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Record W4211218708 · doi:10.1002/agj2.21033

Agronomic and economic performance of 26‐year corn–soybean rotation affected by tillage and fertilization in eastern Canada

2022· article· en· W4211218708 on OpenAlexafffundabout
Bernard Gagnon, Nomena Ravelojaona, Mervin St. Luce, Noura Ziadi

Bibliographic record

VenueAgronomy Journal · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsTillagePloughAgronomyHuman fertilizationLoamCrop rotationYield (engineering)Conventional tillageNo-till farmingGrain yieldField experimentMathematicsEnvironmental scienceSoil waterCropBiologySoil fertilitySoil sciencePhysics

Abstract

fetched live from OpenAlex

Abstract Adoption of conservation practices such as no‐tillage (NT) may benefit soil properties and related yields. However, magnitude of changes is dependent upon time scale, soil characteristics, and climatic conditions, which has received little attention in eastern Canada. A 26‐yr field experiment was conducted on a clay loam soil at L'Acadie, southwestern Quebec, to evaluate the effect of NT vs. moldboard plow (MP) and mineral N (0, 80, and 160 kg N ha –1 ) and P (0, 17.5, and 35 kg P ha –1 ) fertilization on grain yields, soil properties, and annual net returns of a corn ( Zea mays L.)–soybean [ Glycine max (L.) Merr.] rotation. Tillage was performed every year, while fertilizers were only applied to the corn phase. Throughout the years, the site responded well to N fertilization but not consistently to P. Tillage system did not affect corn grain yield in the first 10 yr, but yield gradually declined under NT and produced 2.3 Mg ha –1 less than MP with recommended N rate in the last 8 yr. By contrast, NT reduced soybean yield in the first decade (0.32 Mg ha −1 ) but not thereafter. After 24 yr of implementation, NT largely increased organic matter and Mehlich‐3 P and K in the 0‐to‐5‐cm surface layer, but this did not translate into higher yields. Compared with NT, MP achieved CAN$200 ha –1 more revenue during last years at recommended N rate despite higher operation costs. Results demonstrated that under northern latitudes, this clay soil was not appropriate for NT.

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 score0.105
Threshold uncertainty score0.974

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 head0.006
GPT teacher head0.170
Teacher spread0.164 · 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

Citations8
Published2022
Admission routes3
Has abstractyes

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