Trait prioritization studies have guided research, development and investment decisions for public-sector crop breeding programmes since the 1970s, but the research design, methods and tools underpinning these studies are not well understood. We used PRISMA-ScR (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols) to evaluate research on trait ranking for major crops over the past 40 years (1980–2023). Data extraction and descriptive analysis on 657 papers show uneven attention to crops, lack of systematic sex disaggregation and regional bias. The lack of standardized trait data taxonomy across studies, and inconsistent research design and data collection practices make cross-comparison of findings impossible. In addition, network mapping of authors and donors shows patterns of concentration and the presence of silos within research areas. This study contributes to the next generation of innovation in trait preference studies to produce more inclusive, demand-driven varietal design that moves beyond trait prioritization focused on productivity and yield.
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TI - A scoping review on tools and methods for trait prioritization in crop breeding programmes
AU - Occelli, M.
AU - Mukerjee, R.
AU - Miller, C.
AU - Porciello, J.
AU - Puerto, S.
AU - Garner, E.
AU - Guerra, M.
AU - Gomez, M.I.
AU - Tufan, H.A.
AB - Trait prioritization studies have guided research, development and investment decisions for public-sector crop breeding programmes since the 1970s, but the research design, methods and tools underpinning these studies are not well understood. We used PRISMA-ScR (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols) to evaluate research on trait ranking for major crops over the past 40 years (1980–2023). Data extraction and descriptive analysis on 657 papers show uneven attention to crops, lack of systematic sex disaggregation and regional bias. The lack of standardized trait data taxonomy across studies, and inconsistent research design and data collection practices make cross-comparison of findings impossible. In addition, network mapping of authors and donors shows patterns of concentration and the presence of silos within research areas. This study contributes to the next generation of innovation in trait preference studies to produce more inclusive, demand-driven varietal design that moves beyond trait prioritization focused on productivity and yield.
PY - 2024
UR - https://www.cifor-icraf.org/knowledge/publication/9123/
DO - https://doi.org/10.1038/s41477-024-01639-6
KW - agriculture, crop productions, plant breeding, systematic reviews, taxonomy, trait data
ER -Endnote (.ciw)
%T A scoping review on tools and methods for trait prioritization in crop breeding programmes
%A Occelli, M.
%A Mukerjee, R.
%A Miller, C.
%A Porciello, J.
%A Puerto, S.
%A Garner, E.
%A Guerra, M.
%A Gomez, M.I.
%A Tufan, H.A.
%D 2024
%U https://www.cifor-icraf.org/knowledge/publication/9123/
%R https://doi.org/10.1038/s41477-024-01639-6
%X Trait prioritization studies have guided research, development and investment decisions for public-sector crop breeding programmes since the 1970s, but the research design, methods and tools underpinning these studies are not well understood. We used PRISMA-ScR (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols) to evaluate research on trait ranking for major crops over the past 40 years (1980–2023). Data extraction and descriptive analysis on 657 papers show uneven attention to crops, lack of systematic sex disaggregation and regional bias. The lack of standardized trait data taxonomy across studies, and inconsistent research design and data collection practices make cross-comparison of findings impossible. In addition, network mapping of authors and donors shows patterns of concentration and the presence of silos within research areas. This study contributes to the next generation of innovation in trait preference studies to produce more inclusive, demand-driven varietal design that moves beyond trait prioritization focused on productivity and yield.
%K agriculture
%K crop productions
%K plant breeding
%K systematic reviews
%K taxonomy
%K trait data
Publication year
2024
ISSN
2055-0278
Authors
Occelli, M.; Mukerjee, R.; Miller, C.; Porciello, J.; Puerto, S.; Garner, E.; Guerra, M.; Gomez, M.I.; Tufan, H.A.
Language
English
Keywords
agriculture, crop productions, plant breeding, systematic reviews, taxonomy, trait data
Source
Nature Plants. 10: 402-411
