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Modelling lactation in pasture-based dairy cows varying in production potential

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Adediran, SA (2009) Modelling lactation in pasture-based dairy cows varying in production potential. PhD thesis, University of Tasmania.

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Abstract

The main objective of the thesis was to quantify the genetic and phenotypic determinants
of variation in milk yield and composition, model the lactation pattern of pasture-based
dairy cows varying in genetic potential for milk production and the comparative
evaluation of empirical, mechanistic and random regression models as tools for
management decisions. More than half a million lactation and pedigree data from
Tasmanian dairy farms were sourced mainly from the TasHerd Milk Recording
Organisation and the Elliott Research and Demonstration Station. The data were analysed
using non-linear, generalised linear, mixed linear, multi-trait and random regression
procedures in SAS and ASReml.
Initial and the incline to peak but not peak and total milk yield were significantly
influenced by sire EBV choice. Early lactation milk yield potential was highly correlated
with peak and total milk yield and could be used as an early indicator of a cow's genetic
merit. Genetic (sire estimated breeding value (EBV) and cow production level in early
lactation), physiological (age, parity and body weight), environmental (season and year of
calving, lactation stage, nutrition and herd), factors influenced production traits. In
addition days to first test-day post-partum, lactation length, number of test-days and their
interactions affected curve shapes. Heritability of 305d milk, fat, protein and somatic cell
counts were 0.41, 0.37, 0.32 and 0.28 respectively. Phenotypic correlations between milk
and component yields ranged from -0.03 to 0.92, while genetic correlations ranged
between 0.034 and 0.85. Fourteen lactation functions including 8 empirical, 4 mechanistic and 2 semi-parametric
types were fitted to test-day milk and milk composition yields. Empirical models
adequately modeled the lactation of homogeneous group of cows but had varying error
biases in fitting individual cow's profiles. Random regression, including cubic spline,
models attained acceptable goodness of fit and permitted simultaneous evaluation of
factors affecting curve shapes. Significant contributions of the thesis to lactation modeling are the identification of
suitable functions and the introduction of a new empirical model for pasture-based
systems. High positive correlation between parameter c of this model with peak milk
yield and lactation persistency suggests that it has the potential for future dairy genetic
improvement. The knowledge of factors affecting curve shapes in pasture-based systems
will be relevant in developing appropriate management strategies to mitigate early
lactation production stress and maintain persistency.
Desirable as it is none of the tested mechanistic functions performed well. Suggestions
for future work are; further research into the potential of existing mechanistic models to
fit data across production systems and establishing a basis for understanding the
physiological basis of empirical models. Lack of herd level management input
inconsistent data recording pattern and incomplete test-date records were major obstacles
of the study. Similarly, lack of economic indices made profitability modelling and overall
farm economic analysis difficult. These constitute gaps in the current lactation data
collation systems.

Item Type: Thesis (PhD)
Copyright Holders: The Author
Copyright Information:

Copyright 2009 the Author - The University is continuing to endeavour to trace the copyright
owner(s) and in the meantime this item has been reproduced here in good faith. We
would be pleased to hear from the copyright owner(s).

Additional Information:

Available for library use only and copying in accordance with the Copyright Act 1968, as amended. Thesis (PhD)--University of Tasmania, 2009. Includes bibliographical references

Date Deposited: 25 Nov 2014 00:57
Last Modified: 11 Mar 2016 05:53
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