H. Oebel

Hohenheim University, Stuttgart, Baden-Wuerttemberg, Germany

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Publications (2)3.62 Total impact

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    ABSTRACT: Grain yield often varies within agricultural fields as a result of the variation in soil characteristics, competition from weeds, management practices and their causal interactions. To implement appropriate management decisions, yield variability needs to be explained and quantified. A new experimental design was established and tested in a field experiment to detect yield variation in relation to the variation in soil quality, the heterogeneity of weed distribution and weed control within a field. Weed seedling distribution and density, apparent soil electrical conductivity (ECa) and grain yield were recorded and mapped in a 3.5ha winter wheat field during 2005 and 2006. A linear mixed model with an anisotropic spatial correlation structure was used to estimate the effect of soil characteristics, weed competition and herbicide treatment on crop yield. The results showed that all properties had a strong effect on grain yield. By adding herbicide costs and current grain price into the model, thresholds of weed density were derived for site-specific weed control. This experimental approach enables the variation of yield within agricultural fields to be explained, and an understanding of the effects on yield of the factors that affect it and their causal interactions to be gained. The approach can be applied to improve decision algorithms for the patch spraying of weeds.
    Precision Agriculture 06/2008; 9(3):133-146. DOI:10.1007/s11119-008-9061-5 · 1.93 Impact Factor
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    ABSTRACT: 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 site-specific 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 Global Positioning System-controlled patch spraying. In a 2-year 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.
    Weed Research 05/2006; 46(3):185 - 193. DOI:10.1111/j.1365-3180.2006.00504.x · 1.69 Impact Factor

Publication Stats

104 Citations
3.62 Total Impact Points

Top Journals


  • 2006–2008
    • Hohenheim University
      • Institute of Phytomedicine
      Stuttgart, Baden-Wuerttemberg, Germany

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