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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 #419049

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: Association of individual cow milk fatty acid proportion and variance with milk production

Author
item CAPUTO, MALIA - Council On Dairy Cattle Breeding
item Miles, Asha
item MATTISON, JAY - Collaborator
item SIEVERT, STEVEN - Collaborator
item WU, XIAO-LIN - Council On Dairy Cattle Breeding
item Baldwin, Ransom - Randy
item BURCHARD, JAVIER - Council On Dairy Cattle Breeding
item DURR, JOAO - Council On Dairy Cattle Breeding

Submitted to: International Committee on Animal Recording(ICAR)
Publication Type: Proceedings
Publication Acceptance Date: 9/27/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Milk fatty acid (FA) fractions, de novo (DN), mixed, and preformed (PF), are grouped based on chain length, as < C16:0, C16:0, and > C16:0, respectively. These groups reflect the origin of milk FA synthesis, with DN representing FA synthesis within the mammary gland, PF representing FA coming from the diet or body tissue reserves, and mixed representing all three sources. Understanding the associations of milk FA groups with milk and component yields at the individual cow level may provide insight into making management and dietary decisions. To investigate these associations, milk samples (n = 14,091) were collected during the morning milkings from 1,737 Holstein cows from a herd milking 3x daily and averaging 41 kgs milk/cow. Milk samples were analyzed for FA groups (g/100g fat), fat, true protein, and lactose. Time periods of the first test (FT; 30 ± 2 DIM), peak milk (PT; 68 ± 31 DIM), and mid-lactation (MT; 100 ± 2 DIM) were selected. The variance of the FA groups was calculated for each animal as the variance of FA proportion between tests days within the first 305 DIM. Linear models were fit with FA group (proportion or variance), parity (1 vs >= 2), their interaction, and DIM (FA proportion models only) as the fixed effects and the month of sampling (FA proportion models) or month of calving (variance models) as the random effect. Across all periods, PF was positively associated with test day milk yield and cumulative milk yield through 305 DIM. In contrast, DN was negatively associated with test day milk yield and cumulative milk yield through 305 DIM across all periods (P < 0.1). Interestingly, increased variation in DN within cows across the first 305 DIM was positively associated with cumulative milk yields through 305 DIM (P < 0.01). The relationship between FA and component yields differed among the periods. Energy-corrected milk yield had a significantly negative association with DN at FT (P = 0.04) and a highly significantly positive association with DN at MT (P < 0.01). Still, it was not significantly associated with DN at PT (P = 0.24). The fat yield was negatively associated with DN at FT but was positively associated with DN at PT and MT (P <= 0.01). In contrast, fat yield was positively associated with PF at FT and negatively associated with PF at PT and MT (P <= 0.03). Protein yield was positively associated with DN for multiparous cows, negatively associated with DN for primiparous cows at FT2 (P < 0.01), and positively associated with DN for all parities at MT (P < 0.01). In contrast, protein yield was negatively associated with PF for multiparous cows, positively associated with PF for primiparous cows at FT (P = 0.02), and not significantly associated with PF at PT and MT (P > 0.1). The association of milk FA groups with milk and component yields suggests that milk FA groups may be a useful management tool for making pen grouping decisions, cow selection and breeding decisions, and informing dietary adjustments. However, the variable associations between FA groups and milk performance outcomes by parity and at different lactation stages highlight the importance of considering these factors when making decisions based on a single milk test. Routine milk testing across lactation may allow for tailored management decisions at the individual cow level using these FA groups.