R/ake_b.R
In walmes/RDASC: Reproducible Data Analysis of Cientific Cooperations
#' @name ake_b
#' @title Effect of fungicide sprays programs and pistachio hedging on
#' damage caused by \emph{Alternaria} on commercial pistachio
#' orchard of Tulare County, California.
#'
#' @description The experiment was established in a commercial pistachio
#' orchard in Tulare County, California. The total area sizes 2.9
#' ha with density of 335 plants/ha. In total, 12 plots were set
#' with approximately 80 pistachio trees cv. Kerman spaced at 5.8 m
#' between rows and 5.2 m between plants. Each plot included four
#' rows in width. In the year 2015, a heavy and normal hedging were
#' intercalated, resulting in 6 plots for each hedging type. No
#' hedging was made in 2016. Within each plot, a fungicide free
#' sub-plot with 20 plants (4 rows by 5 plants) was set as a
#' control. Along the plot central rows, four plants (three inside
#' the treated plot and one inside the control sub-plot) were
#' identified for isolate collection, severity and defoliation
#' assessments. In total, 48 plants were identified. The fungicide
#' treatment included three different programs plus the control.
#'
#' \describe{
#'
#' \item{cnt}{Control with no application.}
#'
#' \item{mer2}{Merivon (1st application) and Switch (2nd application);}
#'
#' \item{fon2}{FontelisTM (1st application) and Switch (2nd
#' application);}
#'
#' \item{mer3}{Merivon (1st application), Switch (2nd application) and
#' Gem (third application)}.
#'
#' }
#'
#' The combination of spray program and hedging type allowed two
#' replication plots per treatment.
#'
#' \strong{Fruit quality} - To determine the effect of spray program
#' and pistachio hedging on fruit quality, each of the 48 flaged
#' trees had their fruits harvested in mid September. Fruits were
#' bagged in plastic and identified to allow the localization of
#' plot and tree. Mechanic dehulling was made prior to fruit
#' drying, which occured during 3 days at temperature of 55
#' \eqn{^\circ}C. After drying, fruits were re-placed into an
#' identified plastic bags and stored at cold room at 4
#' \eqn{^\circ}C until analyses. For each one of the 48 bags of
#' samples, three subsamples were prepared including 100 fruits
#' randomly choosen. In order to evaluate the amount of stain
#' caused by the incidence of \emph{Alternaria} late blight in the
#' field, each subsample (composed by 100 fruits) were separated in
#' 5 categories, from 0 (no stain) to 4 (more stain), based on a
#' reference scale.
#'
#' \strong{Sensitivity} - In order to evaluate the fungicide program
#' effect on \emph{A. alternata} SDHI sensitivity, four isolate
#' populations were collected in two years of experiment.
#'
#' In 2015, the population \strong{A} (\eqn{n = 59}) and \strong{B}
#' (\eqn{n = 59}) were collected in late-May and mid-September
#' respectively. In 2016, the population \strong{C} (\eqn{n = 79})
#' and \strong{D} (\eqn{n = 63}) were collected in early-May and
#' mid-September respectively.
#'
#' This arrangement allowed to sample isolates before (\strong{A}
#' and \strong{C}) and after (\strong{B} and \strong{D}) the spray
#' season. To obtain the sensitivity values, three SDHI fungicides
#' stock solutions were prepared at 10 g a.i. liter-1 each. The
#' fungicides used were: technical grade fluopyram-fp (a.i. 99.13\%,
#' Bayer CropScience) and penthiopyrad-pe (a.i. 99.5\%, DuPont
#' Company) diluted in acetone; and the commercial product of
#' fluxapyroxad-fd (Sercadis 300 SC, BASF, The Chemical Company)
#' diluted in sterile deionized water.
#'
#' To determine an isolate's sensitivity to fungicides, stock
#' solution was diluted in autoclaved YBA agar medium at
#' concentrations of 0 (control), 0.01, 0.03, 0.12, 0.48, 1.92,
#' 7.68, 30.72 and 122.88 \eqn{\mu}g/ml. For each tested isolate, a
#' 5 mm mycelial plug was transferred from a 7-day-old colony and
#' placed onto the YBA media supplemented with one of the above
#' fungicide concentrations. Intercalate number of repetitions were
#' prepared, where 0 (control), 0.01, 0.12, 1.92, and 30.72
#' \eqn{\mu}g/ml received two repetitions, and the other doses one.
