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Record W2572597817 · doi:10.29321/maj.10.001164

Morphological Characterization of Fingermillet [Eleusine coracana (L.) Gaertn] Germplasm

2014· article· en· W2572597817 on OpenAlexfundno aff
V. Ulaganathan

Bibliographic record

VenueMadras Agricultural Journal · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLeaf Properties and Growth Measurement
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsGermplasmHeritabilityEleusineBiologyLeaf bladeGenetic variabilityAgronomyForageTest weightHorticultureGrain yieldGenotypeFinger milletGene

Abstract

fetched live from OpenAlex

Genetic variability and correlation coefficients analyses were carried out in 305 fingermillet genotypes between 13 grain yield and yield related traits. Highly significant mean sum of squares due to genotypes and wide range of variability were noticed among the genotypes for all the characters studied. High values for phenotypic and genotypic coefficients were recorded for grain yield per plant and flag leaf blade length, indicating that more variability is present in the germplasm for these characters. All the characters recorded high heritability in the present study indicated that these characters were relatively less influenced by environmental factors and phenotypic selection would be effective for the improvement of these characters. High estimates of variability together with high heritability and high genetic advance were observed for flag leaf sheath width, flag leaf blade width and 1000 grain weight, which indicated that these characters were governed by additive genes and selection would be effective for improvement of such characters. Highly significant positive correlation observed for the characters like days to 50 per cent flowering, productive tillers per plant, plant height, 1000 grain weight, flag leaf sheath length, days to maturity, flag leaf blade length and finger width with grain yield per plant, indicated the possibility of simultaneous improvement of these characters by selection.

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 score0.943
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.179
Teacher spread0.162 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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