Multidimensional item response theory models with general and specific latent traits for ordinal data

The aim of the thesis is to propose a Bayesian estimation through Markov chain Monte Carlo of multidimensional item response theory models for graded responses with complex structures and correlated traits. In particular, this work focuses on the multiunidimensional and the additive underlying latent structures, considering that the first one is widely used and represents a classical approach in multidimensional item response analysis, while the second one is able to reflect the complexity of real interactions between items and respondents. A simulation study is conducted to evaluate the parameter recovery for the proposed models under different conditions (sample size, test and subtest length, number of response categories, and correlation structure). The results show that the parameter recovery is particularly sensitive to the sample size, due to the model complexity and the high number of parameters to be estimated. For a sufficiently large sample size the parameters of the multiunidimensional and additive graded response models are well reproduced. The results are also affected by the trade-off between the number of items constituting the test and the number of item categories. An application of the proposed models on response data collected to investigate Romagna and San Marino residents' perceptions and attitudes towards the tourism industry is also presented.

Identification and genetic diversity in phytoplasmas associated with diseases of cassava and other agronomic relevant crops in south-east Asia and Latin America

Identification and genetic diversity of phytoplasmas infecting tropical plant species, selected among those most agronomically relevant in South-east Asia and Latin America were studied. Correlation between evolutionary divergence of relevant phytoplasma strains and their geographic distribution by comparison on homologous genes of phytoplasma strains detected in the same or related plant species in other geographical areas worldwide was achieved. Molecular diversity was studied on genes coding ribosomal proteins, groEL, tuf and amp besides phytoplasma 16S rRNA. Selected samples infected by phytoplasmas belonging to diverse ribosomal groups were also studied by in silico RFLP followed by phylogenetic analyses. Moreover a partial genome annotation of a ‘Ca. P. brasiliense’ strain was done towards future application for epidemiological studies. Phytoplasma presence in cassava showing frog skin (CFSD) and witches’ broom (CWB) diseases in Costa Rica - Paraguay and in Vietnam – Thailand, respectively, was evaluated. In both cases, the diseases were associated with phytoplasmas related to aster yellows, apple proliferation and “stolbur” groups, while only phytoplasma related to X-disease group in CFSD, and to hibiscus witches’ broom, elm yellows and clover proliferation groups in CWB. Variability was found among strains belonging to the same ribosomal group but having different geographic origin and associated with different disease. Additionally, a dodder transmission assay to elucidate the role of phytoplasmas in CWB disease was carried out, and resulted in typical phytoplasma symptoms in periwinkle plants associated with the presence of aster yellows-related strains. Lethal wilt disease, a severe disease of oil palm in Colombia that is spreading throughout South America was also studied. Phytoplasmas were detected in symptomatic oil palm and identified as ‘Ca. P. asteris’, ribosomal subgroup 16SrI-B, and were distinguished from other aster yellows phytoplasmas used as reference strains; in particular, from an aster yellows strain infecting corn in the same country.

Innovative techniques for sport turf managing: Agronomic and phyisiological implications

The growing substrate of the putting greens is considered a key factor for a healthy turf ecosystem. Actually detailed study on the effects of growth promoting bacteria and biostimulants on a professional sport turf are very limited. This thesis aimed to study the effectiveness of different microorganisms and biostimulants in order to improve the knowledge relative to the relationship between the beneficial microflora and root apparatus of sport turfs. The research project was divided in three principal steps: Initially, commercial products based on biostimulants and microorganisms were tested on a Lolium perenne L. essence grown in a controlled-environment. The principal evaluations were the study of the habitus of plants, biomass production and length of leaves and roots. Were studied the capacity of colonization of microorganisms within root tissues and rhizosphere. In the second step were developed two different biostimulant solutions based on effective microorganisms, mycorrhizae and humic acids. This test was conducted both on an Agrostis stolonifera putting green (Modena Golf & Country Club) in a semi-field condition and within a growth chamber on a Lolium perenne L. essence. Fungicide and chemicals applications were suspended in order to assess the effectiveness of the inoculants for nutrition and control of pests. In the last step, different microorganism mixes and biostimulants were tested on an experimental putting green in the Turf Research Center (TRC) (Virginia Tech, United States) in a real managing situation. The effects of different treatments were studied maintaining all chemicals and mechanicals managements scheduled during a sport season. Both growth-chamber and field results confirmed the capacity of microorganisms based biostimulants to promote the physiologic conditions of the plants, improve the growth of the roots and enhance the aesthetic performance of the turf. Molecular analysis confirmed the capacity of microorganisms to colonize the root tissues.

