Comparison Of Crop Yield Separation Methods

Crop yield separation is one of the important steps in analyzing the impact of meteorological factors on yield.Statistical rice yield data for 1985-2018 from twenty-four counties in Jiangsu were used to analyze the rationality of different separation methods.Six separation methods are 3-year moving mean,5-year moving mean,five-point quadratic smoothing,quadratic exponential smoothing,HP filter and year-to-year increment.Consistencies and differences were analyzed from aspects of trend yield and meteorological yield.In order to select better methods that are able to accurately capture the yield variation caused by meteorological factors,the meteorological yield based on different methods were compared with the typical annual increase and decrease of rice yield records.Finally,the selected methods were verified by the rationality of the relationship between meteorological factors and yields.Results show that: 1)The trend yield curves fitted by different methods were in line with the development of social technology.When compared with the average trend yield of the entire research area,the consistency correlation coefficients of twenty-two counties were greater than 0.5.Thissuggested that different methods do not differ in trend fitting.2)The characteristics of meteorological yield separated by 3-year moving mean,5-year moving mean,five-point quadratic smoothing and quadratic exponential smoothing in each county presented similar variations with significantly less standard deviation than that by the HP filter method and the year-to-year increment method.The result also suggested that the rationality of separating the meteorological yields by 3-year moving mean,5-year moving mean,five-point quadratic smoothing and quadratic exponential smoothing was higher than that by the other two methods.3)The five-point quadratic smoothing method and the 3-year moving mean method were able to capture the yield changes caused by meteorological factors in most typical years in the whole research area.4)Further verification indicated that the positive and negative effects of the meteorological factors captured by the 3-year moving mean and the five-point quadratic smoothing method were consistent with the rice response to climate change.Overall,separation methods of the five-point quadratic smoothing method and the3-year moving mean method are more suitable for this research area and the meteorologicalyields generated by these methods are able to reflect the impact of climate change.5)Crop yield separation is one of the key steps in the design of weather index insurance.It is of great significance to construct weather index accurately and has a certain contribution to reduce the basis risk.This study has obtained the optimal separation methods that suit the situation in Jiangsu Province.However,every method has both advantages and disadvantages.In order to improve and optimize the separation methods,integrating a number of superior separation algorithms and selecting methods according to the performance of algorithms at different analysis stages are proposed to future study,which has a strong potential to provide accurate yield analysis data for reports on impact of climate change on crop production.Meanwhile,the study will provide strong technical support to the study of controlling the basis risk of weather index insurance,which is aimed to reduce the basis risks.