Impact of foliar silicon application on yield attributes of wheat (Triticum aestivum L.) under water deficit environment
Bibliographic record
Abstract
The consequences of climate change, particularly in the form of water deficiency are now evident in different parts of the world that negatively affecting the crop productivity. The current study was conducted to explore the involvement of exogenously applied silicon in reducing the negative effects of drought stress on yield of wheat. The wheat cultivar “Faisalabad- 08” was subjected to two water regimes (normal irrigation and no irrigation) and four levels of silicon including no spray, 0, 0.01 and 0.1 mM. All the silicon levels were applied at three different stages of wheat growth. The sources of the silicon used in the current experiment were sodium silicate, potassium silicate and silicic acid. At maturity of crop different yield parameters (number of tiller per plant, number of spike per plant, number of spikelet per plant, spike length, number of grain per plant, number of grain per spike, number of grain per spikelet, single grain weight and yield per hector) were recorded. The results indicated that the yields of related attributes were significantly reduced under water deficit environment. The application of silicon from the two different sources sodium silicate and potassium silicate was more beneficial to alleviate the negative effects of water deficit on wheat yield. Sodium silicate (0.01 and 0.1 mM) and potassium silicate (0.1 mM) were found more beneficial for enhancing wheat yield under water stress to enhance wheat productivity.
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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 | 0.001 | 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".