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BackgroundThe morphological analysis of olive leaves, fruits and endocarps may represent an efficient tool for the characterization and discrimination of cultivars and the establishment of relationships among them. In recent years, much attention has been focused on the application of molecular markers, due to their high diagnostic efficiency and independence from environmental and phenological variables.ResultsIn this study, we present a semi-automatic methodology of detecting various morphological parameters. With the aid of computing and image analysis tools, we created semi-automatic algorithms applying intuitive mathematical descriptors that quantify many fruit, leaf and endocarp morphological features. In particular, we examined quantitative and qualitative characters such as size, shape, symmetry, contour roughness and presence of additional structures such as nipple, petiole, endocarp surface roughness, etc..ConclusionWe illustrate the performance and the applicability of our approach on Greek olive cultivars; on sets of images from fruits, leaves and endocarps. In addition, the proposed methodology was also applied for the description of other crop species morphologies such as tomato, grapevine and pear. This allows us to describe crop morphologies efficiently and robustly in a semi-automated way.Electronic supplementary materialThe online version of this article (10.1186/s13007-017-0261-8) contains supplementary material, which is available to authorized users.

Arabinogalactan proteins (AGPs) are proteoglycans challenging researchers for decades. However, despite the extremely interesting polydispersity of their structure and essential application potential, studies of AGPs in fruit are limited, and only a few groups deal with this scientific subject. Here, we summarise the results of pioneering studies on AGPs in fruit tissue with their structure, specific localization pattern, stress factors influencing their presence, and a focus on recent advances. We discuss the properties of AGPs, i.e., binding calcium ions, ability to aggregate, adhesive nature, and crosslinking with other cell wall components that may also be implicated in fruit metabolism. The aim of this review is an attempt to associate well-known features and properties of AGPs with their putative roles in fruit ripening. The putative physiological significance of AGPs might provide additional targets of regulation for fruit developmental programme. A comprehensive understanding of the AGP expression, structure, and untypical features may give new information for agronomic, horticulture, and renewable biomaterial applications.

Please cite this article in press as: K.N. Blazakis et al., Whole cell tracking through the optimal control of geometric evolution laws, J. Comput. Phys. (2015), http://dx. AbstractCell tracking algorithms which automate and systematise the analysis of time lapse image data sets of cells are an indispensable tool in the modelling and understanding of cellular phenomena. In this study we present a theoretical framework and an algorithm for whole cell tracking. Within this work we consider that "tracking" is equivalent to a dynamic reconstruction of the whole cell data (morphologies) from static image datasets. The novelty of our work is that the tracking algorithm is driven by a model for the motion of the cell. This model may be regarded as a simplification of a recently developed physically meaningful model for cell motility. The resulting problem is the optimal control of a geometric evolution law and we discuss the formulation and numerical approximation of the optimal control problem. The overall goal of this work is to design a framework for cell tracking within which the recovered data reflects the physics of the forward model. A number of numerical simulations are presented that illustrate the applicability of our approach.