Large datasets allow estimation of feed required for individual milk components or body maintenance. Phenotypic regressions are useful for nutrition management, but genetic regressions are more useful in breeding programs. Dry matter intake records from 8,513 lactations of 6,621 Holstein cows were predicted from phenotypes or genomic evaluations for milk components and body size traits. The mixed models also included DIM, age-parity subclass, trial date, management group, and BW change during 28- and 42-d feeding trials in mid lactation. Phenotypic regressions of DMI on milk (0.014 ± 0.006), fat (3.06 ± 0.01), and protein (4.79 ± 0.25) were much less than corresponding genomic regressions (0.08 ± 0.03, 11.30 ± 0.47, and 9.35 ± 0.87, respectively) or sire genomic regressions multiplied by 2 (0.048 ± 0.04, 6.73 ± 0.94, and 4.98 ± 1.75). Thus, marginal feed costs as fractions of marginal milk revenue were higher from genetic than phenotypic regressions. According to the ECM formula, fat production requires 69% more DMI than protein production. In the phenotypic regression, it was estimated that protein production requires 56% more DMI than fat. However, the genomic regression for the animal showed a difference of only 21% more DMI for protein compared with fat, whereas the sire genomic regressions indicated approximately 35% more DMI for fat than protein. Estimates of annual maintenance in kilograms DMI/kilograms BW per lactation were similar from phenotypic regression (5.9 ± 0.14), genomic regression (5.8 ± 0.31), and sire genomic regression multiplied by 2 (5.3 ± 0.55) and are larger than those estimated by the National Academies for Science, Engineering, and Medicine based on NE
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Toghiani et al. (2024) studied this question.
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