Title of the dataset:
Analysis output from: Potential of boreholes combined with deep-rooted cover crops to ameliorate subsoil compaction

Creators:
Isabella Selin-Norén 
Affiliation: Field Crops, Wageningen University & Research
ORCID: 0000-0003-2481-3252

Derk van Balen 
Affiliation: Field Crops, Wageningen University & Research

Vera Velt 
Affiliation: Field Crops, Wageningen University & Research

Related publications:
Selin-Norén, I.L.M., Velt, V., van Gestel, S., van Balen, D. 2023. Potential of boreholes combined with deep-rooted cover crops to ameliorate subsoil compaction: year 2022; Results from the final year of the experiments; 2022 . Wageningen Research, Report WPR-OT 999.
DOI: https://doi.org/10.18174/634018

Selin-Norén, I.L.M., Velt, V., van Gestel, S., van Balen, D. 2023. Potential of boreholes combined with deep-rooted cover crops to ameliorate subsoil compaction: Results from 2021-2022. Wageningen Research, Report WPR-OT 999.
DOI: https://doi.org/10.18174/588727

Description:
Due to climate change longer periods of drought and high precipitation in short periods of time will become more common. Subsoil compaction causes cropland to be less resilient to such changes due to worse root growth, water infiltration and less capillary rise of water. There is a lack of measures to ameliorate subsoil compaction. Two experiments were performed where the potential of different types of boreholes were compared to deep subsoiling and an untreated reference. Effects on soil structure and crop productivity were analysed. Data and scripts are not provided, only HTML output files.

Keywords:
deep-rooted cover crops; subsoil compaction; boreholes; soil structure;

Spatial coverage:
Lelystad and  Vreedepeel, the Netherlands

Temporal coverage:
2021-2022

This dataset contains the following files:
├──Results from 2020_2022
     ──LS_2020_2021_Soil_Moisture_sensors.html
     ──LS_2020_2022_Bulk_density.html
     ──LS_2020_Penetration_resistance.html
     ──LS_2021-2022_Bulk_density.html
     ──LS_2021_2022_Penetration_resistance.html
     ──LS_2021_Cover_crop.html
     ──LS_2022_Moisture_rings.html
     ──LS_2022_Nitrogen.html
     ──LS_2022_Potato_yield.html
     ──VP_2020_2022_Cover_crop.html
     ──VP_2020_Penetration_resistance.html
     ──VP_2021-2022_Bulk_Density.html
     ──VP_2021-2022_Moisture_rings.html
     ──VP_2021-2022_Nitrate_leaching.html
     ──VP_2021-2022_Penetration_resistance.html
     ──VP_2021_2022_Soil_Moisture_sensors.html
     ──VP_2021_Silage_maize_yield.html
     ──VP_2022_Potato_yield.html
├───Results from final year 2022
     ──LS_2022_Bulk_density.html
     ──LS_2022_Moisture_rings.html
     ──LS_2022_Penetration_resistance.html
     ──VP_2022_Bulk_Density.html
     ──VP_2022_Cover_crop.html
     ──VP_2022_Moisture_rings.html
     ──VP_2022_Nitrate_leaching.html

Explanation of variables:
Glossary Dutch - English
To understand the statistical output this list of explanations can be used. These terms are Dutch words or abbreviations of Dutch words.
•	VP = Vredepeel
•	LS = Lelystad
•	SS - subsoiling
•	SB - small boreholes
•	LB - large boreholes
•	Ref - No mechanical treatment		
•	Figuur - Figure
•	Droge_stof_kg_ha – Dry plant matter in kg/ha
•	Ondergr_bew – Mechanical treatment
•	Gr_bem – Cover crop treatment
•	Blok – Block
•	Bulk_gew_g_cm3 – dried bulk weight of the soil in g/cm3
•	Jaar – year
•	Wortels_loof – roots or leaves
•	Grond - soil
•	Fractie_water – fraction of water in soil
•	No3_meting_gw_mg_no3_l – NO3 measurement ground water in mg NO3/L
•	Knol - tuber
•	Stolon – stolon
•	Loof - leaves


Methods, materials and software:
All data analysis and visualisation was done in R (R Core Team, 2021) and the output is made available as HTML files. Response variables were checked for outliers and type of distribution using boxplots and histograms. Ln-transformations were performed for nitrate concentration in the groundwater, potato yield losses and <70 mm sized potato for Vredepeel. All variables had orthogonal data with four repetitions. For all variables a linear model was fit and an ANOVA was performed. Variable selection was done using the Akaike information criterion (AIC) using the function stepAIC from the package MASS (Venables & Ripley, 2002) with the full tested model containing the mechanical treatment and the cover crop treatment including their interaction, the blocking factor, the row in the experimental setup and year. The interaction term between the treatments was excluded if not statistically significant. In some cases an ANOVA III was used for comparing two models. For nitrate concentration in the groundwater, the moment of sampling and depth of groundwater were also tested for inclusion into the model. Pairwise comparisons were made using the emmeans package (Lenth, 2021). Penetration resistance was analysed per 5 cm of depth. All figures in the results section in were made with ggplot2 (Wickham, 2016). The full data analysis and statistical output is available at this link. Throughout the results section there will be links referring to this site with the HTML file name indicated.


This dataset is published under the CC BY (Attribution) license.
This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator.

