Assessing frost damages using dynamic models in walnut trees: exposure rather than vulnerability controls frost risks

Area of Science:

• Agricultural Science
• Plant Physiology
• Climate Science

Background:

• Frost damage significantly impacts agricultural productivity, necessitating precise risk assessment.
• Traditional frost risk models often lack dynamic simulation of plant hardiness, leading to inaccuracies.

Purpose of the Study:

• To develop and validate a dynamic model for assessing frost risk in walnut trees.
• To compare the predictive accuracy of a photothermal model versus a thermal-only model for frost hardiness.

Main Methods:

• Calibrated two models (photothermal and thermal) using five years of frost hardiness data from two elevations and three walnut genotypes.
• Simulated frost hardiness using temperature, photoperiod, and developmental stage.
• Correlated predicted frost damage with minimum freezing temperatures, frost hardiness, and phenological stage.

Main Results:

• The photothermal model demonstrated higher accuracy (efficiency=0.879) than the thermal model (efficiency=0.801).
• Predicted frost damage strongly correlated with minimum freezing temperatures, not solely with hardiness or phenological stage.
• Frost risk is higher in winter at high elevations and in spring at low elevations for early-developing genotypes.

Conclusions:

• Dynamic simulation incorporating photoperiod is crucial for accurate frost risk assessment in walnuts.
• Early-season frost damage, even if minor, can negatively affect subsequent fruit production.
• Understanding the temporal dynamics of frost vulnerability within flower buds is essential for comprehensive risk management.