A batata-doce é uma das fontes de alimento mais importantes do mundo, sendo muito cultivada no Brasil por agricultores tradicionais. Os caiçaras, habitantes do litoral do Sudeste brasileiro, têm exercido enorme influência na manutenção da diversidade genética em muitas culturas, incluindo a batata-doce. Como os processos de mudanças socioeconômicas e agrícolas nesta região são muito rápidos e têm provocado alterações constantes nesses sistemas agroecológicos, pretendeu-se capturar o nível de diversidade genética mantida por estes agricultores, por meio da morfometria geométrica e caracteres morfoagronômicos, além de avaliar o potencial da cultura para a produção de etanol. Assim, 71 acessos coletados no litoral Norte e do Vale do Ribeira mais seis acessos de um antigo banco de germoplasma e três variedades comerciais de um produtor de Piracicaba foram utilizados nestas avaliações. Para a caracterização morfoagronômica, os acessos foram submetidos às avaliações, com base em 10 descritores quantitativos e 27 qualitativos. Nas avaliações quantitativas, o método de Tocher e UPGMA apresentaram concordância, indicando a produtividade como caráter fundamental na formação dos grupos, por outro lado, não existiu consistência na formação dos grupos entre os métodos ADCP e UPGMA, com base nos caracteres qualitativos. A maior parte da variabilidade encontrada ficou entre os acessos e não se observou qualquer estruturação espacial da varibilidade. A análise elíptica de Fourier (AEF) realizada em 1.437 folhas permitiu a extração dos seis primeiros componentes principais para explicar a maior parte da variabilidade existente nas amostras. A reconstrução do contorno foliar indicou que os dois primeiros componentes principais descreveram as variações quanto ao índice de lobação do limbo e as diferenças na profundidade do seio peciolar, sendo estes caracteres provavelmente de herança qualitativa e quantitativa, respectivamente. A análise multivariada de variância (MANOVA) revelou diferenças significativas entre os acessos avaliados, indicando a presença de variabilidade genética. O método UPGMA demonstrou a existência de grupos com folhas cordiformes, com três lóbulos e com cinco ou mais lóbulos. Na identificação do potencial de etanol foram avaliados os caracteres teor de amido, produtividade (t.ha-1), rendimento de amido, rendimento de etanol em litros por hectare (L.ha-1) e rendimento de etanol em litros por tonelada (L.t-1). O método de Tocher possibilitou a formação de nove grupos. Os acessos mais dissimilares e com média elevada para os caracteres indicaram a possibilidade de seleção de genótipos superiores. Os resultados obtidos nestas avaliações permitem inferir que (1) existe uma alta diversidade genética mantida pelos caiçaras, (2) a AEF pode ser utilizada com sucesso na avaliação da diversidade nesta espécie e (3) a batata-doce apresenta-se como fonte alternativa para geração de bioetanol. / Sweet potato is one of the most important food sources in the world and is widely cultivated in Brazil by traditional farmers. The native human population of the southeastern Brazilian coast, has exerted enormous influence in maintaining genetic diversity in many crops, including sweet potato. As the processes of socioeconomic and agricultural change in this region are very fast and have caused constant changes in their agroecological system, it was intended to capture the genetic diversity level maintained by these farmers through the geometric morphometrics and morphological traits, to evaluate the potential of the crop for the production of ethanol. Thus, 71 accessions collected in the Northern Coast of São Paulo State and in the coast of the Ribeira Valley region, in Southern São Paulo State, plus six accessions from a former germplasm bank and three commercial varieties from a farm in Piracicaba, SP, were used in these assessments. For morphoagronomic characterization, accessions were subjected to evaluation using 10 quantitative and 27 qualitative descriptors. In quantitative assessments, Tocher and UPGMA method showed agreement, indicating productivity as fundamental in the formation of groups. On the other hand, there was no consistency in the groups between the DAPC and UPGMA methods, based on qualitative characters. Most of the variability was found among the accessions and the genetic variability had no spatial structure. The elliptical Fourier analysis (EFA) performed on 1,437 leaves allowed the extraction of the first six principal components and explained most of the variability of the samples. The reconstruction of the leaf outline indicated that the first two principal components described the variation in the leaf blade lobation index and the differences in the depth of the petiole sinus, and these characters probably have qualitative and quantitative inheritance, respectively. Multivariate analysis of variance (MANOVA) revealed significant differences among accessions, indicating the presence of genetic variability. The UPGMA method showed the existence of groups with heart-shaped leaves, both with three lobes and five or more lobes. The potential for ethanol production was evaluated through the starch content, starch yield (t.ha-1), ethanol yield in liters per hectare (L.ha-1) and ethanol yield in liters per tonne (L.t-1). Tocher\'s method made possible the formation of nine groups. The most dissimilar accessions with high average for the traits indicated the possibility of selection of superior genotypes. The results obtained in these assessments allow us to infer that (1) there is a high genetic diversity maintained by the native population, (2) EFA can be successfully used in the evaluation of diversity in this species and (3) the sweet potato is presented as an alternative source to generate bioethanol.

