Supplementary Tables

Complete statistical summary for the vegetative growth of flax

This page contains all supplementary tables cited in the main manuscript, including goodness-of-fit metrics, treatment means, and Analysis of Variance (ANOVA) for all evaluated vegetative traits.

Goodness of Fit

Show code 
readRDS("../results/gof_af.rds") |> 
  gt() |> 
  tab_header(
    title = "Supplementary Table S1",
    subtitle = "Goodness-of-fit metrics for Leaf Area logistic models (per block)"
  ) |> 
  fmt_number(columns = where(is.numeric), decimals = 4)
Supplementary Table S1
Goodness-of-fit metrics for Leaf Area logistic models (per block)
epoca bloco cultivar aic r2 variable
E1 B1 D 92.1544 0.9502 leaf_area
E1 B2 D 96.2183 0.8729 leaf_area
E1 B3 D 91.6287 0.9246 leaf_area
E1 B1 M 98.0237 0.9408 leaf_area
E1 B2 M 99.4571 0.9551 leaf_area
E1 B3 M 100.9898 0.8924 leaf_area
E2 B1 D 58.6348 0.9750 leaf_area
E2 B2 D 70.9637 0.9166 leaf_area
E2 B3 D 65.4323 0.9441 leaf_area
E2 B1 M 79.8645 0.8403 leaf_area
E2 B2 M 78.0279 0.8861 leaf_area
E2 B3 M 74.8398 0.9130 leaf_area

Main Effect Means

Show code 
readRDS("../results/means_summary_af.rds") |> 
  gt(groupname_col = "Factor") |> 
  tab_header(
    title = "Supplementary Table S2", 
    subtitle = "Main Effect Means: Model parameters and critical points for Leaf Area"
  ) |> 
  fmt_number(columns = where(is.numeric), decimals = 5)
Supplementary Table S2
Main Effect Means: Model parameters and critical points for Leaf Area
Level b1 b2 b3 xpi ypi xmap xmdp ymap ymdp
Sowing Season
E1 96.86681 467.21673 0.00899 467.21673 0.21646 318.26514 616.16831 0.00076 −0.00076
E2 65.60805 327.41369 0.00866 327.41369 0.13720 161.08138 493.74601 0.00048 −0.00048
Cultivar
D 69.47417 379.84506 0.00893 379.84506 0.15161 224.16396 535.52616 0.00054 −0.00054
M 93.00068 414.78536 0.00872 414.78536 0.20204 255.18256 574.38815 0.00070 −0.00070

