Photosynthetic Pigments and Photochemical Efficiency in Soursop under Saline Water Irrigation and Nitrogen Sources
Bibliographic record
Abstract
The Studies have shown that nitrogen fertilization can mitigate the effects of saline stress on plants, however, the efficiency may vary according to the source of nitrogen used, specifically on the photosynthetic activity. In this context, the objective of this work was to evaluate the effect of different nitrogen sources on photosynthetic pigments and photochemical efficiency in soursop plants irrigated with distinct salinities. A randomized complete block design was used in a 4 × 4 factorial scheme, with the treatments corresponding to four levels of irrigation water salinity - ECw (0.5, 1.5, 2.5 and 3.5 dS m-1) and four sources of nitrogen (urea, ammonium sulfate, calcium nitrate and potassium nitrate), with three replications. The irrigation with saline water from 0.5 dS m-1 inhibits the concentration of photosynthetic pigments and promotes damages in the photochemical efficiency of photosynthesis at 110 days after transplanting. The different sources of nitrogen do not cause changes in the levels of photosynthetic pigments, however, the fertilization with potassium nitrate mitigates the effect of saline stress on the photochemical efficiency, mainly in the water salinity of 3.5 dS m-1.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".