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ARS Home » Research » Publications at this Location » Publication #250818
Title: Derivation of factors to estimate daily milk yield from one milking of cows milked three times daily

Author
item SCHUTZ, MIKE - Purdue University
item BEWLEY, J - University Of Kentucky
item Norman, H

Submitted to: Journal of Dairy Science
Publication Type: Abstract Only
Publication Acceptance Date: 3/8/2010
Publication Date: 6/24/2010
Citation: Schutz, M., Bewley, J.M., Norman, H.D. 2010. Derivation of factors to estimate daily milk yield from one milking of cows milked three times daily. Journal of Dairy Science. 93(E-Suppl. 1):595(abstr. W32).

Interpretive Summary:

Technical Abstract: The objective was to derive factors to predict daily milk yield when milk is sampled once per d for cows milked three times (3x) per d. Milk weights for all three milkings were recorded automatically by 8 herds and collected by Dairy Herd Improvement supervisors on test-day. Following edits, 196,725 daily milk weight records of 2235 first lactation (L1) cows and 346,508 records of 3385 later lactation (L2) cows remained. Factors currently in use to adjust single milking yields for milking interval (MINT) were applied. Also, 3 methods were compared to estimate factors or equations to predict daily milk yield. Factors were estimated as the ratio of the sum of daily yield to the sum of partial yield within a parity-MINT class (13 intervals in 2 parities) [Method 1] or as the sum of the ratios of daily yield to partial daily yield for each cow-day divided by the number of cow-days within parity-MINT class [Method 2]. Resulting factors from both methods were smoothed, applied to data, and residuals were regressed on days in milk (DIM). Regression equations (n=112) were also developed within parity-MINT-DIM classes (2x7x8) [Method 3] to jointly account for MINT and DIM. Separate factors were derived for milking 1, 2, and 3 for each trait in L1 and L2. Method 3 resulted in consistently stronger correlations between estimated and actual yields, and smallest variances of estimates, and root mean squared errors (rMSE) for milkings 1, 2, and 3 in L1 and L2. Method 3 resulted in rMSE of 3.12 (Milking 1, L1), 3.26 (Milking 2, L1), 3.25 (Milking 3, L1), 4.52(Milking 1, L2), 4.72 (Milking 2, L2)and 4.57 (Milking 3, L2) kg; compared to rMSE of 3.58, 3.66, 3.59, 5.13, 5.41, and 5.09 kg, respectively, from current factors for the same milkings for L1 and L2. The multiple regression methodology (Method 3) appears to provide the most accurate prediction of daily milk weight from a single milking for herds milking 3x daily.