#'
#' Plates were incubated in dark for seven days at room temperature
#' prior to colony measurement, taken from two perpendicular
#' diameters. For each concentration, the inhibition of colony
#' growth (\eqn{L_i}) of isolate \eqn{i} was calculated as \eqn{L_i
#' = (C_{ck}-C_i)/C_{ck}\times 100}, where \eqn{C_{ck}} is the mean
#' colony diameter of the control with no fungicide, and \eqn{C_i}
#' is the mean colony diameter of the isolate \eqn{i} on the
#' supplemented medium.
#'
#' @format A list containing data frames.
#'
#' \code{quality} is a \code{data.frame} with 288 observations and 12
#' variables, described below.
#'
#' \describe{
#'
#' \item{\code{yr}}{Factor variable to indicate the year of experiment.}
#'
#' \item{\code{hed}}{Factor variable to indicate the hedging type on
#' trees. The hedging is the shape the branchs and limbs when
#' pruned. They can be heavy (severe pruning) or normal (regular
#' pruning).}
#'
#' \item{\code{tra}}{Factor variable to indicate the fungicide treatment
#' on field, already described above (\code{cnt}, \code{mer2},
#' \code{fon2} and \code{mer3}). The treatment combines the use of
#' one SDHI fungicide (Merivon or Fontelis) and one or two
#' additional chemical group. THe application is on field.}
#'
#' \item{\code{plo}}{Not an important variable to consider in the
#' analysis. The plot code simply indicate the location of
#' experimental plots, they are represented by one number (from 1 to
#' 3) indicating the rows (for example: each number is composed by 4
#' rows from where the two central rows contain the flagged tree),
#' and letters (from A to D) indicating the change in hedging.}
#'
#' \item{\code{tre}}{Factor variable to indicate tree from where fruits
#' were collected. There are 48 trees identified from 1 to 48, for
#' 2015, and the same identification for 2016 (corresponding to the
#' same trees sampled one year later). As an example: plot "1A",
#' include trees 1, 2, 3 and 4 (1, 2, 3 treated and 4 not treated);
#' and plot "1B" includes trees 5, 6, 7 and 8 (5, 6, 7 treated and 8
#' not treated).}
#'
#' \item{\code{rep}}{Integer variable to indicate repetition. Each
#' fruit sample obtained from a certain tree was sub-sampled by
#' randomly choosing 100 fruits. This subsampling originated 3
#' repetitions for each tree called subsample 1, 2 and 3.}
#'
#' \item{\code{c0}}{Numeric variable that is the number of fruits at
#' stain category 0. Category zero are the number of pistachio
#' fruits with 0\% of the shell surface discolored.}
#'
#' \item{\code{c1}}{Numeric variable that is the number of fruits at
#' stain category 1. Category one are the number of pistachio fruits
#' with 1\% to 10\% of the shell surface discolored.}
#'
#' \item{\code{c2}}{Numeric variable that is the number of fruits at
#' stain category 2. Category two are the number of pistachio fruits
#' with 11\% to 35\% of the shell surface discolored.}
#'
#' \item{\code{c3}}{Numeric variable that is the number of fruits at
#' stain category 3. Category three are the number of pistachio
#' fruits with 36\% to 64\% of the shell surface discolored.}
#'
#' \item{\code{c4}}{Numeric variable that is the number of fruits at
#' stain category 4. Category four are the number of pistachio
#' fruits with 65\% to 100\% of the shell surface discolored.}
#'
#' \item{\code{tot}}{Numeric variable that is the total number of fruits
#' evaluated inside each sub-sample.}
#'
#' }
#'
#' \code{sensitivity} is a \code{data.frame} with 10920 observations and
#' 11 variables, described below.
#'
#' \describe{
#'
#' \item{\code{yr}}{Described before.}
#'
#' \item{\code{hed}}{Described before.}
#'
#' \item{\code{tra}}{Described before.}
#'
#' \item{\code{plot}}{Described before.}
#'
#' \item{\code{pop}}{A 4-level factor variable to indicate the isolate
#' population collected in 2015, "A" and "B", and 2016, "C" and "D".
