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Assessing the potential economic benefits to farmers from various GM crops becoming available in the European Union by 2025: results from an expert survey

Jones, P. J., McFarlane, I. D., Park, J. R. and Tranter, R. B. (2017) Assessing the potential economic benefits to farmers from various GM crops becoming available in the European Union by 2025: results from an expert survey. Agricultural Systems, 155. pp. 158-167. ISSN 0308-521X

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To link to this item DOI: 10.1016/j.agsy.2017.05.005

Abstract/Summary

This paper reports on a study that identified a range of crop-trait combinations that are: agronomically suited to the EU; provide advantages to arable farmers and consumers; and are either already available in international markets, or advancing along the development pipeline and likely to become available by 2025. An expert stakeholder panel was recruited and asked for their views, using the Delphi approach, on the impact of these crop-traits on enterprise competitiveness, through changes to yields, production costs and product prices. In terms of input traits, there was consensus that traits such as herbicide tolerant/insect resistant (HT/IR) maize, HT sugar beet and HT soya bean would provide positive benefits for farmers. Output-side traits such as winter-sown rape with reduced saturated fats, were seen as offering benefits to consumers, but were either likely to be restricted to niche markets, or offer relatively modest price premia to farmers growing them. Our analysis of the financial impact of the adoption of GM crops more widely in the EU, showed that the competitiveness of the agricultural sector could well be improved by this. However, such improvements would be relatively small-scale in that large-scale national natural advantages from either economic or environmental conditions is unlikely to be overturned.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Agriculture, Policy and Development > Economic and Social Sciences Division > Centre for Agricultural Strategy (CAS)
ID Code:71362
Publisher:Elsevier

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