Biomass Accumulation and Growth of Common Bean Plants Under Water and Salt Stresses
Bibliographic record
Abstract
When it is said about quality and quantity of water supplied through irrigation, for common bean cultivation, it is considered sensitive to water and saline stress. The objective of this work was to evaluate the biomass accumulation and growth of common bean plants (Phaseolus vulgaris L.) subjected to irrigation with different water depths, using water with different electrical conductivities. The experiment was carried out in pots under a protected environment located in an experimental area of the Federal Institute of Goiás, Rio Verde Campus, in the city of Rio Verde, Goiás. The design was a randomized complete block design in a 4 × 2 factorial scheme with three replications. 25, 50, 75 and 100% of the evapotranspiration of the crop, and two types of electrical conductivity of irrigation water equal to 0.6 and 3.0 dS m-1. All variables were analyzed using the SISVAR® software, whose mean values for the electrical conductivity treatments were compared by Tukey test at 0.05% probability and water replacement by regression analysis, when significant. The use of irrigation water with electrical conductivity of 3 dS m-1 reduces plant height, number of green leaves and stem diameter at 35 days after sowing, thus reducing dry biomass accumulation and aerial part water accumulation at 20 and 70 days after sowing. The deleterious effects under the dry mass of the aerial part at 70 days after sowing, when using an electrical conductivity of 3 dS m-1, are accentuated by the increase of the water dephts.
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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) | 0.001 | 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".