Dataset.
Table_4_Searching for Abiotic Tolerant and Biotic Stress Resistant Wild Lentils for Introgression Breeding Through Predictive Characterization.XLSX
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330853
Digital.CSIC. Repositorio Institucional del CSIC
- Rubio Teso, María Luisa
- Lara-Romero, Carlos
- Rubiales, Diego
- Parra-Quijano, Mauricio
- Iriondo, José M.
Supplementary Material 4: Total number of evaluated accessions and number of accessions evaluated for lentil rust and broomrape. No. acc = number of accessions assessed; No. cty = number of countries were material was collected in origin. * Some countries host sampled populations of more than one taxon., Crop wild relatives are species related to cultivated plants, whose populations have evolved in natural conditions and confer them valuable adaptive genetic diversity, that can be used in introgression breeding programs. Targeting four wild lentil taxa in Europe, we applied the predictive characterization approach through the filtering method to identify populations potentially tolerant to drought, salinity, and waterlogging. In parallel, the calibration method was applied to select wild populations potentially resistant to lentil rust and broomrape, using, respectively, 351 and 204 accessions evaluated for these diseases. An ecogeographic land characterization map was used to incorporate potential genetic diversity of adaptive value. We identified 13, 1, 21, and 30 populations potentially tolerant to drought, soil salinity, waterlogging, or resistance to rust, respectively. The models targeting broomrape resistance did not adjust well and thus, we were not able to select any population regarding this trait. The systematic use of predictive characterization techniques may boost the efficiency of introgression breeding programs by increasing the chances of collecting the most appropriate populations for the desired traits. However, these populations must still be experimentally tested to confirm the predictions., Peer reviewed
DOI: http://hdl.handle.net/10261/330853
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330853
HANDLE: http://hdl.handle.net/10261/330853
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330853
Ver en: http://hdl.handle.net/10261/330853
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330853
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Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330853
Dataset. 2022
TABLE_4_SEARCHING FOR ABIOTIC TOLERANT AND BIOTIC STRESS RESISTANT WILD LENTILS FOR INTROGRESSION BREEDING THROUGH PREDICTIVE CHARACTERIZATION.XLSX
Digital.CSIC. Repositorio Institucional del CSIC
- Rubio Teso, María Luisa
- Lara-Romero, Carlos
- Rubiales, Diego
- Parra-Quijano, Mauricio
- Iriondo, José M.
Supplementary Material 4: Total number of evaluated accessions and number of accessions evaluated for lentil rust and broomrape. No. acc = number of accessions assessed; No. cty = number of countries were material was collected in origin. * Some countries host sampled populations of more than one taxon., Crop wild relatives are species related to cultivated plants, whose populations have evolved in natural conditions and confer them valuable adaptive genetic diversity, that can be used in introgression breeding programs. Targeting four wild lentil taxa in Europe, we applied the predictive characterization approach through the filtering method to identify populations potentially tolerant to drought, salinity, and waterlogging. In parallel, the calibration method was applied to select wild populations potentially resistant to lentil rust and broomrape, using, respectively, 351 and 204 accessions evaluated for these diseases. An ecogeographic land characterization map was used to incorporate potential genetic diversity of adaptive value. We identified 13, 1, 21, and 30 populations potentially tolerant to drought, soil salinity, waterlogging, or resistance to rust, respectively. The models targeting broomrape resistance did not adjust well and thus, we were not able to select any population regarding this trait. The systematic use of predictive characterization techniques may boost the efficiency of introgression breeding programs by increasing the chances of collecting the most appropriate populations for the desired traits. However, these populations must still be experimentally tested to confirm the predictions., Peer reviewed
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