Evaluating the performance of diverse dairy systems

Abstract

Quantification of technical and environmental measurements from agricultural systems is of interest for both scientific and social reasons, so that types, sources, and amounts of undesirable outputs can be understood, managed and reduced. This cross-disciplinary research provides a holistically measured comparison of diverse genetic lines managed within novel and conventional UK dairy farming systems by employing a range of indicators and modelling techniques alongside a visual representation of the milk production regimes. This research focussed on evaluating Holstein Friesian cows of high and national average genetic merit across four diverse UK dairy production systems, by measuring environmental, health and financial outcomes. Using a Life Cycle Assessment approach and internationally agreed methods, performance indicators were used to assess the efficiency of dairy farming systems. Obtaining greater yields at the expense of high costs was shown to be financially unsustainable, especially under fluctuating milk prices. Management decisions have a clear effect on profitability, as herd replacement and reproduction choices alter the lifetime production of a cow, and the age profile of a herd. Reducing replacement rate by 1% could increase profit by 0.3p per litre in housed management and 0.4p per litre in a grazed system. Long term breeding for milk, fat and protein yield led to an average profit differences of 4p per litre produced, and 2p per litre produced, in housed and grazed systems respectively, when compared to animals of average genetic merit. Carbon accounting showed that average merit footprints across each of the dairy management regimes were significantly higher (p<0.001), on average by 15%. Livestock and embedded emissions were significantly higher from control merit cows (p<0.01). Sources of greenhouse gases varied by dairy management regime highlighting that farm mitigation may prove more effective if applied by system type. Pairwise comparison tests showed greenhouse gases to be significantly different in totals and type across the management systems. The effect of natural variation in the nutritional quality was investigated, and simulated footprints considering variation in diet digestibility and crude protein differed significantly from footprints using standard methods (p<0.001). Mass and economic allocation methods, and land use functional units, resulted in differences in system performance ranking. Eutrophication and acidification potentials provided impact results relating to water and air pollution and were shown to follow a similar system performance ranking as GHG emissions. Dairy system efficiency was found to differ and depend upon model emphasis. Efficiency scores generated by pollutant focused models were wider ranging and, on average, higher for genetically improved animals within housed systems, consuming imported by-product feeds and exporting all manure. However, models which considered P as a non-renewable resource presented a tighter range of efficiency scores across all management regimes, and, did not always favour cows of improved genetics which require higher feed intakes. Divergent results arising from type of model applied generate questions concerning the importance of model emphasis and offer insight into the sustainability of P use within varied dairy management regimes. Sensitivity and uncertainty surrounding financial and environmental measurements can be used to communicate the mutable nature of profitability and environmental outcomes. Performance rankings of the systems differed depending on modelling method, choice of indicator and functional unit, and also whether or not uncertainty of nutritional inputs were included. Trade-offs and synergies associated with the production of milk within current and possible future dairy systems can be communicated graphically in order to illuminate and communicate potential areas of focus to reduce emissions or improve efficiency. Irrespective of dairy management system, genetic selection for production has led to improvement in environmental and financial performance. Emissions from livestock and manure management can be reduced in all dairy systems and differences in emission source type should be considered when assessing mitigation potentials and strategies.