The soybean cyst nematode (SCN) Heterodera glycines Ichinohe is responsible for substantial economic losses in soybean (Glycine max L. Merr.) production throughout the U.S. Results from past efforts to quantify the severity of crop damage resulting from SCN are often subject to variable experimental conditions resulting from differences in weather, soil type, and cultivar. Because of the difficulty in accounting for these variables, a process–oriented crop growth simulation model was chosen as a platform for studying the dynamics of SCN damage and for transferring knowledge between crop production scenarios. The objective of this study was to develop and evaluate hypotheses for coupling SCN damage to the process–oriented crop growth model CROPGRO–Soybean. A monomolecular function was used to relate daily SCN damage to initial population density of SCN eggs. The equation was incorporated into the crop model in order to test two hypotheses of how SCN damage occurs. The first hypothesis was that SCN reduce daily photosynthesis (Pg), while the second hypothesis was that SCN reduce daily potential root water uptake (RWU).
Canopy biomass data collected in 1997 and 1998 from a site in Iowa were used to estimate damage function parameters for two distinct coupling points, one applied to reduce daily photosynthesis (Pg) and the other applied to reduce daily potential root water uptake (RWU). Function parameters were estimated by minimizing the log transformation of root mean square error (RMSE) between predicted and measured canopy biomass collected every 2 weeks during the season in Iowa. Biomass data collected in 1997 and 1998 from an independent site in Missouri were used to validate the SCN damage models. The minimum root mean squared errors (RMSE) of canopy and grain biomass were 0.245 and 0.198 log10(kg ha–1), respectively, for the RWU coupling point, and 0.238 and 0.193 log10(kg ha–1), respectively, for the Pg coupling point at the independent site in Missouri. The damage functions transferred very well to the independent site. Validation showed that the Pg coupling point represented the variability of both canopy and final yield data slightly better than the RWU coupling point.
Available at: http://works.bepress.com/gregory-tylka/178/