Biomedical subjects

Y Guédon

Publications and source records attributed to Y Guédon.

5 recordsLinked to original sources

PubMed2005

Co-ordinated growth between aerial and root systems in young apple plants issued from in vitro culture.

BACKGROUND AND AIMS: In several species exhibiting a rhythmic aerial growth, the existence of an alternation between root and shoot growth has been demonstrated. The present study aims to investigate the respective involvement of the emergence of new organs and their elongation in relation to this phenomenon and its possible genotypic variation in young apple plants. METHODS: Two apple varieties, X6407 (recently named 'Ariane') and X3305 ('Chantecler' x 'Baujade'), were compared. Five plants per variety, issued from in vitro culture, were observed in minirhizotrons over 4 months. For each plant, root emergence and growth were observed twice per week. Growth rates were calculated for all roots with more than two segments and the branching density was calculated on primary roots. On the aerial part, the number of leaves, leaf area and total shoot length were observed weekly. KEY RESULTS: No significant difference was observed between varieties in any of the final characteristics of aerial growth. Increase in leaf area and shoot length exhibited a 3-week rhythm in X3305 while a weaker signal was observed in Ariane. The primary root growth rate was homogeneous between the plants and likewise between the varieties, while their branching density differed significantly. Secondary roots emerged rhythmically, with a 3-week and a 2-week rhythm, respectively, in X3305 and 'Ariane'. Despite a high intra-variety variability, significant differences were observed between varieties in the secondary root life span and mean length. A synchronism between leaf emergence and primary root growth was highlighted in both varieties, while an opposition phase was observed between leaf area increments and secondary root emergence in X3305 only. CONCLUSION: A biological model of dynamics that summarizes the interactions between processes and includes the assumption of a feedback effect of lateral root emergence on leaf emergence is proposed.

Cells, Cultured↗

PubMed2005

Analysis of the plant architecture via tree-structured statistical models: the hidden Markov tree models.

Plant architecture is the result of repetitions that occur through growth and branching processes. During plant ontogeny, changes in the morphological characteristics of plant entities are interpreted as the indirect translation of different physiological states of the meristems. Thus connected entities can exhibit either similar or very contrasted characteristics. We propose a statistical model to reveal and characterize homogeneous zones and transitions between zones within tree-structured data: the hidden Markov tree (HMT) model. This model leads to a clustering of the entities into classes sharing the same 'hidden state'. The application of the HMT model to two plant sets (apple trees and bush willows), measured at annual shoot scale, highlights ordered states defined by different morphological characteristics. The model provides a synthetic overview of state locations, pointing out homogeneous zones or ruptures. It also illustrates where within branching structures, and when during plant ontogeny, morphological changes occur. However, the labelling exhibits some patterns that cannot be described by the model parameters. Some of these limitations are addressed by two alternative HMT families.

Combretaceae↗

PubMed2003

Comparison methods for branching and axillary flowering sequences.

Comparing branching and axillary flowering patterns accurately is a major issue both in botany and in various agronomic contexts. Data take the form of sequences which naturally represent the underlying structural information of branching and axillary flowering patterns. Various comparison methods are proposed based either on sequence alignment or on the computation of dissimilarity measures between (hidden) Markovian models built from sets of sequences. Sequence alignment is a natural complement to the exploratory tools and statistical models proposed in Guédon et al. (J. Theor. Biol. 212 (2001) 481) with the distinctive feature of applying to individual sequences. Comparison methods may also be used to reveal some grouping within a set of sequences or to evaluate the strength of a predefined grouping of sequences. The proposed approach is illustrated by examples corresponding to different plant species and different biological or agronomic objectives.

Computer Simulation↗

PubMed2002

Modelling branching patterns on 1-year-old trunks of six apple cultivars.

The structure resulting from branching on 1-year-old apple tree trunks was analysed in a set of apple cultivars with diverse branching and fruiting habits. Four different lateral types borne on successive nodes were observed when vegetative and flowering fates, as well as sylleptic and proleptic branching, were taken into account. The location and grouping of lateral types along the trunk were analysed for all cultivars, but are detailed for one cultivar only. This cultivar showed a succession of zones, each zone being characterized by its composition of lateral types. Statistical models-hidden semi-Markov chains-were built to take this structure into account and to characterize the cultivar's specific branching pattern. The models showed that most of the branching zones had a similar location in the different cultivars, even though zone composition and zone length differed among cultivars. On a more detailed scale, the nodes bearing a lateral, regardless of its type, were frequently followed by latent buds. The validity of the models and their biological interpretation are discussed with respect to parent shoot dynamics, hormonal gradients and competition between neighbouring buds.

Malus↗

PubMed2001

Pattern analysis in branching and axillary flowering sequences.

In the architectural approach to the study of plants, a major issue is to analyse branching and axillary flowering patterns. Due to the structured expression of the branching process and the noisy character of the observed patterns, we propose an analysis framework which is both structural and probabilistic. Data take the form of sequences which naturally represent the underlying structural information of branching and axillary flowering patterns and allow the application of a large number of methods ranging from exploratory analysis to stochastic modeling. The primary aim of the proposed analysis methods is to reveal patterns not directly apparent in the data, and thus to deepen our biological understanding of the underlying mechanisms that control the branching and the axillary flowering of plants over time and space. The proposed approach is illustrated using a set of examples corresponding to different plant species and different biological or agronomic objectives.

Models, Biological↗