Published online by Cambridge University Press: 20 January 2017
Widespread use of crop yield loss models based on weed density has been limited on account of spatial and temporal variability. Furthermore, research characterizing crop yield loss associated with two or more weed species is lacking for many cropping systems. Therefore, research was conducted to characterize giant foxtail and common lambsquarters leaf area, height, and shoot volume in soybean, to quantify the relative competitive ability of giant foxtail and common lambsquarters in a mixed–weed species environment, and to assess weed density, weed relative leaf area, and weed relative volume as predictors of soybean yield loss. Based on weed density, coefficient estimates of percent soybean yield loss as giant foxtail or common lambsquarters densities approached zero differed between years. In contrast, coefficient estimates of maximum soybean yield loss were similar between years. Based on weed relative leaf area, estimates of giant foxtail or common lambsquarters damage coefficients differed between years. Similarly, estimates of maximum soybean yield loss associated with common lambsquarters leaf area differed between years, whereas estimates of maximum soybean yield loss associated with giant foxtail leaf area did not change over time within a growing season or between years. Based on weed relative volume, estimates of giant foxtail or common lambsquarters damage coefficients differed between years. Similarly, estimates of maximum soybean yield loss associated with common lambsquarters volume differed between years, whereas estimates of maximum soybean yield loss associated with giant foxtail volume did not change over time within a growing season or between years. Based on weed density, weed relative leaf area, or weed relative volume, giant foxtail was more competitive than common lambsquarters in terms of soybean yield loss. Temporal variability of weed density, weed relative leaf area, and weed relative volume indicates that additional parameters may be required to accurately predict weed–crop interactions in a multiple–weed species community.