The Study of Selenium Fertilizer on the Growth of Xiangzayou 787 and Related Molecular Mechanism
Bibliographic record
Abstract
Rapeseed is the largest self-produced oil crop in China which plays an important role in ensuring the safety of edible oil. However, its current per unit yield is far below Canada and Europe. In this study, selenium fertilizer and other micro fertilizers were sprayed on Xiangzayou 787 at the seedling stage. The results showed that the yield per plant increased 24.3% with sprayed selenium compared to the control (CK). Compared with the CK, the chlorophyll content in leaves at the flowering stage was significantly increased by 20.8%, and the soluble sugar content in the silique wall and seeds at the maturity stage was significantly increased and increased by 62.1% during the budding stage. The functional leaves of Xiangzayou 787 with the sprayed selenium fertilizer and the CK were used as raw materials for absolute quantitative transcriptome sequencing analysis. Accompanied with bioinformatics analysis, six differential genes which affect growth were discovered. The expression level of the protein phosphatase 2C gene in the silique wall was significantly higher than that of the CK. The PP2C78 gene was significantly positively correlated with the chlorophyll and soluble sugar content in leaves and the correlation coefficients were 0.539 and 0.547. According to gene expression levels, yield, and physiological indicators, PP2C78 may be a key functional gene affecting rapeseed yield. In this study, selenium fertilizer was found to be an excellent foliar fertilizer for rapeseed; the PP2C78 gene may be helpful for analyzing the yield increasing mechanism and used as a reference for screening new foliar fertilizers.
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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 | 0.001 | 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".