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Record W2047425647 · doi:10.2298/hel0746199r

Rapeseed genetic research to improve its agronomic performance and seed quality

2007· article· en· W2047425647 on OpenAlexaffabout
G. Rakow, Relf-Eckstein J.A., Raney J.P.

Bibliographic record

VenueHelia · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNitrogen and Sulfur Effects on Brassica
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCanolaRapeseedBrassicaGermplasmBiologyAgronomyCropOil productionHorticulture

Abstract

fetched live from OpenAlex

Rapeseed (canola) is the major Canadian oilseed and average annual production was 6,871,600 metric t for the 10-year period 1996-2005. Brassica napus is the only species grown, and only summer annual forms are cultivated in the short season areas of the western Canadian prairie. About 70% of the total production is exported, either as seed (50%) or oil (20%). We utilized inter-specific crosses between B. napus and related species to improve the disease resistance and seed quality of B. napus. We produced yellow-seed forms of B. napus from crosses with B. rapa and B. juncea which have higher seed oil content, and lower meal fiber content to improve the feed value of the meal. We also produced germplasm with high oleic/low linolenic acid content to improve the nutritional value of canola oil as well as its technological qualities for use in the production of solid fats without trans fatty acids. The content of saturated fats in canola oil was reduced to less than 5% of total fatty acids. Inter-specific methodology was also successful in the development of B. juncea mustard as an edible oilseed crop with high yield, disease resistance and seed quality for production in the semiarid regions of the Canadian prairie. This paper will describe the crossing approaches used to develop this germplasm and discuss future research activities for canola improvement.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.457

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 studies0.0000.000
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 head0.024
GPT teacher head0.339
Teacher spread0.315 · 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 designBench or experimental
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

Citations13
Published2007
Admission routes2
Has abstractyes

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