Category Archives: Beef

Canola Supplementation in Late Gestation Cows Increases Calf Growth

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The growth performance of beef calves may be improved using prenatal supplementation of canola in cows

Researchers from USask found that canola-fat based pellet supplementation in the diet of beef cows led to greater growth of their calves from birth to slaughter. This may be due to the permanent alteration in the expression of a gene that is responsible for growth and muscle development. The aim of this project is to determine an optimal level of canola-fat inclusion in the prenatal diet that optimizes calf growth. Understanding the biological and epigenetic pathways that underlie connections between prenatal nutrition and postnatal growth and development can lead to increased predictability of calf performance and novel strategies to improve postnatal growth.

Download the full project summary here.

For more information on this project, please contact Livestock Gentec:

Phone: 780.248.1740
lsgentec@ualberta.ca

Institution: Agriculture and Agri-Food Canada

Primary Investigator: Carolyn Fitzsimmons

Co-Primary Investigator: Bart Lardner (USaskatchewan)

Term: 2021 - 2026

Funding: $137,000 from BCRC

Challenges in Sustaining Beef and Temperate Grasslands in Alberta

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Developing tools to help producers select cattle and manage grazing to maintain productivity and build public trust in sustainability

Grazing is regarded as the most beneficial use of temperate grasslands from both an agricultural and ecological point of view. However, scientists and consumers are often conflicted about the environmental footprint of beef production and the complex relationship between cow-calf production and grassland conservation. The aim of this project is to understand how the variation in pastures, forage grasses, cattle genetics and pasture microbes work together to influence sustainable beef production. Tools will be developed to help producers decide which cattle are better for the grasses on their land and to align forage availability with cattle nutritional needs. The environmental benefits of grazing grasslands will be measured to help build public trust in the beef industry

Download the full project summary here.

For more information on this project, please contact Livestock Gentec:

Phone: 780.248.1740
lsgentec@ualberta.ca

Institution: University of Alberta

Primary Investigator: John Parkins

Co-Primary Investigator: Cameron Carlyle (UAlberta)

Term: 2021 - 2023

Funding: $197,936 from New Frontiers in Research Fund

Improvement of Feed Efficiency, Carcass Traits, Fertility and Profitability in Commercial Beef Cattle

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Acceleration of genetic improvement of Canadian seedstock though increased use of genomic technologies and development of multi-trait indexes that perform in commercial crossbred cattle

Genomic tools can help the beef industry address challenges in global competitiveness, production efficiency, and sustainability. This project bought together international leaders in beef genomics to leverage vast amounts of genomic data and deliver commercial value to producers. The first ‘made in Canada’ genomic tool was developed to assess hybrid vigour (degree of cross-breeding). High hybrid resulted in a net return of $160/cow/year and was associated with improved fertility, stayability, feed efficiency and health resilience. Additionally, two multi-trait indices are being developed for commercial crossbred cattle in Alberta. 1) Feeder Profit Index to improve growth, feed efficiency, carcass quality and profitability in feeder cattle and 2) Replacement Heifer Profit Index to improve hybrid vigour, feed efficiency, fertility and lifetime return for cows in the herd.

Download the full project summary here.

For more information on this project or genomic testing and indexes, please contact Livestock Gentec:

Phone: 780.248.1740
lsgentec@ualberta.ca

Institution: Alberta Agriculture and Forestry

Primary Investigator: John Basarab

Co-Primary Investigator: Donagh Berry (AGRIC), John Crowley (CBBC), Changxi Li (AAFC)

Term: 2015 - 2020

Funding: $849,251 from Genome Alberta

Genetic Analyses of Feed Intake, Feed Efficiency, Female Fertility, and Cow Lifetime Productivity in Beef Cattle Raised in Two Environments

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Optimization of a multiple trait selection index for replacement heifers to reduce production costs and increase sustainability of beef production

Feed efficiency, feed intake, production performance, and fertility are major determinants of sustainable beef production. Understanding genetic correlations among these traits is crucial for optimizing multiple trait selection indices that improve calf crop percentage and sustainability. This project aims to develop a genomic selection tool for improved feed efficiency while maintaining or improving heifer/cow reproductive performance. An accurate and reliable multi-trait selection index for heifers and cows will improve feed efficiency and sustainability, as well as profitability and competitiveness. Production of more efficient cows with improved performance will reduce production cost and carbon intensity.

