Parametric time-to-event analysis to evaluate the germination of faba bean and lentil seeds

This study aimed to evaluate the germination of faba bean (Vicia faba L.) and lentil (Lens culinaris Medikus) seeds after disinfection with sodium hypochlorite and acetic acid, using parametric time-to-event analysis. The germination was evaluated under the effect of four concentrations (0.005%, 0.05%, 0.1%, and 0.5%) of sodium hypochlorite and acetic acid in addition to the control treatment (0%). Seed germination was counted daily for seven days. Seeds that did not germinate by the end of this period were considered censored. The main parametric models used in the time-to-event analysis, Exponential, Weibull, Log-normal, Log-logistic, Logistic, and Gaussian, were adjusted for each product and concentration, plus the control. The model selected was the Log-logistic, and the choice was based on Akaike and weighted Akaike information criteria. The adequacy of the selected model was verified by Cox-Snell residuals. The germination curve estimated by the Log-logistic model demonstrated an inverse relationship between the increase in concentrations and the percentage of germination. It is concluded that to maintain germination above 80% for both crops, the application of sodium hypochlorite should not exceed 0.1%. In the case of acetic acid, concentrations should not exceed 0.05% for Vicia faba and 0.005% for Lens culinaris. The parametric survival model effectively estimated the seed germination.

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Publication Details

Journal
Brazilian Journal of Biometrics
Published
2025-09-03
DOI
https://doi.org/10.28951/bjb.v43i4.763
Primary Topic
Seed Germination and Physiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Parametric time-to-event analysis to evaluate the germination of faba bean and lentil seeds

Sebastião Martins Filho, Marciel Lelis Duarte, Lausanne Soraya de Almeida, Malithi De Silva et al.
Brazilian Journal of Biometrics
Seed Germination and Physiology
article

Parametric time-to-event analysis to evaluate the germination of faba bean and lentil seeds

Sebastião Martins Filho, Marciel Lelis Duarte, Lausanne Soraya de Almeida, Malithi De Silva, Verônica Manhães Saint’Clair
article en

Abstract

This study aimed to evaluate the germination of faba bean (Vicia faba L.) and lentil (Lens culinaris Medikus) seeds after disinfection with sodium hypochlorite and acetic acid, using parametric time-to-event analysis. The germination was evaluated under the effect of four concentrations (0.005%, 0.05%, 0.1%, and 0.5%) of sodium hypochlorite and acetic acid in addition to the control treatment (0%). Seed germination was counted daily for seven days. Seeds that did not germinate by the end of this period were considered censored. The main parametric models used in the time-to-event analysis, Exponential, Weibull, Log-normal, Log-logistic, Logistic, and Gaussian, were adjusted for each product and concentration, plus the control. The model selected was the Log-logistic, and the choice was based on Akaike and weighted Akaike information criteria. The adequacy of the selected model was verified by Cox-Snell residuals. The germination curve estimated by the Log-logistic model demonstrated an inverse relationship between the increase in concentrations and the percentage of germination. It is concluded that to maintain germination above 80% for both crops, the application of sodium hypochlorite should not exceed 0.1%. In the case of acetic acid, concentrations should not exceed 0.05% for Vicia faba and 0.005% for Lens culinaris. The parametric survival model effectively estimated the seed germination.

Brazilian Journal of BiometricsVol. 43(4)
Universidade Federal de Viçosa (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Fundação de Amparo à Pesquisa do Estado de Minas Gerais
Openalex Percentile: Top 83%
Seed Germination and Physiology
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Parametric time-to-event analysis to evaluate the germination of faba bean and lentil seeds — Sebastião Martins Filho, Marciel Lelis Duarte, et al. · Brazilian Journal of Biometrics (2025) | TGRS Research Map | TGRS