Data on 77, 010 daily milk yield (DMY) records of 247 lactations of crossbred cows over a period of 12 years from 2003-2014 were utilized for present experiment was conducted at Livestock Research Station (LRS), Collage of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand, Gujarat, India. Correlation and regression analysis were carried out with Standard week (meteorological standard week) wise data of milk yield and meteorological data (minimum temperature (MIN T), maximum temperature (MAX T), morning relative humidity(RH1), afternoon relative humidity(RH2), morning vapor pressure (VP1), afternoon relative humidity (VP2), wind speed (WS),bright sun shine hour(BSS), rain fall(RF) and evaporation rate (EP)) of 12 years by SAS (Statistical Analysis Software) programme (version 9.3). The overall average DMY of cross bred cows during 12 years period (2003-2014) was 8.73±0.26 kg. Maximum DMY was recorded during March (10.15±0.52 kg) and minimum was recorded during September (7.72±0.34 kg). Average DMY ranged from 4.39±0.37 to 13.83±0.55 kg from 12 year 2003 to 2014. Month of year had significant (P<0.05) effect on daily milk production. Correlation between Standard week wise milk yield data (of all 12 years) and MAX T was positive (0.1893) and significant, Whereas, RH1, RH2 and VP2 had negative and highly significant. RF was also found to be negative but significantly correlated. EP and BSS had positive and highly significant correlation with weekly average MY. There was no significant correlation among weekly average MY and MIN T and VP1 but WS was significantly correlated with average weekly MY. All the partial regression coefficients for independent variables were found significant except RH1, RF and VP2 but coefficient of determination (R2) was found very low (0.1652). Stepwise regression analysis showed that the partial regression coefficient of MIN T and BSS were found negative and highly significant whereas, partial regression coefficient of RH1, WS and EP were found positive and highly significant. The R2 of final model was 0.66 this indicated that the weather parameters (RH1, WS and MIN T) explained about 66% variations in average standard week wise milk production (averaged out of all 12 years data). The partial regression coefficient (R2) of MIN T and RH1 were found negative and significant indicating negative impact on average standard week wise milk yield whereas that of WS had positive impact on average standard week wise milk yield.

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