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Record W6959948338 · doi:10.1139/cjps2011-189

Seeding depth and seeding speed effects on no-till canola emergence, maturity, yield and seed quality

2012· article· en· W6959948338 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLeaf Properties and Growth Measurement
Canadian institutionsnot available
Fundersnot available
KeywordsSeedingCanolaYield (engineering)CultivarSemisSowingPrecipitation

Abstract

fetched live from OpenAlex

Harker, K. N., O'Donovan, J. T., Blackshaw, R. E., Johnson, E. N., Lafond, G. P. and May, W. E. 2012. Seeding depth and seeding speed effects on no-till canola emergence, maturity, yield and seed quality. Can. J. Plant Sci. 92: 795-802. Canola seed costs are substantial, but only a relatively small proportion of planted seeds actually emerge as seedlings. Direct-seeded (no-till) experiments were conducted from 2008 to 2010 at four western Canada locations [Lacombe AB (2007-2010), Lethbridge AB, Indian Head SK, and Scott SK] to determine the influence of cultivar (hybrid vs. open-pollinated), seeding speed (6.4 vs. 11.2 k h-1), and seeding depth (1 vs. 4 cm) on the emergence, maturity, yield, and seed quality of glyphosate-resistant canola. Canola emergence density was positively associated with precipitation levels surrounding the time of seeding; other site and environmental predictors such as soil temperature, soil texture, soil organic matter, latitude and longitude did not consistently influence canola emergence density. The agronomic performance of hybrid canola, including seed yield and quality, was usually superior to open-pollinated canola, but there was no difference in emergence density between the two cultivars. However, the hybrid cultivar emerged 1 d earlier, grew faster and covered the ground more quickly than the open-pollinated cultivar; important results from a crop-weed competition standpoint. Although seeding depth did not influence average canola yield, it often had a major impact on canola emergence density. Under moist conditions, average canola emergence improved from 37 to 62% as seeding depth decreased from 4 to 1 cm, respectively. Seeding at a depth of 1 vs. 4 cm also decreased days to emergence, increased canola ground cover, decreased days to flowering and days to maturity and tended to decrease green seed levels. Relatively high canola emergence rates can reduce the need for additional herbicide applications, herbicide input costs and selection pressure for herbicide resistance. Relatively high canola stand densities can improve the ability of canola to successfully tolerate and accommodate biotic and abiotic stress.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.632

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 studies0.0010.000
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 head0.400
GPT teacher head0.260
Teacher spread0.140 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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