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I.L. Mao

Researcher at Michigan State University

Publications -  27
Citations -  458

I.L. Mao is an academic researcher from Michigan State University. The author has contributed to research in topics: Sire & Population. The author has an hindex of 12, co-authored 27 publications receiving 448 citations.

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Selecting for lactation curve and milk yield in dairy cattle.

TL;DR: From empirical results from applied selection indexes, selecting for both increase of ascent to peak and peak yield did not decrease 305-day milk substantially and Rankings of sires on these indexes were similar to their rankings on milk yield alone.
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Heterogeneity of (Co)Variance and Heritabitity in Different Levels of Intraherd Milk Production Variance and of Herd Average

TL;DR: In this paper, an expectation-maximization algorithm of the REML method was used on 305-d, mature equivalent, first lactation milk records of 366,202 cows that freshened from 1976 through 1987 in the northeastern US.
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Robustness of the Restricted Maximum Likelihood Estimator Derived Under Normality as Applied to Data with Skewed Distributions

TL;DR: In this paper, a one-way random model was used to simulate observations corresponding to sire and error variance components that were either skewed or normally distributed, and the authors investigated the dispersion and asymptotic biasedness properties of variance components estimated by an Expectation Maximization algorithm of the Restricted Maximum Likelihood estimator derived under normality when applied to these distributions.
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Estimation of Residual Energy Intake for Lactating Cows Using an Animal Model

TL;DR: Residual energy intake was estimated for each of 247 Holstein cows, daughters of 127 sires and 226 dams distributed in five herds across the US to measure feed efficiency and was a sum of animal and residual effects.
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Genetic parameters of estimated net energy efficiencies for milk production, maintenance, and body weight change in dairy cows.

TL;DR: Net efficiencies of converting intake energy into energy for maintenance, milk production, and body weight change in a lactation were estimated for 79 Holstein cows by a two-stage multiple regression model, suggesting net energy efficiency for milk yield may be worth consideration for genetic selection in certain dairy cattle populations.