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Cultivating Responsible Plant Breeding Strategies: Conceptual and Normative Commitments in Data-Intensive Agriculture

Hugh F. Williamson, Sabina Leonelli

202211 citationsDOIOpen Access PDF

Abstract

Abstract This chapter argues for the importance of considering conceptual and normative commitments when addressing questions of responsible practice in data-intensive agricultural research and development. We consider genetic gain-focused plant breeding strategies that envision a data-intensive mode of breeding in which genomic, environmental and socio-economic data are mobilised for rapid crop variety development. Focusing on socio-economic data linkage, we examine methods of product profiling and how they accommodate gendered dimensions of breeding in the field. Through a comparison with participatory breeding methods, we argue that the conceptual commitments underpinning current methods of integrating socioeconomic data into calculations of genetic gain can preclude the achievement of key social development goals, and that better engagement with participatory approaches can help address this problem. We conclude by identifying three key avenues towards a data-intensive approach to plant breeding that utilises the diverse sources of relevant evidence available, including socio-economic data, and maximises the chance of developing sustainable and responsible strategies and research practices in this domain: (1) reliable, long-term management of data infrastructures; (2) ongoing critical analysis of the conceptual foundations of specific strategies; and (3) regular transdisciplinary consultations including expertise in the social studies of agricultural science as well as participatory breeding techniques.

Topics & Concepts

NormativeUnderpinningCitizen journalismConceptual frameworkAgricultureLinkage (software)Variety (cybernetics)Participatory action researchKnowledge managementManagement scienceEnvironmental resource managementPolitical scienceSociologyProcess managementEnvironmental planningEngineeringGeographySocial scienceComputer scienceEconomic growthEcologyEconomicsBiologyArtificial intelligenceBiochemistryCivil engineeringGeneLawGenetic Mapping and Diversity in Plants and AnimalsGenetically Modified Organisms ResearchPlant Virus Research Studies
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