Integrated Assessment of the EU’s Greening Reform and Feed Self-Sufficiency Scenarios on Dairy Farms in Piemonte, Italy

Stefano Gaudino, Pytrik Reidsma, Argyris Kanellopoulos, Dario Sacco and Martin K. Van Ittersum
Additional contact information
Stefano Gaudino: Department of Agriculture, Forest and Food Sciences, University of Turin, via L. Da Vinci 44, 10095 Grugliasco, Italy
Pytrik Reidsma: Plant Production Systems Group, Wageningen University, P.O. Box 430, 6700 Wageningen, The Netherlands
Argyris Kanellopoulos: Operations Research and Logistics Group, Wageningen University, Hollandseweg 1, 6708 Wageningen, The Netherlands
Dario Sacco: Department of Agriculture, Forest and Food Sciences, University of Turin, via L. Da Vinci 44, 10095 Grugliasco, Italy
Martin K. Van Ittersum: Plant Production Systems Group, Wageningen University, P.O. Box 430, 6700 Wageningen, The Netherlands

Agriculture, 2018, vol. 8, issue 9, 1-27

Abstract: Specialised dairy farms are challenged to be competitive and yet respect environmental constrains. A tighter integration of cropping and livestock systems, both in terms of feed and manure flows, can be beneficial for the farm economy and the environment. The greening of the direct payments, which was introduced in the European Union’s greening reform in 2013, is assumed to stimulate the transition towards more sustainable systems. The aim of this study was to quantitatively assess the impacts of greening policies on important economic and environmental indicators of sustainability, and explore potential further improvements in policies. The Farm System SIMulator (FSSIM) bioeconomic farm model was used to simulate the consequences of scenarios of policy change on three representative dairy farms in Piedmont, Italy, i.e., an ‘intensive’, an ‘extensive’, and an ‘organic’ dairy farm. Results showed that in general, there is a large potential to increase the current economic performance of all of the farms. The most profitable activity is milk production, resulting in the allocation of all of the available farm land to feed production. Imposing feed self-sufficiency targets results in a larger adaptation of current managerial practice than the adaptations that are required due to the greening policy scenario. It was shown that the cropping system is not always able to sustain the actual herd composition when 90% feed self-sufficiency is imposed. Regarding the greening policies, it is shown that extensive and organic farms already largely comply with the greening constrains, and the extra subsidy is therefore a bonus, while the intensive farm is likely to sacrifice the subsidy, as adapting the farm plan will substantially reduce profit. The introduction of nitrogen (N)-fixing crops in ecological focus areas was the easiest greening strategy to adopt, and led to an increase in the protein feed self-sufficiency. In conclusion, it is important to note that the greening policy in its current form does not lead to reduced environmental impacts. This implies that in order to improve environmental performance, regulations are needed rather than voluntary economic incentives.

Keywords: bioeconomic modelling; dairy farming; greening policy; feed self-sufficiency; agro-environmental indicators; common agricultural policy (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://www.mdpi.com/2077-0472/8/9/137/pdf (application/pdf)
https://www.mdpi.com/2077-0472/8/9/137/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:8:y:2018:i:9:p:137-:d:167616

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().