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Phenotyping template with the Breedbase plot names of a design

Source: R/breedbase_phenotypes.R
phenotype_template.Rd

Makes a table with one row per plot, the plot names that save_breedbase() gives (or gave) to the plots, the design columns (accession, block, rep, row, column) and one empty column per trait. Fill it in (in R or in a spreadsheet) and upload it with save_breedbase_phenotypes().

Usage

phenotype_template(
  design,
  trial_name,
  traits = character(0),
  plot_name_pattern = "{trial}_{accession}_{block}_{rep}",
  plot_names = NULL
)

Arguments

design

A design from augmented_row_column_design(), augmented_prep_design(), resolvable_row_column_design(), as_breedbase_design() or prepare_breedbase_trial().

trial_name

The trial name used when saving the design. For p-rep designs saved as one trial per location, the location is added as in save_breedbase(). Can be omitted for a prepared Breedbase trial.

traits

Trait names as in Breedbase, e.g. "fresh root yield" or "fresh root yield|CO_334:0000013". Can be empty (no trait columns).

plot_name_pattern, plot_names

The same plot naming used in save_breedbase().

Value

A tibble: plot_name, trial_name, accession, plot_number, block, rep, row, col, is_check and one column per trait.

Examples

rc <- augmented_row_column_design(paste0("G", 1:108), paste0("C", 1:4),
                                  12, 12, 4, 4, n_candidates = 5, seed = 1)
sheet <- phenotype_template(rc, "AYT_2026_Ibadan",
                            traits = c("fresh root yield", "dry matter content percentage"))
head(sheet)
#> # A tibble: 6 × 11
#>   plot_name    trial_name accession plot_number block   rep   row   col is_check
#>   <chr>        <chr>      <chr>           <int> <int> <int> <int> <int> <lgl>   
#> 1 AYT_2026_Ib… AYT_2026_… G51                 1     1     1     1     1 FALSE   
#> 2 AYT_2026_Ib… AYT_2026_… G64                 2     1     1     1     2 FALSE   
#> 3 AYT_2026_Ib… AYT_2026_… G97                 3     1     1     1     3 FALSE   
#> 4 AYT_2026_Ib… AYT_2026_… C3                  4     1     1     1     4 TRUE    
#> 5 AYT_2026_Ib… AYT_2026_… G8                  5     2     1     1     5 FALSE   
#> 6 AYT_2026_Ib… AYT_2026_… C2                  6     2     2     1     6 TRUE    
#> # ℹ 2 more variables: `fresh root yield` <dbl>,
#> #   `dry matter content percentage` <dbl>