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Influence of residual manure on selected nutrient elements and microbial composition of soil under long-term crop rotation

2001· article· en· W2064591194 on OpenAlexfundno aff
Adane Fentaye Belay, A. S. Claassens, F. C. Wehner, J.M. Beér

Bibliographic record

VenueSouth African Journal of Plant and Soil · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
FundersDeutscher Akademischer AustauschdienstUniversity of PretoriaMcGill University
KeywordsCrop rotationManureAgronomyNutrientBiomass (ecology)CropEnvironmental scienceCrop yieldBiologyEcology

Abstract

fetched live from OpenAlex

A study was conducted on a long-term field experiment at the University of Pretoria, South Africa, that was established in 1939. The aim was to investigate the effects of residual manure on the characteristics of the total and microbial biomass and their nutrient contents in the soil and on maize yield under long-term crop rotation. It was found that total C, N and available P levels were increased as a result of manure application. Seasonally, these nutrients exhibited variations that appeared to be related to influences of crop rotation. Long-term soil N content in an adjacent native site remained relatively constant while it tended to increase in the control and manured plots. Soil microbial biomass content of C, N, and P and microbial populations were affected by previous manure application, as well as by crop rotation. The biomass and numbers of microflora were generally higher in the manured plots. Manure application also resulted in higher maize yields and had substantial residual effects. Relationships between the different soil properties considered and crop yield are presented and their implications discussed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.011
GPT teacher head0.205
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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

Citations113
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueSouth African Journal of Plant and SoilSame topicSoil Carbon and Nitrogen DynamicsFrench-language works237,207