Food and seed productivity of alfalfa germplasm under increased soil acidity
Bibliographic record
Abstract
Goal. To assess the feed and seed productivity of alfalfa starting material of different eco-geographical origins. Results and Discussion. Based on results of studies of alfalfa germplasm of different eco-geographical origins under natural increased acidity of the soil solution (pH 5.2-5.3), promising starting materials were identified; they were superior to the check variety, ‘Syniukha’, in terms of feed productivity (which was higher by 7-92% or 0.07-0.9 kg/m²) and seed productivity (which was higher by 8-79% or 2.7-26.8 g/m²) in two years of using the grass canopy. We observed that most of the studied accessions (for example, ‘Radoslava’, ‘Aliia’ and others) showed their maximum feed productivity in the first year of using the grass canopy (2021), while in the second year, the feed productivity was slightly reduced, despite improved wetting. However, some of the collection acessions responded positively to this factor and, accordingly, the dry matter output was slightly higher than in the first year of using the grass canopy (‘Elehiia’, ‘Intryha’, ‘Mariskabul’, etc.). It should also be noted separately the heterogeneity of seed formation by plants of the collection accessions. Some yielded relatively stably over the years, others reached the maximum productivity in the first year of using, while in the next year with better conditions, on the contrary, their productivity decreased, apparently because of depletion of the root layer for certain nutrients; most of the accessions showed their maximum productivity in the second year of using. Conclusions. Based on the results of assessments, valuable starting materials were identified; they showed sufficiently high feed and seed productivities: ‘Radoslav’a (Ukraine), ‘Synia 2’ (Ukraine), ‘Elehiia’ (Ukraine), ‘Zaikevycha’ (Ukraine), ‘Mediya’ (Russia), ‘Flandria’ (France), ‘Cordoba’ (Argentina), ‘Mariskabul’ (Bulgaria), ‘Ferax 58’ (Canada), ‘Grilys-1’ (clone No. 3) (Sweden), ‘Mistseva’ (Brazil), and ‘Mistseva’ (Turkey). These accessions are proposed for use in breeding when creating purple medic varieties that would be tolerant to increased soil acidity.
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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 | 0.000 | 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 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".