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Journal of Environmental Quality Abstract -

Crop Yield Response Predicted with Different Characterizations of the Same Ozone Treatments1


This article in JEQ

  1. Vol. 15 No. 3, p. 251-254
    Received: July 24, 1985

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  1. William W. Cure,
  2. John S. Sanders and
  3. Allen S. Heagle2



Data were obtained from three field experiments studying the effects of chronic doses of ozone (O3) on crop yield. All used open-top exposure chambers. Two were of the same design with soybean [Glycine max (L.) Merr.] in 1977 and 1978 and the third was with peanut (Arachis hypogaea L.) in 1980. Exposures had been conducted for 7 h each day starting shortly after crop emergence and ending with maturity. Each experiment included a treatment level below ambient, two at ambient levels, one within and one outside of a chamber, and two to three treatments at levels above ambient established by adding different but constant amounts of O3 to ambient air. Three different characterizations of each O3 treatment were compared as independent variables in simple linear O3 dose-yield response models. Ozone treatments were characterized as (i) the seasonal mean of the daily 7-h means (“7-h mean”), (ii) the seasonal mean of the daily maximum 1-h mean concentrations (“1-h mean”), and (iii) the seasonal maximum 1-h mean concentration (1-h max). The ratio of the 1-h mean to 7-h mean concentration in each treatment was very similar over the range of treatment levels in an experiment. Models of the same yield data developed with either seasonal mean could probably be used interchangeably by converting between concentration scales with a constant multiple. The relation between the 1-h max concentration and either of the seasonal means changed with treatment level within an experiment and was different for similar treatments in different years. The range of yields predicted with models based on 1-h max concentrations using the maximum and minimum ambient O3 concentrations in the 3 yr of these experiments was three to four times that obtained with either seasonal mean model.

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