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Predicting ozone-induced soybean losses: sensitivity to model form and inputs.
J D Kinsman1, W P Saunders, R E Wyzga
1Edison Electric Institute, Washington, DC 20036, USA.
Environmental Pollution (Barking, Essex : 1987)
|January 1, 1988
Summary
This study developed new models to predict soybean yield losses from ozone (O3) exposure. Different O3 dose metrics and soybean cultivars significantly impact predicted crop damage.
Area of Science:
- Agricultural Science
- Environmental Science
- Plant Physiology
Background:
- Ozone (O3) pollution negatively impacts crop yields, particularly for soybeans (Glycine max (L.) Merr.).
- Accurate dose-response models are crucial for predicting agricultural losses due to O3 exposure.
Purpose of the Study:
- To establish and compare alternative dose-response equations for assessing O3 effects on soybean yield.
- To evaluate the sensitivity of O3-induced soybean loss predictions to various model inputs and forms.
Main Methods:
- Fitted linear, quadratic, and Weibull models to relate O3 dose measures to soybean yield for three cultivars.
- Utilized 7-h and 12-h mean, total doses, and percentile O3 concentrations as dose metrics.
- Calculated county-level O3 doses using data from rural and small city monitoring sites.
Main Results:
- Soybean yield loss predictions varied based on O3 dose measures, model forms, and soybean cultivars.
- Inter-year O3 variations and double-cropping practices influenced predicted soybean losses.
- Sensitivity analyses revealed significant impacts of input choices on O3-induced crop damage estimations.
Conclusions:
- The choice of dose-response model and O3 metrics significantly influences soybean yield loss predictions.
- Understanding cultivar-specific responses and environmental factors is essential for accurate O3 impact assessments.
- These findings aid in developing better strategies for mitigating O3 damage in soybean production.