TY - JOUR
T1 - Data-driven approaches can harness crop diversity to address heterogeneous needs for breeding products
AU - van Etten, Jacob
AU - de Sousa, Kauê
AU - Cairns, Jill E.
AU - Dell'Acqua, Matteo
AU - Fadda, Carlo
AU - Guereña, David
AU - van Heerwaarden, Joost
AU - Assefa, Teshale
AU - Manners, Rhys
AU - Müller, Anna
AU - Enrico Pè, Mario
AU - Polar, Vivian
AU - Ramirez-Villegas, Julian
AU - Øivind Solberg, Svein
AU - Teeken, Béla
AU - Tufan, Hale Ann
PY - 2023/4/4
Y1 - 2023/4/4
N2 - This perspective describes the opportunities and challenges of data-driven approaches for crop diversity management (genebanks and breeding) in the context of agricultural research for sustainable development in the Global South. Data-driven approaches build on larger volumes of data and flexible analyses that link different datasets across domains and disciplines. This can lead to more information-rich management of crop diversity, which can address the complex interactions between crop diversity, production environments, and socioeconomic heterogeneity and help to deliver more suitable portfolios of crop diversity to users with highly diverse demands. We describe recent efforts that illustrate the potential of data-driven approaches for crop diversity management. A continued investment in this area should fill remaining gaps and seize opportunities, including i) supporting genebanks to play a more active role in linking with farmers using data-driven approaches; ii) designing low-cost, appropriate technologies for phenotyping; iii) generating more and better gender and socioeconomic data; iv) designing information products to facilitate decision-making; and v) building more capacity in data science. Broad, well-coordinated policies and investments are needed to avoid fragmentation of such capacities and achieve coherence between domains and disciplines so that crop diversity management systems can become more effective in delivering benefits to farmers, consumers, and other users of crop diversity.
AB - This perspective describes the opportunities and challenges of data-driven approaches for crop diversity management (genebanks and breeding) in the context of agricultural research for sustainable development in the Global South. Data-driven approaches build on larger volumes of data and flexible analyses that link different datasets across domains and disciplines. This can lead to more information-rich management of crop diversity, which can address the complex interactions between crop diversity, production environments, and socioeconomic heterogeneity and help to deliver more suitable portfolios of crop diversity to users with highly diverse demands. We describe recent efforts that illustrate the potential of data-driven approaches for crop diversity management. A continued investment in this area should fill remaining gaps and seize opportunities, including i) supporting genebanks to play a more active role in linking with farmers using data-driven approaches; ii) designing low-cost, appropriate technologies for phenotyping; iii) generating more and better gender and socioeconomic data; iv) designing information products to facilitate decision-making; and v) building more capacity in data science. Broad, well-coordinated policies and investments are needed to avoid fragmentation of such capacities and achieve coherence between domains and disciplines so that crop diversity management systems can become more effective in delivering benefits to farmers, consumers, and other users of crop diversity.
KW - gender
KW - genebanks
KW - genotype by environment interactions
KW - plant breeding
KW - socioeconomic heterogeneity
U2 - 10.1073/pnas.2205771120
DO - 10.1073/pnas.2205771120
M3 - Article
C2 - 36972430
AN - SCOPUS:85150979748
SN - 0027-8424
VL - 120
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 14
M1 - e2205771120
ER -