction ofthe time of summer annual weed emergence, which can be used to schedule weedand crop management.

Keywords

AIC criterioninformation-theoretic model comparison approachthermal timeweather dataWeibull model

Information

Type
Weed Biology and Ecology
Information
Weed Science , Volume 62 , Issue 2 , June 2014 , pp. 267 - 279
Copyright
Copyright © Weed Science Society of America 

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