Download the full project summary here.

For more information on this project or genomic testing and indexes, please contact Livestock Gentec:

Phone: 780.248.1740
lsgentec@ualberta.ca

Institution: University of Alberta and Agriculture and Agri-Food Canada

Primary Investigator: John Basarab (UAlberta

Co-Primary Investigator: Changxi Li (AAFC)

Term: 2018 - 2023

Funding: $1,047,314 from BCRC

Development of a Functional Genomic Prediction Platform for Industry Application

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Development of a platform to increase genomic prediction accuracy and promote the use of genomic tools in commercial cattle producers

Genetic improvement of beef production efficiency and carcass quality is a key strategy to enhance national and international competitiveness and sustainability of beef production. However, the rate of genetic improvement using traditional phenotype and/or pedigree based genetic evaluation and selection has been slow for important beef performance traits that are difficult/expensive to measure, such as feed efficiency. In recent years, researchers at Livestock Gentec (AAFC, AAF, UAlberta) developed a number of genomic prediction tools for commercial producers who do not have access to herd improvement tools from a breed association and who want to select the best replacement animals from their own herd. This project aims to refine those genomic tools and to improve prediction accuracy for multiple beef breeds. The genomic prediction platform with improved accuracy will help service providers to deliver genomic decision support tools to their customers, which will allow the beef industry to improve beef production efficiency and quality via selection and management of genetics in their herd.

Download the full project summary here.

This project has led to the development of a Genomic-Enhanced Whole Herd Genetic Management Platform that is now ready for demonstration in the beef industry. For more information or to participate in the new project contact Michael Vinsky:

michael.vinsky@ualberta.ca
https://www.beefgenomicprediction.ca/

Institution: Agriculture and Agri-Food Canada

Primary Investigator: Changxi Li

Co-Primary Investigator: John Basarab (UAlberta)

Term: 2019 - 2021

Funding: $230,328 from Genome Alberta

Development and Deployment of a Computation Tool for Efficient Whole-Genome Sequence Association and Prediction Analysis

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A more statistically powerful and computationally efficient tool is needed to improve the efficiency and accuracy of whole-genome sequence analysis and prediction 

A vast amount of genetic information has been generated from the 1000 bull genome project across 171 cattle breeds. This information can potentially be used to facilitate the discovery of causal mutations and to greatly improve the accuracy of genomic prediction for economically important traits in beef cattle.  Recently, Livestock Gentec has imputed its legacy genotypes on about 25,000 beef individuals to whole-genome sequence data. This project aims to develop a powerful and efficient computing algorithm for whole-genome sequence association and prediction analyses. Successful development of this tool will provide the Alberta beef industry and research institutions with a powerful tool for fast integration of sequence information into genomic research and applications.

Download the full project summary here.

For more information on this project contact Livestock Gentec:

Phone: (780) 248-1740
lsgentec@ualberta.ca

Institution: University of Alberta

Primary Investigator: Graham Plastow

Term: 2020 - 2021

Funding: $120,000 from Genome Alberta

Remote Monitoring of Cattle Performance: A Path Forward to Long Term Sustainability

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Multispectral cameras may improve remote monitoring of cattle and measurement of performance traits in both drylot and extensively managed cattle herds

Feed intake, growth, carcass yield and fatness, methane production and cattle behaviour can be measured by a range of technologies to identify the best animals for breeding or production, or to identify those animals which are sick and require treatment. Currently this requires specialist equipment that are relatively invasive and require significant handling and labour. A new generation of monitoring technologies are based on imaging. Imaging systems offer a number of potential advantages: reduced labour, increased accuracy of measurement or prediction, new phenotypes, and improved animal welfare. This project aims to validate the remote monitoring of cattle using multispectral cameras to determine health, growth and production efficiency. Successful remote monitoring and collection of data on cattle will support the competitiveness and development of precision beef production in Alberta.

