ake_b: Effect of fungicide sprays programs and pistachio hedging on...
In walmes/RDASC: Reproducible Data Analysis of Cientific Cooperations

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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.

cnt: Control with no application.
mer2: Merivon (1st application) and Switch (2nd application);
fon2: FontelisTM (1st application) and Switch (2nd application);
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.

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 ^\circC. After drying, fruits were re-placed into an identified plastic bags and stored at cold room at 4 ^\circC 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 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.

Sensitivity - In order to evaluate the fungicide program effect on A. alternata SDHI sensitivity, four isolate populations were collected in two years of experiment.

In 2015, the population A (n = 59) and B (n = 59) were collected in late-May and mid-September respectively. In 2016, the population C (n = 79) and D (n = 63) were collected in early-May and mid-September respectively.

This arrangement allowed to sample isolates before (A and C) and after (B and 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 μg/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 μg/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 (L_i) of isolate i was calculated as L_i = (C_{ck}-C_i)/C_{ck}\times 100, where C_{ck} is the mean colony diameter of the control with no fungicide, and C_i is the mean colony diameter of the isolate i on the supplemented medium.

A list containing data frames.

quality is a data.frame with 288 observations and 12 variables, described below.

yr: Factor variable to indicate the year of experiment.
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).
tra: Factor variable to indicate the fungicide treatment on field, already described above (cnt, mer2, fon2 and 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.
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.
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).
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.
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.
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.
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.
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.
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.
tot: Numeric variable that is the total number of fruits evaluated inside each sub-sample.

sensitivity is a data.frame with 10920 observations and 11 variables, described below.

yr: Described before.
hed: Described before.
tra: Described before.
plot: Described before.
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.
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.
fun: A factor variable to indicate the SDHI fungicide tested in laboratory. Each isolate collected in field was tested 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 tra and hed affected more or less the sensitivity of fun.
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 μg/ml.
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.
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.
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.

severity is a data.frame with 192 observations and 8 variables, described below.

yr: Described before.
hed: Described before.
tra: Described before.
plot: Described before.
tre: Described before.
rep: Interger variable to indicate repetition. Each variable of patogenicity were accessed twice per tree.
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).
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.

Paulo dos Santos Faria Lichtemberg^1 (http://lattes.cnpq.br/8132272273348880), Ryan D. Puckett (http://kare.ucanr.edu/), Walmes Marques Zeviani^2 (http://www.leg.ufpr.br/~walmes), Connor G. Cunningham (http://kare.ucanr.edu/), Themis J. Michailides (http://ucanr.edu/?facultyid=1535). ^1University of California, Department of Plant Pathology, Kearney agricultural, research and extension center, 9240 S Riverbend Ave, Parlier, California, US. ^2Universidade Federal do Paraná, Departamento de Estatística.

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"))