Studio di caratteri correlati a stress idrico in una collezione di cultivar di frumento duro (Triticum durum Desf.)

L’agricoltura si trova ad affrontare una diminuzione della disponibilità d’acqua ed una crescente domanda della produzione di cereali per scopi alimentari. Sono perciò necessarie strategie di coltivazione innovative per migliorare la produttività e nuovi genotipi migliorati nell'efficienza dell’uso delle risorse in condizioni di siccità. Questi rappresentano gli obietti principali del progetto “DROPS” (Drought tolerant yielding Plants) all’interno del quale ha avuto luogo il mio progetto di Dottorato. La mia attività di ricerca è stata svolta come segue: 1. Caratterizzazione molecolare di un panel di188 accessioni di frumento duro con marcatori SSR e DaRT; 2. Esperimenti in serra su 100 accessioni del panel per valutare la Water-Use Efficiency (WUE) in sei repliche secondo un Alpha Lattice design; 3. Prove sul campo, effettuate secondo un Alpha Lattice design, in due stagioni di crescita: a. 2010/11, valutazione di 100 accessioni presso l’Azienda sperimentale dell'Università di Cadriano (BO); b. 2011/12, valutazione del panel completo in 3 ambienti, con due diversi regimi irrigui In entrambi gli anni, abbiamo valutato caratteri agronomici correlati con il ciclo di sviluppo, la resa di granella e sue componenti, nonché diversi fattori ambientali e del suolo. Per quanto riguarda WUE, abbiamo trovato differenze altamente significative tra accessioni; inoltre, cinque accessioni hanno mostrato elevati valori di WUE e cinque accessioni valori molto bassi di WUE in tutte e sei le repliche. Gli esperimenti di campo nelle stagioni 2011 e 2012 hanno evidenziato differenze altamente significative tra le accessioni del panel per la maggior parte dei caratteri analizzati, confermando inoltre che il panel di fiorisce entro una settimana. L'esperimento del secondo anno ci ha permesso osservare un significativa interazione Genotipo X Ambiente. Questi risultati saranno integrati con ulteriori analisi QTL, per identificare regioni cromosomiche coinvolte nel controllo genetico dei caratteri di interesse e verificare la stabilità dei QTL in diversi ambienti.

Corporate Venture Capital: How established firms use external resources to create new competencies

This Doctoral Dissertation is triggered by an emergent trend: firms are increasingly referring to investments in corporate venture capital (CVC) as means to create new competencies and foster the search for competitive advantage through the use of external resources. CVC is generally defined as the practice by non-financial firms of placing equity investments in entrepreneurial companies. Thus, CVC can be interpreted (i) as a key component of corporate entrepreneurship - acts of organizational creation, renewal, or innovation that occur within or outside an existing organization– and (ii) as a particular form of venture capital (VC) investment where the investor is not a traditional and financial institution, but an established corporation. My Dissertation, thus, simultaneously refers to two streams of research: corporate strategy and venture capital. In particular, I directed my attention to three topics of particular relevance for better understanding the role of CVC. In the first study, I moved from the consideration that competitive environments with rapid technological changes increasingly force established corporations to access knowledge from external sources. Firms, thus, extensively engage in external business development activities through different forms of collaboration with partners. While the underlying process common to these mechanisms is one of knowledge access, they are substantially different. The aim of the first study is to figure out how corporations choose among CVC, alliance, joint venture and acquisition. I addressed this issue adopting a multi-theoretical framework where the resource-based view and real options theory are integrated. While the first study mainly looked into the use of external resources for corporate growth, in the second work, I combined an internal and an external perspective to figure out the relationship between CVC investments (exploiting external resources) and a more traditional strategy to create competitive advantage, that is, corporate diversification (based on internal resources). Adopting an explorative lens, I investigated how these different modes to renew corporate current capabilities interact to each other. More precisely, is CVC complementary or substitute to corporate diversification? Finally, the third study focused on the more general field of VC to investigate (i) how VC firms evaluate the patent portfolios of their potential investee companies and (ii) whether the ability to evaluate technology and intellectual property varies depending on the type of investors, in particular for what concern the distinction between specialized versus generalist VCs and independent versus corporate VCs. This topic is motivated by two observations. First, it is not clear yet which determinants of patent value are primarily considered by VCs in their investment decisions. Second, VCs are not all alike in terms of technological experiences and these differences need to be taken into account.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

New water use efficiency strategies to cope with climate change

Crop water requirements are important elements for food production, especially in arid and semiarid regions. These regions are experience increasing population growth and less water for agriculture, which amplifies the need for more efficient irrigation. Improved water use efficiency is needed to produce more food while conserving water as a limited natural resource. Evaporation (E) from bare soil and Transpiration (T) from plants is considered a critical part of the global water cycle and, in recent decades, climate change could lead to increased E and T. Because energy is required to break hydrogen bonds and vaporize water, water and energy balances are closely connected. The soil water balance is also linked with water vapour losses to evapotranspiration (ET) that are dependent mainly on energy balance at the Earth’s surface. This work addresses the role of evapotranspiration for water use efficiency by developing a mathematical model that improves the accuracy of crop evapotranspiration calculation; accounting for the effects of weather conditions, e.g., wind speed and humidity, on crop coefficients, which relates crop evapotranspiration to reference evapotranspiration. The ability to partition ET into Evaporation and Transpiration components will help irrigation managers to find ways to improve water use efficiency by decreasing the ratio of evaporation to transpiration. The developed crop coefficient model will improve both irrigation scheduling and water resources planning in response to future climate change, which can improve world food production and water use efficiency in agriculture.