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Provedor de dados:  Ciência Rural
País:  Brazil
Título:  Leaf count overdispersion in coffee seedlings
Autores:  Silva,Edilson Marcelino
Furtado,Thais Destefani Ribeiro
Fernandes,Jaqueline Gonçalves
Cirillo,Marcelo Ângelo
Muniz,Joel Augusto
Data:  2019-01-01
Ano:  2019
Palavras-chave:  Poisson model
Negative binomial model
Exponential family
Generalized linear model
Resumo:  ABSTRACT: Coffee crops play an important role in Brazilian agriculture, with a high level of social and economic participation resulting from the jobs created in the supply chain and from the income obtained by producers and the revenue generated for the country from coffee bean export. In coffee plant growth, leaves have a determinant role in higher production; therefore, the leaf count per plant provides relevant information to producers for adequate crop management, such as foliar fertilizer applications. To describe count data, the Poisson model is the most commonly employed model; when count data show overdispersion, the negative binomial model has been determined to be more adequate. The objective of this study was to compare the fitness of the Poisson and negative binomial models to data on the leaf count per plant in coffee seedlings. Data were collected from an experiment with a randomized block design with 30 treatments and three replicates and four plants per plot. Data from only one treatment, in which the number of leaves was counted over time, were employed. The first count was conducted on 8 April 2016, and the other counts were performed 18, 32, 47, 62, 76, 95, 116, 133, and 153 days after the first evaluation, for a total of ten measurements. The fitness of the models was assessed based on deviance values and simulated envelopes for residuals. Results of fitness assessment indicated that the Poisson model was inadequate for describing the data due to overdispersion. The negative binomial model adequately fitted the observations and was indicated to describe the number of leaves of coffee plants. Based on the negative binomial model, the expected relative increase in the number of leaves was 0.9768% per day.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782019000400201
Editor:  Universidade Federal de Santa Maria
Relação:  10.1590/0103-8478cr20180786
Formato:  text/html
Fonte:  Ciência Rural v.49 n.4 2019
Direitos:  info:eu-repo/semantics/openAccess
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