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dc.contributor.authorBRIGHENTI, C. R. G.eng
dc.contributor.authorCIRILLO, M. A.eng
dc.contributor.authorCOSTA, A. L. A.eng
dc.contributor.authorROSA, S. D. V. F. daeng
dc.contributor.authorGUIMARÃES, R. M.eng
dc.date.accessioned2019-05-07T00:50:28Z-
dc.date.available2019-05-07T00:50:28Z-
dc.date.created2019-05-06
dc.date.issued2019
dc.identifier.citationScientia Agricola, v. 76, n. 3, p. 198-207, May/June. 2019eng
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1108760-
dc.descriptionTetrazolium tests use conventional sampling techniques in which a sample has a fixed size. These tests may be improved by sequential sampling, which does not work with fixedsize samples. When data obtained from an experiment are analyzed sequentially the analysis can be terminated when a particular decision has been made, and thus, there is no need to pre-establish the number of seeds to assess. Bayesian statistics can also help, if we have sufficient knowledge about coffee production in the area to construct a prior distribution. Therefore, we used the Bayesian sequential approach to estimate the percentage of viable coffee seeds submitted to tetrazolium testing, and we incorporated priors with information from other analyses of crops from previous years. We used the Beta prior distribution and, using data obtained from sample lots of Coffea arabica, determined its hyperparameters with a histogram and O?Hagan?s 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 that the Bayesian sequential estimation can indeed be used for the tetrazolium test: the average percentage of viability obtained with the conventional frequentist method was 88 %, whereas that obtained with the Bayesian method with both priors was 89 %. However, the Bayesian method required, on average, only 89 samples to reach this value while the traditional estimation method needed as many as 200 samples.eng
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectBeta distributioneng
dc.subjectSeed analysiseng
dc.subjectCoffeeeng
dc.subjectPrior distributioneng
dc.titleBayesian sequential procedure to estimate the viability of seeds Coffea arabica L. in tetrazolium test.eng
dc.typeArtigo de periódicoeng
dc.date.updated2019-05-07T00:50:28Z
dc.subject.nalthesaurusSamplingeng
riaa.ainfo.id1108760eng
riaa.ainfo.lastupdate2019-05-06
dc.contributor.institutionCarla Regina Guimarães Brighenti, Universidade Federal de São João Del-Rei/Departamento de Zootecnia; Marcelo Ângelo Cirillo, Universidade Federal de Lavras- UFLA/Departamento de Estatística; André Luís Alves Costa, Universidade Federal de Lavras- UFLA/Departamento de Estatística; STTELA DELLYZETE VEIGA F DA ROSA, CNPCa; Renato Mendes Guimarães, Universidade Federal de Lavras - UFLA/Deptaramento de Agricultura.eng
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