Aureobasidium pullulans as biological control agent: modes of action

The postharvest phase has been considered an environment very suitable for successful application of biological control agents (BCAs). However, the tri-interaction between fungal pathogen, host (fruit) and antagonist is influenced by several parameters such as temperature, oxidative stresses, oxygen composition, water activity, etc. that could be determining for the success of biocontrol. Knowledge of the modes of action of BCAs is essential in order to enhance their viability and increase their potentialities in disease control. The thesis focused on the possibility to explain the modes of action of a biological control agent (BCA): Aureobasidium pullulans, in particular the strains L1 and L8, control effective against fruit postharvest fungal pathogen. In particular in this work were studied the different modes of action of BCA, such as: i) the ability to produce volatile organic compounds (VOCs), identified by SPME- gas chromatography-mass spectrometry (GC-MS) and tested by in vitro and in vivo assays against Penicillium spp., Botrytis cinerea, Colletotrichum acutatum; ii) the ability to produce lytic enzymes (exo and endo chitinase and β-1,3-glucanase) tested against Monilinia laxa, causal agent of brown rot of stone fruits. L1 and L8 lytic enzymes were also evaluated through their relative genes by molecular tools; iii) the competition for space and nutrients, such as sugars (sucrose, glucose and fructose) and iron; the latter induced the production of siderophores, molecules with high affinity for iron chelation. A molecular investigation was carried out to better understand the gene regulation strictly correlated to the production of these chelating molucules. The competition for space against M. laxa was verified by electron microscopy techniques; iv) a depth bibliographical analysis on BCAs mechanisms of action and their possible combination with physical and chemical treatments was conducted.

Distributed Large-scale Mixed-Integer Optimization with Application to Energy and Multi-robot Networks

Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.