A dataset containing soil physical, chemical, and fertility properties from 50 soil samples collected in the Ucayali region of Peru. This dataset is provided as an example for demonstrating the soil quality index (SQI) calculation workflow.
Format
A data frame with 50 rows and 15 columns:
- SampleID
Character. Unique identifier for each soil sample (UCY001-UCY050)
- Sand
Numeric. Sand content as percentage of soil texture (0-100)
- Silt
Numeric. Silt content as percentage of soil texture (0-100)
- Clay
Numeric. Clay content as percentage of soil texture (0-100)
- BD
Numeric. Bulk density in g/cm³
- pH
Numeric. Soil pH measured in water (1:1)
- OM
Numeric. Organic matter content as percentage
- SOC
Numeric. Soil organic carbon content as percentage
- N
Numeric. Total nitrogen content as percentage
- P
Numeric. Available phosphorus in mg/kg (Olsen method)
- K
Numeric. Exchangeable potassium in mg/kg
- CEC
Numeric. Cation exchange capacity in cmol/kg
- Ca
Numeric. Exchangeable calcium in cmol/kg
- Mg
Numeric. Exchangeable magnesium in cmol/kg
- EC
Numeric. Electrical conductivity in dS/m
Details
The dataset represents typical soil properties found in tropical agricultural soils of the Ucayali region. Values are simulated but based on realistic ranges for this region. The soils are generally acidic (pH 4-7.5), with moderate organic matter content and variable nutrient levels.
This dataset can be used to:
Demonstrate the complete SQI calculation workflow
Test different property selection strategies
Explore various scoring rules and weighting methods
Generate example visualizations
Examples
# Load the dataset
data(soil_ucayali)
# View structure
str(soil_ucayali)
#> 'data.frame': 50 obs. of 15 variables:
#> $ SampleID: chr "UCY001" "UCY002" "UCY003" "UCY004" ...
#> $ Sand : num 42.4 42.7 54.6 41.9 50.1 49.5 57.6 38.3 40.8 38.6 ...
#> $ Silt : num 35.4 30.2 25.4 37.4 30.3 31.8 20.1 44.6 34.4 30.8 ...
#> $ Clay : num 22.2 27.1 20 20.7 19.6 18.7 22.3 17.1 24.8 30.6 ...
#> $ BD : num 1.47 1.47 1.4 1.2 1.33 1.31 1.43 1.29 1.5 1.29 ...
#> $ pH : num 7 6.2 5 5.6 4.9 4.8 4.6 4.7 6.5 5.2 ...
#> $ OM : num 2.46 2.29 2.49 2.88 4.24 2.72 3.77 3.37 2.7 1.42 ...
#> $ SOC : num 1.24 1.22 1.13 1.07 1.38 1.77 0.59 1.71 2.22 2.62 ...
#> $ N : num 0.201 0.05 0.129 0.156 0.105 0.167 0.171 0.148 0.05 0.279 ...
#> $ P : num 7.8 4.5 6.1 7.9 10 3 7 10.3 6.4 8.7 ...
#> $ K : num 131 121 106 113 118 40 123 83 101 88 ...
#> $ CEC : num 10.2 9 15.1 14.3 7.5 11.7 9.3 5.8 12.5 11.8 ...
#> $ Ca : num 5.51 3.56 5.83 4.8 6.48 2.75 4.44 3.87 4.26 3.74 ...
#> $ Mg : num 2.44 1.78 1.78 0.89 2.27 1.67 1.41 0.95 1.62 1.29 ...
#> $ EC : num 0.06 0.26 0.31 0.1 0.3 0.17 0.35 0.3 0.33 0.26 ...
# Summary statistics
summary(soil_ucayali)
#> SampleID Sand Silt Clay
#> Length:50 Min. :29.60 Min. :15.90 Min. :11.30
#> Class :character 1st Qu.:39.25 1st Qu.:25.52 1st Qu.:18.90
#> Mode :character Median :43.45 Median :30.65 Median :23.35
#> Mean :45.21 Mean :31.45 Mean :23.34
#> 3rd Qu.:50.55 3rd Qu.:36.17 3rd Qu.:27.68
#> Max. :64.30 Max. :46.30 Max. :38.00
#> BD pH OM SOC
#> Min. :1.150 Min. :4.100 Min. :1.220 Min. :0.570
#> 1st Qu.:1.280 1st Qu.:4.600 1st Qu.:2.507 1st Qu.:1.240
#> Median :1.335 Median :5.050 Median :2.895 Median :1.585
#> Mean :1.355 Mean :5.192 Mean :3.024 Mean :1.601
#> 3rd Qu.:1.430 3rd Qu.:5.600 3rd Qu.:3.643 3rd Qu.:1.972
#> Max. :1.800 Max. :7.000 Max. :4.860 Max. :2.620
#> N P K CEC
#> Min. :0.0500 Min. : 2.000 Min. : 40.0 Min. : 5.80
#> 1st Qu.:0.1128 1st Qu.: 6.150 1st Qu.: 88.0 1st Qu.:10.22
#> Median :0.1505 Median : 8.050 Median :102.0 Median :11.75
#> Mean :0.1469 Mean : 7.860 Mean :102.2 Mean :12.08
#> 3rd Qu.:0.1755 3rd Qu.: 9.575 3rd Qu.:118.0 3rd Qu.:14.05
#> Max. :0.2790 Max. :15.200 Max. :144.0 Max. :19.30
#> Ca Mg EC
#> Min. :1.130 Min. :0.240 Min. :0.0500
#> 1st Qu.:3.560 1st Qu.:1.292 1st Qu.:0.1700
#> Median :4.410 Median :1.700 Median :0.2400
#> Mean :4.366 Mean :1.701 Mean :0.2374
#> 3rd Qu.:5.178 3rd Qu.:2.180 3rd Qu.:0.3000
#> Max. :6.730 Max. :3.050 Max. :0.5000
# Basic SQI calculation with standard properties
if (FALSE) { # \dontrun{
result <- compute_sqi_properties(
data = soil_ucayali,
properties = c("pH", "OM", "N", "P", "K", "CEC"),
id_column = "SampleID"
)
print(result)
} # }