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首页> 外文期刊>Geoderma: An International Journal of Soil Science >Geostatistical modeling of the spatial variability and risk areas of southern root-knot nematodes in relation to soil properties
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Geostatistical modeling of the spatial variability and risk areas of southern root-knot nematodes in relation to soil properties

机译:与土壤特性相关的南方根结线虫的空间变异性和危险区域的地统计学模型

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Identifying the spatial variability and risk areas for southern root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) is key for site-specific management (SSM) of cotton (Gossypium hirsutum L) fields. The objectives of this study were to: (i) determine the soil properties that influence RKN occurrence at different scales: and (ii) delineate risk areas of RKN by indicator kriging. The study site was a cotton field located in the southeastern coastal plain region of the USA Nested semivariograms indicated that RKN samples, collected from a 50 x 50 m grid. exhibited a local and regional scale of variation describing small and large clusters of RKN population density. Factorial kriging decomposed RKN and soil properties variability into different spatial components. Scale dependent correlations between RKN data showed that the areas with high RKN population remained stable though the growing season. RKN data were strongly correlated with slope (SL) at local scale and with apparent soil electrical conductivity deep (EC) at both local and regional scales, which illustrate the potential of these soil physical properties as surrogate data for RKN population. The correlation between RKN data and soil chemical properties was soil texture mediated. Indicator kriging (IK) maps developed using either RKN, the relation between RKN and soil electrical conductivity or a combination of both, depicted the probability for RKN population to exceed the threshold of 100 second stage juveniles/100 cm(3) of soil. Incorporating EC, as soft data improved predictions favoring the reduction of the number of RKN observations required to map areas at risk for high RKN population.
机译:识别南部根结线虫[Meloidogyne incognita(Kofoid&White)Chitwood](RKN)的空间变异性和风险区域对于棉花(Gossypium hirsutum L)棉田进行定点管理(SSM)是关键。这项研究的目的是:(i)确定在不同尺度上影响RKN发生的土壤特性;以及(ii)通过指示克里格法划定RKN的风险区域。研究地点是位于美国东南沿海平原地区的棉田。嵌套半变异函数表明,RKN样本是从50 x 50 m的网格中收集的。展示了描述RKN人口密度的大小集群的局部和区域变化规模。阶乘克里金法将RKN和土壤特性变异性分解为不同的空间成分。 RKN数据之间的比例相关性表明,尽管生长期较高,但RKN人口较高的地区仍保持稳定。 RKN数据与局部尺度的坡度(SL)以及局部和区域尺度的表观土壤电导率深层(EC)密切相关,这说明了这些土壤物理性质作为RKN种群替代数据的潜力。 RKN数据与土壤化学性质之间的相关性是由土壤质地介导的。使用RKN,RKN与土壤电导率或二者的关系开发的指标克里金(IK)图描述了RKN种群超过100个第二阶段幼虫/ 100 cm(3)的阈值的概率。合并EC,因为软数据改善了预测,有利于减少绘制高RKN人口风险地区所需的RKN观测数。

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