The main objectives were to analyze milking-to-milking variability in milk yield, fat and protein percentages, and somatic cell count (SCC). Additional objectives were to investigate the factors that affect variation in milk fat percentage and to study the seasonal variations in milk, fat, and protein yields and SCC. A total of 16 farms (14 milked 2x and 2 milked 3x) across Canada participated in a 5-d milk-sampling study, with 27,328 milk samples collected and analyzed for fat and protein yields and SCC. Descriptive statistics for both 2x and 3x herds for milk yield and fat and protein percentages followed a typical pattern throughout lactation, and the somatic cell linear scores were higher in early lactation for first-lactation cows (4.7 vs. 3.8) but were higher at the end of lactation for cows in second lactation or greater (5.1 vs. 4.9). The 2x herds had higher milk yields in the morning (approximately 17 vs. approximately 14 kg), whereas the 3x herds had the lowest milk yields in the morning, and yields peaked at the evening milking (approximately 9 vs. approximately 11.2 kg). A herd management questionnaire was distributed to participating producers to investigate the relationship between management variables and variations in milk fat percentage over the 5-d sampling period. Data from the questionnaire determined that milking period had a significant effect on milk fat in 2x herds, with fat percentage 1.11% lower in the morning compared with the evening milking period. Seasonal differences in milk, fat, and protein yields were investigated in 910 cows on 3 farms, with 5,517 fat and 5,534 protein samples. The seasonal differences in fat yield [summer = 1.02 +/- 1.05 kg/d (SEM); winter = 1.19 +/- 1.05 kg/d] and protein yield (summer = 0.85 +/- 1.05 kg/d; winter = 0.96 +/- 1.05 kg/d) were significant only for first lactation. Understanding the variability in milk yield, fat and protein percentages, and SCC is important when making management decisions and in milk-recording programs.
The objectives of this study were to compare the multiple trait prediction (MTP) model estimate of 305-d lactation yield with the 305-d daily milk yield data from on-farm automated meters and software and to examine the accuracy of electronic identification (ID). Twenty-four-hour milk and component yields are calculated by using milk weights and samples collected 8 to 10 times/yr by Dairy Herd Improvement (DHI) organizations. Daily milk weights were collected from cows on 20 Canadian farms that used parlor milking systems with electronic ID and that were enrolled in a regular DHI program. A total of 10,175 DHI test days from 1,103 cows with complete 305-d lactation yields were entered into the MTP model, and lactation yields were predicted. Test days were grouped into first, second, and third and greater lactations and within each lactation group, days in milk were categorized in 3 stages (5 to 60, 61 to 120, and 120 to 305 d in milk) for a total of 9 classes. Agreement analysis was used to compare the 305-d sum of daily milk to the MTP 305-d lactation yield predictions by using inputs from test days throughout the lactations. Results indicated that the MTP model overestimated lactation yields across all parity groups, ranging from 310 to 1,552 kg in parity 1, 640 to 2,000 kg in parity 2, and 567 to 1,476 kg in parity 3 and greater. A preliminary examination of electronic ID accuracy was conducted on 4 farms. Two electronic ID systems were examined for cow ID accuracy by verifying the ID number appearing in the parlor with the corresponding ear tag number. There were no ID errors on 3 of 4 farms tested and only a very small number of errors (3/80) on the fourth farm, indicating that the electronic ID systems used in milking parlors identify cows accurately.
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