#' Each population was collected before and after the spray season
#' in field, for this reason they belong to the same location but
#' the individuals inside the each population are unique, meaning
#' that isolate number one, tested for the population "A" will never
#' be tested in a different population.}
#'
#' \item{\code{iso}}{A factor variable to differenciate the isolates
#' collected during the preparation of populations "A", "B", "C" and
#' "D". They will never repeat because each isolate is sampled from
#' the population of isolates only one in the field. So, this is an
#' unique ID for isolates.}
#'
#' \item{\code{fun}}{A factor variable to indicate the SDHI fungicide
#' tested in laboratory. Each isolate collected in field was tested
#' \emph{in vitro} for its sensitivity of fluopyram "FP",
#' fluxapyroxad "FD", and penthiopyrad "PE". The shift in
#' sensitivity for "FP", "PE", and "FD" is the information we aimed
#' to have at the end of this experiment to know, which combination
#' of \code{tra} and \code{hed} affected more or less the
#' sensitivity of \code{fun}.}
#'
#' \item{\code{dos}}{A numeric factor variable to indicate the dose of
#' fungicide prepared inside the petri plate. Each dose was
#' prepared by the dilution of fungicide stock solution on YBA
#' media. The measure unit for fungicide dose is \eqn{\mu}g/ml.}
#'
#' \item{\code{rep}}{A numeric variable to indicate the repetition of
#' fungicide dose used to calculate the EC50 (sensitivity) of each
#' isolate. The repetitions were intercalate, two and one plate per
#' dose. Control received two repetitions as well.}
#'
#' \item{\code{d1}}{A numeric response variable for the first colony
#' diameter measured in mm. However the data on the table need to
#' be divided by 100. Decimals were ignored to facilitate the
#' typing of collected data.}
#'
#' \item{\code{d2}}{A numeric response variable for the second colony
#' diameter measured in mm. However the data on the table need to
#' be divided by 100. Decimals were ignored to facilitate the
#' typing of collected data.}
#'
#' }
#'
#' \code{severity} is a \code{data.frame} with 192 observations and
#' 8 variables, described below.
#'
#' \describe{
#'
#' \item{\code{yr}}{Described before.}
#'
#' \item{\code{hed}}{Described before.}
#'
#' \item{\code{tra}}{Described before.}
#'
#' \item{\code{plot}}{Described before.}
#'
#' \item{\code{tre}}{Described before.}
#'
#' \item{\code{rep}}{Interger variable to indicate repetition. Each
#' variable of patogenicity were accessed twice per tree.}
#'
#' \item{\code{inc}}{Ordered categorical variable to indicate
#' incidence. Its a 1 to 5 subjective scale that means 1 (worst or
#' high incidence) to 5 (best or low incidence).}
#'
#' \item{\code{def}}{Numeric variable to indicate the tree defoliation.
#' Defoliation was measured as the number of leaves in the floor at
#' the east and west side of each plant counted inside a frame of 1
#' square meter randomly placed.}
#'
#' }
#'
#' @source Paulo dos Santos Faria Lichtemberg\eqn{^1}
#' (\url{http://lattes.cnpq.br/8132272273348880}), Ryan D. Puckett
#' (\url{http://kare.ucanr.edu/}), Walmes Marques Zeviani\eqn{^2}
#' (\url{http://www.leg.ufpr.br/~walmes}), Connor G. Cunningham
#' (\url{http://kare.ucanr.edu/}), Themis J. Michailides
#' (\url{http://ucanr.edu/?facultyid=1535}). \eqn{^1}University of
#' California, Department of Plant Pathology, Kearney agricultural,
#' research and extension center, 9240 S Riverbend Ave, Parlier,
#' California, US. \eqn{^2}Universidade Federal do Paraná,
#' Departamento de Estatística.
#' @examples
#'
#' data(ake_b)
#' str(ake_b)
#'
#' library(reshape)
#' library(lattice)
#' library(latticeExtra)
#'
#' #--------------------------------------------
#' # Quality.