Download the full project summary here.

For more information on this project contact Livestock Gentec:

Phone: (780) 248-1740
lsgentec@ualberta.ca

Institution: University of Alberta

Primary Investigator: Graham Plastow

Term: 2021 - 2023

Funding: $196,000 from RDAR

Development and Demonstration of a Genomic-Enhanced Whole Herd Genetic Management Platform to Improve Beef Production Efficiency and Quality

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A platform to aid producers in herd genetic management will increase genomic tool adoption and improve beef production efficiency and quality

Constant improvement of beef production efficiency and quality is essential to enhance the competitiveness of the beef industry. A key strategy to improve beef production efficiency and quality is to manage the genetics of the whole cattle herd to achieve optimal beef production performance. This project aims to refine and demonstrate the Genomics Whole Herd Management Platform to the beef industry. The platform will allow beef producers to easily access information on the genomic profile of their herd including status or ranking of genetic merit for production traits and hybrid vigour. Based on the genomic profile, producers will be able to select breeding stock (sire and dam) that will optimize genetic gain and improve efficiency and profitability.

Download the full project summary here.

For more information or to participate in the project contact Michael Vinsky:

michael.vinsky@ualberta.ca
https://www.beefgenomicprediction.ca/

Institution: Agriculture and Agri-Food Canada

Primary Investigator: Changxi Li

Co-Primary Investigator: John Basarab (UAlberta)

Term: 2021 - 2024

Funding: $318,900 from BCRC

Demonstrating the Impact of Genomics-Enhanced Whole Herd Genetic Management Platform on Reducing Beef GHG Emissions

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Reducing beef cattle greenhouse gas emissions can be achieved through an effective and accessible genomic selection and whole herd genetic management program

More efficient cattle consume less feed and produce less GHG emissions than inefficient cattle. Additionally, cattle with enhanced retained hybrid vigour (more cross-breeding) have improved reproductive performance and reduced GHG emissions. Beef cattle GHG emissions can be reduced through genetic selection, but the industry lacks effective and science based tools to select and breed more efficient cattle with maximum hybrid vigour. This project aims to demonstrate the genomics enhanced whole herd management platform to the beef industry. The adoption of this tool can help the beef industry make genomic decisions for their herd more easily and contribute towards improved efficiency and sustainability.

Download the full project summary here.

For more information or to participate in the project contact Michael Vinsky:

michael.vinsky@ualberta.ca
https://www.beefgenomicprediction.ca/

Institution: Agriculture and Agri-Food Canada

Primary Investigator: Changxi Li

Co-Primary Investigator: John Basarab (UAlberta), Graham Plastow (UAlberta)

Term: 2021 - 2024

Funding: $487,370 Emissions Reduction Alberta (ERA)

Using DNA Pooling for Breeding Management in Commercial Cow-Calf Herds

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DNA pooling will increase the accessibility of genomic management to commercial beef producers to improve efficiency, profitability and sustainability.

The Canadian beef industry is challenged to remain globally competitive while improving efficiency and sustainability. To address these challenges, the beef industry must continue to evolve using advanced technologies such as genomics. An innovative approach to reducing the cost and labour associated with genotyping is DNA pooling, where information is collected on a group of individuals. This project aims to validate a low-cost DNA tool to monitor herd-level genomic breed composition, hybrid vigour and sire contribution by pooling the DNA from a group of animals. DNA pooling can be used to develop grouping strategies to increase carcass uniformity and value. Additionally, increasing hybrid vigour on the herd level can improve health and resilience, reduce carbon footprint and result in improved economic net returns.

Download the full project summary here.

For more information or to participate in the project contact Livestock Gentec

(780) 248-1740
lsgentec@ualberta.ca

Institution: University of Alberta

Primary Investigator: John Basarab

Co-Primary Investigator: Graham Plastow (UAlberta), Changxi Li (AAFC)

Term: 2021 - 2022

Funding: $381,500 (RDAR)