A decision-support tool for investment analysis of automated oestrus detection technologies in a seasonal dairy production system
E. B. Thomas A B , K. A. Dolecheck
A E , T. B. Mark B , C. R. Eastwood C , B. T. Dela Rue C and J. M. Bewley D
A Department of Animal and Food Sciences, University of Kentucky, Lexington, KY 40546, USA.
B Department of Agricultural Economics, University of Kentucky, Lexington, KY 40546, USA.
C DairyNZ, Private Bag 3221, Hamilton 3240, New Zealand.
D CowFocused Housing, 100 Killarney Drive, Bardstown, KY 40004, USA.
E Corresponding author. Email: karmella.dolecheck@uky.edu
Animal Production Science 59(12) 2280-2287 https://doi.org/10.1071/AN17730
Submitted: 24 October 2017 Accepted: 28 April 2019 Published: 13 September 2019
Journal Compilation © CSIRO 2019 Open Access CC BY-NC-ND
Abstract
Context: Advances in automated oestrus detection have made this an attractive technology to help reduce manual oestrus detection labour on dairy farms.
Aims: A decision-support tool was created to help farmers estimate the investment outcome of adopting automated oestrus detection technologies in a seasonal dairy production system.
Methods: A decision-support tool was created using Excel 2011 (Microsoft Inc., Redmond, WA, USA). The tool allows farmers to input both current herd reproductive management costs and performance and automated oestrus detection technology system costs and performance to receive herd-specific estimates of investment benefit. The investment analysis outputs include the net present value (NPV), internal rate of return (IRR), and payback period associated with automated oestrus detection adoption. Two different automated oestrus detection technologies were compared with visual oestrus detection aided by tail paint with a 72.0% oestrus detection rate (sensitivity) to demonstrate the value of the investment analysis tool. The alternative scenarios, technology one and technology two, were compared over an eight-year investment period.
Key results: Technology one, with a 62.4% oestrus detection rate, resulted in a negative NPV and IRR (–NZ$182 567 and –100% respectively), indicating a poor investment. Technology two, with an oestrus detection rate of 91.0%, provided a positive NPV and IRR (NZ$177 890 and 38.7% respectively), indicating a beneficial investment. The payback period for technology one was estimated as >10 years, whereas technology two’s payback period was <1 year.
Conclusions: The investment tool results are dependent on farm-specific and automated oestrus detection inputs.
Implications: Farmers can use farm-specific inputs in the tool to aid them when considering adoption of new automated oestrus detection technologies.
Additional keywords: precision dairy farming, precision dairy monitoring, seasonal dairying.
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