Agronomic value of alfalfa semi‐hybrids across contrasting Italian environments
Bibliographic record
Abstract
Abstract Alfalfa ( Medicago sativa L.) semi‐hybrids of genetically distant material may display heterosis, but their agronomic value is hardly known. Our study evaluated two two‐way and one three‐way semi‐hybrids and two synthetic varieties for 3‐year herbage dry‐matter yield (DMY) in four agricultural environments of Northern Italy formed by the factorial combination of irrigated or rain‐fed cropping by pure stand (PS) or mixed stand (MS) with vigorous grasses to verify (1) the yield advantage of semi‐hybrid material and (2) the ability of a phenotyping platform with eight managed environments used in a prior study to reproduce the population adaptive responses in agricultural environments. The semi‐hybrids derived from putative heterotic populations selected from Italian germplasm, Egyptian germplasm, and a semi‐erect pool from Eastern Europe, Canada, and Spanish Mielga germplasm. The three‐way semi‐hybrid showed wide adaptation and over 17% greater DMY than a variety selected from the Italian genetic base (set as a reference for synthetic variety breeding). The two‐way semi‐hybrids showed specific adaptation to the irrigated MS environment (where alfalfa was outcompeted) or PS environments that agreed with features of their exotic parent population, and over 19% greater yield than the reference synthetic variety in the environments where they were specifically adapted. The phenotyping platform reproduced largely the population × environment interaction effects across agricultural environments.
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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 | 0.000 | 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 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".