# Fall and Winter Temperatures, Together with Spring Temperatures, Determine the First Flowering Date of Prunus armeniaca L

## TL;DR

This study shows that fall and winter temperatures, along with spring temperatures, help predict when apricot trees will first bloom in spring.

## Contribution

The study demonstrates that fall and winter temperatures significantly reduce prediction errors in bloom timing when combined with the ADP method.

## Key findings

- The ADP method had the lowest prediction error for apricot first flowering date.
- Fall and winter temperatures explained 96% of the remaining prediction error from the ADP method.
- Including temperature predictors reduced the root mean square error to 0.6162 days.

## Abstract

Chilling and spring temperature accumulation are both considered key factors determining the timing of the spring bloom in many flowering plants. The accumulated developmental progress (ADP) method predicted the first flowering date (FFD) of a species of Rosaceae well in a previous study. However, whether this approach can be applied to other species, and whether the prediction errors in FFD based on the ADP method can be further accounted for by fall and winter temperatures (FWTs), remains unknown. The ADP method and two others were tested using a 39-year apricot FFD data series. The goodness of fit obtained with each method was assessed using the root mean square error (RMSE) between the observed and predicted FFDs. We used the residuals obtained using the ADP method as a response variable to fit generalized additive models (GAMs) including six FWTs as predictors. The GAMs generated based on different combinations of predictors were compared using Akaike’s information criterion (AIC) to test whether using FWTs can reduce prediction error. The ADP method had the lowest RMSE, which equaled 3.0904 days. Together, the number of cold days, the number of chilling hours, the mean value of the daily maximum temperatures, and the mean value of the daily mean temperatures from 1 November of the preceding year to the starting date accounted for 96% of the deviance in the residuals obtained using the ADP method. Including these predictors reduced the RMSE to 0.6162 days. The ADP method is a valid technique to quantify the effect of spring temperatures from a given starting date on the FFD. The FWTs and the number of cold days can also influence the FFD. The present work provides evidence that FWTs including daily maximum temperatures and spring mean temperatures together determine the FFD of apricot.