Niche differentiation modulates metabolites abundance and composition in silicon fertilizer amended soil during sugarcane growth
Bibliographic record
Abstract
BACKGROUND: As one of the vital crops globally, sugarcane (Saccharum officinarum L.) has been one of model crops for conducting metabolome research. Although many studies have focused on understanding bioactive components in specific sugarcane tissues, crucial questions have been left unanswered about the response of metabolites to niche differentiation such as different sugarcane tissues (leaf, stem and root), and soil regions (rhizosphere and bulk) under silicon (Si) amended soils. Here, nontargeted metabolite profiling method was leveraged to assess the similarities and differences in the abundance and community composition of metabolites in the different sugarcane and soil compartments. Identify the compartment-specific expression patterns of metabolites, and their association with cane agronomic traits and edaphic factors. We also investigated the response of sugarcane agronomic traits and edaphic factors to Si amended soil. RESULTS: We found that Si fertilizer exhibited the advantages of overwhelmingly promoting the height and theoretical production of cane, and profoundly increased soil Si content by 24.8 and 27.0%, while soil available potassium (AK) was enhanced by 3.07 and 2.67 folds in the bulk and rhizosphere soils, respectively. It was also noticed that available phosphorus (AP) in the rhizosphere soil tremendously increased by 105.5%. We detected 339 metabolites in 30 samples using LC-MS/MS analyses, 161 of which were classified and annotated, including organooxygen compounds (19.9%), carboxylic acids and derivatives (15.5%), fatty acyls (15.5%), flavonoids (4.4%), phenols (4.4%), and benzene and substituted derivatives (3.7%). In addition, the total percentages covered by these core metabolites in each compartment ranged from 94.0% (bulk soil) to 93.4% (rhizosphere soil), followed by 87.4% (leaf), 81.0% (root) and 80.5% (stem), suggesting that these bioactive compounds may have migrated from the belowground tissues and gradually filtered in various aboveground niches of the plant. We also observed that the variations and enrichment of metabolites abundance and community were compartment-specific. Furthermore, some key bioactive compounds were markedly associated with plant growth parameters and soil edaphic. CONCLUSION: Taken together, we hypothesized that Si utilization can exhibit the advantage of enhancing edaphic factors and cane agronomic traits, and variations in metabolites community are tissue-specific.
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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".