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| Home > Publications database > Quantifying the effects of soil variability on crop growth using apparent soil electrical conductivity measurements |
| Journal Article | FZJ-2015-01036 |
; ; ; ; ;
2015
Elsevier Science
Amsterdam [u.a.]
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Please use a persistent id in citations: doi:10.1016/j.eja.2014.12.004
Abstract: 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.
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