Abstract

Barnyardgrass, common lambsquarters, redroot pigweed, and wild mustard are among the most common weeds in cropping systems throughout North America. Crop and weed competition models that predict phenological development across environments are useful research tools for advancing our knowledge of population dynamics or crop and weed competition. Phenological parameter estimates for such models require verification under field conditions. Field studies were conducted in 1999 and 2000 to determine growth and phenological development of these species under noncropped conditions to compare parameters developed previously from controlled environment studies. Weeds were planted on three separate planting dates in each year. Growth and phenological development were recorded. Number of leaves on the mainstem of all weed species, except common lambsquarters, was not affected by planting dates. Rate of leaf appearance described as a function of days after emergence ranged from 0.48 to 0.89, 0.10 to 0.31, 0.33 to 0.65, and 0.24 to 0.29 leaves d−1for common lambsquarters, barnyardgrass, redroot pigweed, and wild mustard, respectively. When expressed as a function of growing degree days (GDD), rate of leaf appearance for these species ranged from 0.04 to 0.05, 0.01 to 0.02, 0.04 to 0.07, and 0.02 to 0.03 leaves GDD−1, respectively. Planting date had differential effects on the rate of stem elongation and final plant height of each species in the 2 yr. Final plant biomass was also influenced by the time of planting; in general, weeds planted by mid-May had more biomass than those planted later. Parameters developed to describe phenological development under field conditions were comparable to those reported previously from controlled environment studies. We conclude that phenological parameters quantified under controlled environmental studies were comparable to those developed under field conditions for these weed species. Thus, either experimental method can be used to parameterize weed phenological development to initialize crop and weed competition models with reasonable confidence.

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