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1 September 2000 Modeling weed emergence as a function of meteorological records
Andrea C. Grundy, Andrew Mead
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Unique long-term historical emergence records were used to assess the association between weed seedling emergence and various elements of meteorological data. These elements included both temperature-based and rainfall-related variables in the 7-d periods before and during which emergence occurred. Five weed species (Stellaria media, Chenopodium album, Capsella bursa-pastoris, Matricaria perforata, and Veronica hederifolia) with contrasting emergence patterns were studied in disturbed soil. Logistic regression analysis was used to identify meteorological variables of interest and allowed their relative importance to be assessed and ranked. Logistic regression was further used to associate probabilities of emergence with observed levels of important individual meteorological elements. This approach enabled prediction of the probability of emergence following given meteorological conditions and hence an assessment of the risk of omitting weed control measures. Predictions were made based on single meteorological variables and compared with observed data. Results indicated that temperature was the dominant factor in predicting emergence. Soil moisture, while also important, was a secondary factor only becoming important once the species-specific temperature requirement had been satisfied. The potential for further development of the model is discussed.

Nomenclature: Stellaria media (L.) Vill. STEME, common chickweed; Chenopodium album L. CHEAL, common lambsquarters; Capsella bursa-pastoris (L.) Medicus CAPBP, shepherd's-purse; Matricaria perforata Merat. MATIN, scentless chamomile; Veronica hederifolia L. VERHE, ivyleaf speedwell.

Andrea C. Grundy and Andrew Mead "Modeling weed emergence as a function of meteorological records," Weed Science 48(5), 594-603, (1 September 2000).[0594:MWEAAF]2.0.CO;2
Received: 16 November 1999; Published: 1 September 2000
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