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Record W2281935339 · doi:10.21273/hortsci.35.3.399b

062 Development of Southernpea [Vigna unguiculata (L.) Walp.] Cultivars with an Enhanced Persistent Green Seed Phenotype

2000· article· en· W2281935339 on OpenAlexaff
Richard L. Fery, Judy A. Thies

Bibliographic record

VenueHortScience · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCultivarVignaBiologyCotyledonHorticultureGreen houseBotanyAgronomy

Abstract

fetched live from OpenAlex

The development of southernpea cultivars with a persistent green seed color has been the subject of much interest in the U.S. horticultural industry for more than two decades because seeds of such cultivars can be harvested at the dry seed stage of maturity without loss of their fresh green color. Two genes, gt ( green testa ) and gc ( green cotyledon ), are known that condition a persistent green seed color in southernpea. The gt gene was identified more than 25 years ago, but cultivars containing this gene have not been well-accepted by the industry because of the frequent occurrence of discolored (brown stains) seeds. Cultivars containing the more recently discovered gc gene, however, do not produce the discolored seeds and are used extensively in the frozen food industry. Efforts to develop cream-, blackeye-, and pinkeye-types of cultivars containing both the gt and gc genes are nearing completion. The dry seeds harvested from candidate cultivars homozygous for both the gt and gc genes are stain free and exhibit a deeper and more uniform green color than seeds harvested from cultivars homozygous for just one of the genes. It is anticipated that newer cultivars containing both of the genes that condition a persistent green seed color will not only have an enhanced value to the frozen food industry, but will also have great potential for use in the dry pack industry.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.201
Teacher spread0.183 · 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

Citations1
Published2000
Admission routes1
Has abstractyes

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