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Record W2524637967 · doi:10.3389/fpls.2016.01474

The Associative Changes in Scutellum Nuclear Content and Morphology with Viability Loss of Naturally Aged and Accelerated Aging Wheat (Triticum aestivum) Seeds

2016· article· en· W2524637967 on OpenAlexafffund
Zaheer Ahmed, Hui Yang, Yong‐Bi Fu

Bibliographic record

VenueFrontiers in Plant Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsScutellumBiologyMorphology (biology)Accelerated agingBotanyHorticultureAgronomyGerminationChemistry

Abstract

fetched live from OpenAlex

plant genetic resources. However, little attention has been paid to study the process of seed deterioration and seed aging signals under storage. An attempt was made here to investigate morphological and molecular changes in the scutellum and aleurone sections of naturally or artificially aged wheat seeds using TUNEL assay and DAPI staining. Twelve wheat genotypes or samples exposed to natural ageing (NA) or accelerated ageing (AA) were assayed and these samples had germination rates ranging from 11 to 93%. The assayed samples showed substantial changes in scutellum, but not aleurone. The nuclei observed in the majority of the scutellum cells of the NA seed samples of lower germination rates were longer in size and less visible, while the scutellum cell morphology or arrangement remained unchanged. In contrast, longer AA treatments resulted in the loss of scutellum cell structure, collapse of cell layers, and disappearance of honey comb arrangements. These nuclei and structural changes were consistent with the DNA assessments of nuclear alternations for the selected wheat samples. Interestingly, the sample seed germination loss was found to be associated with the reductions in the scutellum nuclear content and with the increases in the scutellum nuclei length to width ratio. These findings are significant for understanding the process of wheat seed deterioration and are also useful for searching for sensitive seed aging signals for developing tools to monitor seed viability under storage.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
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 head0.020
GPT teacher head0.216
Teacher spread0.197 · 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 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

Citations18
Published2016
Admission routes2
Has abstractyes

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