Two-Factors Design: Augmented Design in RCBD

Planning an experiment follows a reproducible routine:

  1. Load required libraries: Load inti, knitr, and dplyr packages.
  2. Define factor levels: Set up lists with genotypes, treatments, and management factors.
  3. Dispatch design generator: Choose between CRD, RCBD, Split-plot, or Augmented designs.
  4. Plot the field sketch: Verify spatial layouts and serpentine/zigzag sequences.
  5. Label design: Design the experimental labels to facilitate the data collection.
  6. Export to Field Book app: Generate field-ready sheets with trait parameters.
# Install packages and dependencies

library(inti)
library(dplyr)
library(huito)

Designs with Two Factors

When evaluating two or more factors, four designs become available: CRD, RCBD, Split-plot RCBD, and Augmented.

Augmented Design in RCBD (Augmented RCBD)

The Augmented Design is recommended for screening large collections of entries (e.g., accessions or candidate clones) when seed or space is limited, repeating check varieties in each block while evaluating new entries only once.

# 1. Define checks (commercial controls) and new accessions
checks <- c("INIA_415", "INIA_420")
entries <- paste0("Geno_", 1:50)

# 2. Generate Augmented layout: 18 entries + (2 checks x 3 blocks) = 24 plots
design <- design_augmented(
  checks = checks,
  entries = entries,
  blocks = 5,
  zigzag = FALSE,
  seed = 2026
)

# Fieldbook preview

fb <- design$fieldbook 

fb %>% 
  knitr::kable(caption = "Augmented RCBD Fieldbook preview")
Augmented RCBD Fieldbook preview
qrcode plots ntreat entry type checks block sort rows cols design
inkaverse_1001_INIA_415 1001 1 INIA_415 check 1 1 1 1 1 augmented
inkaverse_1002_Geno_38 1002 40 Geno_38 test 0 1 2 1 2 augmented
inkaverse_1003_Geno_31 1003 33 Geno_31 test 0 1 3 1 3 augmented
inkaverse_1004_Geno_36 1004 38 Geno_36 test 0 1 4 1 4 augmented
inkaverse_1005_Geno_45 1005 47 Geno_45 test 0 1 5 1 5 augmented
inkaverse_1006_Geno_29 1006 31 Geno_29 test 0 1 6 1 6 augmented
inkaverse_1007_Geno_5 1007 7 Geno_5 test 0 1 7 1 7 augmented
inkaverse_1008_Geno_44 1008 46 Geno_44 test 0 1 8 1 8 augmented
inkaverse_1009_INIA_420 1009 2 INIA_420 check 1 1 9 1 9 augmented
inkaverse_1010_Geno_34 1010 36 Geno_34 test 0 1 10 1 10 augmented
inkaverse_1011_Geno_27 1011 29 Geno_27 test 0 1 11 1 11 augmented
inkaverse_1012_Geno_33 1012 35 Geno_33 test 0 1 12 1 12 augmented
inkaverse_2001_INIA_420 2001 2 INIA_420 check 1 2 1 2 1 augmented
inkaverse_2002_Geno_50 2002 52 Geno_50 test 0 2 2 2 2 augmented
inkaverse_2003_Geno_37 2003 39 Geno_37 test 0 2 3 2 3 augmented
inkaverse_2004_Geno_15 2004 17 Geno_15 test 0 2 4 2 4 augmented
inkaverse_2005_INIA_415 2005 1 INIA_415 check 1 2 5 2 5 augmented
inkaverse_2006_Geno_18 2006 20 Geno_18 test 0 2 6 2 6 augmented
inkaverse_2007_Geno_41 2007 43 Geno_41 test 0 2 7 2 7 augmented
inkaverse_2008_Geno_24 2008 26 Geno_24 test 0 2 8 2 8 augmented
inkaverse_2009_Geno_12 2009 14 Geno_12 test 0 2 9 2 9 augmented
inkaverse_2010_Geno_43 2010 45 Geno_43 test 0 2 10 2 10 augmented
inkaverse_2011_Geno_10 2011 12 Geno_10 test 0 2 11 2 11 augmented
inkaverse_2012_Geno_19 2012 21 Geno_19 test 0 2 12 2 12 augmented
inkaverse_3001_Geno_40 3001 42 Geno_40 test 0 3 1 3 1 augmented
inkaverse_3002_Geno_16 3002 18 Geno_16 test 0 3 2 3 2 augmented
inkaverse_3003_INIA_420 3003 2 INIA_420 check 1 3 3 3 3 augmented
inkaverse_3004_Geno_3 3004 5 Geno_3 test 0 3 4 3 4 augmented
inkaverse_3005_Geno_25 3005 27 Geno_25 test 0 3 5 3 5 augmented
inkaverse_3006_Geno_8 3006 10 Geno_8 test 0 3 6 3 6 augmented
inkaverse_3007_Geno_42 3007 44 Geno_42 test 0 3 7 3 7 augmented
inkaverse_3008_Geno_46 3008 48 Geno_46 test 0 3 8 3 8 augmented
inkaverse_3009_Geno_47 3009 49 Geno_47 test 0 3 9 3 9 augmented
inkaverse_3010_Geno_4 3010 6 Geno_4 test 0 3 10 3 10 augmented
inkaverse_3011_INIA_415 3011 1 INIA_415 check 1 3 11 3 11 augmented
inkaverse_3012_Geno_32 3012 34 Geno_32 test 0 3 12 3 12 augmented
inkaverse_4001_Geno_13 4001 15 Geno_13 test 0 4 1 4 1 augmented
inkaverse_4002_Geno_35 4002 37 Geno_35 test 0 4 2 4 2 augmented
inkaverse_4003_Geno_14 4003 16 Geno_14 test 0 4 3 4 3 augmented
inkaverse_4004_Geno_49 4004 51 Geno_49 test 0 4 4 4 4 augmented
inkaverse_4005_INIA_420 4005 2 INIA_420 check 1 4 5 4 5 augmented
inkaverse_4006_Geno_26 4006 28 Geno_26 test 0 4 6 4 6 augmented
inkaverse_4007_Geno_2 4007 4 Geno_2 test 0 4 7 4 7 augmented
inkaverse_4008_Geno_9 4008 11 Geno_9 test 0 4 8 4 8 augmented
inkaverse_4009_Geno_17 4009 19 Geno_17 test 0 4 9 4 9 augmented
inkaverse_4010_Geno_39 4010 41 Geno_39 test 0 4 10 4 10 augmented
inkaverse_4011_INIA_415 4011 1 INIA_415 check 1 4 11 4 11 augmented
inkaverse_4012_Geno_20 4012 22 Geno_20 test 0 4 12 4 12 augmented
inkaverse_5001_Geno_23 5001 25 Geno_23 test 0 5 1 5 1 augmented
inkaverse_5002_Geno_22 5002 24 Geno_22 test 0 5 2 5 2 augmented
inkaverse_5003_Geno_7 5003 9 Geno_7 test 0 5 3 5 3 augmented
inkaverse_5004_Geno_21 5004 23 Geno_21 test 0 5 4 5 4 augmented
inkaverse_5005_Geno_1 5005 3 Geno_1 test 0 5 5 5 5 augmented
inkaverse_5006_Geno_30 5006 32 Geno_30 test 0 5 6 5 6 augmented
inkaverse_5007_Geno_11 5007 13 Geno_11 test 0 5 7 5 7 augmented
inkaverse_5008_INIA_420 5008 2 INIA_420 check 1 5 8 5 8 augmented
inkaverse_5009_Geno_6 5009 8 Geno_6 test 0 5 9 5 9 augmented
inkaverse_5010_INIA_415 5010 1 INIA_415 check 1 5 10 5 10 augmented
inkaverse_5011_Geno_48 5011 50 Geno_48 test 0 5 11 5 11 augmented
inkaverse_5012_Geno_28 5012 30 Geno_28 test 0 5 12 5 12 augmented

