New genetic resources for aphid resistance were identified from a newly developed wheat mutant library
Bibliographic record
Abstract
Reports on development of resilient wheat mutants to aphid infestation—causing heavy losses to wheat production in many parts of the world, are scanty. The present study aimed to identify genetic diversity of wheat mutants in terms of varying degree of resistance to aphid infestation which can help protect wheat crop, improve yields and enhance food security. Resistance response to aphid infestation was studied on newly developed 33 wheat mutants, developed through irradiating seed of an elite wheat cultivar "Punjab-11" with gamma radiations, during three normal growing seasons at two sites. Data on various traits including aphid count per plant, biochemical traits, physiological traits and grain yield was recorded. Meteorological data was also collected to unravel the impact of environmental conditions on aphid infestation on wheat plants. Minimum average aphid infestation was found on Pb- M -2725, Pb- M -2550, and Pb- M -2719 as compared to the wild type. High yielding mutants Pb- M -1323, Pb- M -59, and Pb- M -1272 supported the moderate aphid infestation. The prevailing temperature up to 25 °C showed positive correlation (0.25) with aphid count. Among biochemical traits, POD (0.34), TSP (0.33), TFA (0.324) exhibited a high positive correlation with aphid count. In addition, CAT (0.31), TSS (0.294), and proline content (0.293) also showed a positive correlation with aphid count. However, all physiological traits depicted negative correlation with aphid count, while, a very weak correlation (0.12) was found between mean aphid count and grain yield. In PCA biplots, the biochemical variables clustered together with aphid count, while physiological variables grouped with grain yield. Biochemical parameters contributed most, towards first dimension of the PCA (48.6%) as compared to the physiological variables (13%). The FAMD revealed that mutant lines were major contributor towards total variation; Pb- M -1027, Pb- M -1323, Pb- M -59 were found to be the most diverse lines. The PCA revealed that biochemical parameters played a significant role in explaining variations in aphid resistance, emphasizing their importance in aphid defense mechanisms. The identified mutants can be utilized by the international wheat community for getting insight into the molecular circuits of resistant mechanism against aphids as well as for designing new KASP markers. This study also highlights the importance of considering both genetic and environmental factors in the development of resilient wheat varieties and pave the way for further investigations into the molecular mechanisms underpinning aphid resistance in wheat.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".