Submitted to: Journal of Nematology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/18/1998
Publication Date: N/A
Interpretive Summary: Precision farming technology may help reduce external input costs for crop production, increase crop production efficiency and yield, and improve water quality by reducing pesticide contamination. But, sampling pest distribution to wisely use this new technology can be prohibitively expensive. If pest distribution over fields were relatively constant over time, then costs for sampling pests to make management decisions using precision farming technology could be reduced by sampling less frequently than once a year. But, basic information on the stability of pest distribution in farmers' fields over time is lacking. Soybean cyst nematode is a widespread, yield reducing pest for soybean producers. The goal of this research was to determine whether the spatial pattern of soybean cyst nematode in a field was stable over time when no attempt was made to control it. Nematode densities were sampled in fall and spring over four years in a southeastern Missouri soybean field. This research shows that soybean cyst nematode density was very unstable over four years even though the field was heavily infested with this pest. In fact, fall soybean cyst nematode densities could not be used to predict spring nematode densities. Likewise, spring or fall soybean cyst nematode densities were unrelated to soybean yield, suggesting that other factors limited yield. These results suggest that costs of nematode sampling would be prohibitively expensive and make the use of precision farming technology to manage soybean cyst nematode unprofitable. This information will benefit primarily soybean producers, particularly those using Precision Farming Technology.
Technical Abstract: Soybean cyst nematode, Heterodera glycines, is found throughout soybean production areas of the United States, but the nematode's distribution is not uniform within states, counties and individual fields. The goal of this research was to determine the spatial pattern of H. glycines population density in a field and whether it was stable over time in the absence of management practices. Geostatistical methods were used to describe and map the distribution of H. glycines over four years in a soybean (Glycine max) field in southeastern Missouri. Semivariograms and kriging, an interpolation method, were used to prepare isoarithmic contour maps and associated error maps. In the field studied, fall H. glycines population density was poorly related to spring density because of overwinter mortality. The distribution of peak H. glycines population density within the field changed from year to year, although high densities swere often detected in the same general region of the field. The patchiness of H. glycines distribution within a field was verified. Yield was not related to H. glycines egg population density at planting, indicated that unmeasured variables were also reducing yield.