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ARS Home » Midwest Area » Morris, Minnesota » Soil Management Research » Research » Publications at this Location » Publication #108232
Title: MODELING SEEDLING EMERGENCE

Author
item Forcella, Frank
item ARNOLD, ROBERTO - UNIV OF BUENOS AIRES
item SANCHEZ, RUDOLFO - UNIV OF BUENOS AIRES
item GHERSA, CLAUDIO - UNIV OF BUENOS AIRES

Submitted to: Field Crops Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/15/1999
Publication Date: N/A
Citation: N/A

Interpretive Summary: Knowing when weed seedlings emerge is one of the most critical aspects of weed control. Being able to predict the timing of seedling emergence would be of considerable benefit to crop consultants and to producers. Until recently, however, researchers have not been able to devise practical methods for prediction of seedling emergence. This review article explains sthe components of seedling emergence and outlines methods that may be used to predict various stages of the process. The review emphasizes a procedure for predicting weed seedling emergence that appears to provide reliable results with a minimum of information required by those using the procedure. This procedure employs both soil temperature and soil water content as the two most important factors regulating seedling emergence. Despite our increasing ability to predict seedling emergence, there still are many natural and management factors governing emergence that remain poorly understood. Water-logging, compaction, seed redistribution by tillage, salinity, and so forth remain to be studied thoroughly in terms of their effects on the timing of seedling emergence. This review identifies knowledge gaps where research should be concentrated to develop science-based tools to control weeds that will save producers and crop consultants time and money. Environmental concerns associated with chemical herbicides will also be reduced.

Technical Abstract: The most common approaches to predicting or documenting seedling emergence are imprecise. Mechanistic models that simulate seed dormancy and germination and seedling elongation as functions of measured or estimated environmental variables seem to be the most promising approach to the problem, but they also are the most difficult models to develop. These models will need to integrate soil water potential and soil temperature (hydrothermal time), diurnal soil temperature fluctuations, oxygen deficiency, light quality, and seed burial depth to better describe the direct and interactive effects on and among seed dormancy alleviation and induction, seed germination, and seedling elongation. In the mean time, creation and use of simpler empirical models, which also employ microclimate and soil factors for predictions, may provide sufficiently accurate predictions of seedling emergence until better mechanistic models are developed.