Soil quality data from Mesa Redonda at Villaverde del Río (ES-SE), field campaign 2023-03
Creators
-
1.
University of Tübingen
Description
Soil quality is a key feature for agriculturual management and to discribe the growing potential for field crops. It involves soil organic carbon content (SOC), soil acidity (pH), cation exchange capacity (CEC) and water content at field capacity (θFC). Since these soil properties are time consuming and costly to measure, we employed machine learning models to predict them from MIR spectra.
The dataset was used to predict soil organic carbon (%), clay (<2 µm), silt (2-50 µm), and sand (50-2000 µm) content (%) and pH on samples that were not analysed with wet chemistry. Subsequently, cation exchange capacity (cmol kg⁻¹; doi:10.1016/j.catena.2017.07.002) and water content at field capacity (cm³ cm⁻³; doi:10.1111/ejss.12192) were calculated with the referenced pedo-transfer functions. The soil samples were taken in an area around Villaverde del Río, Andalusia, Spain, in the Sierra Morena mountain range (Palaeozoic granite, gneiss, and slate) and at the Guadalquivir river flood plain (Pleistocene marl, calcarenite, coarse sand, and Holocene sands and loams). Present soil types according to USDA Soil Taxonomy are Alfisols, Entisols, Inceptisols, and Vertisols.
For more details see "SFB 1070 A02 - Short report on pedological analysis at Mesa Redonda, Villaverde del Río, ES-SE".
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Additional details
Related works
- Continues
- Dataset: 10.1594/PANGAEA.938522 (DOI)
- Dataset: 10.1594/PANGAEA.938512 (DOI)
Dates
- Collected
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2023-03-06/2023-03-18Field campaign
Data quality
- Accuracy
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The soil properties were modelled from MIR spectra. The model evaluation with the 10-fold cross-validation showed high model accuracies for all soil properties with R² ranging from 0.9 to 0.96, CCC ranging from 0.89 to 0.97 and a RMSE of 0.21 % for SOC, 0.31 for pH_KCl, and 4.32 to 6.12 % for the grain size fractions clay, silt and sand (see "Short report on pedological analysis at Mesa Redonda.pdf" for details).
- Completeness
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All entities are complete
- Conformity
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Soil organic carbon content was measured with Vario EL III (Elementar, Hanau, DE)
Soil acidity was measured with pH-electrode SenTix 81 (WTW, Weilheim, DE)
Grain size of sand, silt and clay was measured with SediGraph III (Micromeritics, Unterschleißheim, DE); DIN 19683-1 and DIN 19683-2
Cation exchange capacity (CEC) was calculated with a pedotransfer function (Khaledian et al., 2017)
Water content at field capacity (θFC) was calculated with a pedotransfer function (Tóth et al., 2015)
MIR spectra were measured with a Vertex 80v (Bruker Optics, Ettlingen, DE)
Soil quality index was calculated as arithmetic mean of soil quality ratings of SOC, CEC and θFC (Hazelton & Murphy, 2007); Pulido et al., 2017; Rentschler et al., 2022)
- Consistency
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no contradiction
- Credibility
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The soil properties were modelled from MIR spectra. The model evaluation with the 10-fold cross-validation showed high model accuracies for all soil properties with R² ranging from 0.9 to 0.96, CCC ranging from 0.89 to 0.97 and a RMSE of 0.21 % for SOC, 0.31 for pH_KCl, and 4.32 to 6.12 % for the grain size fractions clay, silt and sand (see "Short report on pedological analysis at Mesa Redonda.pdf").
- Processability
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Data is completely machine readable
- Relevance
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The data is relevant for soil sciences and related disciplines in the context of soil quality and agronomy.
- Timeliness
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not applicable
- Understandability
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The data is understandable and interpretable by soil scientists and related disciplines, e.g. geography, agronomy and ecology.
Study design and Methodology
- Analysis unit
- geographic unit
- Character set
- utf-8
- Data source type
- research data
- Data type
- double, integer
- General data format
- numeric, geospatial
- Lifecycle event type
- sampling, data processing
- Mode of collection
- field observation, laboratory observation
- Sampling procedure
- stratified
- Software package
- r