The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
The function ltcchk conducts Line x Tester analysis when
the data contains crosses and checks. The experimental design may be
RCBD or Alpha lattice design.
# Load the package
library(gpbStat)
#Load the dataset
data(alphaltcchk)
# View the structure of dataframe.
str(alphaltcchk)
#> 'data.frame': 54 obs. of 6 variables:
#> $ replication: chr "r1" "r1" "r1" "r1" ...
#> $ block : chr "b2" "b4" "b2" "b6" ...
#> $ line : int 1 2 3 4 5 1 2 3 4 5 ...
#> $ tester : int 11 11 11 11 11 12 12 12 12 12 ...
#> $ check : int NA NA NA NA NA NA NA NA NA NA ...
#> $ yield : num 41.7 66 71.6 53.8 54.9 ...
# Conduct Line x Tester analysis
result = ltcchk(alphaltcchk, replication, line, tester, check, yield, block)
#>
#> Analysis of Line x Tester: yield
# View the output
result
#> $Means
#> Testers
#> Lines 11 12 13
#> 1 55.11815 56.00024 48.86192
#> 2 46.10276 47.18926 51.60208
#> 3 57.17833 63.38786 39.82822
#> 4 51.82018 53.52738 44.06331
#> 5 45.08720 59.65115 58.72662
#>
#> $`Overall ANOVA`
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Replication 2 40.56006 20.28003 0.112 0.8946
#> Blocks within Replication 15 1605.96516 107.06434 0.591 0.8474
#> Treatments 17 2522.99574 148.41151 0.820 0.6571
#> Crosses 14 1845.00871 131.78634 0.728 0.7244
#> Checks 2 407.62289 203.81144 1.126 0.3450
#> Lines 4 256.94867 64.23717 0.439 0.7777
#> Testers 2 418.43308 209.21654 1.431 0.2943
#> Lines X Testers 8 1169.62696 146.20337 0.808 0.6039
#> Error 19 3439.50344 181.02650 NA NA
#> Total 53 456.78239 NA NA NA
#>
#> $`Coefficient of Variation`
#> [1] 25.44511
#>
#> $`Genetic Variance`
#> Genotypic Variance Phenotypic Variance Environmental Variance
#> 42.71049 223.73699 181.02650
#>
#> $`Genetic Variability `
#> Phenotypic coefficient of Variation Genotypic coefficient of Variation
#> 28.287998 12.359492
#> Environmental coefficient of Variation <NA>
#> 25.445114 0.190896
#>
#> $`Line x Tester ANOVA`
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Lines 4 256.9487 64.23717 0.439 0.7777
#> Testers 2 418.4331 209.21654 1.431 0.2943
#> Lines X Testers 8 1169.6270 146.20337 0.808 0.6039
#>
#> $`GCA lines`
#> 1 2 3 4 5
#> 1.450 -3.578 1.588 -2.073 2.612
#>
#> $`GCA testers`
#> 11 12 13
#> -0.815 4.075 -3.260
#>
#> $`SCA crosses`
#> Testers
#> Lines 11 12 13
#> 1 2.606 -1.401 -1.205
#> 2 -1.380 -5.184 6.564
#> 3 4.529 5.848 -10.377
#> 4 2.832 -0.351 -2.480
#> 5 -8.586 1.088 7.498
#>
#> $`Proportional Contribution`
#> Lines Tester Line x Tester
#> 13.92669 22.67919 63.39412
#>
#> $`GV Singh & Chaudhary`
#> Cov H.S. (line) Cov H.S. (tester)
#> -9.1073559 4.2008782
#> Cov H.S. (average) Cov F.S. (average)
#> -0.5096931 -13.3738060
#> F = 0, Adittive genetic variance F = 1, Adittive genetic variance
#> -2.0387724 -1.0193862
#> F = 0, Variance due to Dominance F = 1, Variance due to Dominance
#> -23.2154182 -11.6077091
#>
#> $`Standard Errors`
#> S.E. gca for line S.E. gca for tester S.E. sca effect
#> 4.484870 3.473965 7.768022
#> S.E. (gi - gj)line S.E. (gi - gj)tester S.E. (sij - skl)tester
#> 6.342563 4.912928 10.985642
#>
#> $`Critical differance`
#> C.D. gca for line C.D. gca for tester C.D. sca effect
#> 9.386940 7.271092 16.258657
#> C.D. (gi - gj)line C.D. (gi - gj)tester C.D. (sij - skl)tester
#> 13.275138 10.282877 22.993213# Load the package
library(gpbStat)
#Load the dataset
data("rcbdltcchk")
# View the structure of dataframe.
str(rcbdltcchk)
#> tibble [72 × 5] (S3: tbl_df/tbl/data.frame)
#> $ replication: num [1:72] 1 2 3 4 1 2 3 4 1 2 ...
