Microbial communities and soil chemical features associated with commercial production of the medicinal mushroom Ganoderma lingzhi in soil
Bibliographic record
Abstract
Crop production, including mushroom farming, may cause significant changes to the underlying substrates which in turn, can influence crop quality and quantity during subsequent years. Here in this study, we analyzed the production of the medicinal mushroom Ganoderma lingzhi and the associated soil microbial communities and soil chemical features over 24 months from April 2015 to April 2017. This Basidiomycete mushroom, known as Lingzhi in China, is commonly found on dead trees and wood logs in temperate and subtropical forests. Its economic and medicinal importance have propelled the development of a diversity of cultivation methods. The dominant method uses wood logs as the main substrate, which after colonization by Lingzhi mycelia, are buried in the soil to induce fruiting. The soil microbial communities over the 24 months were analyzed using the Illumina HiSeq platform targeting a portion of the bacterial 16S rRNA gene and the fungal internal transcribed spacer 1 (ITS1). Overall, a significant reduction of Lingzhi yield was observed over our experimentation period. Interestingly, temporal changes in soil microbial compositions were detected during the 24 months, with the fungal community showing more changes than that of bacteria in terms of both species richness and the relative abundance of several dominant species after each fruiting. The soil chemical features also showed significant changes, with decreasing soil nitrogen and phosphorus concentrations and increasing soil pH and iron content after each fruiting. We discuss the implications of our results in sustainable Lingzhi production in soil.
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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 | 0.001 |
| 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".