#'
#' db <- melt(ake_b$quality[, -ncol(ake_b$quality)],
#' id.vars = 1:6,
#' id.measure = grep("c\\d", names(ake_b$quality)))
#' names(db)[ncol(db) - 1:0] <- c("categ", "freq")
#' str(db)
#'
#' useOuterStrips(
#' xyplot(freq ~ categ | hed + factor(yr),
#' groups = tra,
#' data = db,
#' xlab = "Treatments",
#' ylab = "Number of fruits",
#' jitter.x = TRUE,
#' auto.key = TRUE,
#' type = c("p", "a")))
#'
#' useOuterStrips(
#' xyplot(freq ~ categ | tra + factor(yr),
#' groups = hed,
#' data = db,
#' xlab = "Hed",
#' ylab = "Number of fruits",
#' jitter.x = TRUE,
#' auto.key = TRUE,
#' type = c("p", "a")))
#'
#' #--------------------------------------------
#' # Sensitivity.
#'
#' xyplot(d1 ~ d2 | as.factor(dos),
#' groups = tra,
#' data = ake_b$sensitivity,
#' as.table = TRUE,
#' scales = "free")
#'
#' # Unique levels of fungicide dose.
#' x <- sort(unique(ake_b$sensitivity$dos))
#'
#' # Variance of distance between doses.
#' esp <- function(p) {
#' u <- x^p
#' u <- (u - min(u))
#' u <- u/max(u)
#' var(diff(u))
#' }
#'
#' # Optimise de power parameter to the most equally spaced set.
#' op <- optim(par = c(p = 0.5), fn = esp)
#'
#' p <- seq(0, 1, by = 0.01)
#' v <- sapply(p, esp)
#' plot(log(v) ~ p, type = "o")
#' abline(v = op$par)
#'
#' # Sensitivity plot of each isolate.
#' xyplot(d1 ~ dos^0.2 | factor(iso),
#' strip = FALSE,
#' data = ake_b$sensitivity,
#' groups = fun,
#' type = c("p", "a"),
#' as.table = TRUE,
#' scales = list(draw = FALSE))
#'
#' #--------------------------------------------
#' # Severity.
#'
#' combineLimits(
#' useOuterStrips(
#' xyplot(inc + def ~ tra | yr,
#' outer = TRUE,
#' groups = hed,
#' data = ake_b$severity,
#' scales = list(y = list(relation = "free")),
#' type = c("p", "a"))
#' )
#' )
#'
#' xyplot(inc + def ~ tre,
#' outer = TRUE,
#' groups = yr,
#' data = ake_b$severity,
#' scales = list(y = list(relation = "free")),
#' type = c("p", "a"))
#'
NULL
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#' @name ake_b
#' @title Effect of fungicide sprays programs and pistachio hedging on
#' damage caused by \emph{Alternaria} on commercial pistachio
#' orchard of Tulare County, California.
#'
#' @description The experiment was established in a commercial pistachio
#' orchard in Tulare County, California. The total area sizes 2.9
#' ha with density of 335 plants/ha. In total, 12 plots were set
#' with approximately 80 pistachio trees cv. Kerman spaced at 5.8 m
#' between rows and 5.2 m between plants. Each plot included four
#' rows in width. In the year 2015, a heavy and normal hedging were
#' intercalated, resulting in 6 plots for each hedging type. No
#' hedging was made in 2016. Within each plot, a fungicide free
#' sub-plot with 20 plants (4 rows by 5 plants) was set as a
#' control. Along the plot central rows, four plants (three inside
#' the treated plot and one inside the control sub-plot) were
#' identified for isolate collection, severity and defoliation
#' assessments. In total, 48 plants were identified. The fungicide
#' treatment included three different programs plus the control.
#'
#' \describe{
#'
#' \item{cnt}{Control with no application.}
#'
#' \item{mer2}{Merivon (1st application) and Switch (2nd application);}
#'
#' \item{fon2}{FontelisTM (1st application) and Switch (2nd
#' application);}
#'
#' \item{mer3}{Merivon (1st application), Switch (2nd application) and
#' Gem (third application)}.
#'
#' }
#'
#' The combination of spray program and hedging type allowed two
#' replication plots per treatment.
#'
#' \strong{Fruit quality} - To determine the effect of spray program
#' and pistachio hedging on fruit quality, each of the 48 flaged
#' trees had their fruits harvested in mid September. Fruits were
#' bagged in plastic and identified to allow the localization of
#' plot and tree. Mechanic dehulling was made prior to fruit
#' drying, which occured during 3 days at temperature of 55
#' \eqn{^\circ}C. After drying, fruits were re-placed into an
#' identified plastic bags and stored at cold room at 4
#' \eqn{^\circ}C until analyses. For each one of the 48 bags of
#' samples, three subsamples were prepared including 100 fruits
#' randomly choosen. In order to evaluate the amount of stain
#' caused by the incidence of \emph{Alternaria} late blight in the
#' field, each subsample (composed by 100 fruits) were separated in
#' 5 categories, from 0 (no stain) to 4 (more stain), based on a
#' reference scale.
