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Record W3119787067 · doi:10.5539/jas.v13n2p56

Genetic Effects on Corn Seed Longevity

2021· article· en· W3119787067 on OpenAlexvenueno aff
Armando Dornelas Mota, Camila Ribeiro, Régis de Castro Carvalho, Flávia Maria Avelar Gonçalves

Bibliographic record

VenueJournal of Agricultural Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de Minas GeraisConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsDiallel crossHeterosisHybridBiologyLongevityGerminationTraitAdditive genetic effectsMaternal effectBiotechnologyHorticultureHeritabilityGeneticsComputer science

Abstract

fetched live from OpenAlex

This study aimed to elucidate the maternal and paternal genetic effects of the physiological quality of hybrid seed corn over time, as well as the contribution of heterosis for this trait. The seeds of single hybrids, reciprocals and parents were obtained by manual crosses in a complete diallel cross scheme. The analyses of germination and accelerated aging were performed and the data were analyzed with Tukey test and Griffing method. The quadratic components of general combining ability were similar to the effects of specific combining ability and superior to reciprocal, in most evaluation periods, implying that the effects on seed quality characters were attributed to genes of additive effect and genes of non-additive effect. The maternal effect of corn seed longevity was highly significant however its contribution was smaller than general combining ability and specific combining ability effects, but proved to be important in combinations of parents with lower estimate of general combining ability.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.232

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 science0.0000.000
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 head0.013
GPT teacher head0.217
Teacher spread0.205 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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