Participatory AI for inclusive crop improvement

Violet Lasdun, Davíd Güereña, Berta Ortiz-Crespo, Stephen Mutuvi, Michael Selvaraj and Teshale Assefa

Agricultural Systems, 2024, vol. 220, issue C

Abstract: Crop breeding in the Global South faces a ‘phenotyping bottleneck’ due to reliance on manual visual phenotyping, which is both error-prone and challenging to scale across multiple environments, inhibiting selection of germplasm adapted to farmer production environments. This limitation impedes rapid varietal turnover, crucial for maintaining high yields and food security under climate change. Low adoption of improved varieties results from a top-down system in which farmers have been more passive recipients than active participants in varietal development.

Keywords: Image-based phenotyping; Participatory plant breeding; Computer vision; On-farm variety evaluation; AI-assisted data-collection; Human centered design (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:220:y:2024:i:c:s0308521x2400204x

DOI: 10.1016/j.agsy.2024.104054

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