#'
#' \strong{Sensitivity} - In order to evaluate the fungicide program
#' effect on \emph{A. alternata} SDHI sensitivity, four isolate
#' populations were collected in two years of experiment.
#'
#' In 2015, the population \strong{A} (\eqn{n = 59}) and \strong{B}
#' (\eqn{n = 59}) were collected in late-May and mid-September
#' respectively. In 2016, the population \strong{C} (\eqn{n = 79})
#' and \strong{D} (\eqn{n = 63}) were collected in early-May and
#' mid-September respectively.
#'
#' This arrangement allowed to sample isolates before (\strong{A}
#' and \strong{C}) and after (\strong{B} and \strong{D}) the spray
#' season. To obtain the sensitivity values, three SDHI fungicides
#' stock solutions were prepared at 10 g a.i. liter-1 each. The
#' fungicides used were: technical grade fluopyram-fp (a.i. 99.13\%,
#' Bayer CropScience) and penthiopyrad-pe (a.i. 99.5\%, DuPont
#' Company) diluted in acetone; and the commercial product of
#' fluxapyroxad-fd (Sercadis 300 SC, BASF, The Chemical Company)
#' diluted in sterile deionized water.
#'
#' To determine an isolate's sensitivity to fungicides, stock
#' solution was diluted in autoclaved YBA agar medium at
#' concentrations of 0 (control), 0.01, 0.03, 0.12, 0.48, 1.92,
#' 7.68, 30.72 and 122.88 \eqn{\mu}g/ml. For each tested isolate, a
#' 5 mm mycelial plug was transferred from a 7-day-old colony and
#' placed onto the YBA media supplemented with one of the above
#' fungicide concentrations. Intercalate number of repetitions were
#' prepared, where 0 (control), 0.01, 0.12, 1.92, and 30.72
#' \eqn{\mu}g/ml received two repetitions, and the other doses one.
#'
#' Plates were incubated in dark for seven days at room temperature
#' prior to colony measurement, taken from two perpendicular
#' diameters. For each concentration, the inhibition of colony
#' growth (\eqn{L_i}) of isolate \eqn{i} was calculated as \eqn{L_i
#' = (C_{ck}-C_i)/C_{ck}\times 100}, where \eqn{C_{ck}} is the mean
#' colony diameter of the control with no fungicide, and \eqn{C_i}
#' is the mean colony diameter of the isolate \eqn{i} on the
#' supplemented medium.
#'
#' @format A list containing data frames.
#'
#' \code{quality} is a \code{data.frame} with 288 observations and 12
#' variables, described below.
#'
#' \describe{
#'
#' \item{\code{yr}}{Factor variable to indicate the year of experiment.}
#'
#' \item{\code{hed}}{Factor variable to indicate the hedging type on
#' trees. The hedging is the shape the branchs and limbs when
#' pruned. They can be heavy (severe pruning) or normal (regular
#' pruning).}
#'
#' \item{\code{tra}}{Factor variable to indicate the fungicide treatment
#' on field, already described above (\code{cnt}, \code{mer2},
#' \code{fon2} and \code{mer3}). The treatment combines the use of
#' one SDHI fungicide (Merivon or Fontelis) and one or two
#' additional chemical group. THe application is on field.}
#'
#' \item{\code{plo}}{Not an important variable to consider in the
#' analysis. The plot code simply indicate the location of
#' experimental plots, they are represented by one number (from 1 to
#' 3) indicating the rows (for example: each number is composed by 4
#' rows from where the two central rows contain the flagged tree),
#' and letters (from A to D) indicating the change in hedging.}
#'
#' \item{\code{tre}}{Factor variable to indicate tree from where fruits
#' were collected. There are 48 trees identified from 1 to 48, for
#' 2015, and the same identification for 2016 (corresponding to the
#' same trees sampled one year later). As an example: plot "1A",
#' include trees 1, 2, 3 and 4 (1, 2, 3 treated and 4 not treated);
#' and plot "1B" includes trees 5, 6, 7 and 8 (5, 6, 7 treated and 8
#' not treated).}
#'
#' \item{\code{rep}}{Integer variable to indicate repetition. Each
#' fruit sample obtained from a certain tree was sub-sampled by
