TurgorLossPoint {pvcurveanalysis} | R Documentation |
Turgor Loss Point
Description
Determines the x coordinate (RWD) of the turgor loss point in a set of experimentally obtained pressure volume curves.
Usage
TurgorLossPoint(
data,
sample = "sample",
water.potential = "water.potential",
RWD = "RWD",
graph = TRUE,
show.legend = TRUE
)
Arguments
data |
data frame containing columns of equal lengths giving at least the numerical coordinates of the curve: water potential (MPa) and RWD (%), ordered by sample by descending water potential. A column containing the sample IDs is optionally required if several samples were measured. |
sample |
optional name of the column in data containing the sample ID, default: "sample" |
water.potential |
optional name of the column in data containing the numeric water potential values (MPa), default: "water.potential" |
RWD |
optional name of the column in data containing numeric relative water deficit values (%), default: "RWD" |
graph |
set FALSE if no plots are to be returned |
show.legend |
set FALSE if no legend is to be shown in the plots |
Details
Before using this function, check the data for an initial plateau. Data points in the initial part of the water potential
versus RWD plot with a stronger then expected decline need to be omitted.
The data is fitted using the Gauss-Newton algorithm of nls() to a combined exponential and linear
model. The exponential and linear parts are extracted and RWD at turgor loss point is localized at their point of minimum distance.
Value
List splitted by sample consisting of
turgor.loss.point |
coordinates of the turgor loss point (RWD) |
formula |
formula of the exponential and linear part of the combined fits |
coef |
coefficients of combined model |
conf_int |
upper (97.5 %) and lower (2.5 %) border of 95 % confidence interval of model parameters |
If graph = TRUE, the plotted original data is displayed with the exponential and linear fit of the combined model as well as the x-coordinate (RWD) of the turgor loss point.
Examples
# get sample data
data <- RelativeWaterDeficit(pressure_volume_data)[pressure_volume_data$sample == 10, ]
# identify turgor loss point in curve
turgor_loss_point <- TurgorLossPoint(data)