This study was carried out to evaluated the effect of meteorological parameters data in five years on six wheat genotypes yield. These data were collected with yield of wheat in Biekola research station in 2011- 2016. Three methods were used to analyze the data. In combined analysis, obtained significant difference for years, genotypes and their interaction at 1% level. Morvarid and N-91-7 had the most yield in 2015-2016. Although all genotypes were well-functioning due to climate conditions in this year. In correlation matrix, observednegative relationships sunshine hours and rainfall to genotypes yieldespecially for N-91-9. This genotype showed thatis susceptible to high rainfall. Using principle component analysis, revealed the latent roots that the correlation matrix could not show. Three factors explained 87-95 percent of variance in relation to the yield data. In first component, cloud cover and air humidity were significant positive parameters. These parameters could reduce the effect of excessive dryness and thereby increase yield. On the other hand, rainfall and sunshine hours had negative correlationbecause of the distribution at the inappropriate time for all genotypes. What of the results obtained, the occurrence of climate changeclimate in the southern parts of the Caspian Sea (North of Iran) which increased rainfall in October, November, December and Significant reduction of itin April, May and June.

Keywords: Caspian Sea, correlation, principle component analysis, meteorological, wheat genotypes.