- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
This study arises from the need for quantitative methods to assess risks of frost damage in agriculture. Classical mathematical functions were used to model damage due to freezing temperatures and a simple method based on experimental data is described to estimate the model parameters. Using survival data of vegetative and flower buds of deciduous fruit trees reported in the specialized literature, three sigmoidal functions were tested: logistic, Gompertz and Richards. The logistic function was chosen as the best model through the analysis of three comparative criteria: Root Mean Square Error (RMSE), statistical significance of parameters and Akaike Information Criterion (AIC). A parameter estimation method was developed based on a solution of a linear equation system of 2 × 2 fed only by two pairs of data, obtained from the simulated evolution of LT10 and LT90 for buds of apricot, cherry, apple and pear. The evolution of lethal temperatures (LT10 and LT90) fit well to a monomolecular function (r2 between 0.907 and 0.997, mean errors fluctuating between 0.5 °C and 1.3 °C). The method proved to be a good estimator of survival of buds and flowers, starting from published values of lethal temperatures. However, the model is highly sensitive to errors in the estimation of lethal temperatures during the flowering period. This study shows that it is possible to model crop response to freezing temperature, on the basis of limited data on freezing damage. Considering the simplicity of the method, it may be a useful tool to assess risks of frost damage and to improve models of climate change impacts.
4. Conclusions When data of freezing survival are limited, the developed methodology in this paper allows the construction oflogistic curves using two lethal temperatures, LT10 and LT90. The values of LT1 and LT90 can be obtained from a monomolecular model of lethal temperatures when these are unknown. Because of its simplicity and low demand of experimental data, this method is readily applicable to other crop species and can be incorporated in crop simulation models, allowing the quantification of expected damages due to freezing temperatures in differentlocations having data on minimum temperatures. This modelling exercise showed that with available experimental information it is possible to model survival of reproductive organs, which are the most sensitive to freezing temperatures. This methodology is a first step to incorporate sigmoid models in frost risk assessmentin cases or species with limited quantitative information. This approach is a good starting point to build quantitative models of frost injury in fruit species, which is essential for economic evaluation of frost damage. In addition, this study provides a useful tool for assessing climate risks in the context of current and future climatic scenarios.