Development of a Benchmarking Tool for Dairy Herd Management Using Routinely Collected Herd Records

Abstract

Continuous assessment of the herd status is important in order to monitor and adjust to changes in the welfare and health status but can be time consuming and expensive. In this study, herd status indicators from routinely collected dairy herd improvement (DHI) records were used to develop a remote herd assessment tool with the aim to help producers and advisors benchmark the herd status and identify herd management issues affecting welfare and health. Thirteen DHI indicators were selected from an initial set of 72 potential indicators collected on 4324 dairy herds in Eastern Canada. Data were normalized to percentile ranks and aggregated to a composite herd status index (HSI) with equal weights among indicators. Robustness analyses indicated little fluctuation for herds with a small HSI (low status) or large HSI (high status), suggesting that herds in need of support could be prioritized and effectively monitored over time, limiting the need for time-consuming farm visits. This tool allows evaluating herds relative to their peers through the composite index and highlighting specific areas with opportunities for improvements through the individual indicators. This procedure could be applied to similar multidimensional livestock farming issues, such as environmental and socio-economic studies.

Embedding animal welfare in sustainability assessment: an indicator approach

“…This multivariate statistical procedure allows for trends or patterns within variables to be observed, helping to identify correlations between data points (Eriksson, 2018). Warner et al (2020) utilised the PCA procedure on routinely collected herd data in the development of a composite welfare index for benchmarking dairy farms in Canada. The primary component derived from the PCA accounts for the maximum volume of total variance in the observed variables, and the second component generated is correlated with some of the observed variables which are not correlated with the first component, and any subsequent components relaying a progressively smaller amount of variance (O'Shea et al, 2018).…”

“…The theoretical model to inform variable selection is drawn from Warner et al (2020) andDe Vries et al (2011) who utilised routinely collected herd data, similar to the data available for this study, in their assessments of farm management and animal welfare. De Vries et al (2011) identified three important dimensions of animal welfare: (i) production intensity, (ii) milk production and composition and (iii) management and facilities, and relevant variables were chosen to reflect these.…”

“…Due to the constraints of the dataset, the scope of the indicators is limited to the herd level. In line with the approach utilised by Warner et al (2020) and De Vries et al (2011) to assess herd welfare status, the following eight variables were proposed for the indicator development: (i) stocking rate, (ii) dairy calf mortality, (iii) fatto-protein ratio, (iv) SCC, (v) milk yield, (vi) days at grass, (vii) building investment and (viii) housing type.…”

“…These four principles have similar objectives to the "Five Freedoms" (FAWC, 2009) and are predominately measured at animal level, and thus are considered a useful guide for the measurement of animal welfare (EFSA, 2012). However, as the collection of such animal-based data is not feasible on a large, nationally representative scale, the utilisation of routinely collected data to assess the quality of herd management and animal welfare on farms has also been explored as a more practical alternative (Nyman et al, 2011;Warner et al, 2020). De Vries et al (2011) identified numerous variables of routine herd data (VRHD), categorised across management, milk production and milk composition categories, and compared these with established welfare indicators (WIs), to identify associations between the two assessments.…”

“…The WQ protocol utilised CIs to develop a welfare index, based upon numerous animal-based measures at the herd level (de Graaf et al, 2017), with a subsequent study developing a composite health indicator (De Vries et al, 2013). In their assessment of herd welfare, Warner et al (2020) devised a CI from routinely collected herd-level data from dairy farms in Canada. The objective of this paper is to update an existing suite of farm-level sustainability indicators, developed using data from the Irish Farm Accountancy Data Network (FADN), to include a measure of animal welfare on Irish dairy farms, in order to test the relationship between welfare and other aspects of sustainability, and to record welfare changes through time.…”