exponential_chill: Exponential chilling model (Legave _et al._ 2008, 2013)

In EduardoFernandezC/dormancyR: Functions to Compute Chill Metrics

Exponential chilling model (Legave et al. 2008, 2013)

Description

This function computes the chill using an exponential function proposed by Legave et al. (2008) and Legave et al. (2013). This model, which uses Tmax as input an a threshold of 15 Celsius degree, was selected by the authors as one of the "bests" over several alternatives.

Usage

exponential_chill(ExtrDailyTemp, summ = TRUE)

Arguments

ExtrDailyTemp	Dataframe containing columns "Tmax" and "Tmin". These values must correspond to daily records
summ	Boolean parameter indicating whether the computed metric should be provided as cumulative values over the period or as the actual accumulation for each hour

References

Legave J., Farrera I., Almeras T. and Calleja M. 2008. Selecting models of apple flowering time and understanding how global warming has had and impact on this trait. J. Horticult. Sci. Biotechnol. 83(1): 76 - 84. doi:10.1080/14620316.2008.11512350

Legave J., Blanke M., Christen D., Giovannini D, Mathieu V. and Oger R. 2013. A comprehensive overview of the spatial and temporal variability of apple bud dormancy release and blooming phenology in Western Europe. Int. J. Biometeorol. 57(2): 317 - 331. doi:10.1007/s00484-012-0551-9

Examples

library(chillR)

#Example 1

exponential_chill(KA_weather, summ = FALSE)

#Example 2

tempResponse_daily(KA_weather, Start_JDay = 345, End_JDay = 58, 
models = list(Exp_Chill = exponential_chill))

EduardoFernandezC/dormancyR documentation built on Aug. 24, 2022, 7:21 a.m.