# Field layout visualization
tarpuy_plotdesign(
  data = design,
  factor = "type",          
  fill = c("plots", "entry")
)

Label

The experimental field book generated by the design is used as the input data for label creation. Each row represents an experimental unit, allowing the automatic generation of individualized labels.

Customize the label layout

The label layout can be customized by combining text, images and QR codes. Each layer can use values from the experimental field book, allowing automatic generation of labels for every experimental plot.

Load package and import fonts.

font <- c("Permanent Marker", "Tillana", "Courgette")

huito_fonts(font)

You can find more fonts in https://fonts.google.com/

Label design

label <- fb %>%
  label_layout(
    size = c(5.2, 10)
    ,
    border_color = "#5C0000"
    ,
    border_width = 1.5
  ) %>%
  include_image(
    value = "https://inkaverse.com/img/inkaverse.png"
    ,
    size = c(1.3, 1.5)
    ,
    position = c(0.8, 9.1)
  )  %>%
  include_text(
    value = "plots"
    ,
    position = c(4.2, 9.1)
    ,
    size = 20
    ,
    color = "black"
    ,
    fontface = "bold"
    ,
    font = font[1]
  )  %>%
  include_image(value = "https://huito.inkaverse.com/img/scale.pdf"
                ,
                size = c(5, 1)
                ,
                position = c(2.6, 7.7)) %>%
  include_barcode(value = "qrcode"
                  ,
                  size = c(5, 5)
                  ,
                  position = c(2.6, 4.7)) %>%
  include_text(
    value = "checks"
    ,
    position = c(2.6, 2)
    ,
    size = 12
    ,
    prefix = "Checks: "
    ,
    color = "blue"
    ,
    font = font[2]
    , 
    fontface = "bold"
  )  %>%
    include_text(
    value = "entry"
    ,
    position = c(2.6, 1.5)
    ,
    size = 12
    ,
    prefix = "Entry: "
    ,
    color = "red"
    ,
    font = font[2]
    , 
    fontface = "bold"
  )  %>%
  include_image(value = "https://huito.inkaverse.com/img/scale.pdf"
                ,
                size = c(5, 1)
                ,
                position = c(2.6, 0.6)) 

Label preview

The preview mode label_print(mode = "preview") generate a example of the label design from a random row of the data set.

label %>% 
  label_print(mode = "preview")

Generate the complete labels

If you want generate the complete labels list, change: label_print(mode = "complete").

label %>% 
  label_print(mode = "complete"
              , filename = "vertical-aug")