Genetic characterisation and agronomic and nutritional value of bitter vetch (Vicia ervilia), an under-utilised species suitable for low-input farming systems
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
Bitter vetch (Vicia ervilia (L.) Willd.), a grain legume crop well adapted in marginal soils, has mainly been used for animal feed. Nowadays, bitter vetch seeds in feed formulations are replaced by other protein sources such as soybean meal. However, in the context of sustainable economic development, it may be beneficial to enhance the cultivation of bitter vetch landraces in marginal areas. Fifty-six bitter vetch accessions of different provenance were preliminarily characterised by microsatellite DNA analysis to discriminate landraces suitable for specific and restricted environments. Twenty-two landraces of two genetically different groups were then selected for further characterisation by agro-morphological analyses. Being late-flowering with a seed yield of up to 3–4 t ha–1 in experimental field conditions, with neither chemical nor water input, these plants will be valuable material for long-term study to develop new cultivars adapted for seed production under organic agricultural systems in Southern Europe. The seeds of these 22 landraces were also evaluated, with positive results, as partial replacement of soybean in rabbit diets.
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