Rajbir SinghSINGH, NITESH KUMARY.P. Singh, Nazim Ali2018-07-312018-07-312015MODELING LACTATION CURVE IN MURRAH BUFFALOES USING MONTHLY TEST DAY MILK YIELDShttp://krishikosh.egranth.ac.in/handle/1/5810062753MODELING LACTATION CURVE IN MURRAH BUFFALOES USING MONTHLY TEST DAY MILK YIELDSThe present study was undertaken on first lactation production and reproduction records of 191 Murrah buffaloes maintained at GLF, Hisar and LRC, SVPUAT, Meerut over a period of 12 years (2003-2014). The data were classified according to season, period, age groups to study the effect of non-genetic factors.The overall least squares means of age at first calving (AFC), lactation length (LL), 305 days or less milk yields (305DMY) were obtained as 1278.891 ± 18.42 days;335.29 ± 5.95 days and 2447.867± 41.23 kg, respectively. Period had highly significant effect (P≤0.01) on Age at first calving and first lactation 305 days or less milk yield, whereas significant effect (P≤0.05) of period was found on first lactation length. However, the effect of season on all first lactation traits was found to be non-significant; whereas effect of age groups was also found to be non-significant on all first lactation traits. The data were used to estimate lactation curve parameters for three lactation curve models viz., Inverse polynomial function (IPF), Gamma type function (GF) and Mixed log function (MLF). The mean of monthly test day milk yields (MTDMY) increased from 5.373 ± 0.177 kg on MTDMY1 to a peak yield of 10.636 ± 0.214 kg (MTDMY3) for first lactation. The estimates of coefficient of determination (R2) and root mean square error (RMSE) for IPF, GF and MLF were 99.49%, 97.24%, 98.08% and 0.223kg, 0.117kg, 0.081kg, respectively. IPF fitted best to the MTDMY data followed by MLF on the basis of higher R2 and lower RMSE estimates, whereas GF fitted least.By using backward elimination method of multiple linear regression, lactation 305DMY could be predicted as early as 125th day of lactation on the basis of fifth test day milk yield aloneennullThesis