ANOVA Summary

Show code 
readRDS("../results/anova_af.rds") |> 
  filter(term != "Residuals", Parameter != "xpi") |> 
  gt() |> 
  tab_header(
    title = "Supplementary Table S3",
    subtitle = "ANOVA Summary: Model parameters and critical points for Leaf Area"
  ) |> 
  fmt_number(columns = where(is.numeric), decimals = 5) |> 
  tab_style(
    style = cell_text(color = "red", weight = "bold"),
    locations = cells_body(
      rows = p.value < 0.05
    )
  )
Supplementary Table S3
ANOVA Summary: Model parameters and critical points for Leaf Area
Parameter term GL SQ QM Fcal p.value
b1 Season 1.00000 2,931.32875 2,931.32875 16.26390 0.00686
b1 Cultivar 1.00000 1,660.48982 1,660.48982 9.21290 0.02294
b1 bloco 2.00000 578.73620 289.36810 1.60550 0.27640
b1 Season:Cultivar 1.00000 241.74771 241.74771 1.34129 0.29082
b2 Season 1.00000 58,634.66721 58,634.66721 17.95547 0.00546
b2 Cultivar 1.00000 3,662.47227 3,662.47227 1.12154 0.33035
b2 bloco 2.00000 20,225.43353 10,112.71677 3.09678 0.11914
b2 Season:Cultivar 1.00000 4,259.83208 4,259.83208 1.30447 0.29692
b3 Season 1.00000 0.00000 0.00000 0.09951 0.76310
b3 Cultivar 1.00000 0.00000 0.00000 0.04059 0.84699
b3 bloco 2.00000 0.00003 0.00001 3.88426 0.08275
b3 Season:Cultivar 1.00000 0.00000 0.00000 0.00367 0.95365
ypi Season 1.00000 0.01885 0.01885 13.32951 0.01069
ypi Cultivar 1.00000 0.00763 0.00763 5.39473 0.05923
ypi bloco 2.00000 0.00584 0.00292 2.06410 0.20790
ypi Season:Cultivar 1.00000 0.00173 0.00173 1.22642 0.31051
xmap Season 1.00000 74,120.20836 74,120.20836 58.91937 0.00026
xmap Cultivar 1.00000 2,886.46026 2,886.46026 2.29449 0.18061
xmap bloco 2.00000 4,413.81913 2,206.90956 1.75431 0.25125
xmap Season:Cultivar 1.00000 4,475.29629 4,475.29629 3.55749 0.10823
xmdp Season 1.00000 44,961.66445 44,961.66445 5.46860 0.05796
xmdp Cultivar 1.00000 4,530.76244 4,530.76244 0.55107 0.48592
xmdp bloco 2.00000 53,508.45801 26,754.22900 3.25406 0.11038
xmdp Season:Cultivar 1.00000 4,049.68342 4,049.68342 0.49255 0.50908

Goodness of Fit

Show code 
readRDS("../results/gof_ap.rds") |> 
  gt() |> 
  tab_header(
    title = "Supplementary Table S4",
    subtitle = "Goodness-of-fit metrics for Plant Height logistic models (per block)"
  ) |> 
  fmt_number(columns = where(is.numeric), decimals = 4)
Supplementary Table S4
Goodness-of-fit metrics for Plant Height logistic models (per block)
epoca bloco cultivar aic r2 variable
E1 B1 D 66.3935 0.9785 plant_height
E1 B2 D 61.7407 0.9891 plant_height
E1 B3 D 72.5145 0.9690 plant_height
E1 B1 M 76.0310 0.9717 plant_height
E1 B2 M 83.5905 0.9522 plant_height
E1 B3 M 81.8164 0.9562 plant_height
E2 B1 D 60.7096 0.9674 plant_height
E2 B2 D 48.5308 0.9881 plant_height
E2 B3 D 74.0980 0.9064 plant_height
E2 B1 M 68.6819 0.9388 plant_height
E2 B2 M 59.2642 0.9609 plant_height
E2 B3 M 63.7990 0.9449 plant_height

Main Effect Means

Show code 
readRDS("../results/means_summary_ap.rds") |> 
  gt(groupname_col = "Factor") |> 
  tab_header(
    title = "Supplementary Table S5", 
    subtitle = "Main Effect Means: Model parameters and critical points for Plant Height"
  ) |> 
  fmt_number(columns = where(is.numeric), decimals = 5)
Supplementary Table S5
Main Effect Means: Model parameters and critical points for Plant Height
Level b1 b2 b3 xpi ypi xmap xmdp ymap ymdp
Sowing Season
E1 92.66452 685.49906 0.00456 685.49906 0.10362 386.76668 984.23144 0.00018 −0.00018
E2 106.82804 587.90582 0.00507 587.90582 0.12165 307.24299 868.56865 0.00023 −0.00023
Cultivar
D 116.20156 722.50312 0.00458 722.50312 0.12090 406.22671 1,038.77953 0.00021 −0.00021
M 83.29100 550.90176 0.00506 550.90176 0.10437 287.78296 814.02056 0.00020 −0.00020

