On the characterization of flowering curves using Gaussian mixture models

Autor: Gilles Michel, Frédéric Proïa, Tatiana Thouroude, Jérémy Clotault, Alix Pernet
Přispěvatelé: Laboratoire Angevin de Recherche en Mathématiques (LAREMA), Université d'Angers (UA)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche en Horticulture et Semences (IRHS), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA)-Université d'Angers (UA), Université d'Angers (UA)-Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Université d'Angers (UA)
Jazyk: angličtina
Rok vydání: 2016
Předmět:
0106 biological sciences
0301 basic medicine
Statistics and Probability
FOS: Computer and information sciences
Reblooming behavior
Normal Distribution
Principal component analysis
Flowers
Rosa
Quantitative Biology - Quantitative Methods
Statistics - Applications
01 natural sciences
General Biochemistry
Genetics and Molecular Biology
Normal distribution
Correlation
Set (abstract data type)
03 medical and health sciences
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
Statistics
[SDV.BV]Life Sciences [q-bio]/Vegetal Biology
Computer Simulation
Applications (stat.AP)
Classification of curves
Quantitative Methods (q-bio.QM)
Mathematics
Flowering curves
Models
Statistical
General Immunology and Microbiology
Basis (linear algebra)
Characterization of curves
Applied Mathematics
General Medicine
Mixture model
Characterization (materials science)
030104 developmental biology
Recurrent flowering
Modeling and Simulation
FOS: Biological sciences
Longitudinal k-means algorithm
Gaussian mixture models
General Agricultural and Biological Sciences
Selection criterion
Algorithms
010606 plant biology & botany
Zdroj: Journal of Theoretical Biology
Journal of Theoretical Biology, Elsevier, 2016, 402, pp.75-88. ⟨10.1016/j.jtbi.2016.04.022⟩
ISSN: 0022-5193
1095-8541
DOI: 10.1016/j.jtbi.2016.04.022⟩
Popis: 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.
Comment: 28 pages, 27 figures
Databáze: OpenAIRE
Externí odkaz: