Effects of feeding level and genetic merit on the efficiency of pasture-based dairy systems : field and modelling studies : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Animal Science at Massey University, Palmerston North, New Zealand

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The objective of this thesis was to develop and validate a dynamic and stochastic whole-farm model that can predict physical and economic performance of pasture-based dairy systems; explore interactions between cow genetic merit, feeding level (supplementation and stocking rate) and market prices; and be applied to both ryegrassbased and lucerne-based pasture dairy systems. The effects of, and interactions between, stocking rate (SR), supplementation and genetic merit of cows on grazing dairy systems were reviewed, approaching both the physical and economic impact of these factors. The performance of strains of Holstein- Friesian cows in experiments from Ireland, Australia and New Zealand was summarised, and a meta-analysis that explores the relationship between herbage allowance and herbage intake was included. The development of the whole-farm model was completed in three steps. Firstly, a model was developed and validated that predicts herbage intake at grazing for dairy cows with or without supplementary feeding and that combines physical, metabolic and ingestive constraints. Secondly, an animal model that predicts energy intake, milk yield and live weight change of a single cow at grazing (e-Cow model) was developed and validated. This model also integrates the above intake model, a mammary gland model and a body lipid change model. The e-Cow model, which is available as a web-based version, combines nutritional and genetic drives to control energy partitioning within the cow. It also accounts for genetic differences between cows and is sensitive to genotype by environment interactions. The third and final step was the development and validation of a stochastic and dynamic whole-farm model that predicts physical and economic performance of grazing dairy systems (e-Dairy model). Both the e-Cow and the e-Dairy models simulate the performance of individual cows on a daily basis and were developed using Visual Basic programming language. The validation of the whole-farm model (e-Dairy) was conducted for ryegrassbased dairy systems using existing data from a 3-year farmlet experiment comparing five levels of SR (2.2 to 4.3 cows/ha) conducted in New Zealand, with cows offered 0.15 t dry matter (DM) supplement/cow/year. The validation of the model for lucernebased dairy systems was performed with data from a 2-year farmlet experiment designed and completed as part of the current research. This experiment compared three levels of SR (1.6 to 2.6 cows/ha) for cows offered 1.8 t DM supplements/cow/year in Argentina. An indigestible intake marker developed from a purified enriched lignin (LIPE®) was used to estimate individual herbage intake for a short-period within the farmlet experiment. Stochastic simulations (n=200) using the whole-farm model (e-Dairy) suggest that for ryegrass-based New Zealand dairy systems (ratio $/kg milk to $/kg supplement of 1.1 ± 0.31), the increase in SR from 2.8 to 3.5 cows/ha together with an increase in imported supplements from 0.15 to 1.45 t DM/cow/year can be profitable only when milk price is higher than $NZ5.5/ kg MS ($US4.1). Simulations for lucerne-based dairy systems in Argentina (ratio $/kg milk to $/kg supplement of 1.8 ± 0.55), suggest that the increase in SR from 1.6 to 2.6 cows/ha, with a fixed amount of imported supplements per cow at 1.8 t DM/cow/year would increase operating profit across the range of milk prices tested ($US 3.3 ± 0.84/kg MS). The e-Dairy model can be used to explore the effects and interactions of feeding level and genetic merit of cows for grazing dairy systems with differing calving patterns as well as evaluating the trade-offs between profit and the associated risk. It could also potentially be used, after further development, to simulate the genetic evaluation of cows and bulls under different selection objectives and selection schemes such as progeny tests for bulls.
Dairy cattle, Feeding and feeds, Pasture, Computer simulation, Computer models, New Zealand