Geostatistical modeling of the spatial variability and risk areas of southern root-knot nematodes in relation to soil properties.
Geostatistical modeling of the spatial variability and risk areas of southern root-knot nematodes in relation to soil properties.
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DOI：
10.1016/j.geoderma.2010.02.024
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发表时间：
2010-05
期刊：
影响因子：
6.1
通讯作者：
Sullivan D
中科院分区：
文献类型：
--
作者：
Ortiz BV;Perry C;Goovaerts P;Vellidis G;Sullivan D
确定南方根结线虫（Meloidogyne incognita (Kofoid & White) Chitwood） （RKN）的空间变异和风险区域是棉花（Gossypium hirsutum L.）田间特定管理（SSM）的关键。本研究的目的是：(i)确定在不同尺度上影响RKN发生的土壤性质；（ii）用指标克里格法划定RKN的风险区域。研究地点是位于美国东南沿海平原地区的一片棉田。嵌套半变异图表明，从50×50 m网格中收集的RKN样本表现出局部和区域尺度的变化，描述了RKN种群密度的大小集群。析因克里格将RKN和土壤性质变异分解为不同的空间分量。RKN数据的尺度相关关系表明，RKN种群高的地区在整个生长季节都保持稳定。RKN数据在局部尺度上与坡度（SL）、在局部和区域尺度上与土壤电导率深度（ECa-d）密切相关，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的相关性是由土壤质地介导的。利用RKN、RKN与土壤电导率之间的关系或两者的结合开发的指标克里格（IK）图描绘了RKN种群超过100第二阶段幼虫/100 cm3土壤阈值的概率。将ECa-d作为软数据纳入预测，有利于减少绘制高RKN人口风险地区所需的RKN观测数量。
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 50×50 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 (ECa-d) 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 cm3 of soil. Incorporating ECa-d as soft data improved predictions favoring the reduction of the number of RKN observations required to map areas at risk for high RKN population.
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影响因子：
6.1
作者：
Castrignanò, A;Giugliarini, L;Martinelli, N
通讯作者：
Martinelli, N
DOI：
10.1007/s00254-002-0600-5
发表时间：
2002-11-01
期刊：
ENVIRONMENTAL GEOLOGY
影响因子：
--
作者：
Lin, YP;Chang, TK;Tseng, CH
通讯作者：
Tseng, CH
影响因子：
2.1
作者：
Avendaño, F;Schabenberger, O;Melakeberhan, H
通讯作者：
Melakeberhan, H
影响因子：
6.1
作者：
GOOVAERTS, P
通讯作者：
GOOVAERTS, P
影响因子：
2.8
作者：
Grunwald, S;Goovaerts, P;Lamsal, S
通讯作者：
Lamsal, S