Effect of fungal colonization on mechanical performance of cork

The industrialization of traditional processes relies on the scientific ability to understand the empirical evidence associated with traditional knowledge. Cork manufacturing includes one operation known as stabilization, where humid cork slabs are extensively colonized by fungi. The implications of fungal growth on the chemical quality of cork through the analysis of putative fungal metabolites have already been investigated. However, the effect of fungal growth on the mechanical properties of cork remains unexplored. This study investigated the effect of cork colonization on the integrity of the cork cell walls and their mechanical performance. Fungal colonization of cork by Chrysonilia sitophila, Mucor plumbeus Penicillium glabrum, P. olsonii, and Trichoderma longibrachiatum was investigated by microscopy. Growth occurred primarily on the surface of the cork pieces, but mycelium extended deeper into the cork layers, mostly via lenticular channels and by hyphal penetration of the cork cell wall. In this first report on cork decay in which specific correlation between fungal colonization and mechanical proprieties of the cork has been investigated, all colonizing fungi except C. sitophila, reduced cork strength, markedly altering its viscoelastic behaviour and reducing its Young’s modulus.

Revealing fungal activity in the presence of ionic liquids

Dissertation presented to obtain the Ph.D degree in Biochemistry

Atomic force microscopy assisted with electron and ion beam microscopy for the direct measurement of biostructures and DNA samples

Dissertation to obtain a Master degree in Biotechnology

Characterization of processed materials by electrical currents: development of equipment and applications

Dissertação para obtenção do Grau de Mestre em Engenharia Mecânica

Microscopy image segmentation by active contour models

In this thesis a semi-automated cell analysis system is described through image processing. To achieve this, an image processing algorithm was studied in order to segment cells in a semi-automatic way. The main goal of this analysis is to increase the performance of cell image segmentation process, without affecting the results in a significant way. Even though, a totally manual system has the ability of producing the best results, it has the disadvantage of taking too long and being repetitive, when a large number of images need to be processed. An active contour algorithm was tested in a sequence of images taken by a microscope. This algorithm, more commonly known as snakes, allowed the user to define an initial region in which the cell was incorporated. Then, the algorithm would run several times, making the initial region contours to converge to the cell boundaries. With the final contour, it was possible to extract region properties and produce statistical data. This data allowed to say that this algorithm produces similar results to a purely manual system but at a faster rate. On the other hand, it is slower than a purely automatic way but it allows the user to adjust the contour, making it more versatile and tolerant to image variations.