cochran.crd {agridat} | R Documentation

## Potato scab infection with sulfur treatments

### Description

Potato scab infection with sulfur treatments

### Format

A data frame with 32 observations on the following 5 variables.

`inf`

  infection percent

`trt`

  treatment factor

`row`

  row

`col`

  column

### Details

The experiment was conducted to investigate the effect of sulfur on controlling scab disease in potatoes. There were seven treatments. Control, plus spring and fall application of 300, 600, 1200 lbs/acre of sulfur. The response variable was infection as a percent of the surface area covered with scab. A completely randomized design was used with 8 replications of the control and 4 replications of the other treatments.

Although the original analysis did not show significant differences in the sulfur treatments, including a polynomial trend in the model uncovered significant differences (Tamura, 1988).

### Source

W.G. Cochran and G. Cox, 1957. Experimental Designs, 2nd ed. John Wiley, New York.

### References

Tamura, R.N. and Nelson, L.A. and Naderman, G.C., (1988). An investigation of the validity and usefulness of trend analysis for field plot data. Agronomy Journal, 80, 712-718.

http://doi.org/10.2134/agronj1988.00021962008000050003x

### Examples

    data(cochran.crd)
    dat <- cochran.crd

    # Field plan
    if(require(desplot)){
      desplot(inf~col*row, data=dat,
              text=trt, cex=1, # aspect unknown
              main="cochran.crd")
    }

    # CRD anova.  Table 6 of Tamura 1988
    contrasts(dat$trt) <- cbind(c1=c(1,1,1,-6,1,1,1),   # Control vs Sulf
                                c2=c(-1,-1,-1,0,1,1,1)) # Fall vs Sp
    m1 <- aov(inf ~ trt, data=dat)
    anova(m1)
    summary(m1, split=list(trt=list("Control vs Sulf"=1, "Fall vs Spring"=2)))

    # Quadratic polynomial for columns...slightly different than Tamura 1988
    m2 <- aov(inf ~ trt + poly(col,2), data=dat)
    anova(m2)
    summary(m2, split=list(trt=list("Control vs Sulf"=1, "Fall vs Spring"=2)))

[Package agridat version 1.16 Index]