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Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

Evaluating rates of technology adoption and milking practices on New Zealand dairy farms

J. P. Edwards A B , B. T. Dela Rue A and J. G. Jago A
+ Author Affiliations
- Author Affiliations

A DairyNZ, Private Bag 3221, Hamilton 3240, New Zealand.

B Corresponding author. Email: Paul.Edwards@dairynz.co.nz

Animal Production Science 55(6) 702-709 https://doi.org/10.1071/AN14065
Submitted: 3 February 2014  Accepted: 11 April 2014   Published: 13 June 2014

Abstract

This study assessed technology use and evaluated rates of technology adoption and milking practices on New Zealand dairy farms. Industry surveys were conducted in 2008 and 2013, when farmers were asked a series of questions relating to their physical farm details, their role in the business, their attitudes towards technology, the technologies they had on-farm and their levels of satisfaction. In total, 532 and 500 respondents were questioned in the two surveys, respectively, with a similar representation of rotary and herringbone dairies. Questions relating to attitudes towards new technologies were subjected to a cluster analysis using the 2013 dataset. Farmers were classified into two categories, ‘fast’ and ‘slow’ adopters. Fast adopters are more likely to have a rotary, with a larger farm and more cows. The most common technology in herringbone dairies is automatic vat washing and in rotary dairies automatic cluster removers (ACR). Rotary dairies equipped with ACR, automatic drafting and automatic teat spraying achieve greater labour utilisation (cows/labour unit). Around half of farmers with herringbone dairies sometimes or always wait for slow-milking cows to milk out and 85% of farmers do not know the their ACR settings, highlighting significant potential to improve milking efficiency. Overall, technology is associated with greater labour utilisation. However, the benefits of each technology should be scrutinised to ensure appropriate investment decisions are made by farmers.

Additional keywords: automation, dairy, decision support, labour efficiency.


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