Field experiments were conducted in 1999 at Stoneville, MS, to determine the potential of multispectral imagery for late-season discrimination of weed-infested and weed-free soybean. Plant canopy composition for soybean and weeds was estimated after soybean or weed canopy closure. Weed canopy estimates ranged from 30 to 36% for all weed-infested soybean plots, and weeds present were browntop millet, barnyardgrass, and large crabgrass. In each experiment, data were collected for the green, red, and near-infrared (NIR) spectrums four times after canopy closure. The red and NIR bands were used to develop a normalized difference vegetation index (NDVI) for each plot, and all spectral bands and NDVI were used as classification features to discriminate between weed-infested and weed-free soybean. Spectral response for all bands and NDVI were often higher in weed-infested soybean than in weed-free soybean. Weed infestations were discriminated from weed-free soybean with at least 90% accuracy. Discriminant analysis models formed from one image were 78 to 90% accurate in discriminating weed infestations for other images obtained from the same and other experiments. Multispectral imagery has the potential for discriminating late-season weed infestations across a range of crop growth stages by using discriminant models developed from other imagery data sets.
Nomenclature: Barnyardgrass, Echinochloa crus-galli (L.) Beauv. #3 ECHCG; browntop millet, Brachiaria ramosa (L.) Stapf # PANRA; large crabgrass, Digitaria sanguinalis (L.) Scop. # DIGSA; soybean, Glycine max (L.) Merr.
Additional index words: Discriminant analysis, multispectral, remote sensing, normalized difference vegetation index, weed detection.
Abbreviations: DGPS, differential global positioning system; exp., experiment; NDVI, normalized difference vegetation index; NIR, near infrared; POST, postemergence; PRE, preemergence.