Correlations and Path Analysis in Segregating Cowpea Generations Regarding Biological Nitrogen Fixation
Bibliographic record
Abstract
The objective of this research was to evaluate the correlations between variables related to the biological nitrogen fixation (BNF) in segregating generations of cowpea and to unfold these correlations in direct and indirect effects, through path analysis. An outdoor bench experiment was conducted at Carpina Experimental Sugarcane Station of, located at the Zona da Mata region of the State of the Pernambuco, Northeast of Brazil (Federal Rural University of Pernambuco), between March and April 2016. The seeds were planted in 20 cm × 30 cm polyethylene bags, using a substrate composed of a mixture of vermiculite and sand washed in a ratio of 1:1. Bradyrhizobium references, recommended for culture, were used as a mixture of two strains. Parental and F2, F3 and F4 generations were evaluated in a randomized block design with four replicates. Data collection was performed 45 days after the emergency (DAE). Phenotypic correlations and path analysis of the number of nodules per plant (NN), nodules dry mass (NDM), dry roots mass (DRM), dry mass of aerial part (DMAP), nodulation efficiency (NODE) and nitrogen accumulated in the aerial part (NAAP). The phenotypic correlations between the variables related to the BNF showed high magnitudes, demonstrating that there is a great influence of each of the variables on the others, furthermore the path analysis of the coefficients indicated that all the primary components (NN, NDM, DRM, DMAP and NODE) must be considered when it is desired to increase the NAAP in segregating generations of cowpea.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".