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首页> 外文期刊>European Journal of Agronomy >Quantifying the effects of soil variability on crop growth using apparent soil electrical conductivity measurements
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Quantifying the effects of soil variability on crop growth using apparent soil electrical conductivity measurements

机译:使用表观土壤电导率测量量化土壤变异性对作物生长的影响

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摘要

Spatial heterogeneity of crop growth within fields is rarely quantified but essential for estimating yield and optimizing crop management. Relationships in fields between crop growth and soil physical characteristics have been described before but an unrealistically high number of invasive measurements have to be made to obtain spatially continuous soil information. Alternatively, non-invasive methods are available for characterizing soil heterogeneity but relationships to growth characteristics have rarely been investigated. Here, we use an electromagnetic induction (EMI) sensor to measure the apparent electromagnetic conductivity of the soil (ECa), which can be used as a proxy for the relative spatial variability of the prevailing soil properties. We evaluate relationships between ECa and soil and crop characteristics assuming that measured ECa patterns relate to observed growth patterns in the field. The test fields were located in Western Germany where different crops (winter wheat, winter barley, and sugar beet) were grown between 2011 and 2013. Measurements include soil texture, soil moisture and crop growth characteristics taken frequently throughout the vegetation periods for plant height, leaf area index (LAI), dry matter of plants and selected organs (green leaves and storage organs). Spatial variability was observed for soil and crop characteristics that differed among fields, crops and years. Good correlations between ECa and soil texture and soil moisture confirmed that ECa measurements are suitable for characterizing spatial differences in soil properties for our test sites. Averaged over all sampling dates of a vegetation period the differences in the spatial variability of crop characteristics were small between the years and crops considered. However, the within-field crop growth heterogeneity changed throughout the growing period depending on the crop development stage. Correlations were found between ECa and the crop characteristics that varied with time and were most pronounced in the main growth phase when LAI approached its maximum. Crop height correlated better with ECa than yield, LAI, and dry matter but differences were observed between fields, years and crops. Our results suggest that in dry years soil patterns have a stronger influence on the crop growth patterns than in wetter years when water limitation is less severe. We conclude that ECa measurements are suitable for detecting spatial patterns in soil characteristics that influence the spatial crop growth patterns for the region, years and crops considered. However, relationships between patterns in crop growth and soil characteristics within fields are more complex and require further investigation. (C) 2014 Elsevier B.V. All rights reserved.
机译:田间作物生长的空间异质性很少被量化,但是对于估计产量和优化作物管理至关重要。先前已经描述了作物生长与土壤物理特性之间的田间关系,但是必须进行大量不实际的侵入式测量才能获得空间连续的土壤信息。另外,非侵入性方法可用于表征土壤异质性,但很少研究与生长特性的关系。在这里,我们使用电磁感应(EMI)传感器来测量土壤的表观电磁传导率(ECa),可以用作主要土壤属性的相对空间变异性的代理。假设测得的ECa模式与田间观察到的生长模式相关,我们评估ECa与土壤和作物特性之间的关系。试验场位于德国西部,2011年至2013年间种植了不同的农作物(冬小麦,冬大麦和甜菜)。测量包括土壤质地,土壤湿度和整个植物生长时期针对植物高度经常采集的作物生长特征,叶面积指数(LAI),植物和选定器官(绿叶和贮藏器官)的干物质。土壤和作物特征的空间变异性在田间,作物和年份之间有所不同。 ECa与土壤质地和土壤水分之间的良好相关性证明,ECa测量值适合表征我们测试地点土壤特性的空间差异。在一个植被期的所有采样日期取平均值,所考虑的年份和作物之间作物特征的空间变异性差异很小。然而,田间作物生长异质性在整个生长期根据作物的生长阶段而变化。发现ECa与作物特性之间的相关性随时间变化,并且在LAI接近最大值时在主要生长期最为明显。作物高度与ECa的相关性比产量,LAI和干物质更好,但在田间,年份和作物之间观察到差异。我们的结果表明,在干旱年份,水分限制不太严重的情况下,土壤模式对农作物生长模式的影响要强于潮湿年份。我们得出结论,ECa测量值适合检测土壤特征中的空间格局,这些特征会影响所考虑的区域,年份和作物的空间作物生长格局。但是,作物生长方式与田间土壤特性之间的关系更为复杂,需要进一步研究。 (C)2014 Elsevier B.V.保留所有权利。

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