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Record W1998825457 · doi:10.4141/s02-045

Effect of rate, frequency and incorporation of feedlot cattle manure on soil nitrogen availability, crop performance and nitrogen use efficiency in east-central Saskatchewan

2004· article· en· W1998825457 on OpenAlexafffundvenueabout
S.P. Mooleki, J.J. Schoenau, J. Charles, Guosong Wen

Bibliographic record

VenueCanadian Journal of Soil Science · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsFeedlotAgronomyManureLoamCanolaHordeum vulgareEnvironmental scienceCropNitrogenFertilizerBeef cattleAnimal scienceBiologySoil waterPoaceaeChemistrySoil science

Abstract

fetched live from OpenAlex

A study was initiated in 1996 in the Black Soil zone in east-central Saskatchewan to examine soil and crop response to application of feedlot cattle manure at different application rates, frequencies and incorporation timing in a sandy loam and loam soil. Three rates of feedlot cattle manure (approx. 100, 200 and 400 kg total N ha -1 ) were applied annually and under reduced frequency application regimes. Canola (Brassica napus, L.), spring wheat (Triticum aestivum, L.), hulless barley (Hordeum vulgare, L.) and canola were seeded in spring of 1997, 1998, 1999 and 2000, respectively. Pre-seeding available N (0–60 cm) increased with application rates. Annual application resulted in a linear increase in grain yield with application rates but had no effect on grain N concentration. Cumulative N use efficiency was low (7–10%) with no significant difference among treatments. Single application showed significant residual fertility benefit in the second year but not in the third year except at the high rate. Incorporation timing of feedlot cattle manure had no impact on soil or crop performance. Low availability of N in feedlot cattle manure over the short-term suggests the need for high application rates or addition of supplemental N fertilizer in order to meet crop N requirements. Key words: Feedlot cattle manure, N availability, manure management, N use efficiency

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 score0.208
Threshold uncertainty score0.969

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 studies0.0000.001
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 head0.010
GPT teacher head0.197
Teacher spread0.187 · 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

Citations73
Published2004
Admission routes4
Has abstractyes

Explore more

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