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Indirect strategies in dairy cows to reduce environmental footprint and improve efficiency


Project Description

Post summary

The Economic Breeding Index is the breeding goal used by the majority of Irish dairy farmers and encompasses 7 suites of traits known to impact on-farm profitability however does not include efficiency or environmental footprint. Their inclusion in the EBI has been hampered over lack of unbiased data availability from large numbers of commercial animals due to the expense and difficulty of their recording. Negative energy balance is a function of milk output and energy intake and because of its association with reproductive performance and health status can have serious repercussions for the environmental footprint of the herd. Body size is related to feed intake and thus also likely related to some direct environmental traits like methane emissions, while milk solids output relative to body size could be a useful indicator of efficiency.

The objective of this PhD programme is to explore the use of routinely available milk yield, milk solids and body weight data to indirectly predict efficiency and environmental footprint using data from the more than 10,000 lactations existing in the Moorepark research herd data base combined with data from the national data base.

Average lactation cow live-weight and total milk solids yield per lactation as well as lifetime milk solids yield, and its per-lactation deviation from body weight will be calculated and the relationship between these traits with feed intake and efficiency will be investigated through alternative modelling approaches. Variance components for these traits will be estimated. One strategy to increase milk yield per lactation while minimising metabolic stress in the critical period of the lactation, is to reduce the lactation profile peak while increasing the lactation persistency. Optimal strategies related to lactation peak-persistency statistics will be evaluated and the extent of variability in the new phenotypes and their amenability to national evaluations will be assessed.
This Walsh Fellow project will be part of a larger “GREENBREED” project.

Person specification

Qualifications

Essential

• Applicants should hold or expect to attain, as a minimum a 2:1 Honours degree, or equivalent, in Agricultural Science, Veterinary Science, Statistics or a related discipline.

Desirable

• MSc in Animal Science, Animal Breeding, Statistics or a related discipline

Skills & Competencies

Essential

• Applicants whose first language is not English must submit evidence of competency in English, please see WIT’s English Language Requirements for details.

Desirable

• Excellent data analysis and IT skills, organizational skills and communication skills (both written and oral)
• Ability to work as part of a team as well, as under own initiative
• Ability to work under pressure to meet project deadlines
• Flexibility and ability to problem-solve

Funding Notes

€24,000 per annum (prior to deduction of college fees) for 4 years.

Further information

For any informal queries, please contact

Prof. Donagh Berry, Teagasc Moorepark Dairy Production Research Centre, Fermoy, Co. Cork
Phone +353 (0)53 9171217 email: or
Dr. Siobhán Walsh, Department of Science, Waterford Institute of Technology, Waterford
Phone +353 (0)51 302290 email:

For queries relating to the application and admission process please contact the Postgraduate Admissions Office via email or telephone +353 (0)51 302883.

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