Avaliação do modelo de estimativa gama incompleto (Wood, 1967) e fatores que influenciam na curva de lactação de cabras leiteiros.

Abstract

Goat farming is one of the main agricultural activities in the world, with herds presente on all continents, with Brazil being the country that is more prepared in herd with dairy aptitude in South America. The objective of this work was to determine the factors that influence the lactation curve, as well as to evaluate the effectiveness of the estimation model proposed by Wood (1967) for dairy goats. Controls were used for 261 lactations of Saanen and Alpine goats, controlled between 2009 and 2021. To adjust the lactations, the Incomplete Range function was used (Wood, 1967). The influences of non-genetic factors on total milk production and the parameters estimated by the Incomplete Gamma function were evaluated. The factors used to compose the sources of variation were: calving year, calving season and calving order. It is observed that Saanen goats were more productive than Alpine goats throughout the lactation curve. The estimated values of milk production (kg) by the regression model of Wood (1967) obtained a satisfactory fit. The peak time was reached, for both breeds, in the first week of lactation and the peak production was estimated close to the real values observed in the first control. Higher initial productions were observed in the years 2011 and 2016, together with the production at 91 days, which presented the highest production in the year 2016. Higher productions were observed in the dry season for Saanen and Alpine goats, with the exception of late lactation for the Alpine breed that showed no significant difference. Fourth-order calving animals were more productive. The use of the proposed regression model in selection programs is indicated, as well as selection and management strategies should be implemented considering the environmental components of the calving season and the reproductive age of the animals.