Incidents and performance of healthy tubers and rotten potato field infested with naturally Ralstonia solanacearum Race 3/Bv 2A, after application of inorganic amendments and a rotation crop in Carhuaz Peru, 2006.
Application of inorganic amendment and crop rotation to control bacterial wilt of the potato (MBP).
data(Chz2006)
An object of class list with two elements: wilt and yield
Experimental field, 2006. Data Kindly provided by Pedro Aley.
amendment amendment
crop crop
block block
plant plant
wilt_percent a numeric vector, wilt percentage at 60 days
health a numeric vector, kg/8m2
rot a numeric vector, kg/8m2
International Potato Center. CIP - Lima Peru.
#> List of 2 #> $ wilt :'data.frame': 1920 obs. of 5 variables: #> ..$ amendment : Factor w/ 4 levels "0C","3C","3C1Z",..: 1 1 1 1 1 1 1 1 1 1 ... #> ..$ crop : Factor w/ 4 levels "Cabbage","Corn",..: 4 4 4 4 4 4 4 4 4 4 ... #> ..$ block : num [1:1920] 1 1 1 1 1 1 1 1 1 1 ... #> ..$ plant : num [1:1920] 1 2 3 4 5 6 7 8 9 10 ... #> ..$ wilt_percent: num [1:1920] 0 0 50 0 0 0 0 0 0 0 ... #> $ yield:'data.frame': 48 obs. of 5 variables: #> ..$ amendment: Factor w/ 4 levels "0C","3C","3C1Z",..: 1 1 1 1 1 1 1 1 1 1 ... #> ..$ crop : Factor w/ 4 levels "Cabbage","Corn",..: 3 3 3 1 1 1 2 2 2 4 ... #> ..$ block : num [1:48] 1 2 3 1 2 3 1 2 3 1 ... #> ..$ health : num [1:48] 1.2 1.85 1.9 4.5 2.35 2.37 2.65 1.38 1.65 3.18 ... #> ..$ rot : num [1:48] 1.3 1.39 2.1 0.5 0.31 0.4 0.15 0.3 0.2 0.14 ...wilt <- Chz2006$wilt yield <- Chz2006$yield means <- tapply.stat(wilt[,5], wilt[,1:3],function(x) mean(x,na.rm=TRUE)) names(means)[4]<-"wilt_percent" model <- aov(wilt_percent ~ block + crop, means) anova(model)#> Analysis of Variance Table #> #> Response: wilt_percent #> Df Sum Sq Mean Sq F value Pr(>F) #> block 1 15.82 15.820 0.2858 0.5957 #> crop 3 108.07 36.024 0.6508 0.5868 #> Residuals 43 2380.27 55.355cv.model(model)#> [1] 123.1466yield <- yield[order(paste(yield[,1],yield[,2],yield[,3])),] correlation(means[,4],yield[,4],method="spearman")#> #> Spearman's rank correlation rho #> #> data: means[, 4] and yield[, 4] #> p-value = 2.994637e-08 #> alternative hypothesis: true rho is not equal to 0 #> sample estimates: #> rho #> -0.7004247