عنوان مقاله [English]
Introduction: Milking activity is one of the most important daily activities in industrial dairy farms, which accounts for about 80 percent of the annual milking costs and more than 50 percent of the daily activities of each dairy farm. Milking speed (MS) is an important functional trait to dairy producers and in few countries (e.g. Canada), MS have been recorded for several years by milk recording agencies. Functional traits include traits related to animal health, feed efficiency, milkability, and calving ease. Milkability is the ease of milking in dairy cows (Gäde 2007). One of the important traits related to milkability is milking speed and usually, milkability is evaluated by measuring this trait (Gray et al. 2012). Milking speed refers to the amount of milk released from the mammary glands per minute (Klindworth 2003). Due to the effect of milking speed on udder health and labor productivity, this trait is considered a very important one from an economic point of view and has been emphasized in dairy cow selection programs for many years (Karacaören et al. 2006). However, there is evidence that increasing of milking speed is associated with increasing of udder health problems such as mastitis, and as a result, the optimal milking speed is considered by breeders. Milking speed can be assessed based on two indicators; 1) Scoring based on 1 to 5 points and 2) Using electronic stopwatch and flowmeter. The advantage of using a stopwatch is that it is being used easier than a flowmeter and the duration of its use is being reduced, However, the need for a technician to be present during milking is a major drawback of this method (Beard, K. 1993). This study aimed to estimate genetic parameters for milking speed and association between milking speed and milk components (somatic cell score, protein percentage, and fat percentage), in Holstein dairy cows in Isfahan province, Iran.
Material and Methods: Data were 5292 observations related to 1762 cows in 7 herds of Holstein dairy cows in Isfahan between October 2015 and April 2016. The distribution of MS scores was skewed toward faster milking speeds. Milk components data, including fat percentage, protein percentage and somatic cell count, belong to the same date, was obtained from the Isfahan Farmers' Cooperative (Vahdat). Only herds with complete pedigree information and three milkings records per day were selectected for final dataset. The milking time of each animal was measured by using a stopwatch and recorded in the form. Data editing quality control was performed by using Excel (2013) and FoxPro 9.0. The average milking flow rate criterion(amount of produced milk in kilograms divided by the milking time in minutes) was used to evaluate the trait of milking speed. To generate data with normal distribution, the somatic cell count (SCC) was transformed to somatic cell score (SCS) by natural logarithmic conversion. Pedigree was traced back to the founder generation. (Co)variance components were estimated using a DMU software package with an average-information (AI)-REML algorithm for the analysis of multivariate mixed models (Madsen and Jensen, 2013).Genetic evaluations and Best Linear Unbiasd Prediction (BLUP) of breeding values for milking speed was computed with the animal model by DMU program.
Results and Discussion: The results of the analysis of variance showed that the effects of herd, milking frequency, parity, and stage of lactation on milking speed were significant (p <0.01) and remained in the model. However, the effect of age at the first calving on this trait was not significant (p > 0.05). Mean of milking speed of the animals in this study was 1.96 ± 0.75 kg/min, and the least square means of milking speed in the population was 2.11 (±0.01) kg/min. The highest least square means of milking speed belonged to the third-parity cows with a mean of 2/21 (±0.01) kg/min and the least square means of milking speed belonged to the primiparous cows with mean of 1/98 (±0.02). Older cows have higher-capacity gland cisterns, and consequently, their cisterns can store more milk than the cisterns of primiparous cows. More milk stored in the cisterns can put more pressure on the teat sphincter and escape more quickly. By stages of lactation, the highest least square means of milking speed was observed in group 4 (the cows in the 51 to 65 DIM) with mean of 2/32 (±0.05) kg/min which can be due to the location of the animal in its milk yield peak. Also, the lowest least square means of milking speed was related to group 15 (the cows in the 321 to 350) with mean of 1.79 (±0.04) kg/min. In late lacataion stage, the amount of milk produced by the cow will reach the lowest possible level during its lactation stage. The estimated heritability of the milking speed in this study was 0.22 (±0.06). The results of this study showed that the traits related to milkability have moderate heritability. A high genetic correlation was observed between milking speed and milk yield (0.90) and milking time (-0.83). The estimated genetic correlation between milking speed with fat percentage and protein percentage was high and negative, -0.69 and -0.47, respectively. In this study, the estimated genetic correlation between milking speed and somatic cell score showed that selecting to increase the milking speed would reduce the somatic cell count. In general, Genetic evaluations for MS can provide useful information for breeding decisions because of the moderate heritability of MS.
Conclusion: Milking speed has a moderate heritability that allows selection to improve this trait in breeding programs.