#> $ line : num [1:72] 1 1 1 1 1 1 1 1 1 1 ...
#> $ tester : num [1:72] 6 6 6 6 7 7 7 7 8 8 ...
#> $ check : num [1:72] NA NA NA NA NA NA NA NA NA NA ...
#> $ yield : num [1:72] 74.4 70.9 60.9 68 91.8 ...
# Conduct Line x Tester analysis
result1 = ltcchk(rcbdltcchk, replication, line, tester, check, yield)
#>
#> Analysis of Line x Tester with crosses and checks: yield
# View the output
result1
#> $Means
#> Testers
#> Lines 6 7 8
#> 1 68.550 107.640 52.640
#> 2 73.265 97.640 85.650
#> 3 100.885 111.540 117.735
#> 4 105.795 64.450 46.855
#> 5 84.150 81.935 94.820
#>
#> $`Overall ANOVA`
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Replication 3 181.4450 60.48168 0.750 0.5274
#> Treatments 17 26842.2856 1578.95798 19.583 0.0000
#> Crosses 14 26199.6543 1871.40388 23.211 0.0000
#> Checks 2 551.0746 275.53731 3.417 0.0405
#> Lines 4 10318.3614 2579.59035 1.457 0.3009
#> Testers 2 1718.9258 859.46289 0.485 0.6327
#> Lines X Testers 8 14162.3672 1770.29589 21.956 0.0000
#> Error 51 4111.9998 80.62745 NA NA
#> Total 71 31135.7305 NA NA NA
#>
#> $`Coefficient of Variation`
#> [1] 10.47362
#>
#> $`Genetic Variance`
#> Genotypic Variance Phenotypic Variance Environmental Variance
#> 379.61908 460.24652 80.62745
#>
#> $`Genetic Variability `
#> Phenotypic coefficient of Variation Genotypic coefficient of Variation
#> 25.0236394 22.7263258
#> Environmental coefficient of Variation <NA>
#> 10.4736166 0.8248168
#>
#> $`Line x Tester ANOVA`
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Lines 4 10318.361 2579.5903 1.457 0.3009
#> Testers 2 1718.926 859.4629 0.485 0.6327
#> Lines X Testers 8 14162.367 1770.2959 21.956 0.0000
#>
#> $`GCA lines`
#> 1 2 3 4 5
#> -9.960 -0.718 23.817 -13.870 0.732
#>
#> $`GCA testers`
#> 6 7 8
#> 0.292 6.404 -6.697
#>
#> $`SCA crosses`
#> Testers
#> Lines 6 7 8
#> 1 -8.019 24.959 -16.940
#> 2 -12.546 5.717 6.828
#> 3 -9.461 -4.918 14.378
#> 4 33.136 -14.321 -18.815
#> 5 -3.111 -11.438 14.548
#>
#> $`Proportional Contribution`
#> Lines Tester Line x Tester
#> 39.383578 6.560872 54.055550
#>
#> $`GV Singh & Chaudhary`
#> Cov H.S. (line) Cov H.S. (tester)
#> 67.441205 -45.541650
#> Cov H.S. (average) Cov F.S. (average)
#> 2.680894 412.168303
#> F = 0, Adittive genetic variance F = 1, Adittive genetic variance
#> 10.723574 5.361787
#> F = 0, Variance due to Dominance F = 1, Variance due to Dominance
#> 844.834223 422.417112
#>
#> $`Standard Errors`
#> S.E. gca for line S.E. gca for tester S.E. sca effect
#> 2.592095 2.007828 4.489639
#> S.E. (gi - gj)line S.E. (gi - gj)tester S.E. (sij - skl)tester
#> 3.665775 2.839497 6.349309
#>
#> $`Critical differance`
#> C.D. gca for line C.D. gca for tester C.D. sca effect
#> 5.203847 4.030882 9.013327
#> C.D. (gi - gj)line C.D. (gi - gj)tester C.D. (sij - skl)tester
#> 7.359351 5.700529 12.746770These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.