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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #416752
Research Project: Increasing Accuracy of Genomic Prediction, Developing Algorithms, Selecting Markers, and Evaluating New Traits to Improve Dairy Cattle

Location: Animal Genomics and Improvement Laboratory

Title: Analysis of factors affecting daily milk yields: an initial case study in an automatic thrice-milking farm

Author
item WU, XIAO-LIN - Council On Dairy Cattle Breeding
item CAPUTO, MALIA - Council On Dairy Cattle Breeding
item WIGGANS, GEORGE - Council On Dairy Cattle Breeding
item NORMAN, H - Council On Dairy Cattle Breeding
item Miles, Asha
item Van Tassell, Curtis - Curt
item Baldwin, Ransom - Randy
item SIEVERT, STEVEN - Collaborator
item MATTISON, JAY - Collaborator
item BURCHARD, JAVIER - Council On Dairy Cattle Breeding
item DURR, JOAO - Council On Dairy Cattle Breeding

Submitted to: Interbull Annual Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/30/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: The methodologies and parameters for estimating daily milk yields in the United States were mainly developed from the 1960s through the 1990s. A recent initiative by the Council on Dairy Cattle Breeding, USDA-AGIL, and the National DHIA aims to update these methods and parameters for estimating daily yields by collecting and analyzing milking data from dairy farms. This study, serving as an initial case study, examined the factors influencing daily milk yield estimation at a dairy farm in New York State and compared the performance of the existing method with a recently proposed one. In total, 63,562 milking data were extracted from approximately 2,200 cows milked thrice daily in this farm. Data cleaning eliminated incomplete or missing records, retaining 47,670 entries from 1,869 cows for subsequent analyses. The average partial yields in kilograms (milking interval time in hours) of the three milkings were 14.6, 16.5, and 13.8 (7.88, 8.79, and 7.25), respectively. Analysis of variance revealed significant effects of milking interval time and months in milk on proportional daily milk yields. The lactation effects on proportional daily yields were significant for the first two milkings but not for the third milking. Nevertheless, the relative importance of milking interval time and lactations was very low. This model was equivalent to Wiggans (1986) model with additional categorical variables for lactations and months in milk. The polynomial-interaction-regression model analysis showed significant effects from partial yields and significant interactions between partial yields and milking interval times on daily yields. The latter model gave more accurate estimates than the Wiggans (1986) model. Regarding the relative predictability of the three milkings, the 2nd milkings, having the longest average milking interval time, gave more accurate estimates than the 1st and 3rd milkings. The calculated MCFs in this farm increased slightly for the 1st milkings and remained roughly comparable (or slightly decreased) for the 2nd and 3rd milkings compared to the Wiggans (1986) assessment. These results suggest only minor changes in daily yield correction factors over the past four decades.