Physiological Indices and Growth of Castor Bean Irrigated With Waters of Different Cationic Nature
Bibliographic record
Abstract
It was proposed, in the present study, to evaluate the gas exchange and the growth of the castor bean cv. BRS Energia due to the isolated or mixed cationic nature of irrigation water. The study was conducted in drainage lysimeters under greenhouse conditions, using an Eutrophic Greyish Argissolo with a sandy-loam texture in the municipality of Campina Grande, Brazil. A randomized block design was used with six cationic composition of irrigation water (S1-control, S2-Na+, S3-Ca2+, S4-Na++Ca2+, S5-K+ and S6-Na++Ca2++Mg2+ with four replicates, each composed of five plants. The plants under the control treatment were submitted to irrigation with low salinity water (ECw = 0.6 dS m-1) and the remaining treatments were irrigated with ECw of 4.5 dS m-1 prepared with salts of different cations in chloride form. The gas exchanges and the growth of the castor bean cv. BRS Energy were determined at 100 days after sowing. The gas exchanges and the growth of the castor cv. BRS Energy were more sensitive to the variation in the electrical conductivity of the water compared to the cationic nature of the water, being the least deleterious effect observed in the plants irrigated with potassic water. The plants irrigated with water of potassium composition obtained the highest values for stomatal conductance, transpiration and rate of assimilation of CO2; at 100 days after sowing; the castor bean cv. BRS Energia showed sensitivity to the presence of sodium and calcium salts in irrigation water.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".