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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 #353487

Research Project: Improving Feed Efficiency and Environmental Sustainability of Dairy Cattle through Genomics and Novel Technologies

Location: Animal Genomics and Improvement Laboratory

Title: Common on-farm dietary and productions parameters may be used to discrimate between high and low efficiency lactating dairy cows

Author
item Iwaniuk, Marie E - University Of Maryland
item Connor, Erin
item Erdman, Richard - University Of Maryland

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 5/22/2018
Publication Date: 5/22/2018
Citation: Iwaniuk, M., Connor, E.E., Erdman, R.A. 2018. Common on-farm dietary and productions parameters may be used to discrimate between high and low efficiency lactating dairy cows [abstract]. In: Proceedings of the 32nd Annual Symposium of the Department of Animal and Avian Sciences, College Park, MD. p. 5-16.

Interpretive Summary:

Technical Abstract: Feed is the single largest expense associated with producing milk on dairy farms so producers are interested in exploring methods to improve dairy feed efficiency (FE). Dairy FE is calculated as the ratio of 3.5% fat-corrected milk (FCM; kg/d) per unit of dry matter intake (DMI; kg/d). Although the equation to calculate FE is simple, the vast majority of dairy cows are fed in large groups such that the DMI of individual cows is unknown and FE cannot be determined. Measuring individual cow DMI on a typical dairy farm is not practical, as it is a parameter that requires intense labor and resources to measure. Therefore, it is imperative to be able to distinguish between high and low efficiency dairy cows without measuring DMI so that producers can select highly efficient cows for their current herds as well as future herds through genetic selection. Previous research has shown that dietary alterations such as ionophore supplementation, increased dietary fat and protein supplementation, and dietary mineral manipulation can significantly affect FE. In addition, several commonly measured productions parameters such as milk yield and milk fat yield are positively correlated with FE as these parameters are used to calculate FCM. Therefore, we hypothesized that common on-farm measurements such as dietary and production parameters can be used to predict the FE of an individual cow. The objective of this study is to develop a discriminant function that will accurately predict the efficiency status (high vs. low) of individual cows based on dietary and production parameters using a discriminant analysis. The data used for this project were obtained from the laboratory of Dr. Erin Connor at the United States Department of Agriculture and the dataset included production data for 524 individual cows resulting in 8,081 total weekly production records. This dataset will be used to develop and validate a discriminate function using PROC DISCRIM in SAS (9.3) and the discriminant function will serve to distinguish between high and low FE dairy cows. Dairy producers will be able to utilize the results of this study to estimate the FE status (high vs. low) of individual cows within their herds to select for high efficiency dairy cows. Selecting cows based on high FE will reduce feed costs for producers, which will result in increased profitability.