Table 1.
Key performance indicators derived from FBS statistics in order to compare the intensity of production and characteristics among farms.
Fig 1.
Statistical workflow used to analyse the key performance indicators (KPIs).
- Number of clusters selected was determined by BIC (Bayesian Information Criterion).
Fig 2.
PCA results for all key performance indicator values across all years (2001–2014).
Panels on the left show the PCA scores for individual farms, on the right loading for individual metrics.
Fig 3.
Procrustes analysis of annual variation in relationships among key performance indicators (KPIs) are derived from principle component analysis of annual data over the years 2001–2014, based on the sum of squared distances.
Table 2.
Clustering analysis results, indicating the number, configuration and distinctiveness (mixing probabilities) of clusters for each of the survey years.
Fig 4.
Trends in mean key performance indicator values for all identified clusters over the period 2001–2014.
The number of farms in each cluster is represented by the size of symbol. Intensive systems are represented by triangles and extensive systems by circles. The solid black line represents the KPI annual average. The distance among all clusters in all years of study is represented by the colour scale MDS. This distance allows identifying which clusters are more similar.
Table 3.
Comparison of key performance indicators (KPIs) between 2001 and 2014 for extensive (E) and intensive (I) farm cluster.