Description and typology of intensive Chios dairy sheep farms in Greece

Abstract

The aim was to assess the intensified dairy sheep farming systems of the Chios breed in Greece, establishing a typology that may properly describe and characterize them. The study included the total of the 66 farms of the Chios sheep breeders' cooperative Macedonia. Data were collected using a structured direct questionnaire for in-depth interviews, including questions properly selected to obtain a general description of farm characteristics and overall management practices. A multivariate statistical analysis was used on the data to obtain the most appropriate typology. Initially, principal component analysis was used to produce uncorrelated variables (principal components), which would be used for the consecutive cluster analysis. The number of clusters was decided using hierarchical cluster analysis, whereas, the farms were allocated in 4 clusters using k-means cluster analysis. The identified clusters were described and afterward compared using one-way ANOVA or a chi-squared test. The main differences were evident on land availability and use, facility and equipment availability and type, expansion rates, and application of preventive flock health programs. In general, cluster 1 included newly established, intensive, well-equipped, specialized farms and cluster 2 included well-established farms with balanced sheep and feed/crop production. In cluster 3 were assigned small flock farms focusing more on arable crops than on sheep farming with a tendency to evolve toward cluster 2, whereas cluster 4 included farms representing a rather conservative form of Chios sheep breeding with low/intermediate inputs and choosing not to focus on feed/crop production. In the studied set of farms, 4 different farmer attitudes were evident: 1) farming disrupts sheep breeding; feed should be purchased and economies of scale will decrease costs (mainly cluster 1), 2) only exercise/pasture land is necessary; at least part of the feed (pasture) must be home-grown to decrease costs (clusters 1 and 4), 3) providing pasture to sheep is essential; on-farm feed production decreases costs (mainly cluster 3), and 4) large-scale farming (feed production and cash crops) does not disrupt sheep breeding; all feed must be produced on-farm to decrease costs (mainly cluster 3). Conducting a profitability analysis among different clusters, exploring and discovering the most beneficial levels of intensified management and capital investment should now be considered.

Characterisation of terminal sire sheep farm systems, based on a range of environmental factors: a case study in the context of genotype by environment interactions using Charollais lambs

“…For this reason, the present analysis investigated whether it was possible to construct clusters of farms with similar environments and management systems using typology techniques. With the exception of the study by Morgan-Davies et al (2012), the present study differed slightly to other typology studies, due to the fact that PCO analysis was used rather than principal component analysis (PCA) (Köbrich et al, 2003;Gelasakis et al, 2012). Gower (1966), comments that the use of PCA is not suitable when the data set includes qualitative, or discrete data, therefore when considering the mix of quantitative and discrete data used in the current study, PCO was selected.…”

An overview of farming system typology methodologies and its use in the study of pasture-based farming system: a review

“…The more is the heterogeneity of farming systems (which are less known by the scientist) more input (observed) variables should be chosen to the typology of these systems and more of the variables contribute substantially to main principal components. For instance Castel et al (2003), Usai et al (2006), Milán et al (2006) and Gelasakis et al (2012) use numerous variables in PCA, mainly due to their structural nature, while Ruiz et al (2008) and Castel et al (2011) use lesser number and they refer to the farm dimension, farm management and animal productivity. At the same time, it occurs that the more is the heterogeneity of farming systems more should be the farm sample size.…”

“…Many authors after presenting the strengths and weaknesses of the different obtained groups, provide strategies for improving production systems. For example, Ruiz et al (2008) proposed improvements in the grazing use and labor management as well as the increase of farmer's advices and Gelasakis et al (2012) established four different farmer attitudes related to the on-farm feed production and the extent of pasture which aim to achieve the decrease of the production costs. However, some authors present the strengths and weaknesses of different obtained clusters (diagnosis) but propose making more studies to draw up such strategies (Castel et al, 2010).…”

“…Some examples of data collection in livestock farming systems using a structured direct questionnaire for indepth interviews, including questions properly selected to obtain a general description of farm characteristics and overall management practices are the following: Daskalopoulou & Petrou (2002) and Gelasakis et al (2012) in Greece; Castel et al (2003) in Andalusia, Spain; Gaspar et al (2008) in Extremadura, Spain, Marey-Pérez et al (2011) in Galicia, Spain; Paz et al (2005) in Argentina; Usai et al (2006) in Italy; Milán et al (2006), Castel et al (2010) in Poland and Carmona et al (2010) in Chile.…”

The relation between input-output transformation and gastrointestinal nematode infections on dairy farms

“…The factors influencing the level of disease and economic performance for each individual farm cannot be studied in a feasible way. However, by using classification systems, different types of farms may be identified with different interactions between input use, animal disease and efficiency (Usai et al, 2006;Gelasakis et al, 2012).…”