Morphological characterization and in vitro digestibility of seven Lathyrus sativus (grass pea) accessions originating from Eurasia, Africa, and Canada
Bibliographic record
Abstract
Abstract Lathyrus sativus is considered as an important economical source of high-quality proteins and adaptability to global climate change. To detect accessions useful for future breeding strategies, the genetic variability among and within seven Lathyrus sativus accessions was assessed by morphological characters and the in vitro digestibility study. An important genetic diversity was found using various morphological traits. The significant heterogeneity revealed by variance analysis (ANOVA) and correlation test could be elucidated by the different geographical origins of the studied accessions and the natural selection of grass pea. The Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) exhibited the accumulation of several genotypes in the same cluster which confirm that these genotypes are not dispersed according to their origin. Whereas, the individuals of grass pea from Ethiopia were collected in distinct group indicating that these samples are close each other’s and are different from the other accessions. In the same aim, the in vitro digestion model showed that most of the proteins were digested after 60-min incubation except the β-lathyrin protein. The different digestion kinetics found could be used as a method to distinguish different crop accessions. In fact, the densitometry analysis of β-lathyrin protein band showed that grass pea from Ethiopia, Germany, Bangladesh, and Morocco were more digested than grass pea from Canada, Afghanistan, and Greece in gastric phase, and Grass pea from Afghanistan and Germany were more digested than the rest of the samples in duodenal phase.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".