Sunflower Defoliation

Source: R/AgainStart.R

Seventy-two field trials were conducted by applying four defoliation treatments (non-defoliated control, 33%, 66%, and 100%) at different growth stages (stage) ranging from pre-flowering (1) to physiological maturity (5) in four different locations of Navarre, Spain: Carcastillo (1), Melida (2), Murillo (3), and Unciti (4). There are two response variables: yield in kg/ha of the sunflower and numseed, the number of seeds per sunflower head. Data are stored in the data frame SUNFLOWER.

SUNFLOWER

Format

A data frame with 72 observations on the following 5 variables:

  • location (a factor with levels A, B, C, and D for locations Carcastillo, Melida, Murillo, and Unciti, respectively)

  • stage (a factor with levels stage1, stage2, stage3, stage4, and stage5)

  • defoli (a factor with levels control, treat1, treat2, and treat3)

  • yield (sunflower yield in kg/ha)

  • numseed (number of seeds per sunflower head)

Source

Muro, J., et. al. 2001. “Defoliation Effects on Sunflower Yield Reduction.” Agronomy Journal, 93: 634-637.

References

Ugarte, M. D., Militino, A. F., and Arnholt, A. T. 2015. Probability and Statistics with R, Second Edition. Chapman & Hall / CRC.

Examples

summary(aov(yield ~ stage + defoli + stage:defoli, data = SUNFLOWER))
#>              Df   Sum Sq Mean Sq F value  Pr(>F)   
#> stage         4  5186036 1296509   1.267 0.29495   
#> defoli        3 13720078 4573359   4.468 0.00726 **
#> stage:defoli 12 16236084 1353007   1.322 0.23500   
#> Residuals    52 53224683 1023552                   
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
ggplot(data = SUNFLOWER, aes(numseed, yield, color = defoli)) + geom_point() + 
geom_smooth(method = "lm", se = FALSE) + facet_grid(location ~ .)
#> `geom_smooth()` using formula 'y ~ x'