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Record W2098947552 · doi:10.5539/jas.v4n9p126

Nitrogen Immobilization by Congo Grass Roots Impairs Cotton Initial Growth

2012· article· en· W2098947552 on OpenAlexvenueno aff
Ciro Antônio Rosolem, Fábio Steiner, Samuel Menegatti Zoca, Carlos Ducatti

Bibliographic record

VenueJournal of Agricultural Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAgronomyCongo redStrawShootBrachiariaNitrogenAmmoniumChemistryBiologyForage

Abstract

fetched live from OpenAlex

In crop-livestock integration systems the presence of both grass roots in the soil and straw on the surface can temporarily immobilize nitrogen. This study examined the persistence of grass residues in the system as well as their effects on cotton response to N when grown after Congo grass (Brachiaria ruziziensis, Syn. Urochloa ruziziensis). Congo grass was grown in pots with soil. Next, cotton was grown in the same pots without residues, with whole plant residues (Congo grass roots and shoots) or root residues (grass roots) and fertilized with N as ammonium nitrate. Congo grass and cotton roots were separated using stable carbon isotope fractioning. Congo grass roots showed higher C/N ratio than shoots, losing 14% of its mass after 45 days and increasing soil N immobilization. The lower N availability resulted in N deficient and shorter cotton plants with lower dry matter yields. Nevertheless, the application of 80 to 120 mg kg-1 of N compensated the immobilization by the soil microorganisms, allowing cotton to show normal growth. When Congo grass is present in the cropping system, the effects of the decaying roots on soil N dynamics and availability are more important than those of the straw left on the soil surface.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.242

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 communication0.0000.002
Open science0.0010.000
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 head0.232
Teacher spread0.221 · 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

Citations16
Published2012
Admission routes1
Has abstractyes

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