Biochar Amendment Modifies Expression of Soybean and Rhizoctonia solani Genes Leading to Increased Severity of Rhizoctonia Foliar Blight
Bibliographic record
Abstract
Application of biochar, a pyrolyzed biomass from organic sources, to agricultural soils is considered a promising strategy to sustain soil fertility leading to increased plant productivity. It is also known that applications of biochar to soilless potting substrates and to soil increases resistance of plants against diseases, but also bear the potential to have inconsistent and contradictory results depending on the type of biochar feedstock and application rate. The following study examined the effect of biochar produced from maple bark on soybean resistance against Rhizoctonia foliar blight (RFB) disease caused by Rhizoctonia solani, and examined the underlying molecular responses of both soybean and R. solani during interaction with biochar application. Soybean plants were grown in the presence of 1%, 3% or 5% (w/w) or absence of maple bark biochar for two weeks, and leaves were infected with R. solani AG1-IA. At lower concentrations (1% and 3%), biochar was ineffective against RFB, however at the 5% amendment rate, biochar was conducive to RFB with significant increase in disease severity. For the first time, soybean and R. solani responsive genes were monitored during the development of RFB on detached leaves of plants grown in the absence and presence of 5% biochar at 0, 6, 12 and 24 hours post-inoculation (h.p.i.). Generally, large decreases in soybean transcript abundances of genes associated with primary metabolism such as glycolysis, tricarboxylic acid (TCA) cycle, starch, amino acid and glutathione metabolism together with genes associated with plant defense and immunity such as salicylic acid and jasmonic acid pathways were observed after exposure of soybean to high concentration of biochar. Such genes are critical for plant protection against biotic and abiotic stresses. The general down-regulation of soybean genes was tightly linked with an increased susceptibility to RFB. In conjunction, R. solani genes associated with carbohydrate metabolism were up-regulated, while genes involved in redox reactions and detoxification had varying effects. In conclusion, this study presents strong evidence that maple bark biochar increased susceptibility of soybean to a foliar disease. This condition is partly mediated by the down-regulation of soybean genes leading to reduced immunity and also affecting R. solani
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".