Cover crop potential of pea lines derived from crosses with nodulation mutants
Bibliographic record
Abstract
Abstract Over the past century, numerous studies have addressed the physiology and genetics of biological nitrogen fixation (BNF) in legumes—targeting improvements through screening of existing germplasm, hybridization, and mutagenesis. Although these efforts have not been successful in commercializing grain pea ( Pisum sativum ) varieties with enhanced BNF, they offer promising avenues for improving pea BNF for forage and cover crop (CC) cultivation. To examine this approach, we tested the performance of a panel of 20 pea lines derived from crosses between high‐yielding pea cultivars and two supernodulated pea mutants, Frisson‐ Sym29 and Rondo‐ nod3 . The pea lines, parents, and mutant checks were trialed during the 2020 and 2021 growing seasons in Chico, CA, under rainfed conditions. Nodulation, the percent of nitrogen derived from the atmosphere (%Ndfa), biomass and nitrogen accumulation, and days to flowering of progenies were compared to their parent varieties and mutant donors. Overall, tested materials performed similarly in both study years. The pea produced an average dry biomass of 1694 kg in 2020 and 1964 kg in 2021 while accumulating 53.3 kg N ha −1 in 2020 and 57.1 kg N ha −1 in 2021. The materials produced up to 120 and 126 nodules plant −1 , weighing 126 and 217 mg plant −1 , in 2020 and 2021, respectively. Genotypic variations for agronomic and N‐fixation traits were mainly associated with variations of parent cultivars and mutants. This study suggests that screening nodulation and aboveground and belowground biomass at pre‐commercial breeding stages might yield effective CC varieties compared to screening solely for %Ndfa and grain yield.
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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 | 0.000 |
| 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) | 0.001 | 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".