ANOVA Summary

Show code 
readRDS("../results/anova_ap.rds") |> 
  filter(term != "Residuals", Parameter != "xpi") |> 
  gt() |> 
  tab_header(
    title = "Supplementary Table S6",
    subtitle = "ANOVA Summary: Model parameters and critical points for Plant Height"
  ) |> 
  fmt_number(columns = where(is.numeric), decimals = 5) |> 
  tab_style(
    style = cell_text(color = "red", weight = "bold"),
    locations = cells_body(
      rows = p.value < 0.05
    )
  )
Supplementary Table S6
ANOVA Summary: Model parameters and critical points for Plant Height
Parameter term GL SQ QM Fcal p.value
b1 Season 1.00000 601.81645 601.81645 0.51761 0.49892
b1 Cultivar 1.00000 3,249.31436 3,249.31436 2.79466 0.14561
b1 bloco 2.00000 5,952.20377 2,976.10189 2.55967 0.15711
b1 Season:Cultivar 1.00000 2,274.25119 2,274.25119 1.95603 0.21145
b2 Season 1.00000 28,573.32138 28,573.32138 1.44758 0.27423
b2 Cultivar 1.00000 88,341.07965 88,341.07965 4.47552 0.07877
b2 bloco 2.00000 125,466.55664 62,733.27832 3.17818 0.11449
b2 Season:Cultivar 1.00000 9,600.01759 9,600.01759 0.48635 0.51166
b3 Season 1.00000 0.00000 0.00000 0.41918 0.54131
b3 Cultivar 1.00000 0.00000 0.00000 0.37188 0.56435
b3 bloco 2.00000 0.00001 0.00000 1.53040 0.29037
b3 Season:Cultivar 1.00000 0.00000 0.00000 0.73618 0.42383
ypi Season 1.00000 0.00097 0.00097 2.23362 0.18566
ypi Cultivar 1.00000 0.00082 0.00082 1.87938 0.21947
ypi bloco 2.00000 0.00107 0.00053 1.22274 0.35858
ypi Season:Cultivar 1.00000 0.00442 0.00442 10.13335 0.01900
xmap Season 1.00000 18,972.05156 18,972.05156 2.52842 0.16291
xmap Cultivar 1.00000 42,086.76633 42,086.76633 5.60894 0.05565
xmap bloco 2.00000 51,134.36127 25,567.18064 3.40736 0.10264
xmap Season:Cultivar 1.00000 19,967.73288 19,967.73288 2.66112 0.15395
xmdp Season 1.00000 40,133.64309 40,133.64309 1.01666 0.35223
xmdp Cultivar 1.00000 151,549.78106 151,549.78106 3.83902 0.09778
xmdp bloco 2.00000 232,680.40415 116,340.20207 2.94710 0.12837
xmdp Season:Cultivar 1.00000 2,986.85534 2,986.85534 0.07566 0.79249

Goodness of Fit

Show code 
readRDS("../results/gof_nf.rds") |> 
  gt() |> 
  tab_header(
    title = "Supplementary Table S7",
    subtitle = "Goodness-of-fit metrics for Leaf Number logistic models (per block)"
  ) |> 
  fmt_number(columns = where(is.numeric), decimals = 4)
Supplementary Table S7
Goodness-of-fit metrics for Leaf Number logistic models (per block)
epoca bloco cultivar aic r2 variable
E1 B1 D 93.4669 0.9465 leaf_number
E1 B2 D 110.3749 0.7581 leaf_number
E1 B3 D 104.4329 0.8491 leaf_number
E1 B1 M 95.0313 0.9360 leaf_number
E1 B2 M 96.9291 0.9453 leaf_number
E1 B3 M 105.9092 0.7982 leaf_number
E2 B1 D 76.8690 0.9249 leaf_number
E2 B2 D 92.3730 0.6301 leaf_number
E2 B3 D 79.2999 0.9076 leaf_number
E2 B1 M 82.5137 0.8979 leaf_number
E2 B2 M 88.9461 0.8076 leaf_number
E2 B3 M 71.3668 0.9651 leaf_number

