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 |