Yield and Nutrient Uptake of Common Bean Cultivars as Affected by Plant Population and Growing Season
Bibliographic record
Abstract
Brazil’s production of common bean is insufficient to supply the domestic market. Factors such as plant density, cultivar, growing season, and nutrient uptake affect bean yield, suggesting the need for more studies to optimize bean production. The objective of this work was to evaluate the effect of plant density on seed yield components and nutrient uptake of two common bean cultivars grown in two different seasons. Field experiments were carried out at the IAPAR experimental site in Santa Tereza do Oeste, Paraná, Brazil in the wet and dry season using five planting densities: 6, 8, 10, 12, and 14 plants m-1. The experimental design was randomized blocks with four replications and two bean cultivars of different growth types. The cultivars used were ‘IPR Curió’ (type I) and ‘IPR Tangará’ (type II), both have erect plant architecture and belong to the Carioca group. Obtained data underwent analysis of variance and regression. Macronutrient uptake was not affected by crop density probably due to nutrient availability and compensatory growth of the crop. High crop density per linear meter decreased the number of seeds and pods per plant but did not affect the first pod height or yield in both cultivars and seasons.
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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".