Open AccessLactation curves in west African Dwarf and Red Sokoto goats
Author(s) -
M. N. Bemji,
O. A. Osinowo
Publication year - 2021
Publication title -
nigerian journal of animal production
Language(s) - English
Resource type - Journals
ISSN - 0331-2062
DOI - 10.51791/njap.v37i2.1386
Subject(s) - breed , mathematics , linear regression , lactation , zoology , regression , regression analysis , statistics , goodness of fit , polynomial regression , biology , veterinary medicine , medicine , pregnancy , genetics
Four mathematical functions (incomplete gamma, non linear regression, mixed log, and polynomial regression) were fired to 202 weekly lactations of 8 West African Dwarf and 9 Red Sokoto goats to ascertain the accuracy of prediction of individual milk production. The accuracy was assessed by the magnitude of R2 and the proportion of individual lactations well predicted. All the functions tested generally gave good fit to the observed data with slight tendency to consistently under- estimate daily milk yield. The pooled R2 estimates for all models exceeded 70%. Both breeds showed similar peak yields (P>0.05) averaging 420.65 ml during the first week of lactation. The proportion of individual lactations accurately predicted most of the models (incomplete gamma. mixed log and polynomial regression) were moderate Red Sokoto breed to high (87.5%) for West African Dwarf breed. R2 values generated from the jit of non-linear regression model however showed significant (P<0.05) breed difference with indication that more West African Dwarf goats (87.5%) had better fit (R2 = 0.863) than Red Sokoto goats (44.44%) with R: estimated at 0.693. The apparently reasonable trends in goodness of fit shown by the models. despite the limitation in number of records. points to the fact that predictive equations could be developed with increase in data size to predict future yields from incomplete lactation records.