Summer Rice–Winter Potato Rotation Suppresses Various Soil-Borne Plant Fungal Pathogens
Bibliographic record
Abstract
Growing potatoes (Solanum tuberosum) using the idle rice fields in Southern China and the Indo-Gangetic Plains of India in the winter season through the rice–potato rotation (RC) system could support future food security. However, the modulation capacity of the RC system on soilborne fungal pathogens is still unclear. In the current study, a pot experiment was designed and conducted to monitor the dynamics of soil fungal community composition between the potato monoculture (CC) system and the RC system, where the two systems were set with the same soil conditions: autoclaving with fertilization; autoclaving without fertilization; autoclave-free with fertilization; and autoclave-free without fertilization. Then, the uncultivated soil (CK) and root-zone soil samples of conditions under the two systems were collected, and then soil physiochemical properties and enzymatic activities were determined. Next, the high-variable region (V5–V7) of fungal 18S rRNA genes of the samples were amplified and sequenced through the PCR technique and the Illumina Miseq platform, respectively. Finally, the fungal species diversity and composition, as well as the relative abundance of fungal pathogens annotated against the Fungiuld database in soil samples, were also investigated. The results showed that the RC could significantly (p < 0.05) increase soil fungal species diversity and decrease the relative abundance of soil fungal pathogens, where the RC could suppress 23 soil fungal pathogens through cultivating the rice during the summer season and 93.75% of the remaining pathogens through winter-season cultivation. Seven-eighths of the conditions under RC have lower pathogenic MGIDI indices (6.38 to 7.82) than those of the CC (7.62 to 9.63). Notably, both rice cultivation and winter planting reduced the abundance of the pathogenic strain ASV24 under the Colletotrichum genus. The bipartite fungal network between the pathogens and the non-pathogens showed that the pathogenic members could be restricted through co-occurring with the non-pathogenic species and planting crops in the winter season. Finally, the redundancy analysis (RDA) indicated that soil pH, electronic conductivity, available phosphorus content, and various enzyme activities (cellulase, urease, sucrase, acid phosphatase, catalase, polyphenol oxidase) could be the indicators of soil fungal pathogens. This experiment demonstrated that the rice–potato rotation system outperformed the potato monoculture on suppressing soilborne fungal pathogenic community.
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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".