Abstract
To improve the effectiveness of community-based breeding programs for increased milk production, the values of different udder measurements for predicting milk production traits during the milking period were assessed over 3 yr on 273 Awassi ewes. Machine milking of ewes began after weaning, 56 d after parturition, and continued until the milk yield of the ewes was <200 mL/d. Milk yield obtained by hand milking and milk composition were measured weekly, and days in milk, total milk yield, and total yields of protein, fat, and nonfat solids in milk were calculated for each ewe. On d 70 of milking, morphological traits of the whole udder (circumference, width, height, and length), udder cistern (height), and teats (length, width, and position score) were measured. On the same day, the milk yield of ewes was recorded by hand milking. Positive and moderate to strong correlations (r=0.36 to 0.76) between udder circumference and width, teat width, and milk production traits of total milk yield, and total yields of protein, fat, and nonfat solids were found. However, a more accurate predictor of milk production traits was milk yield on d 70, as higher positive correlations between this variable and the milk production traits were found (r=0.63 to 0.89). Nine farmers were invited to independently estimate the hand-milked milk yield performance of a sample of 169 ewes (d 15 to 45 of milking) by visually observing each ewe and making a subjective linear score (1 to 5). Their assessments were significantly correlated with milk yield on the day of the observation (r=0.52), total milk yield (r=0.50), and days in milk (r=0.45). Considering the perception details provided by farmers concerning each of the subjective linear scores, it was found that most predictive linear udder measurements of udder circumference and width and teat width identified in this study were implicit in these scores. The predictive ability of the measurements studied have practical implications for community-based breeding programs involving improvement of milk production—not just in Syria, but in other countries in dry areas as well—because it is possible for experienced farmers to visually assess milk production of dairy ewes or take simple udder measurements with predictive value.
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