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Record W2880464294 · doi:10.5539/jas.v10n8p477

Accelerated Aging for the Evaluation of the Physiological Potential of Eggplant Seeds

2018· article· en· W2880464294 on OpenAlexvenueno aff
Cristiane Deuner, Danillo B. Rodrigues, Lílian Vanussa Madruga de Tunes, Ana Sofia Almeida, ANNA S. SUÑÉ, Andréa Bicca Noguez Martins, H. L. Chagas, Éwerton Gewehr, Luis Henrique Konzen, Bruna Barreto dos Reis

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsAccelerated agingGerminationCultivarSeedlingHorticultureWater contentMoistureSeed testingBiologyAgronomyChemistry

Abstract

fetched live from OpenAlex

The use of healthy and vigorous seeds is necessary to ensure adequate plant stands, therefore, vigor tests are used to measure the physiological potential of seeds alongside with the germination test. The objective of this study was to evaluate different procedures for the estimation of the physiological potential of eggplant seeds through the accelerated aging test. Seed lots were tested for moisture content, germination, first count of germination, seedling emergence and speed of emergence index. Then, seeds were subjected to the conventional accelerated aging test, using an unsaturated NaCl solution or a NaCl saturated solution, for 24, 48 and 72 hours at 41 °C, estimating the moisture content after each period of aging. The treatments were allocated in a completely randomized design, with four treatments (seed lots) and four replicates. The use of the saturated solution of NaCl decreases the absorption of water and the rate of deterioration of eggplant seeds during the accelerated aging test, providing more uniform results. The accelerated aging test allows eggplant seed lots from cv. Napoli to be ranked at different levels of vigor and, among the procedures tested, the combinations 41 °C/48 hours and 41 °C/72 hours allowed the proper assessment of the physiological potential of seeds of this cultivar.

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)0.0010.000
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 head0.075
GPT teacher head0.315
Teacher spread0.240 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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