The Precision Approach of the Lactation Curve in Sirohi Goats Using Non-Linear Models

Lactation knowledge enables total milk yield prediction from single and multiple lactation test days. The objective of this study was to compare different non-linear lactation curve models and to select the best fit model for evaluation of the Sirohi goat’s milk production curve. Data retrieved fortnightly test day milk yield (FTDMY) in the various days (15, 30, 45, 60, 75, 90, 105, 120, 135 and 150) at 22.630 fortnightly test day milk yield of 2,263 Sirohi does in different lactations at All India Coordinated Research project area period from 2004 to 2016. Gamma, inverse quadratic polynomial, exponential, mixed log, and polynomial regression were evaluated to describe the lactation curve. The mean FTDMY increased from 0.811 ± 0.004 kg on Td1 (15th day of lactation) to 1.025 ± 0.005 kg on Td3 (45th day of lactation) and then decreased to 0.379 ± 0.001 kg on Td10 (150th day of lactation), with a coefficient of variation ranging from 20.40% to 28.68%. The polynomial regression function had the best adjusted R2 value of 99.4% and the smallest root mean square error of 0.003 kg., with expected peak yield, persistency, and total milk yield were 1.03 kg, 60.8%, and 115.73%, respectively. Out of the five lactation curve models examined, the polynomial regression function produced an outstanding model for predicting fortnightly test day milk output in Sirohi goats, with a relatively strong R2 and a low root mean square error (RMSE).