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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 #399504

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: Implementation of feed efficiency in Iranian Holstein breeding program

item NADRI, SARA - Isfahan University Of Technology
item SADEGHI-SEFIDMAZGI, ALI - University Of Tehran
item ZAMANI, POUYA - Bu-Ali Sina University
item GHORBANI, GHOLAM REZA - Isfahan University Of Technology
item Toghiani, Sajjad

Submitted to: Animals
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/27/2023
Publication Date: 3/31/2023
Citation: Nadri, S., Sadeghi-Sefidmazgi, A., Zamani, P., Ghorbani, G., Toghiani, S. 2023. Implementation of feed efficiency in Iranian Holstein breeding program. Animals. 13(7):1216.

Interpretive Summary: Including feed efficiency in breeding objectives for dairy cattle is desirable because of the potential benefit for increased sustainability and herd profitability. An investigation of selection indices that included direct and indirect selection for feed efficiency traits showed that the best total response was observed when residual feed intake was directly included as a selection criterion. Using indicator traits (e.g., type traits) could be a useful proxy in the absence of direct genetic evaluations for feed efficiency. Breeding objectives of the current Iranian selection index, which currently focuses on future production and marketing environment, could include feed efficiency in future evaluations.

Technical Abstract: Improving the feed efficiency of dairy cows has a significant effect on economic profitability because of lower feeding costs. To examine the economic effect of feed efficiency on breeding objectives for Iranian Holsteins, economic weights were calculated through trait-by-trait and multiple-trait bioeconomic modeling. Production and economic data were obtained from 7 large dairy herds. Meta-analysis was used for genetic analysis of feed efficiency traits with production, reproduction, longevity, type, and body size traits. The weighted means of estimated heritabilities for residual feed intake (RFI), days in milk (DMI), milk yield (MY), fat yield (FY), protein yield (PY), productive life (PL), and days open (DO) were 0.19, 0.21, 0.22, 0.22, 0.22, 0.10, and 0.03, respectively. Genetic correlations for RFI were low and positive with MY, but low and negative with FY, and PY. In addition, the genetic correlations between RFI with DO and PL were negative, but it was moderate for PL and high for DO. Genetic correlations for DMI were high and positive with production traits (MY, FY, PY) and PL but low and negative with DO. Mean economic weights per cow per year across herds were estimated to be $0.34/kg for MY, $6.93/kg for FY, $5.53/kg for PY, -$1.68/kg for DMI, -$1.70/kg for RFI, $0.47/mo for PL, and -$2.71/d for DO. The Iranian selection index was revised to improve feed efficiency based on selection index theory through a deterministic model. Including direct and indirect selection for feed efficiency traits in different selection indices showed that including RFI rather than DMI was more advantageous economically for breeding objectives. The feed efficiency sub-index (FE$) introduced by Holstein Association USA was adopted to be relevant to Iranian economics and production systems. However, the discrepancy between Iranian and US genetic coefficients in FE$ can be attributed to differences in genetic and phenotypic parameters as well as the economic value for each trait in FE$. More precise Iranian EV for each trait in FE$ can be determined by collecting DMI data from Iranian herds and initiating genetic evaluation for RFI.