#' randomly choosing 100 fruits. This subsampling originated 3
#' repetitions for each tree called subsample 1, 2 and 3.}
#'
#' \item{\code{c0}}{Numeric variable that is the number of fruits at
#' stain category 0. Category zero are the number of pistachio
#' fruits with 0\% of the shell surface discolored.}
#'
#' \item{\code{c1}}{Numeric variable that is the number of fruits at
#' stain category 1. Category one are the number of pistachio fruits
#' with 1\% to 10\% of the shell surface discolored.}
#'
#' \item{\code{c2}}{Numeric variable that is the number of fruits at
#' stain category 2. Category two are the number of pistachio fruits
#' with 11\% to 35\% of the shell surface discolored.}
#'
#' \item{\code{c3}}{Numeric variable that is the number of fruits at
#' stain category 3. Category three are the number of pistachio
#' fruits with 36\% to 64\% of the shell surface discolored.}
#'
#' \item{\code{c4}}{Numeric variable that is the number of fruits at
#' stain category 4. Category four are the number of pistachio
#' fruits with 65\% to 100\% of the shell surface discolored.}
#'
#' \item{\code{tot}}{Numeric variable that is the total number of fruits
#' evaluated inside each sub-sample.}
#'
#' }
#'
#' \code{sensitivity} is a \code{data.frame} with 10920 observations and
#' 11 variables, described below.
#'
#' \describe{
#'
#' \item{\code{yr}}{Described before.}
#'
#' \item{\code{hed}}{Described before.}
#'
#' \item{\code{tra}}{Described before.}
#'
#' \item{\code{plot}}{Described before.}
#'
#' \item{\code{pop}}{A 4-level factor variable to indicate the isolate
#' population collected in 2015, "A" and "B", and 2016, "C" and "D".
#' Each population was collected before and after the spray season
#' in field, for this reason they belong to the same location but
#' the individuals inside the each population are unique, meaning
#' that isolate number one, tested for the population "A" will never
#' be tested in a different population.}
#'
#' \item{\code{iso}}{A factor variable to differenciate the isolates
#' collected during the preparation of populations "A", "B", "C" and
#' "D". They will never repeat because each isolate is sampled from
#' the population of isolates only one in the field. So, this is an
#' unique ID for isolates.}
#'
#' \item{\code{fun}}{A factor variable to indicate the SDHI fungicide
#' tested in laboratory. Each isolate collected in field was tested
#' \emph{in vitro} for its sensitivity of fluopyram "FP",
#' fluxapyroxad "FD", and penthiopyrad "PE". The shift in
#' sensitivity for "FP", "PE", and "FD" is the information we aimed
#' to have at the end of this experiment to know, which combination
#' of \code{tra} and \code{hed} affected more or less the
#' sensitivity of \code{fun}.}
#'
#' \item{\code{dos}}{A numeric factor variable to indicate the dose of
#' fungicide prepared inside the petri plate. Each dose was
#' prepared by the dilution of fungicide stock solution on YBA
#' media. The measure unit for fungicide dose is \eqn{\mu}g/ml.}
#'
#' \item{\code{rep}}{A numeric variable to indicate the repetition of
#' fungicide dose used to calculate the EC50 (sensitivity) of each
#' isolate. The repetitions were intercalate, two and one plate per
#' dose. Control received two repetitions as well.}
#'
#' \item{\code{d1}}{A numeric response variable for the first colony
#' diameter measured in mm. However the data on the table need to
#' be divided by 100. Decimals were ignored to facilitate the
#' typing of collected data.}
#'
#' \item{\code{d2}}{A numeric response variable for the second colony
#' diameter measured in mm. However the data on the table need to
#' be divided by 100. Decimals were ignored to facilitate the
#' typing of collected data.}
#'
#' }
#'
#' \code{severity} is a \code{data.frame} with 192 observations and
#' 8 variables, described below.
