Data: Rainfall thresholds as support for timing fungicide applications in the control of potato late blight in Peru

Source: R/huasahuasi.R

Timing fungicide sprays based on accumulated rainfall thresholds can be a successful component of integrated management packages that include cultivars with moderate or high levels of resistance to late blight. The simplicity of measuring accumulated rainfall means that the technology can potentially be used by resource-poor farmers in developing countries.

The experimental unit was formed by 4 furrows of 1.8 m of length, with distance between furrows from 0.90 m and between plants of 0.30 m. In each furrow was installed 5 plants. The experiment had 3 repetitions. From the beginning of the experiment were fulfilled the following treatments Thresholds 40 mm: Apply the fungicide when 40 precipitation mm accumulates. The minimum interval between applications will be of 7 days. Schedule 7 days: The applications should be carried out every 7 days calendar. Without application: No fungicide application will be made. The evaluation of the severity of the late blight in each treatment started to emergency 80 percentage and then evaluations were made every 7 days until being observed a physiological maturation of the crop.

data(huasahuasi)

Format

An object of class list with two elements: AUDPC and YIELD

@details

  • block a factor with levels I, II, and III

  • trt a factor with levels 40mm, 7-days, and Non-application

  • clon a factor with levels C386209.10, C387164.4, Cruza148, Musuq, and Yungay

  • y1da y1da

  • y2da y2da

  • y3ra y3ra

  • d44 44 days

  • d51 51 days

  • d100 100 days

Source

Experimental field, 2003. Data Kindly provided by Wilmer Perez.

References

International Potato Center. CIP - Lima Peru.

Examples


library(agricolae)
data(huasahuasi)
names(huasahuasi)
#> [1] "AUDPC" "YIELD"
str(huasahuasi$AUDPC)
#> 'data.frame':	450 obs. of  13 variables:
#>  $ block: Factor w/ 3 levels "I","II","III": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ trt  : Factor w/ 3 levels "40mm","7-days",..: 1 1 1 1 1 1 1 1 1 1 ...
#>  $ clon : Factor w/ 5 levels "C386209.10","C387164.4",..: 2 2 2 2 2 2 2 2 2 2 ...
#>  $ plant: num  1 2 3 4 5 6 7 8 9 10 ...
#>  $ d44  : num  0 0 0 0 0 0 0 0 0 0 ...
#>  $ d51  : num  0 0 0 0 0 0 0 0 0 0 ...
#>  $ d58  : num  0 0 0 0 0 0 0 0 0 0 ...
#>  $ d65  : num  0 0 0 0 0 0 0 0 0 0 ...
#>  $ d72  : num  0 0 0 0 0 0 0 0 0 0 ...
#>  $ d79  : num  0 0 0 0 0 0 0 0 0 0 ...
#>  $ d86  : num  0 0 0 0 0 0 0 0 0 0 ...
#>  $ d93  : num  0 0 0 1 1 0 0 0 0 0 ...
#>  $ d100 : num  0 0 0 1 1 0 0 0 0 0 ...
str(huasahuasi$YIELD)
#> 'data.frame':	45 obs. of  6 variables:
#>  $ block: Factor w/ 3 levels "I","II","III": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ trt  : Factor w/ 3 levels "40mm","7-days",..: 1 1 1 1 1 2 2 2 2 2 ...
#>  $ clon : Factor w/ 5 levels "C386209.10","C387164.4",..: 2 1 3 5 4 2 1 3 5 4 ...
#>  $ y1da : num  22.8 10.8 1.6 10.9 3.5 ...
#>  $ y2da : num  5.5 8 11.7 9.9 5.1 7 12.5 9.15 8.8 4.6 ...
#>  $ y3da : num  4.14 6.1 4.15 5.2 2.4 7.6 3.6 4.9 5.9 3.5 ...