Evaluation of Some Biochemical Responses in Resistance of Fifteen Bread Wheat (Triticum aestivum L.) Genotypes to Wheat streak mosaic virus
Bibliographic record
Abstract
Two greenhouse experiments were conducted in 2008-2010 at College of Agriculture, Shiraz University, Iran to evaluate the effectiveness of changes in protein content, peroxidase activity, phenolic compounds, free amino acids content and proline in response to wheat streak mosaic virus (WSMV) infection, in screening resistant bread wheat (Triticum aestivum L.) genotypes. Fifteen wheat genotypes consisting of WSMV tolerant, intermediate and susceptible genotypes were grown in two randomized complete designs with three replications. The experiments only differed with respect to their inoculation (either infected or non-infected). The results indicated that viral infection increased the total protein and peroxidase activity of leaves in tolerant genotypes but viral infection decreased them in susceptible genotypes. Phenolic compounds increased in all infected genotypes but these increases are the highest in tolerant genotypes as compared to intermediate and susceptible ones. Viral infection reduced free amino acids in genotypes in general. The changes in proline content did not show a typical trend in tolerant, intermediate or susceptible genotypes. The analysis of variance indicated that the linear regression of leaf damage rating on the changes in total protein, peroxidase activity and phenols in the leaf was significant but the linear regression of leaf damage rating on the changes in free amino acids and proline in the leaf was not significant. Our results demonstrate the changes in total protein, peroxidase activity and phenolic compounds in a genotype could be used as suitable biochemical markers for assessing the WSMV tolerant wheat plants when grown under infected condition.
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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) | 0.000 | 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".