Evaluating Growth and Yield Parameters of Five Quinoa (Chenopodium quinoa W.) Genotypes Under Different Salt Stress Conditions
Bibliographic record
Abstract
Soil salinization is a global problem which restricts the choice of crop for cultivation. Management and reclamation of salinity using costly techniques may not be affordable by subsistence farmers. Therefore, it is important to look for new alternate crops like “quinoa” which are more salt-tolerant. As crops vary in their tolerance to salinity, they need to be evaluated for different salinity conditions. This study was conducted to evaluate five quinoa (Chenopodium quinoa W.) genotypes (ICBA-Q1, ICBA-Q2), ICBA-Q3, ICBA-Q4 and ICBA-Q5) for salinity tolerance under four artificially induced salinity (5, 10, 15, 20 dS m-1) levels. The pot trials were conducted in a greenhouse, using 6 kg of Fluvisol soil in each pot. For comparison, trials were also conducted under field conditions. The parameters studied were rate of seed germination, plant height, fresh and dry biomass, chlorophyll content and grain yield. As expected, salinity had generally an inhibitory effect on all parameters. Out of the five quinoa varieties (ICBA-Q1 to ICBA-Q5), ICBA-Q3 and ICBA-Q4 proved to be more salt-tolerant. Therefore these two genotypes are recommended to farmers for large-scale adaptation.
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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".