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). Manuscript profile

The data on 6772 growth records of Sirohi goats maintained at All India Coordinated Research Projecton Sirohi goat at Livestock Research Station, Vallabhnagar, Udaipur, India, and recorded between 2004 and 2016, were analysed to study the growth related traits and their genetic control. The overall least squares means of body weight at birth, W3M, W6M, W9M, W12M, were 2.34 ± 0.03, 12.44 ± 0.19, 16.31 ± 0.22, 20.08 ± 0.47 and 25.09 ± 0.40 kg, respectively while least-squares means for pre- and post-weaning average daily gains were 113.66 ± 2.15 and 46.17 ± 0.94 g/day, respectively. The various non-genetic factors exhibited variable effects on the growth traits at different phases of age. Cluster and period of birth had significant effect on all growth traits. Season of birth had significant effect except birth weight. Summer born kids heavier and higher body weight and pre- and post-weaning gains than winter and rainy season born kids. Males had a higher weight and higher daily gain than females at almost all stages of growth. Kids of primiparous dams had significantly lower birth weight as compared to multiparous dams’ kids. Single born kids had a distinct advantage over those born in multiple births at all stages of growth. The regression on dam’s weight at kidding were positive significant for all stages of growth traits. The heritability estimates of all body weights and weight gains at different stages of growth were moderate (0.16-0.28), except for post-weaning average daily gain, which had low heritability (0.07±0.01). The phenotypic and genetic correlations among the different growth traits were positive and high, except for phenotypic correlation between pre- and post-weaning gains which was negative. Four non-linear growth models, viz., Gompertz, Brody, Logistic and Von Bertalanffy were used to describe the growth pattern in Sirohi kids based on the growth parameters. The highest R2 value and lowest mean absolute error (MAE), akaike’s information criteria (AIC) and mean absolute percentage error (MAPE) values were observed in Brody model. Manuscript profile