The objective of this research was to evaluate the accuracy of remote sensing for detecting weed infestation levels during early-season Glycine max production. Weed population estimates were collected from two G. max fields approximately 8 wk after planting during summer 1998. Seedling weed populations were sampled using a regular grid coordinate system on a 10- by 10-m grid. Two days later, multispectral digital images of the fields were recorded. Generally, infestations of Senna obtusifolia, Ipomoea lacunosa, and Solanum carolinense could be detected with remote sensing with at least 75% accuracy. Threshold populations of 10 or more S. obtusifolia or I. lacunosa plants m−2 were generally classified with at least 85% accuracy. Discriminant analysis functions formed for detecting weed populations in one field were at least 73% accurate in identifying S. obtusifolia and I. lacunosa infestations in independently collected data from another field. Due to highly variable soil conditions and their effects on the reflectance properties of the surrounding soil and vegetation, accurate classification of weed-free areas was generally much lower. Current remote sensing technology has potential for in-season weed detection; however, further advancements of the technology are needed to insure its use in future prescription weed management systems.

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A study was conducted to evaluate the accuracy of different weed sampling scales to accurately describe populations in soybean. Three soybean fields were sampled at 8 and 6 weeks after planting in 1998 and 1999, respectively. All weed species were counted on a 10 m grid, using a 0.58-m 2 quadrat. Data were eliminated from the original 10 m grid sample of weeds for each field to develop 40 m, 60 m, and 80 m independent data sets. Distribution and population maps were interpolated using an inverse distance weighted method. Data were extracted from the interpolated maps at known coordinates so that the observed population and the predicted population could be compared. The 10 m grid served as a standard to which all others were compared. No differences in population accuracies between each scale were detected when results were compared on a per weed basis, except when weed populations were very high, generally exceeding 400 plants ha )1 . When the weed density was not at an extreme, the results from these data indicate the ability to describe or account for the weed population fairly accurately, when using coarser grid sizes. These results also suggest that when using a regular grid coordinate system as the sampling structure, an increase from a 10 m scale to an 80 m scale will not cause a significant loss of information when weed populations were not extreme and will provide the necessary information for making suitable weed treatment decisions. However, some small weed patches were not detected with the coarser sampling scales, and the larger sampling scales would not meet their needs if the producerÕs objective is complete control of a species.