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Financing Streams Of Post-Registration Variety Testing: A Case Study From Poland

Author

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  • UGLIS, JAROSŁAW
  • KOZERA-KOWALSKA, MAGDALENA

Abstract

This paper addresses the measures taken to implement progress in agriculture, with particular emphasis on the role played by Post-Registration Variety Testing (PRVT). Special attention was paid to assessing the structure of financing streams for PRVT in Poland, how they evolve over time and how they differ between locations. The Reports on the Implementation of the Post-Registration Variety Testing (PRVT) Program in 2010-2021 were used as source materials. Studies were carried out using 2010 constant prices. This paper found an increase in the number of PRVT research projects and experiments over the study period, which contributed to promoting biological progress, although the uses of PRVT findings differed between regions. Focus was also placed on the restructuring of financing for post-registration testing, with two leading streams being identified, namely the state budget and funds delivered by third parties, including private operators. The authors emphasized the importance of earmarked subsidies allocated to PRVT in the state budget, and the role they play in stimulating the transfer of knowledge and in promoting advancements and preserving biodiversity in Polish agriculture. The conclusion also points out the importance of PODs also in terms of the suitability of varieties for production in particular regions and under given technological conditions, which is in line with, among other things, the goals of the UN’s 2030 Agenda for Sustainable Development, i.e. SDG 12 (ensuring sustainable consumption and production patterns) and SDG 15 (protecting, restoring and promoting sustainable use of terrestrial ecosystems, sustainably managing forests, combating desertification, halting and reversing land degradation, and halting biodiversity loss).

Suggested Citation

  • Uglis, Jarosław & Kozera-Kowalska, Magdalena, 2022. "Financing Streams Of Post-Registration Variety Testing: A Case Study From Poland," Roczniki (Annals), Polish Association of Agricultural Economists and Agribusiness - Stowarzyszenie Ekonomistow Rolnictwa e Agrobiznesu (SERiA), vol. 2022(4).
  • Handle: RePEc:ags:paaero:330077
    DOI: 10.22004/ag.econ.330077
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    Cited by:

    1. Patryk Hara & Magdalena Piekutowska & Gniewko Niedbała, 2023. "Prediction of Pea ( Pisum sativum L.) Seeds Yield Using Artificial Neural Networks," Agriculture, MDPI, vol. 13(3), pages 1-19, March.

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