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Record W2914010966

Effect of forage legumes on phosphorus availability to the following wheat crop in a Black Chernozem

2013· article· en· W2914010966 on OpenAlexfundaboutno aff
M. Rehmut, J.J. Schoenau, P. G. Jefferson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
FundersMinistry of Agriculture - Saskatchewan
KeywordsChernozemAgronomyForagePhosphorusCropEnvironmental scienceAgroforestryBiologySoil waterChemistrySoil science
DOInot available

Abstract

fetched live from OpenAlex

Including forage legumes in rotation with annual crops could increase phosphorus (P) availability to the annual crop due to their deep roots and intensive mycorrhizal infection. However, the benefit of forage legumes to increase soil P availability to the subsequent crop has gained less attention in the western Canada. The aim of this study was to investigate the impact of short rotation forage legumes on P availability to the following crop. Forage legumes evaluated in this study were red clover and alfalfa in comparison to an annual legume (pea) and non-legume (flax). The study was conducted at four sites across Saskatchewan. This poster reports on the results at one site near Melfort, SK. In this experiment, two-year alfalfa rotation produced the highest (P = 0.015) biomass yield. Inclusion of short rotation forage legumes had positive impact on wheat grain yield (P < 0.001) , but it did not affect wheat straw P uptake (P = 0.76). The amounts of soil P fractions extracted from all treatments were generally similar. The results suggested that a two year rotation of legumes may be too short a time period to significantly enhance in soil P availability to the following crop.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.230
Teacher spread0.219 · 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.

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

Citations1
Published2013
Admission routes2
Has abstractyes

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