Morphophysiology of ‘Faga 11’ Cashew Rootstock Under Saline Water Irrigation and Exogenous Proline Application
Bibliographic record
Abstract
Due to the reduced availability of good-quality water in the semi-arid region of Northeast Brazil, the utilization of saline waters in irrigation became an alternative for the expansion of agriculture in this region. Thus, it is necessary to develop techniques which can make viable the use of these waters in agriculture. Given the above, this study aimed to evaluate the morphophysiology of ‘FAGA 11’ cashew rootstock subjected to different levels of irrigation water salinity and exogenous proline application through the leaves. The experiment was carried out in a greenhouse of the Federal University of Campina Grande, at the Center of Sciences and Agri-Food Technology, Campus of Pombal, PB, Brazil, in a randomized block design, in 5 × 4 factorial scheme, with three replicates and two plants per plot. Treatments consisted of different levels of irrigation water electrical conductivity—ECw (0.3; 1.0; 1.7; 2.4 and 3.1 dS m-1) combined with proline concentrations applied through the leaves—PC (0; 4; 8 and 12 mM). Irrigations with water up to ECw of 1.37 dS m-1 may be used as it causes an acceptable 10% reduction in the variables of morphology of cashew FAGA 11 seedlings. The proline concentrations tested, with the exception of the Dickson’s quality index of seedlings, did not attenuate the deleterious effects of irrigation water salinity on the cashew FAGA 11 rootstock seedlings.
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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 | 0.001 |
| 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".