Analysis of the pig genome for the identification of genomic regions affecting production traits

The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.

Identification of CNV and QTL for productive and functional traits in dairy cattle using dense SNP chips

The thesis identify CNV structural variants as possible markers for genomic selection and identify QTL regions for Fatty Acid Content in the Italian Brown Swiss population. Additionally it maps the QTL for mastitis resistance in the Valdostana Red Pied cattle.

Genetic basis of variation for root traits and response to heat stress in durum wheat

Durum wheat is the second most important wheat species worldwide and the most important crop in several Mediterranean countries including Italy. Durum wheat is primarily grown under rainfed conditions where episodes of drought and heat stress are major factors limiting grain yield. The research presented in this thesis aimed at the identification of traits and genes that underlie root system architecture (RSA) and tolerance to heat stress in durum wheat, in order to eventually contribute to the genetic improvement of this species. In the first two experiments we aimed at the identification of QTLs for root trait architecture at the seedling level by studying a bi-parental population of 176 recombinant inbred lines (from the cross Meridiano x Claudio) and a collection of 183 durum elite accessions. Forty-eight novel QTLs for RSA traits were identified in each of the two experiments, by means of linkage- and association mapping-based QTL analysis, respectively. Important QTLs controlling the angle of root growth in the seedling were identified. In a third experiment, we investigated the phenotypic variation of root anatomical traits by means of microscope-based analysis of root cross sections in 10 elite durum cultivars. The results showed the presence of sizeable genetic variation in aerenchyma-related traits, prompting for additional studies aimed at mapping the QTLs governing such variation and to test the role of aerenchyma in the adaptive response to abiotic stresses. In the fourth experiment, an association mapping experiment for cell membrane stability at the seedling stage (as a proxy trait for heat tolerance) was carried out by means of association mapping. A total of 34 QTLs (including five major ones), were detected. Our study provides information on QTLs for root architecture and heat tolerance which could potentially be considered in durum wheat breeding programs.

Exploration Of Survival Traits In The White-Nose Syndrome-Affected Big Brown Bat (Eptesicus Fuscus)

The widespread mortality of hibernating bats is associated with the emerging infectious disease white-nose syndrome (WNS), and has provoked a strong interest in understanding which bats will survive, and why? The ability of infected bats to resist WNS may depend upon variation in the expression of different characteristics. In a captive colony of big brown bats, I sought to characterize the phenotypic variability, repeatability, and survivability for several key ¿survival¿ traits, including: torpor patterns, microclimate preferences, and wound healing capacity. Torpor patterns were profiled using temperature sensitive dataloggers throughout the hibernation season, while microclimate preferences were quantified by using temperature-graded boxes and thermal imaging. In order to assess wound healing capacity, small wing biopsies were obtained from each bat and healing progress was tracked for one month. Individuals exhibited a wide range of phenotypes that were significantly influenced by sex and body condition. Repeatability estimates suggest that there is not a strong genetic basis for the observed variation in torpor patterns or microclimate preferences. Certain phenotypes (e.g., BMI) were associated with an increased probability of overwinter survivorship, which suggests a basis for intra-species differences in WNS susceptibility. The results from this project provide novel insight into what we know about ¿who will survive,¿ and will influence the direction and implementation of future conservation and mitigation strategies.