R/color_potential.R

In fruclimadapt: Evaluation Tools for Assessing Climate Adaptation of Fruit Tree Species

#' Evaluation of weather conditions for anthocyanin formation
#' in apple skin
#'
#' This function estimates the number of days that can be 
#' considered as highly favorable or unfavorable for anthocyanin 
#' accumulation in the skin of red apple cultivars during a
#' user defined pre-harvest period (30 days  by default). 
#' A highly favorable day (Cool day) is considered when the daily 
#' maximum temperature is below 26ºC, a highly unfavorable day (Hot day)
#' when the minimum temperature is above 20ºC (Lin-Wang et al, 2011). It
#' also calculates an empirical index in which daily thermal amplitude 
#' is corrected to account for the effective range of temperatures for
#' anthocyanin accumulation in the skin (TA_cef). The index considers that
#' daily temperatures above 26ºC are increasingly less favorable for 
#' anthocyanin formation, and thus calculates a corrected maximum 
#' temperature using a linear function up to 35ºC, where it is left 
#' constant at a value of 16, so that the adjusted daily thermal amplitude 
#' for Tmax>26ºC is smaller than the observed. 
#' The average of maximum and minimum temperatures during the same 
#' period is also provided. The function allows testing for several 
#' harvest dates.
#'
#' @param climdata a dataframe with daily maximum and minimum temperatures.
#'  Must contain the columns Year, Month, Day, Tmax, Tmin.
#' @param harvest a vector with expected harvest days
#' (expressed as day of the year)
#' @param span the period (in days) before harvest that will be analyzed. By 
#' default, this parameter is set in 30 days.
#' @return dataframe with the number of highly favorable (Cool_d) 
#' and unfavorable (Hot_d) days for apple red color, as well as the sums of
#' the observed (TA_obs) and effective (TA_cef) daily thermal amplitudes.
#' The average of the maximum (Tmax_avg) and minimum (Tmin_avg) 
#' temperatures for each year (Year) in the series during the 
#' 30 days previous to each harvest date (Day_h) is also provided.
#' @author Carlos Miranda, \email{carlos.miranda@@unavarra.es}
#' @references
#'
#' Lin-Wang K, Micheletti D et al, 2011. High temperature reduces apple fruit
#' colour via modulation of the anthocyanin regulatory complex. Plant, Cell
#' and Environment 34, 1176-1190.
#'
#' @examples
#'
#' # Select the appropiate columns from Tudela_DW example dataset, create
#' # a vector or harvest dates and estimate the number favorable and 
#' # unfavorable days on each year in the dataset.
#' library(magrittr)
#' library(dplyr)
#' Weather <- Tudela_DW %>%
#'    select(Year, Month, Day, Tmax, Tmin) %>% 
#'    filter (Tudela_DW$Year<=2002)
#' harvest <- c(225, 250, 275)
#' Color_assess <- color_potential(Weather, harvest)
#'
#' @export color_potential
#' @import magrittr dplyr 
#' @importFrom lubridate make_date yday

color_potential <- function(climdata, harvest, span=30)
{
  climdata <- select(climdata,"Year","Month","Day","Tmax","Tmin") %>%
    mutate(Date = make_date(Year, Month, Day),
           DOY = yday(Date),
           Cool=if_else(Tmax<=26,1,0),
           Hot=ifelse(Tmin>=20,1,0),
           TA=Tmax-Tmin,
           TA_adj=ifelse(Tmax<=26,Tmax-Tmin,
                        ifelse(Tmax>35,16-Tmin, (51-Tmax)-Tmin)))
  seasons <- unique(climdata$Year)

  colorpot_cn <- c("Year","Harvest_d","Cool_d","Hot_d","TA_obs","TA_cef","Tmax_avg","Tmin_avg")
  colorpot.df <-data.frame(matrix(ncol=8, nrow=0, byrow=FALSE))
  colnames(colorpot.df) <- colorpot_cn

  for (sea in 1:length(seasons)){
    Anno <- as.numeric(seasons[sea])
    climdata_fil <- climdata %>%
      filter(climdata$Year==Anno)
    for (nharv in 1:length(harvest)){
      Day_h <- as.numeric(harvest[nharv])
      evacol_fil <- climdata_fil %>%
        filter(climdata_fil$DOY>(Day_h-span) & climdata_fil$DOY<=Day_h) %>%
        summarise(Cool_d=sum(Cool),Hot_d=sum(Hot),TA_obs=sum(TA),
                  TA_cef=sum(TA_adj),Tmax_avg=mean(Tmax),Tmin_avg=mean(Tmin)) %>%
        select(Cool_d,Hot_d,TA_obs,TA_cef,Tmax_avg,Tmin_avg)
      new.row.df <- data.frame(Anno,Day_h) %>%
        cbind(evacol_fil)
      colorpot.df <-rbind(colorpot.df,new.row.df)
    }
  }
  colorpot.df <- colorpot.df %>% rename(Year=Anno)
  return(colorpot.df)
}