| Title: | USDA Northern Region Uniform Soybean Tests Dataset |
| Version: | 1.0.0 |
| Author: | Matheus Dalsente Krause
|
| Maintainer: | Matheus Dalsente Krause <krause.d.matheus@gmail.com> |
| Description: | Data sets used by 'Krause et al. (2022)' <doi:10.1101/2022.04.11.487885>. It comprises phenotypic records obtained from the USDA Northern Region Uniform Soybean Tests from 1989 to 2019 for maturity groups II and III. In addition, soil and weather variables are provided for the 591 observed environments (combination of locations and years). |
| URL: | https://github.com/mdkrause/soyurt |
| NeedsCompilation: | no |
| Language: | en-US |
| License: | CC BY 4.0 |
| Encoding: | UTF-8 |
| Depends: | R (≥ 3.5.0) |
| LazyData: | true |
| LazyDataCompression: | xz |
| RoxygenNote: | 7.2.0 |
| Suggests: | spelling |
| Packaged: | 2022-06-10 14:41:03 UTC; mdkrause |
| Repository: | CRAN |
| Date/Publication: | 2022-06-13 06:30:03 UTC |
Phenotype
Description
Modeled data set by Krause et al. (2022) from the USDA Northern Region Uniform Soybean Tests. The data contains 4,257 experimental genotypes evaluated at 63 locations and 31 years resulting in 591 location-year combinations (environments) with 39,006 yield values belonging to matirity groups II and III from 1989 to 2019. Annual PDF reports from the Northern Region of the USDA Uniform Soybean Tests were obtained from https://ars.usda.gov/mwa/lafayette/cppcru/ust. The data retrieved from the published PDF files represent averages for seed yield for each genotype evaluated at each trial in location-year combinations. Seed yield was adjusted to 13% moisture and results were reported in bushels per acre (bu/ac). For more information about the trial field plot design and agronomic practices, please refer to the PDF files. The raw data can also be downloaded from Soybase: https://soybase.org/ncsrp/queryportal/.
Usage
pheno
Format
A data frame in tidy format with 39,006 observations on the following 13 variables:
yearyears, 31 levels (1989 - 2019)
locationlocations, 63 levels (observed locations in the historical series)
latitudelatitude
longitudelongitude
altitudealtitude
trialname of the trial that originated the phenotypic record
checkindicator variable for variety checks, 2 levels (yes or no)
maturity_groupgenotype's maturity group, 2 levels (II or III)
Ggenotype, 4,257 levels
eBLUEempirical best linear unbiased estimate of genotype means
SEstandard error of genotype means on a location level
average_planting_dateaverage planting date on a location level (MM/DD/YY)
average_maturity_dateaverage maturity date on a location level in days after planting
Source
Krause, M. D., Dias, K. O. G., Singh, A. K., and Beavis. W. D. (2022). Using large soybean historical data to study genotype by environment variation and identify mega-environments with the integration of genetic and non-genetic factors. bioRxiv, doi: 10.1101/2022.04.11.487885
Soil variables
Description
Soil variables in a depth interval of 5 to 15 cm were obtained from Soilgrids (https://soilgrids.org/) for the 63 observed locations in the historical series analyzed by Krause et al. (2022). The R code used to download and process the soil data can be retrieved at https://github.com/mdkrause/VarComp-ME/blob/main/soil_data.R.
Usage
soil
Format
A data frame in tidy format with 504 observations on the following 5 variables:
Featuresoil variables, 8 levels
locationlocations, 63 levels (observed locations in the historical series)
Soil_Gridmean values of the soil variables (Feature)
LATlocation latitude
LONlocation longitude
Details
Levels of Feature:
- bdod_5-15cm_mean:
Bulk density of the fine earth fraction (cg/m
^3)- cec_5-15cm_mean:
Cation Exchange Capacity of the soil (mmol(c)/kg)
- clay_5-15cm_mean:
Proportion of clay particles (< 0.002 mm) in the fine earth fraction (g/kg)
- nitrogen_5-15cm_mean:
Total nitrogen (cg/kg)
- phh2o_5-15cm_mean:
Soil pH (pH
\times10)- sand_5-15cm_mean:
Proportion of sand particles (
>0.05 mm) in the fine earth fraction (g/kg)- silt_5-15cm_mean:
Proportion of silt particles (
\ge0.002 mm and\leq0.05 mm) in the fine earth fraction (g/kg)- soc_5-15cm_mean:
Soil organic carbon content in the fine earth fraction (dg/kg)
Source
Krause, M. D., Dias, K. O. G., Singh, A. K., and Beavis. W. D. (2022). Using large soybean historical data to study genotype by environment variation and identify mega-environments with the integration of genetic and non-genetic factors. bioRxiv, doi: 10.1101/2022.04.11.487885
Weather variables
Description
Weather variables obtained from NASA's Prediction of Worldwide Energy Resource (https://power.larc.nasa.gov/) for the 591 environments in the historical series analyzed by Krause et al. (2022).
Usage
weather
Format
A data frame in messy format with 504 observations on the following 5 variables:
locationlocations, 63 levels (observed locations in the historical series)
LONlongitude
LATlatitude
DOYday of the year
YYYYMMDDcalendar date in the format YYYY/MM/DD
daysFromStartdays from average planting date
T2Mdaily average temperature at 2 meters
T2M_MAXdaily maximum temperature at 2 meters
T2M_MINdaily minimum average temperature at 2 meters
PRECTOTrainfall precipitation
WS2Mwind speed at 2 meters
RH2Mrelative humidity at 2 meters
T2MDEWdew point at 2 meters
ALLSKY_SFC_LW_DWNdownward thermal infrared (longwave) radiative flux
ALLSKY_SFC_SW_DWNinsolation incident on a horizontal surface
nduration of sunshine in hours
VPDthe deficit of vapor pressure
SPVthe slope of saturation vapor pressure curve
ETPevapotranspiration
PETPdeficit of evapotranspiration
GDDgrowing degree-days
FRUEeffect of temperature on radiation use efficiency
T2M_RANGEdaily temperature range at 2 meters
PTTphotothermal time (GDD
\timesdaylight in hours)PTRphotothermal ratio (GDD / daylight in hours)
Note
Comprehensive R Archive Network (CRAN) policy limits R package size to 5 Mb. In order to give the users new opportunities of data analysis, we provide weather data for all combinations of locations (63) and years (31), resulting in information for 1,953 environments. If an environment was not observed in a given year, weather data was retrieved with the average planting and maturity data based on the empirical data for that location. This data set can be downloaded here.
Source
Krause, M. D., Dias, K. O. G., Singh, A. K., and Beavis. W. D. (2022). Using large soybean historical data to study genotype by environment variation and identify mega-environments with the integration of genetic and non-genetic factors. bioRxiv, doi: 10.1101/2022.04.11.487885