The decision for dairy farmers to invest in automated oestrus detection (AOD) technologies involves the weighing up of the costs and benefits of implementation. In this paper, through a review of the existing literature, we examine the impacts of investment in AOD technologies in relation to the profitability and technical performance of dairy farms. Peer-reviewed articles published between 1970 and 2019 on the investment viability of AOD technologies were collated and analysed. We capture the different measures used in assessing the economic performance of investment in AOD technologies over time which include net present value (NPV), milk production, Benefit-Cost Ratio (BCR), internal rate of return (IRR) and payback period (PBP). The study concludes that investment in AOD technologies is not only worthwhile but also contributes to farm profitability.

This paper evaluates the impact of membership of the Business Development Groups (BDG), a participatory extension programme in Northern Ireland on the economic performance of participating farmers for dairy and sheep enterprise groups. The study employs the conditional difference-in-differences approach which combines a non-parametric matching estimator with a difference-in-differences analytical technique to obtain a credible best-estimates of the causal effect of BDG membership on farmers’ economic performance assuming that BDG participation is as good as random after controlling for observable farm characteristics and that the parallel trends assumption holds between BDG participants and non-participants. The results of the analyses showed that membership in the BDG programme has a statistically significant impact on the economic performance of participating farmers. Specifically, the results showed that farmers who are members of the dairy and sheep BDGs increased their gross margin by £109.10 and £17.10 per head respectively compared to farmers that are non-members of the BDGs. The results of the study provide robust evidence to inform policy development around the area of participatory extension programmes. It also supports the design of efficient agricultural education and extension systems that incorporates the ideas of the farmers themselves through peer-to-peer learning thereby maximising the economic and social benefits accruable from such programmes.

Profitable dairy farming requires continuous appraisal and adaptation of production systems in response to changing market and agricultural policy conditions. Geopolitical and climate events have exemplified the exposure of farm incomes to the increased volatility associated with often-global market factors. In this context, bio-economic models can be a useful tool for researchers seeking to understand the financial resilience of different production systems to these changing circumstances. The AFBI Dairy Systems Model is presented and used to simulate the impacts of alternative price scenarios for Northern Ireland-based dairy systems. The whole farm model consists of four interdependent components, comprising farm system, animal nutrition, feed supply and financial sub models. The model is used to evaluate how fluctuations in milk, concentrate, fertiliser, contractor, and electricity prices, as well as interest rate changes, affect three distinct production systems. The financial performance of all systems was sensitive to variations in milk and concentrate prices but relatively insensitive to variations in fertiliser, contractor, and electricity prices and interest rate changes. The profitability of a low-output system was less exposed to variations in prices. In contrast, a high-output system was more exposed to price variations. However, a medium-input system was the most profitable across the majority of price scenarios investigated.