Main Effect Means

Show code 
readRDS("../results/means_summary_nf.rds") |> 
  gt(groupname_col = "Factor") |> 
  tab_header(
    title = "Supplementary Table S8", 
    subtitle = "Main Effect Means: Model parameters and critical points for Leaf Number"
  ) |> 
  fmt_number(columns = where(is.numeric), decimals = 5)
Supplementary Table S8
Main Effect Means: Model parameters and critical points for Leaf Number
Level b1 b2 b3 xpi ypi xmap xmdp ymap ymdp
Sowing Season
E1 120.03457 281.03311 0.00635 281.03311 0.18777 69.04974 493.01649 0.00046 −0.00046
E2 101.01244 172.69364 0.00894 172.69364 0.22367 20.65962 324.72765 0.00079 −0.00079
Cultivar
D 105.12950 218.11180 0.00786 218.11180 0.20241 44.37288 391.85072 0.00062 −0.00062
M 115.91751 235.61495 0.00743 235.61495 0.20904 45.33648 425.89342 0.00063 −0.00063

ANOVA Summary

Show code 
readRDS("../results/anova_nf.rds") |> 
  filter(term != "Residuals", Parameter != "xpi") |> 
  gt() |> 
  tab_header(
    title = "Supplementary Table S9",
    subtitle = "ANOVA Summary: Model parameters and critical points for Leaf Number"
  ) |> 
  fmt_number(columns = where(is.numeric), decimals = 5) |> 
  tab_style(
    style = cell_text(color = "red", weight = "bold"),
    locations = cells_body(
      rows = p.value < 0.05
    )
  )
Supplementary Table S9
ANOVA Summary: Model parameters and critical points for Leaf Number
Parameter term GL SQ QM Fcal p.value
b1 Season 1.00000 1,085.52429 1,085.52429 6.19969 0.04717
b1 Cultivar 1.00000 349.14335 349.14335 1.99404 0.20762
b1 bloco 2.00000 100.69880 50.34940 0.28756 0.75988
b1 Season:Cultivar 1.00000 7.89583 7.89583 0.04509 0.83886
b2 Season 1.00000 35,212.32683 35,212.32683 18.64515 0.00499
b2 Cultivar 1.00000 919.08126 919.08126 0.48666 0.51153
b2 bloco 2.00000 2,108.36892 1,054.18446 0.55820 0.59934
b2 Season:Cultivar 1.00000 165.01608 165.01608 0.08738 0.77750
b3 Season 1.00000 0.00002 0.00002 9.62917 0.02103
b3 Cultivar 1.00000 0.00000 0.00000 0.25860 0.62924
b3 bloco 2.00000 0.00001 0.00000 1.87641 0.23284
b3 Season:Cultivar 1.00000 0.00000 0.00000 0.17671 0.68885
ypi Season 1.00000 0.00387 0.00387 8.16941 0.02887
ypi Cultivar 1.00000 0.00013 0.00013 0.27866 0.61652
ypi bloco 2.00000 0.00345 0.00173 3.65046 0.09179
ypi Season:Cultivar 1.00000 0.00093 0.00093 1.97494 0.20953
xmap Season 1.00000 7,024.80906 7,024.80906 45.09862 0.00053
xmap Cultivar 1.00000 2.78561 2.78561 0.01788 0.89799
xmap bloco 2.00000 2,264.11649 1,132.05824 7.26771 0.02494
xmap Season:Cultivar 1.00000 31.29035 31.29035 0.20088 0.66974
xmdp Season 1.00000 84,963.40218 84,963.40218 13.86211 0.00982
xmdp Cultivar 1.00000 3,476.71695 3,476.71695 0.56724 0.47986
xmdp bloco 2.00000 5,604.84264 2,802.42132 0.45723 0.65340
xmdp Season:Cultivar 1.00000 978.78218 978.78218 0.15969 0.70328