On the characterization of flowering curves using Gaussian mixture models.
J Theor Biol
; 402: 75-88, 2016 08 07.
Article
em En
| MEDLINE
| ID: mdl-27113781
ABSTRACT
In this paper, we develop a statistical methodology applied to the characterization of flowering curves using Gaussian mixture models. Our study relies on a set of rosebushes flowering data, and Gaussian mixture models are mainly used to quantify the reblooming properties of each one. In this regard, we also suggest our own selection criterion to take into account the lack of symmetry of most of the flowering curves. Three classes are created on the basis of a principal component analysis conducted on a set of reblooming indicators, and a subclassification is made using a longitudinal k-means algorithm which also highlights the role played by the precocity of the flowering. In this way, we obtain an overview of the correlations between the features we decided to retain on each curve. In particular, results suggest the lack of correlation between reblooming and flowering precocity. The pertinent indicators obtained in this study will be a first step towards the comprehension of the environmental and genetic control of these biological processes.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Distribuição Normal
/
Modelos Estatísticos
/
Rosa
/
Flores
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
J Theor Biol
Ano de publicação:
2016
Tipo de documento:
Article