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Record W4353088457 · doi:10.3389/fmicb.2023.1138580

Effect of natural weed and Siratro cover crop on soil fungal diversity in a banana cropping system in southwestern China

2023· article· en· W4353088457 on OpenAlexaff
Wenlong Zhang, Paul H. Goodwin, Si-Jun Zheng, Xundong Li, Shengtao Xu

Bibliographic record

VenueFrontiers in Microbiology · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanana Cultivation and Research
Canadian institutionsUniversity of Guelph
FundersNational Natural Science Foundation of China
KeywordsCover cropBiologyAgronomyWeedIntercropping

Abstract

fetched live from OpenAlex

Introduction Natural weed cover and a legume cover crop were examined to determine if they could impact soil fungal diversity as an indicator of soil quality in banana production. Methods Banana in Yunnan Province, China, was grown under three treatments: conventional tillage (bare soil), natural weed cover (primarily goosegrass ( Eleusine indica (L.) Gaerth)), or a cover crop (Siratro ( Macroptilium atropurpureum (DC.) Urb.)). Analysis of the soil fungal communities between 2017 and 2020 was done by Illumina Miseq high-throughput sequencing. Results Most significant effects were in the intercropping area for the treatments, whereas it was rarely observed in the furrow planted with banana. Based on the Shannon and Simpson diversity indices, soil fungal diversity in the intercropping area significantly decreased following planting banana in 2017 with all three treatments. However, both the Shannon and Simpson diversity indices showed that there were significant increases in fungal soil diversity in 2019 and 2020 with natural weed cover or Siratro compared to bare soil. At the end of the experiment, significant increases in fungal genera with Siratro compared to bare soil were observed with Mortierella , Acremonium , Plectophaerella , Metarhizium and Acrocalymma , and significant decreases were observed with Fusicolla , Myrothecium , Exserohilum , Micropsalliota and Nigrospora . Siratro resulted in higher stability of the soil fungal microbiome by increasing the modularity and the proportion of negative co-occurrences compared to bare soil. For fungal guilds, Siratro significantly increased saprotrophs_symbiotrophs in 2019 and 2020 and significantly decreased pathogens_saprotrophs in 2020 compared to bare soil. Discussion Using Siratro as a cover crop in the intercropping area of banana helped maintain soil fungal diversity, which would be beneficial for soil health with more symbiotrophs and less pathogens in the soil. However, further research is needed to determine the long-term impact of weed or Siratro cover crop on the fungal soil ecosystem and growth of banana.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.222
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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