MétaCan
Menu
Back to cohort

Manipulation of <i>in vivo</i> pollination techniques to improve the fertilization efficiency of interspecies crosses in the genus <i>Phaseolus</i>

2007· article· en· W2130430263 on OpenAlexafffund
V. Gurusamy, Albert Vandenberg, Kirstin E. Bett

Bibliographic record

VenuePlant Breeding · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhaseolusPollenBiologyPollinationGerminationBackcrossingHybridBotanyHuman fertilizationIntrogressionHorticultureAgronomyGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Phaseolus angustissimus A. Gray contains genes for traits of interest for dry bean (P. vulgaris) breeders. F1 hybrids can be produced but introgression through backcrossing has been a problem. One of the main impediments is the time required between pollination and fertilization when F1 hybrids of P. vulgaris/P. angustissimus are backcrossed with P. vulgaris. In an attempt to reduce this time, the effect of alternative pollination techniques was studied. The rate and the time of fertilization were ascertained using three different pollen types (pollen germinated in vitro, fresh pollen (FP) mixed in pollen‐germinating media and FP), and two methods of pollination (cut‐style and stigmatic pollinations). An optimal in vitro pollen germination medium for Phaseolus pollen was developed. Low temperatures (6–9°C) were demonstrated to be necessary for Phaseolus pollen germination. Pollination using a cut‐style technique coupled with pregerminated pollen reduced the time for fertilization in the backcrosses of interspecies hybrids by approximately 28 h. This technique improved the success rate of fertilization in wide crosses of Phaseolus designed to introgress genes from wild relatives.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.025
GPT teacher head0.236
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2007
Admission routes2
Has abstractyes

Explore more

Same venuePlant BreedingSame topicPlant pathogens and resistance mechanismsFrench-language works237,207