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Linking weed patterns with soil properties: a long-term case study

机译:将杂草模式与土壤属性联系起来:长期案例研究

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The spatial distribution and density of different weed species were monitored during a long-term survey over a period of 9 years on a 5.8 ha arable field and related to soil properties. Weed seedlings were determined every year in spring on a regular grid with 429 observation points (15 x 7.5 m; net study area = 4 ha). Dominant weed species were Chenopodium album, Polygonum aviculare, Viola arvensis and different grass weeds, clearly dominated by Alopecurus myosuroides. A non-invasive electromagnetic induction survey was conducted to evaluate available water capacity directly in the field at high spatial resolution. Further soil properties were evaluated following the minimum-invasive approach with soil sampling and subsequent mid-infrared spectroscopy. Plant available nutrients were analysed with conventional lab methods. Redundancy analysis served to describe the effect of soil properties, different years and field crops on weed species variability. Seven soil properties together explained 30.7% of the spatial weed species variability, whereas 28.2% was explained by soil texture, available water capacity and soil organic carbon. Maps for site-specific weed management were created based on soil maps. These maps permit several benefits for precision crop protection, such as a better understanding of soil-weed inter-relations, improved sampling strategies and reduction in herbicide use.
机译:在5.8公顷可耕的领域的9岁周内监测不同杂草物种的空间分布和密度,并与土壤属性有关。杂草幼苗每年在春天在常规网格上测定429个观察点(15 x 7.5米;净研究区= 4公顷)。占优势杂草种类的蛋白酒专辑,Polygonum Aviculare,Viola arvensis和不同的草杂草,明显由Alopecurus myosuroides占主导地位。进行了非侵入式电磁感应调查,以在高空间分辨率下直接评估现场的可用水能。通过具有土壤采样和后续中红外光谱的最小侵入性方法来评估进一步的土壤性质。用常规实验室方法分析植物可用营养素。冗余分析用于描述土壤性质,不同年份和田间作物对杂草物种变异性的影响。七种土壤属性共同解释了30.7%的空间杂草物种变异性,而28.2%通过土壤质地,可用水容量和土壤有机碳解释。基于土壤图创建了特定于现场杂草管理的地图。这些地图允许对精密作物保护的几个好处,例如更好地了解土壤 - 杂草间相互作用,改善采样策略和降低除草剂使用。

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