9 3D

  • Dataset

  • calc: Limestone concentration

  • comp: Organic matter concentration

  • folha: Dry matter (leaf)

dados <- read.table('biomassa.txt', h=T)

head(dados)
##   calc comp folha      caule      raiz     total
## 1    0    0  0.54  1.0779592 0.9574259  2.575385
## 2    0    0  0.53  0.9679592 1.1518259  2.649785
## 3    0    0  0.69  1.1879592 1.2059592  3.083918
## 4    0    0  0.71  1.3079592 1.3163592  3.334318
## 5    0    5  4.29 11.3879592 2.8091592 18.487118
## 6    0    5  4.53  9.7179592 3.1315592 17.379518

9.1 3D

  • Model
modfolha <- lm(folha ~ calc + comp  + I(calc^2) + I(comp^2) + 
             calc:I(comp^2), data=dados)

calcario <- seq(0,3.76,0.12)
composto <- seq(0,40,2.5)

graf <- expand.grid(calc=calcario,comp=composto)

resp <- predict(modfolha, newdata=graf)

9.2 3D

wireframe(resp ~ graf$comp + graf$calc,
 drape=TRUE, colorkey=TRUE,    col='transparent', 
 ylim=c(0,4),
 scales = list(arrows = FALSE, y=list(at=c(0.25,2,3.72))),
 screen = list(z = 30, x = -60),
 xlab=list(expression(paste('Organic matter (g/dm'^{3},')')), 
  rot=20),
 ylab=list(expression(paste('Limestone (g/dm'^{3},')')), 
 rot=-48),
 zlab=list('Dry matter (leaf) (g/plant)', rot=95),
 par.box = list(col=c(1,1,NA,NA,1,NA,1,1,1)))

9.3 3D