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Record W3007060262 · doi:10.1002/agj2.20097

Damage to the primary root in response to cattle slurry placed near seed may compromise early growth of corn

2020· article· en· W3007060262 on OpenAlexaff
Ingeborg Frøsig Pedersen, Peter Sørensen, Khagendra Raj Baral, Gitte Holton Rubæk

Bibliographic record

VenueAgronomy Journal · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsUniversity of Guelph
FundersMiljø- og Fødevareministeriet
KeywordsAgronomySlurryBiologyRoot (linguistics)CompromiseEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Placement of cattle slurry below the row could potentially replace mineral phosphorus (P) starter fertilizer in corn ( Zea mays ) production, but a concentrated slurry layer near the seed may also restrict root growth. This study was designed to assess how the distance between seed and layer‐banded slurry affected initial growth of corn. In a pot experiment with corn on a coarse sandy soil, nitrogen‐labeled ( 15 N) cattle slurry was placed 1.5, 5, 8.5, or 12 cm below the seed, and responses on early root growth, shoot biomass, and nutrient uptake were studied. Soil chemical properties near the slurry band were determined in unplanted soil. Placement of slurry 1.5 cm below the seed damaged the primary root, which subsequently reduced shoot biomass and N uptake. Shoot P uptake remained unaffected by slurry placement depth. The 15 N assay revealed that plants were able to take up N from the slurry band despite damage to the primary root. The shoot biomass was higher in the inorganic N and P treatment than in the slurry treatments. Within a few centimeters above the slurry band, the soil was characterized by high moisture and high concentrations of ammonium and nitrite 21 and 35 d after slurry application, which may have caused the damages of the primary root. We conclude that placement of slurry near the seed can damage the primary root of corn. To prevent root injuries, banded slurry should be placed at least 5 cm below the seed.

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 score0.348
Threshold uncertainty score0.213

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)0.0000.000

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 head0.020
GPT teacher head0.216
Teacher spread0.196 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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