The Study On Low Temperature Forecasting Model And The Measures Preventing Damage Of Banana In Zhangzhou

Banana was one of main fruits of Zhangzhou where the place was of south subtropics, and low temperature affected the yield of banana frequently, which made serious economy loss. Low temperature had become the one of nature disasters restricting the development of banana industry. Therefore, it is quite significant to study and forecast low temperature disaster of banana in science theory and production practice on the spot. The text started from agricultural meteorology and physiology, the affecting degree of eight low temperature factors on the yield of banana in Zhangzhou city, Pinghe county, Yunxiao county, and Huaan county was investigated, the temperature and the yield of banana in the future in four areas mentioned were forecasted, the banana planting areas in Zhangzhou were programmed, some measures preventing damage by low temperature were put forward, and the following results were come out.(l)The result of correlation analysis among low temperature factors and between the factors and the yield of banana by linear regression showed that: accept it is not linearly correlative between x₆and x₃, so is x₇ and x₃, all the coefficients among eight factors were prominent, and the correlation between eight low temperature factors and the yield of banana gradated: x₃>x₇>x₅>x₆>x₈>x₄>x₁ >x₂. That is the correlationcoefficient between the daily difference temperature (x₃) and yield of banana was the greatest the best prominent and negative; the second was the average temperature of daily average temperature in every sliding five days (x₇ ), but daily averagetemperature (x₂ ) was the least. Therefore, the daily difference temperature is critical oneof the factors affected the output of banana suffered from low temperature disaster.(2) The result of prediction on low temperature model established by season level model of time sequence analysis showed that: the forecasting value was close to factual value in most years except for a few years, the prediction was good, and the model couldforecast the average of daily minimum temperature in every a period ten days ( T_DX|— ) in the future. The result of prediction of the average of daily minimum temperature in every a...