title: Application of a progressive-difference method to identify climatic factors causing variation in the rice yield in the Yangtze Delta, China.
abstract: Time series of rice yields consist of a technology-driven trend and variations caused by climate fluctuations. To explore the relationship between yields and climate, the trend and temporal variation often have to be separated. In this study, a progressive-difference method was applied to eliminate the trend in time series. By differentiating yields and climatic factors in 2 successive years, the relationship between variations in yield and climatic factors was determined with multiple-regression analysis. The number of hours of sunshine, the temperature and the precipitation were each defined for different intervals during the growing season and used as different regression variables. Rice yields and climate data for the Yangtze Delta of China from 1961 to 1990 were used as a case study. The number of hours of sunshine during the tillering stage and the heading to milk stage particularly affected the yield. In both periods radiation was low. In the first period, the vegetative organs of the rice crop were formed while in the second period solar radiation was important for grain filling. The average temperature during the tillering to jointing stage reached its maximum, which affected rice yields negatively. Precipitation was generally low during the jointing and booting stages, which had a positive correlation with yield, while high precipitation had a negative effect during the milk stage. The results indicate that the climatic factors should be expressed as 20- to 30-day averages in the Yangtze Delta; a shorter or longer period, e.g. 10 or 40 days, is less appropriate.
authors.affiliation: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing. yes@dls.iog.ac.cn
authors.forename: Q
authors.initials: Q
authors.lastname: Yu
authors.forename: H
authors.initials: H
authors.lastname: Hengsdijk
authors.forename: J D
authors.initials: JD
authors.lastname: Liu
mesh_terms: D002681:China; D002980:Climate; D015233:Models, Statistical; D012275:Oryza / Q000254:growth & development*; D013997:Time Factors; D014887:Weather