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Record W2892164956 · doi:10.21833/ijaas.2018.10.010

Correlation and genetic component studies for peduncle length affecting grain yield in wheat

2018· article· en· W2892164956 on OpenAlexfundno aff
Muhammad Umer Farooq

Bibliographic record

VenueInternational Journal of ADVANCED AND APPLIED SCIENCES · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
FundersAlberta Agricultural Research Institute
KeywordsPeduncle (anatomy)BiologyHybridYield (engineering)Quantitative trait locusGenetic variationSelection (genetic algorithm)AgronomyGrain yieldHorticultureGeneGenetics

Abstract

fetched live from OpenAlex

The main emphasis of wheat breeders is to strive for genetically more stable, high yielding varieties than the pre-released ones to sustain the yield. Yield improvement efforts should be made while considering all contributing factors that can improve it. The role of peduncle length influencing yield and other supporting features are barely taken into consideration, and still not fully elucidated. Understanding and utilization of plant natural response will help to develop genetically and morphologically more adaptable genotypes for ever-increasing feed demand. The present research was conducted to assess the nature of gene action controlling inheritance of these traits coupled with manipulating role for yield traits. In this regard, 27 F1 hybrids were developed by crossing 9 female and 3 male parents using Line Tester (LT) mating design and evaluated for yield and its related traits. The analysis of variance for combining ability pointed out the presence of broad genetic variation in material with highly heritable nature. Correlation studies portrayed strong phenotypic and genotypic association between peduncle length, plant height, flag leaf area, spike length and grain weight/plant. Strong association of peduncle length with other yield contributing traits may be utilized as an indirect selection criterion for yield improvement. Hence, short stature and high yielding varieties can be developed by controlling the favourable genes for peduncle length. All yield related traits except peduncle length, spike length, and flag leaf area were controlled by dominant genes. Selection in the later generations for peduncle length may indirectly improve yield.

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 score0.813
Threshold uncertainty score0.101

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)0.0000.000

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 head0.037
GPT teacher head0.298
Teacher spread0.260 · 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

Citations25
Published2018
Admission routes1
Has abstractyes

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Same venueInternational Journal of ADVANCED AND APPLIED SCIENCESSame topicWheat and Barley Genetics and PathologyFrench-language works237,207