Weed IPM programs have not enjoyed the success of insect and disease programs because much of the weed control effort consists of preemergence herbicides applied before or at planting when no weeds are present. Because weed infestations cannot be assessed, herbicides are applied in combinations intended to control any combination of weeds that might occur. This practice results in unnecessary and excessive use of herbicides. The University of Connecticut has developed a soil test procedure that includes extracting weed seeds and measuring soil physical and chemical properties. Weed populations can be predicated based on this information.
Knowing the weed population likely to develop in a crop field would permit tailoring chemical and cultural weed management practices to address only those weeds likely to be a problem. This would provide effective "scouting" and serve as the basis of weed IPM programs. Limiting preemergence herbicide applications to those needed to control those species predicted to be present would reduce herbicide applications.
The equations developed at the University of Connecticut to predict weed populations based on pre planting soil tests were field tested in 1996 at seven sites. The equation for lambsquarters and crabgrass were evaluated With lambsquarters, the equations predicted an average for all sites of 71 plants per square meter. Average populations of 55.6 plants per square meter were observed for an accuracy of 79%. An action threshold of one lambsquarters per square meter was adopted and, based on this, the equations predicted the appropriate weed management response in six of seven samples for an accuracy of 86%.
With crabgrass, the average predicted population was 86.8 plants per square meter while the observed was two for an accuracy of 2.3%. Based on an action threshold of one plant per square meter, the equations accurately predicted the proper weed management response in seven of seven cases for a 100% accuracy rate.
The area sampled represented approximately 50 acres. If sweet corn was grown on all fields, the soil tests would have identified 20 acres that did nor require treatment for crabgrass control resulting in a savings of approximately 60 pounds of herbicide active ingredient.
To further increase the accuracy of the weed emergence predictions, experiments were conducted to determine the suitability of using a nonlinear poikilotherm rate equation to describe the relationship between germination and temperature, and a Weibull function to fit the cumulative seed germination for three annual weed species, redroot pigweed (Amaranthus retroflexus L.), lambsquarters (Chenopodium album L.) And large crabgrass (Digitaria sanguinalis{ L.} Scop.) Temperature ranges from 10oC to 34oC were evaluated at 3oC intervals. Temperature influenced the duration of seed germination of three weed species, with the relationships of median germination time and constant temperature forming a curve which refutes the degree-day concept. Median times ranged from 17.7 days at 10oC for lambsquarters, and from 9.9 days at 13oC to 2.5 days at 34oC. For all species, "most" means "are greater than median," thus indicating the distributions are skewed to the right. No germination was observed at 10oC for crabgrass and 34oC for lambsquarters.
Coupling both models to a simulation model for weed prediction improves the accuracy because it avoids the drawbacks of the degree-day approach from both biophysical and statistical aspects. The output includes information on the day of first emergence, peak emergence, and last emergence for a population. The predicted results can he used to optimize weed control timing, or can be used as input into larger population dynamics models.
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