MétaCan
Menu
Back to cohort

The Impact of Wheat Growth Stages on Soil Microbial Communities in a Rain-Fed Agroecosystem

2025· article· en· W4409329200 on OpenAlexaff
Yosef Steinberger, May Levi, Itaii Applebaum, Chen Sherman, Tirza Doniger, Adrian Unc

Bibliographic record

VenueMicroorganisms · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAgroecosystemAgronomyBiomass (ecology)RhizospherePhenologyEcosystemBiologyAbiotic componentSubstrate (aquarium)AgricultureBacteriaEcology

Abstract

fetched live from OpenAlex

Wheat is the largest terrestrial agricultural crop globally. This study was conducted to determine the soil microbial biomass, soil CO2 evolution, and physiological profile in the rhizosphere of the winter wheat rain-fed Triticum aestivum along the development stages in a rain-fed semi-arid agro-ecosystem. The data show that a significant, over 100-fold increase in the utilization of four substrate groups (benzoic acid, amino acid, carbohydrates, and carboxylic acid) occurred in the wheat soil rhizosphere along the wheat growth phenology. After the stubble field stage, there was a notable decrease in the utilization of all four substrates. The occurrence of each substrate in the soil aligns with the below-ground rhythm of wheat plant biomass growth. The abundance of fine roots, categorizing wheat plant roots, in the soil at maturity and the stubble field stage may explain the heightened activity and diversity of copiotroph bacteria. This association suggests a potential link between the richness of fine roots and the increased activity and diversity of copiotroph bacteria in the soil. The findings clarify the impact of constraining abiotic factors, coupled with the phenological influences of wheat plants, and their combined effects on substrate utilization by microbial communities in a rain-fed Triticum aestivum wheat field.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.223
Teacher spread0.213 · 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 designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueMicroorganismsSame topicSoil Carbon and Nitrogen DynamicsFrench-language works237,207