MétaCan
Menu
Back to cohort
Record W2397865002 · doi:10.1139/cjss-2015-0134

Corn yield components response to nitrogen fertilizer as a function of soil texture

2016· article· en· W2397865002 on OpenAlexafffundvenueabout
Athyna N. Cambouris, Noura Ziadi, Isabelle Perron, Khaled D. Alotaibi, Mervin St. Luce, Nicolas Tremblay

Bibliographic record

VenueCanadian Journal of Soil Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsLoamSoil textureAgronomyNitrogenFertilizerLeaching (pedology)Yield (engineering)ChemistrySoil waterEnvironmental scienceSoil scienceBiologyMaterials science

Abstract

fetched live from OpenAlex

Information on how soil texture and related soil properties affect corn (Zea mays L.) nitrogen (N) response is needed to improve N management in corn production. We conducted a study at 12-site yr in Quebec to assess the effect of N rate (0–250 kg N ha −1 ) and soil surface textural groups [clay, loam, sandy belonging to the gleysolic soil order (Sg), and sandy belonging to the podzolic soil order (Sp)] on corn grain yield, stover yield, total N uptake (TNU), nitrogen uptake efficiency (NUE), thousand kernel weight (TKW), test weight, and chlorophyll meter readings (CMR). Corn was more responsive to N rate in the clay soil textural group for most of the parameters due to lower soil N supply, and least responsive in the Sp group, except for test weight and CMR, due to possibly greater leaching in this group. The CMR at flowering accounted for 87%, 87%, 82%, and 25% of the variation in grain yield, TNU, TKW, and test weight, respectively. This study suggests that soil surface texture has a major influence on corn N response, but other soil properties such as drainage may also be important.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.220
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

Citations46
Published2016
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Soil ScienceSame topicCrop Yield and Soil FertilityFrench-language works237,207