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Record W4401209700 · doi:10.31413/nativa.v2i4.1689

INFLUÊNCIA DO TEOR DE UMIDADE NA GERMINAÇÃO DE SEMENTES DE Parapiptadenia rigida (BENTH.) BRENAN

2014· article· pt· W4401209700 on OpenAlexaff
Lucas Damo Marangoni, Marlove Fátima Brião Muniz, Raquel Barros Binotto, Jordana Georgin, Caciara Gonzatto Maciel

Bibliographic record

VenueNativa · 2014
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicGrowth and nutrition in plants
Canadian institutionsCanadian Pacific Railway (Canada)
Fundersnot available
KeywordsHorticultureGerminationWater contentMoistureChemistryBiology

Abstract

fetched live from OpenAlex

Parapiptadenia rigida é uma espécie arbórea nativa amplamente encontrada na região central e sul do Brasil, é indicada para recuperação de áreas degradadas em virtude de sua baixa exigência física do solo e por ser heliófila. Devido aos poucos estudos sobre os efeitos do teor de umidade no comportamento fisiológico e sanitário de sementes de angico, o presente trabalho teve como objetivo definir teores de umidade adequados para produção e conservação da viabilidade das sementes. As sementes foram coletadas em dez árvores no campus da UFSM e seu teor de umidade foi homogeneizado em ambiente de laboratório por cinco dias. Determinou-se o Teor de Umidade (TU) das amostras juntamente com o Peso de Mil Sementes (PMS) submetidas à secagem em estufa 105 ± 3 °C/24h. Para obtenção de teores maiores de umidade as sementes foram submetidas à umidade elevada (100%) em gerbox por um e dois dias. O valor mínimo e máximo de teor de umidade foi, respectivamente, 3% e 100% (base seca). Foram avaliados o vigor e a incidência de fungos em cada teor de umidade. A análise estatística foi realizada por meio do software Assistat. O teor de umidade não afetou a incidência de fungos, entretanto interferiu em alguns testes de vigor. Palavras-chave: angico-vermelho, teste de vigor, incidência de fungos, condutividade elétrica. INFLUENCE OF MOISTURE CONTENT IN SEED GERMINATION OF Parapiptadenia rigida (BENTH.) BRENAN ABSTRACT Parapiptadenia rigida is a native tree species widely found in central and southern Brazil, indicated for regeneration of rundown areas due to its low physical soil requirement and to its heliophile style. Regarding the few studies on the effects of moisture content on the physiological and health behavior of the angico seeds, the present study aimed to define suitable moisture content for production and preservation on seeds viability. Seeds were collected from ten trees in the UFSM campus and then their moisture content was homogenized in a laboratory of environment for five days. The Moisture Content (MC) of the samples were gauged along with the weight of thousand seeds (WTS) dried up in a drying oven at 105 ± 3 ° C/24h. To obtain higher moisture levels, some seeds went through high humidity level (100%) in gerbox for one and two days. The minimum and maximum moisture content was, respectively, 3% and 100% (dry basis). The vigor and the incidence of fungi in each moisture level were evaluated. Statistical analysis was performed using the software Assistat. The moisture content did not affect the incidence of fungi, however interfered with some vigor tests. Keywords: angico, vigor test, fungi incidence, electric conductivity. DOI: http://dx.doi.org/10.14583/2318-7670.v02n04a07

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 score0.005
Threshold uncertainty score0.009

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.242
Teacher spread0.229 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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