Abstract:

Taking the wine grapes from Fangshan district, Beijing as the research object, based on the wine grapes' phenological and quality indicators sample data from wineries and long-term meteorological data, the analytic hierarchy process, stepwise regression, multiple regression were used to establish wine grape quality evaluation index and wine grape quality meteorological index. The quality meteorological index insurance product for the wine grape in Fangshan district was designed by the probability optimal statistical method to calculate the distribution of the quality meteorological index and the parameter method to determine the pure insurance premium rate. Results showed that: (1) the weights of total sugar content, sugar-to-acid ratio, and pH value to the quality of wine grapes in Fangshan district were 0.643, 0.283, and 0.074, respectively. From 0.099 to 0.905, the wine grape quality evaluation index provided a good representation of quality. (2) the key meteorological factors affecting the quality of wine grapes are the average daily maximum temperature in the 20 days before harvest, total precipitation throughout the entire growth period, average relative humidity during the pigmentation period, and daily average precipitation during the pigmentation period. With a correlation coefficient of 100.38 (P<0.001), the quality meteorological index for wine grapes established based on stepwise regression is consistent with the quality loss rate of wine grapes. (3) Johnson SB distribution was the optimal distribution model for the quality meteorological index of wine grapes in Fangshan district. The pure premium rate for the quality meteorological index of wine grape insurance product was 11.75%. The break-even problem caused by climate change can be addressed by setting concession or rate adjustment coefficients based on the insurer's actual needs and risk estimates.

Key words: Beijing, Wine grape, Quality meteorological index, Pure rate