Paper
27 June 2019 Land-based or landless dairy farms? Preliminary insights from Greece
A. Ragkos, A. Theodoridis, G. Koutouzidou
Author Affiliations +
Proceedings Volume 11174, Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019); 111741H (2019) https://doi.org/10.1117/12.2532487
Event: Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019), 2019, Paphos, Cyprus
Abstract
During the last 15 years significant changes have been witnessed in the Greek dairy cattle sector. Smaller farms are replaced by large, highly intensive ones. Within this intensification process, dairy cattle do not graze but are fed indoors, with feeding costs standing for a very high percentage of total production costs. This paper provides some preliminary evidence from a farm survey regarding the economic implications of producing feedstuff on-farm (land-based) as opposed to buying from markets (landless farms). Although the former strategy is considered to provide economic benefits and flexibility to farms, this is not confirmed by a descriptive technical and economic analysis. The results show that farms producing part of their feeds achieve limited variable cost savings, but they are burdened with excessive losses in terms of labour requirements and land use costs (paid or implicit). On the contrary, farms buying feedstuff exclusively from markets produce with significantly lower costs. The paper concludes that the issue of choosing the preferred feeding strategy is rather complex, requires further analysis with statistical and econometric methods and needs to consider system -, farm - and farmer-specific characteristics, as uniform conclusions cannot be derived.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Ragkos, A. Theodoridis, and G. Koutouzidou "Land-based or landless dairy farms? Preliminary insights from Greece", Proc. SPIE 11174, Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019), 111741H (27 June 2019); https://doi.org/10.1117/12.2532487
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KEYWORDS
Statistical analysis

Agriculture

Data processing

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