Germplasm banks are the most significant repository for plant genetic resources for food and agriculture (PGRFA) worldwide. Despite their strategic importance, national germplasm banks of tropical megadiverse developing countries such as Colombia have extremely limited funds. Therefore, making strategic decisions about research investment is essential. Here, we designed a data-driven approach to build an index that sorts Colombian PGRFA into three groups: high, medium, or low priority, based on four pillars of information from open-access databases and aligned with the sustainable goals of no poverty and zero hunger: Geographic origin, vulnerability status, economic benefits, and food security importance. We analyzed 345 PGRFA using the index, separating them into two groups, 275 already conserved in the Colombian germplasm bank (BGVCOL group) and 70 not currently conserved in the BGVCOL (NCB group). We used fuzzy logic to classify each PGRFA by each pillar and integrate it to obtain a priority index. Missing data for native crops were frequent in the BGVCOL group. Therefore we adopted an imputation strategy to fill the gaps and calculated the uncertainty. After applying the index, PGRFA with higher priority were 24 (8.72%) from the BGVCOL (i.e., 15 potatoes, three tomatoes, two tree tomatoes, pineapple, cocoa, papaya, and yacon) and one from NCB (i.e., coffee). We concluded that this methodology successfully prioritized PGRFA in Colombia and shows the big holes of knowledge for future research and alternatives to improve this index. The versatility of this methodology could be helpful in other genebanks with budget limitations for research investment.
Supplementary information: The online version contains supplementary material available at 10.1007/s10531-023-02599-7.
Keywords: Crop species; Ex situ conservation; Fuzzy logic; Genebanks; Germplasm banks; Information imputation.
© The Author(s) 2023.