Simulated augmented randomized complete block design with 48 chickpea accessions (tested once) and four checks replicated in each of six blocks.
Format
A data frame with 72 rows and 4 variables:
- block
Factor, block (B1-B6).
- entry
Factor, checks C1-C4 and accessions IC-001 to IC-048.
- seed_yield
Seed yield (kg/ha).
- plant_height
Plant height (cm).
Examples
data(chickpea_augmented)
anova_augmented(chickpea_augmented, "seed_yield", "entry", "block",
check_names = c("C1", "C2", "C3", "C4"))
#>
#> ======================================================================
#> AUGMENTED RANDOMIZED COMPLETE BLOCK DESIGN
#> ======================================================================
#> Response : seed_yield
#> Blocks : 6
#> Checks : 4
#> Test entries : 48
#>
#> ANOVA (treatments adjusted for blocks)
#> Source Df Sum Sq Mean Sq F value Pr(>F)
#> Blocks (ignoring treatments) 5 283298.94 56659.79 16.914 0.0000 ***
#> Treatments (eliminating blocks) 51 1055984.00 20705.57 6.181 0.0002 ***
#> Tests vs Checks 1 75533.36 75533.36 22.548 0.0003 ***
#> Checks 3 84692.33 28230.78 8.427 0.0016 **
#> Tests 47 895758.31 19058.69 5.689 0.0003 ***
#> Residuals 15 50247.67 3349.84
#> Signif. codes: *** p < 0.001, ** p < 0.01, * p < 0.05, NS not significant
#>
#> ANOVA (blocks adjusted; treatments partitioned)
#> Source Df Sum Sq Mean Sq F value Pr(>F)
#> Blocks (eliminating treatments) 5 53633.33 10726.67 3.202 0.0365 *
#> Treatments (ignoring blocks) 51 1285649.61 25208.82 7.525 0.0001 ***
#> Checks 3 84692.33 28230.78 8.427 0.0016 **
#> Tests 47 1125423.92 23945.19 7.148 0.0001 ***
#> Checks vs Tests 1 75533.36 75533.36 22.548 0.0003 ***
#> Residuals 15 50247.67 3349.84
#> Signif. codes: *** p < 0.001, ** p < 0.01, * p < 0.05, NS not significant
#>
#> Grand mean = 1439.861 CV = 4.02% MSE = 3349.8444 (df = 15)
#>
#> Standard errors of difference and CD (alpha = 0.05)
#> Comparison SEd CD
#> Two check means 33.416 71.224
#> Two test entries (same block) 81.852 174.463
#> Two test entries (different blocks) 91.513 195.055
#> Test entry vs check mean 67.868 144.657
#>
#> Check means
#> Entry Raw_mean SE
#> C2 1537.50 23.629
#> C3 1537.33 23.629
#> C4 1475.17 23.629
#> C1 1392.67 23.629
#>
#> Top 10 test entries (adjusted; best check = C2)
#> Entry Adjusted_mean Pct_over_check_mean Pct_over_best_check Sig_vs_best
#> IC-039 1743.92 17.38 13.43 higher
#> IC-028 1712.42 15.26 11.38 higher
#> IC-011 1637.42 10.21 6.50 ns
#> IC-010 1604.42 7.99 4.35 ns
#> IC-022 1592.17 7.17 3.56 ns
#> IC-036 1560.92 5.07 1.52 ns
#> IC-043 1560.67 5.05 1.51 ns
#> IC-037 1559.92 5.00 1.46 ns
#> IC-003 1550.42 4.36 0.84 ns
#> IC-001 1545.42 4.02 0.51 ns
#>
#> Genetic parameters of test entries
#> Parameter Value
#> Mean of tests 1416.958
#> Range (min) 1151.917
#> Range (max) 1743.917
#> Phenotypic variance 19058.687
#> Genotypic variance 15708.843
#> Error variance 3349.844
#> PCV (%) 9.743
#> GCV (%) 8.845
#> Heritability (broad sense, %) 82.424
#> Genetic advance 234.745
#> GA as % of mean 16.567