Genetic and genomic resources of lentil: status, use and prospects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Extensive collections of lentil germplasm now exist in various genebanks around the world. This germplasm including wild Lens species has been used in plant introduction strategies and in efforts to widen the potential sources of increasing genetic diversity in the breeding programmes of lentil. Improved techniques are emerging to overcome hybridization barriers between species and as a result, interspecific hybrids have been successfully obtained between species. Several interspecific recombinant inbred line populations have been developed. Selected and backcrossed lentil lines are currently in advanced yield trial stages, and desirable traits such as yield, disease resistance and agronomic traits have been incorporated into cultivated lentil especially from Lens ervoides , generating a wider spectrum of variability. Secondly, further expansion of the overall pool of germplasm and examination of allelic variation at the nucleotide level will benefit lentil-breeding programmes by augmenting phenotype-based variation to further advance cultivar development. Genomic resources for lentil are limited now, but this situation is changing rapidly as the cost of genotyping has declined. As a result, two successive expressed sequence tags (EST) projects were undertaken under the NAPGEN EST project initiative ( http://www.nrc-cnrc.gc.ca/eng/programs/pbi/plant-products/napgen/.htm ) and an Agricultural Development Fund project initiative. We emphasize that creation of intraspecific and interspecific genetic populations, genetic maps, association maps, quantitative trait loci and marker-assisted selection technologies for implementation in the breeding programme will enhance deployment of genes responsible for traits of interest. The economical use of genomic technologies for use in germplasm resource management and genetic improvement is on the near horizon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it