Hbirkou, Christine: Heterogeneity of soil properties at the field-scale and spatial patterns of soil-borne pests and weeds. - Bonn, 2012. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5n-27419
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5n-27419,
author = {{Christine Hbirkou}},
title = {Heterogeneity of soil properties at the field-scale and spatial patterns of soil-borne pests and weeds},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2012,
month = apr,

note = {Soil heterogeneity at the field-scale not only affects crop growth and yield, but also spatial patterns of soil-borne pests and weeds. Therefore, site-specific management in due consideration of soil variability is required within the scope of precision crop protection. The focus of this study was the use of minimal- and non-invasive sensor technologies at the field-scale to improve (i) the assessment of soil organic carbon (SOC), (ii) management strategies for the beet cyst nematode Heterodera schachtii and (iii) the appreciation for complex interrelations of soil properties and weeds.
A detailed knowledge on high-resolution SOC heterogeneity in agricultural soils is required, because SOC affects other soil properties such as aggregate stability or soil respiration. The small-scale spatial variability of SOC was determined using imaging spectroscopy in the visible and near-infrared region on long-term uniformly cultivated test fields with varying soil surface conditions (roughness, vegetation). Soil reflectance was recorded by the aircraft-mounted hyperspectral sensor HyMap (450 – 2500 nm). Site-specific characteristics affected the calibration models; highest prediction accuracy was performed over a bare, fine soil (R2 = 0.80). A generated pixel-wise map (8 × 8 m) on the basis of hyperspectral data visualise the SOC heterogeneity more realistic than an interpolated map based on conventional soil sampling. In addition, the prediction of SOC over a time period of three years was possible.
Soil texture is often referred to be the dominant soil property affecting the population density of the beet cyst nematode H. schachtii. The apparent electrical conductivity (ECa), which is known to be strongly related to soil texture and porosity, was measured with the non-invasive EM38 sensor. On fields heterogeneous in texture and porosity, moderate (R2 = 0.47) and strong (R2 = 0.74) correlations were observed between ECa and nematode population density. ECa values and soil taxation maps reveal that H. schachtii prefers deep soils with medium to light texture, a high proportion of wide pores and non-stagnic water conditions. Management maps on the basis of ECa and soil taxation maps indicate areas with different soil-related living conditions for H. schachtii.
The spatial distribution and density of four weed species was observed within a long-term survey over nine years on an arable field and related to soil properties. The dominance of the weed species varied between the years, but the spatial patterns remained stable during the whole study period. Soil properties were analysed conventionally in the laboratory and via mid-infrared spectroscopy-partial least squares regression (MIRS-PLSR) or EM38 measurements. Multivariate statistics were used to describe the effect of soil properties, indicating that soil texture, available water capacity and SOC explained 28.2% of the weed species variability. The spatial distribution of soil properties can be used to create maps for site-specific weed management. The study provide evidence that minimal- and non-invasive sensor technologies such as MIRS-PLSR, airborne hyperspectral imaging or EM38 measurements are practical methods to detect soil heterogeneity at the field-scale. SOC and soil texture, both important parameters for the occurrence of soil-borne pests and weeds, can be characterised with high spatial resolution. Management maps on the basis of soil properties permit several benefits for precision crop protection, such as improved site-specific management strategies of pests and weeds.},

url = {https://hdl.handle.net/20.500.11811/5093}

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