Genetic Diversity of Moroccan Orobanche crenata Populations Revealed by Sequence-Related Amplified Polymorphism Markers
Bibliographic record
Abstract
Orobanche crenata Forsk. is a root holoparasitic plant that affects legume species in Mediterranean basin especially in Northern Africa. This parasitic weed is particularly problematic in faba bean (Vicia faba L.) and lentil (Lens culinaris Medik.) fields. In Morocco, development of legume resistant/tolerant genotypes is considered the most economical and ecological control strategy against O. crenata. Efficient selection of resistant/tolerant cultivars requires prerequisite knowledge of the genetic diversity of the parasite. Thus, the present study focused on the assessment of the genetic diversity among and within Moroccan O. crenata populations, growing in faba bean fields, using Sequence-Related Amplified Polymorphism markers (SRAP). This marker system proved to be a powerful and an efficient tool for the evaluation of the genetic diversity among O. crenata populations. In fact, a total of 101 markers were identified and used for the Analysis of Molecular Variance (AMOVA), among which 98 bands were polymorphic (97.02%), indicating considerable genetic variation of these O. crenata populations. However, at population level, low level of polymorphic loci was observed with a percentage ranging between 41.58% and 67.33%. The Jaccard’s similarity coefficient and Principal Coordinate Analysis (PCoA) showed a clear differentiation among O. crenata samples according to the geographical origin of each population. AMOVA analysis revealed also a large extent of variation among O. crenata populations (60%; p < 0.010). Our outputs on molecular genetics of O. crenata combined with future epidemiological studies of these populations should clarify occurrence of O. crenata pathotypes and thereby validate the relevance of using multisite screening trials during breeding programs.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".