Intervention of internal correlations in the morphogenesis of higher plants

Identifying Developmental Patterns in Structured Plant Phenotyping Data

Technological breakthroughs concerning both sensors and robotized plant phenotyping platforms have totally renewed the plant phenotyping paradigm in the last two decades. This has impacted both the nature and the throughput of data with the availability of data at high-throughput from the tissular to the whole plant scale. Sensor outputs often take the form of 2D or 3D images or time series of such images from which traits are extracted while organ shapes, shoot or root system architectures can be deduced. Despite this change of paradigm, many phenotyping studies often ignore the structure of the plant and therefore loose the information conveyed by the temporal and spatial patterns emerging from this structure. The developmental patterns of plants often take the form of succession of well-differentiated phases, stages or zones depending on the temporal, spatial or topological indexing of data. This entails the use of hierarchical statistical models for their identification.The objective here is to show potential approaches for analyzing structured plant phenotyping data using state-of-the-art methods combining probabilistic modeling, statistical inference and pattern recognition. This approach is illustrated using five different examples at various scales that combine temporal and topological index parameters, and development and growth variables obtained using prospective or retrospective measurements.

Integrative models for joint analysis of shoot growth and branching patterns

Plants exhibit dependences between shoot growth and branching that generate highly structured patterns. The characterization of the patterning mechanism is still an open issue because of the developmental processes involved with both succession of events (e.g. internode elongation, axillary shoot initiation and elongation) and complex dependences among neighbouring positions along the parent shoot. Statistical models called semi-Markov switching partitioned conditional generalized linear models were built on the basis of apple and pear tree datasets. In these models, the semi-Markov chain represents both the succession and lengths of branching zones, whereas the partitioned conditional generalized linear models represent the influence of parent shoot growth variables on axillary productions within each branching zone. Parent shoot growth variables were shown to influence specific developmental events. On this basis, the growth and branching patterns of two apple tree (Malus domestica) cultivars, as well as of pear trees (Pyrus spinosa) between two successive growing cycles, were compared. The proposed integrative statistical models were able to decipher the roles of successive developmental events in the growth and branching patterning mechanisms. These models could incorporate other parent shoot explanatory variables, such as the local curvature or the maximum growth rate of the leaf.

How young trees cope with removal of whole or parts of shoots: an analysis of local and distant responses to pruning in 1-year-old apple (Malus xdomestica; Rosaceae) trees

PREMISE OF STUDY

Manipulation of tree architecture by pruning provides an experimental context to analyze architectural plasticity resulting from competition between developing organs. The objective of this study was to quantify the effects of the removal of all or part of shoots through pruning on the redistribution of growth and flowering at spatial and temporal levels.

METHODS

Two types of pruning cuts were applied: (1) heading cuts of either the main stem or laterals and (2) thinning cuts (i.e., complete removal) of laterals. These two types of cuts were applied in summer and winter on 1-yr-old cultivars of Fuji and Braeburn apple trees. Tree topology and geometry were described over 3 years, and responses were analyzed for both local and distant scales.

RESULTS

Heading cuts induced quasi-deterministic local responses on pruned axes, whereas responses to thinning cuts were more variable. For the main stem and laterals, responses over greater spatial and temporal scales were highlighted with (1) stronger growth the year after summer pruning and (2) modification of branching and flowering along the unpruned parts after winter pruning.

CONCLUSIONS

Pruning typically induced growth redistribution toward traumatic reiterations and enhanced growth of the remaining unpruned axes with a concomitant decrease of flowering and cambial growth. Although results could be interpreted in relation to the root-shoot balance, tree responses appeared highly cultivar-specific.

Plant architecture: a dynamic, multilevel and comprehensive approach to plant form, structure and ontogeny

BACKGROUND AND AIMS

The architecture of a plant depends on the nature and relative arrangement of each of its parts; it is, at any given time, the expression of an equilibrium between endogenous growth processes and exogenous constraints exerted by the environment. The aim of architectural analysis is, by means of observation and sometimes experimentation, to identify and understand these endogenous processes and to separate them from the plasticity of their expression resulting from external influences.

SCOPE

Using the identification of several morphological criteria and considering the plant as a whole, from germination to death, architectural analysis is essentially a detailed, multilevel, comprehensive and dynamic approach to plant development. Despite their recent origin, architectural concepts and analysis methods provide a powerful tool for studying plant form and ontogeny. Completed by precise morphological observations and appropriated quantitative methods of analysis, recent researches in this field have greatly increased our understanding of plant structure and development and have led to the establishment of a real conceptual and methodological framework for plant form and structure analysis and representation. This paper is a summarized update of current knowledge on plant architecture and morphology; its implication and possible role in various aspects of modern plant biology is also discussed.

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.

Patterns of size and fate relationships of contiguous organs in the apple (Malus domestica) crown

•  In apple (Malus domestica), the size of a shoot and the vegetative or reproductive fate of the terminal bud on that shoot are considered to be related phenomena but with contrasted results depending on studies. Our hypothesis was that these relationships would be partly cultivar-dependent. •  Over a 3-yr period, the size relationships between shoots and fruit on two architecturally contrasted apple cultivars were assessed. For shoots, flowering frequency (dependent variable) was related to subtending shoot size (independent variable). •  Linear correlations were adjusted for size relationships between contiguous shoots in the same year (inflorescence vs bourse-shoot), and between years with differences in slopes and intercepts between the two cultivars. The relationships between the size of a shoot and flowering frequency differed between the two cultivars, with high flowering whatever shoot size vs parabolic relationships between the two variables, respectively. •  It is concluded that the relationships between shoot size and fate are cultivar-dependent. It is speculated that the flowering pattern not only depends on the property of the shoot alone, but also on the structural proportions of the parent branch and branching density.