Udder Traits as a predictor of milk yield in Abergelle Goats: Waghimra zone, Northern Ethiopia

Abstract

Abstract Milk production and growth are traits with adequate genetic variation to allow selection responses. Accurate prediction of milk yield is a prerequisite for every effective genetic improvement program. This study was conducted to predict milk yield using udder traits in Abergelle goats in the Waghimra zone. Data on milk yield, linear udder score, and udder measurement were collected from 259 healthy and mastitis-free goats at 14-day intervals after one week of parturition, with two measurements in each of the three lactation stages. Linear score traits were scored subjectively using a nine-point linear scale. Parity and management were considered explanatory variables to determine milk yield. The animals were classified into six parity groups. A GLM procedure using SAS/STAT® Software, version 9 of the SAS system for Windows (SAS Institute, Inc., 2002), was used for data analysis. Best-fit models were selected based on the coefficient of determination (R2), correlation coefficient (r), and applicability to farm conditions. As parity increases, milk yield, udder depth, width and teat length increase. When Milk yield was regressed to linear udder measurements, udder circumference explained about 70% of the variation in milk yield. The second udder measurement was udder depth, which contributed 73% of the variation in average daily milk yield. Hence, udder circumference has a predictive ability for milk production, is simple to measure, and is consistent with lactation stage and parity. While adding the depth of the udder to the circumference of the udder could improve the accuracy of the prediction.