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RESEARCH ARTICLE

A decision-support tool for autumn management in a spring-calving pasture-based dairy system

Mark Neal A C , Jane Kay A , Sally Peel A and Sean McCarthy B
+ Author Affiliations
- Author Affiliations

A DairyNZ Ltd, Hamilton 3240, New Zealand.

B Kerry Group, Castleisland V93, Ireland.

C Corresponding author. Email: mark.neal@dairynz.co.nz

Animal Production Science 57(7) 1343-1349 https://doi.org/10.1071/AN16468
Submitted: 20 July 2016  Accepted: 9 January 2017   Published: 12 April 2017

Abstract

Success in a pasture-based dairy system relies on matching feed supply and feed demand in a profitable manner. Autumn is an important period for decision making to maximise current-season profitability, while ensuring key targets such as cow body condition score and the level of average pasture cover are met for the upcoming season. There are many tactical management strategies for farmers to consider during autumn to ensure that profitability is maximised in the current and next season (e.g. feeding crops, purchasing or using available supplementary feeds, reducing milking frequency, grazing off young stock, culling, or drying off cows). The complexity of trade-offs among these factors from January to calving, and the need to assess the impact of each of these on seasonal profitability led to the development of the ‘DairyNZ Autumn Management Resource’. This resource is an energy-based model that calculates the profit from different management strategies in pasture-based spring-calving systems. Feed demand is initially set to ensure that target body condition is achieved for the next season, and can then be altered using variables such as milking frequency, number of cows in milk and stock grazing on-farm. The assumption is made that energy supply comes from grazed pasture and crop first, followed by conserved forages, with the opportunity to fill remaining gaps with purchased feed. The model is a decision-support resource for farmers during the autumn that compares the economics of different management strategies in the current season, while ensuring that the performance in the next season is not compromised.

Additional keywords: agricultural systems, dairying, decision-support systems, economics.


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