Author
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Donald, William |
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Submitted to: Weed Science
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 2/29/2000 Publication Date: N/A Citation: N/A Interpretive Summary: Weed biology software, such as USDA's WeedCast, may help improve the efficacy and profitability of weed management, while minimizing unintended, negative environmental effects, such as soil erosion and water contamination by herbicides, fertilizers, and sediment. This weed biology software may help improve mechanical weed control, such as rotary hoeing or rfield cultivation, as well as herbicide application by better timing and matching weed control measures to when mixed weed populations emerge and are most susceptible to control. WeedCast software is one way of packaging weed biology information so that producers can best make weed management decisions. But, databases of weed emergence phenology and early season growth are needed if such weed biology decision aids are to become more useful. Canada thistle is a serious, persistent, perennial weed problem in many crops throughout the northern Great Plains and Corn Belt, including corn, soybeans, and spring wheat. If decision-aid software models of weed emergence and growth are ever to help producers better time weed management, they must be able to predict perennial weed shoot emergence from underground overwintering buds. In this research, Canada thistle shoot emergence from adventitious root buds in spring was well modeled using degree day-heat sums. The model was verified using additional, independently gathered sets of observations at two other sites. The model provides a better understanding of air temperature effects on Canada thistle shoot emergence and will be used in developing improved weed control technology for use by farmers and agricultural consultants. Technical Abstract: If decision-aid software models of weed emergence and growth are ever to help producers better time weed management, they must be able to predict perennial weed shoot emergence from vegetative propagules. In this research, Canada thistle shoot emergence from adventitious root buds in spring was modeled using degree (C) day-heat sums. Fractional Canada thistle shoot emergence was best modeled as a logistic dose-response function of degree (C) day-heat sum, as follows: Y = 1.108/(1 +(X/488.344)**-5.161) where Y = fractional Canada thistle shoot emergence (0 to 1) and X = heat sum in degree (C) days above 0 C after Julian day 91 (April 1) with an upper limit of 800 degree (C) days (r**2 = 0.83). This empirical model was validated by graphing observed versus model-predicted Canada thistle shoot emergence using two independently gathered data sets, one of Canada thistle emergence in fall chisel-plowed spring wheat (r**2 = 0.82) and the other in no-till fallow (r**2 = 0.63). The model slightly overestimated low (< ~ 7% at 0.1 fractional emergence) and underestimated emergence at high fractional emergence (10-20% at 0.8-1.0 fractional emergence). Below an emergence fraction of 0.8, the model adequately estimated observed emergence to within about 10% of the predicted regression line. |