#'
#' \describe{
#'
#' \item{\code{yr}}{Described before.}
#'
#' \item{\code{hed}}{Described before.}
#'
#' \item{\code{tra}}{Described before.}
#'
#' \item{\code{plot}}{Described before.}
#'
#' \item{\code{tre}}{Described before.}
#'
#' \item{\code{rep}}{Interger variable to indicate repetition. Each
#' variable of patogenicity were accessed twice per tree.}
#'
#' \item{\code{inc}}{Ordered categorical variable to indicate
#' incidence. Its a 1 to 5 subjective scale that means 1 (worst or
#' high incidence) to 5 (best or low incidence).}
#'
#' \item{\code{def}}{Numeric variable to indicate the tree defoliation.
#' Defoliation was measured as the number of leaves in the floor at
#' the east and west side of each plant counted inside a frame of 1
#' square meter randomly placed.}
#'
#' }
#'
#' @source Paulo dos Santos Faria Lichtemberg\eqn{^1}
#' (\url{http://lattes.cnpq.br/8132272273348880}), Ryan D. Puckett
#' (\url{http://kare.ucanr.edu/}), Walmes Marques Zeviani\eqn{^2}
#' (\url{http://www.leg.ufpr.br/~walmes}), Connor G. Cunningham
#' (\url{http://kare.ucanr.edu/}), Themis J. Michailides
#' (\url{http://ucanr.edu/?facultyid=1535}). \eqn{^1}University of
#' California, Department of Plant Pathology, Kearney agricultural,
#' research and extension center, 9240 S Riverbend Ave, Parlier,
#' California, US. \eqn{^2}Universidade Federal do Paraná,
#' Departamento de Estatística.
#' @examples
#'
#' data(ake_b)
#' str(ake_b)
#'
#' library(reshape)
#' library(lattice)
#' library(latticeExtra)
#'
#' #--------------------------------------------
#' # Quality.
#'
#' db <- melt(ake_b$quality[, -ncol(ake_b$quality)],
#' id.vars = 1:6,
#' id.measure = grep("c\\d", names(ake_b$quality)))
#' names(db)[ncol(db) - 1:0] <- c("categ", "freq")
#' str(db)
#'
#' useOuterStrips(
#' xyplot(freq ~ categ | hed + factor(yr),
#' groups = tra,
#' data = db,
#' xlab = "Treatments",
#' ylab = "Number of fruits",
#' jitter.x = TRUE,
#' auto.key = TRUE,
#' type = c("p", "a")))
#'
#' useOuterStrips(
#' xyplot(freq ~ categ | tra + factor(yr),
#' groups = hed,
#' data = db,
#' xlab = "Hed",
#' ylab = "Number of fruits",
#' jitter.x = TRUE,
#' auto.key = TRUE,
#' type = c("p", "a")))
#'
#' #--------------------------------------------
#' # Sensitivity.
#'
#' xyplot(d1 ~ d2 | as.factor(dos),
#' groups = tra,
#' data = ake_b$sensitivity,
#' as.table = TRUE,
#' scales = "free")
#'
#' # Unique levels of fungicide dose.
#' x <- sort(unique(ake_b$sensitivity$dos))
#'
#' # Variance of distance between doses.
#' esp <- function(p) {
#' u <- x^p
#' u <- (u - min(u))
#' u <- u/max(u)
#' var(diff(u))
#' }
#'
#' # Optimise de power parameter to the most equally spaced set.
#' op <- optim(par = c(p = 0.5), fn = esp)
#'
#' p <- seq(0, 1, by = 0.01)
#' v <- sapply(p, esp)
#' plot(log(v) ~ p, type = "o")
#' abline(v = op$par)
#'
#' # Sensitivity plot of each isolate.
#' xyplot(d1 ~ dos^0.2 | factor(iso),
#' strip = FALSE,
#' data = ake_b$sensitivity,
#' groups = fun,
#' type = c("p", "a"),
#' as.table = TRUE,
#' scales = list(draw = FALSE))
#'
#' #--------------------------------------------
#' # Severity.
#'
#' combineLimits(
#' useOuterStrips(
#' xyplot(inc + def ~ tra | yr,
#' outer = TRUE,
#' groups = hed,
#' data = ake_b$severity,
#' scales = list(y = list(relation = "free")),
#' type = c("p", "a"))
#' )
#' )
#'
#' xyplot(inc + def ~ tre,
#' outer = TRUE,
#' groups = yr,
#' data = ake_b$severity,
#' scales = list(y = list(relation = "free")),
#' type = c("p", "a"))
#'
NULL
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