Physiological Responses of Cowpea (Vigna unguiculata) Under Irrigation With Saline Water and Biostimulant Treatment
Bibliographic record
Abstract
Cowpea (Vigna unguiculata) is one of the world’s main crops, and it is a fundamental source of protein for semiarid regions population. In these regions, the use of high salts concentration water in irrigation systems is one of the major factors that contributes to reduced cowpea yield. One way to alleviate the negative effects of salinity is through the biostimulants application, which is a product that has beneficial substances to the plants metabolism. The aim of this study was to evaluate the application of biostimulant in cowpea cultivars under irrigation with saline water. The study was carried out in the Agrarian Sciences Center, of the Department of Agronomic and Forest Sciences of the Federal Rural University of the Semi-Arid, in the city of Mossoró, RN. The experimental design was completely randomized, with four replications. The treatments were arranged in 5 × 2 × 2 factorial scheme, with five doses of biostimulant (0, 15, 30, 45 and 60 mL L-1), two electrical conductivities of the irrigation water (0.5 and 5.0 dS m-1), and two cowpea cultivars (IPA-206 and BRS Guariba). The evaluated characteristics were: chlorophyll content index, stomatal conductance, net photosynthesis, internal CO2 concentration, transpiration rate, shoot height, stem diameter and shoot dry mass. The biostimulant application was not efficient in attenuating the salinity stress effect on the development of cowpea cultivars. The higher biostimulant concentrations along with the use of saline water increased the negative effects of salinity on the cowpea plants physiology. There was no difference between the cultivars regarding the tolerance to saline stress and the application of biostimulant.
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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".