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Bayesian sequential procedure to estimate the viability of seeds Coffea arabica L. in tetrazolium test

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dc.contributor.author Brighenti, Carla Regina Guimarães
dc.contributor.author Cirillo, Marcelo Ângelo
dc.contributor.author Costa, André Luís Alves
dc.contributor.author Rosa, Sttela Dellyzete Veiga Franco da
dc.contributor.author Guimarães, Renato Mendes
dc.date.accessioned 2019-10-31T13:32:27Z
dc.date.available 2019-10-31T13:32:27Z
dc.date.issued 2019-05
dc.identifier.citation BRIGHENTI, C. R. G. et al. Bayesian sequential procedure to estimate the viability of seeds Coffea arabica L. in tetrazolium test. Scientia Agrícola, Piracicaba, v. 76, n. 3, p. 198-207, mai./jun. 2019. pt_BR
dc.identifier.issn 1678-992X
dc.identifier.uri http://dx.doi.org/10.1590/1678-992x-2017-0123 pt_BR
dc.identifier.uri http://www.sbicafe.ufv.br/handle/123456789/12281
dc.description.abstract Tetrazolium tests use conventional sampling techniques in which a sample has a o Zootecnia, Av. Visconde do Rio Preto, s/n — 36301-360 — fixed size. These tests may be improved by sequential sampling, which does not work with fixed- s São João Del-Rei, MG — Brasil. size samples. When data obtained from an experiment are analyzed sequentially the analysis can OM 2Universidade Federal de Lavras -— Depto. de Estatística, C.P. be terminated when a particular decision has been made, and thus, there is no need to pre-es- "O 3037 - 37200-000 - Lavras, MG - Brasil. tablish the number of seeds to assess. Bayesian statistics can also help, if we have sufficient = Embrapa Café, PqEB, s/n - 70770-901 - Brasília, DF — knowledge about coffee production in the area to construct a prior distribution. Therefore, we Brasil. used the Bayesian sequential approach to estimate the percentage of viable coffee seeds sub- os “Universidade Federal de Lavras — Depto. de Agricultura. mitted to tetrazolium testing, and we incorporated priors with information from other analyses — *Corresponding author <carlabrighentiQufs).edu.br> of crops from previous years. We used the Beta prior distribution and, using data obtained from Ss sample lots of Coffea arabica, determined its hyperparameters with a histogram and O'Hagan's O Edited by: Marcin Kozak methods. To estimate the lowest risk, we computed the Bayes risks, which provided us with a = basis for deciding whether or not we should continue the sampling process. The results confirm e Received April 13, 2017 that the Bayesian sequential estimation can indeed be used for the tetrazolium test: the average Fi; Accepted January 06, 2018 percentage of viability obtained with the conventional frequentist method was 88 %, whereas that v obtained with the Bayesian method with both priors was 89 %. However, the Bayesian method E required, on average, only 89 samples to reach this value while the traditional estimation method O needed as many as 200 samples. pt_BR
dc.format pdf pt_BR
dc.language.iso en pt_BR
dc.publisher Escola Superior de Agricultura "Luiz de Queiroz" pt_BR
dc.relation.ispartofseries Scientia Agrícola;v.76, n.3, p.198-207, 2019;
dc.rights Open Access pt_BR
dc.subject Beta distribution pt_BR
dc.subject Seed analysis pt_BR
dc.subject Sampling pt_BR
dc.subject Coffee pt_BR
dc.subject Prior distribution pt_BR
dc.subject.classification Cafeicultura::Sementes e mudas pt_BR
dc.title Bayesian sequential procedure to estimate the viability of seeds Coffea arabica L. in tetrazolium test pt_BR
dc.type Artigo pt_BR

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