Information on temporal and spatial variation in weed seedling populations within agricultural fields is very important for weed population assessment and management. Primarily, spatial information allows a potential reduction in herbicide use, when post-emergent herbicides are only applied to field sections with high weed infestation levels. This paper presents a system for sitespecific weed control in sugar beet, maize, winter wheat, winter barley, winter rape and spring barley. The system includes on-line weed detection using digital image analysis, computer-based decision making and GlobalPositioning System-controlled patch spraying. In a 2year study, herbicide use with this map-based approach was reduced in winter cereals by 6-81% for herbicides against broad leaved weeds and 20-79% for grass weed herbicides. Highest savings were achieved in cereals followed by sugar beet, maize and winter rape. The efficacy of weed control varied from 85% to 98%, indicating that site-specific weed management will not result in higher infestation levels in the following crops. Keywords: weed distribution, site-specific weed control, patch spraying, on-line weed detection, decision support systems, crop rotation. GERHARDS R & OEBEL H (2006) Practical experiences with a system for site-specific weed control in arable crops using real-time image analysis and GPS-controlled patch spraying. Weed Research 46, 185-193.
Information on temporal and spatial variation in weed seedling populations within agricultural fields is very important for weed population assessment and management. Most of all, it allows a potential reduction in herbicide use, when post-emergence herbicides are only applied to field sections with weed infestation levels higher than the economic weed threshold; a review of such work is provided. This paper presents a system for site-specific weed control in sugarbeet (Beta vulgaris L.), maize (Zea mays L.), winter wheat (Triticum aestivum L.) and winter barley (Hordeum vulgare L.), including online weed detection using digital image analysis, computer-based decision making and global positioning systems (GPS)-controlled patch spraying. In a 4-year study, herbicide use with this map-based approach was reduced in winter cereals by 60% for herbicides against broad-leaved weeds and 90% for grass weed herbicides. In sugarbeet and maize, average savings for grass weed herbicides were 78% in maize and 36% in sugarbeet. For herbicides against broad-leaved weeds, 11% were saved in maize and 41% in sugarbeet.
Intensive surveys were conducted in 2 fields in eastern Nebraska to determine the spatial stability of common sunflower, velvetleaf, green and yellow foxtail, and hemp dogbane over 4 yr (1992 to 1995). The 1st field was planted to soybean in 1992 and corn in 1993, 1994, and 1995. The 2nd field was planted to corn in 1992 and 1994 and soybean in 1993 and 1995. Weed density was sampled prior to postemergence herbicide application at approximately 800 locations per year in each field on a regular 7 m grid. The same locations were sampled every year. Weed density at locations between the sample sites was determined by linear triangulation interpolation. Weed seedling distribution was significantly aggregated, with large weed-free areas in both fields. Common sunflower, velvetleaf, and hemp dogbane patches were very persistent in diameter in the east-west and north-south directions and in location and area over 4 yr in the 1st field. Foxtail distribution and density continuously increased in each of the 4 yr in the first field and decreased in the 2nd field. A geographic information system was used to overlay maps from each year for a species. This showed that 36% of the sampled area was continuously free of common sunflower, 62.5% was free of hemp dogbane, and 11.5% was free of velvetleaf in the 1st field, but only 1% was free of velvetleaf in the 2nd field. The persistence of broadleaf weed patches suggests that weed seedling distributions mapped in one year are good predictors of future seedling distributions. Improved and more efficient sampling methods are needed.
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