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Record W2056255117 · doi:10.2134/agronj2009.0057

Barley Yield and Nutrient Uptake for Soil Amended with Fresh and Composted Cattle Manure

2009· article· en· W2056255117 on OpenAlexaffabout
J.J. Miller, Bruce Beasley, C. F. Drury, Bernie J. Zebarth

Bibliographic record

VenueAgronomy Journal · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsStrawAgronomyHordeum vulgareManureSilageLoamDry matterFertilizerNutrientAnimal sciencePhosphorusChemistryEnvironmental sciencePoaceaeBiologySoil water

Abstract

fetched live from OpenAlex

Limited research exists on the long‐term effect of fresh (FM) versus composted manure (CM) from beef cattle on barley ( Hordeum vulgare L.) yield and nutrient uptake. Barley was grown (1999–2007) as silage on an irrigated clay loam soil in southern Alberta where organic amendments and fertilizer were annually applied for 9 yr in the fall of 1998 to 2006. The treatments were three rates (13, 39, 77 Mg ha −1 dry wt.) of FM or CM containing either straw or wood‐chip bedding, one inorganic fertilizer treatment, and a nonfertilized control. Nine years of annual application of FM and CM resulted in similar aboveground dry matter yield, and total N and total P uptake compared with inorganic fertilizer. However, apparent nitrogen recovery (ANR) and phosphorus recovery (APR) were significantly lower for FM and CM (5–9%) than inorganic (22–47%). Barley dry matter yield, ANR, and APR were similar for FM and CM. Manure type influenced N and P uptake, but the effects varied with bedding type and year. The N and P uptake were greater for CM with straw than the other three treatments except FM with straw. The DM yield was similar for straw and wood bedding, but ANR was greater for straw (10%) than wood (7%). Bedding influenced N uptake, P uptake, and APR, but the effects varied with manure type, rate, and year. Based on the results of this study, producers converting from FM to CM, or from straw to wood‐chip bedding, should suffer no loss in barley silage production.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.375

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 head0.196
Teacher spread0.188 · 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

Citations65
Published2009
Admission routes2
Has abstractyes

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