A cultura da batata-doce assume papel importante no cenário agrícola nacional por ser considerada uma espécie altamente versátil, que consegue suprir as necessidades nutricionais da população, além de atualmente ser foco da cadeia de produção do etanol, pelo seu elevado teor de amido. Apesar da importância dessa cultura, ela é pouco estudada e, no que se refere ao melhoramento genético dessa espécie, os estudos são ainda mais escassos. Essa falta de informações acerca dos genótipos mais adaptados às condições de determinada região é um dos principais problemas enfrentados pelos produtores de batata-doce que não conseguem atingir o máximo de produtividade, pois as variedades utilizadas não conseguem expressar o seu potencial. Visando a aceleração dos programas de melhoramento, surge como alternativa a realização da seleção precoce, podendo-se realizar o descarte de materiais com características desfavoráveis nas primeiras gerações clonais. Para auxiliar na seleção precoce, a utilização de técnicas multivariadas como a análise GGE Biplot é de fundamental importância para se atingir sucesso na seleção. Dessa forma, os objetivos do presente trabalho foram (a) avaliar a eficiência da seleção precoce em batata-doce, bem como identificar possíveis correlações entre características morfológicas, para auxiliar na seleção de genótipos superiores; (b) identificar genótipos produtivos e que apresentem características de raiz favoráveis para o mercado e com elevado teor de amido para serem utilizados em futuros programas de melhoramento. Os experimentos foram realizados em casa de vegetação, onde foram avaliados em três épocas distintas, além de uma vez a campo para a mensuração dos caracteres relacionados à produção e ao teor de amido. Pelos resultados observados, nota-se que a utilização da técnica de seleção precoce em batata-doce pode não ser eficiente pelo comportamento que os genótipos assumiram no decorrer das avaliações, já que a correlação entre épocas foi muito baixa ou até mesmo inexistente, o que dificulta a seleção em etapas iniciais do programa. Porém, com relação às correlações entre as características em uma mesma época, nota-se que várias delas apresentaram correlações positivas, levando à interpretação de que se selecionarmos para uma determinada característica, automaticamente selecionaremos para outra correlacionada a esta. Os resultados para os caracteres produtivos indicam que existem genótipos que apresentam elevado potencial produtivo, superior à média nacional e também apresentam características desejáveis na forma e tamanho das raízes tuberosas. Além dessas características, algumas contêm elevado teor de amido, o que é altamente desejável para a indústria de biocombustíveis. Pode-se concluir que a técnica de seleção precoce não é recomendável para a cultura, mas existem características altamente correlacionadas em uma época específica. Existem genótipos que podem ser utilizados em programas de melhoramento, tanto pelo seu elevado potencial produtivo e características de raiz desejáveis quanto pela concentração de amido. / The culture of sweet potato plays an important role in the national agricultural scenario because it is considered a highly versatile species that can meet the nutritional needs of the population, in addition to currently being the focus of the ethanol supply chain, for their high starch content. Despite the importance of this crop, it is little studied and, in relation to the genetic improvement of this species, studies are still more scarce. This lack of information about the genotypes most adapted to the conditions of a given region is one of the main problems faced by sweet potato producers who fail to achieve maximum productivity, as the varieties used can not express their potential. Aiming at the acceleration of plant breeding programs, the alternative of performing early selection arises, and the disposal of materials with unfavorable characteristics can be carried out in the first clonal generations. And to assist in the early selection, using multivariate techniques such as GGE Biplot analysis is crucial to achieving success. Thus, the objectives of this study were (a) to evaluate the efficiency of early selection in sweet potatoes, as well as to identify possible correlations between morphological characteristics, in order to assist in the selection of superior genotypes; (b) to identifying productive genotypes that exhibit favorable root characteristics for the market and with high starch content for use in future breeding programs. The experiments were conducted both in greenhouse and in field conditions, where the traits related to production and starch content were assessed at three different times and one time, respectively. The results indicate that the use of the early selection technique in sweet potatoes may not be efficient, on the basis of the behavior shown by the genotypes in the assessments, since the correlation between assessment times was very low or even non-existent, making it difficult for selection to be applied in the initial stages of the program. However, regarding the correlations between the characteristics in the same assessment instance, it can be noted that several of them had positive correlations, implying that, if a particular feature is selected for, that automatically selects for others correlated to this. The results for the productive characters indicate that there are genotypes that have high yield potential, higher than the national average and that also have desirable characteristics regarding the shape and size of the tuberous roots. In addition to these features, some accessions have high starch content, which is highly desirable for the biofuel industry. It can be concluded that the early selection technique is not recommended for this crop, but there are nonetheless highly correlated characters at particular times. There are genotypes that can be utilized in breeding programs, both for their high yield potential associated to desirable root characteristics and for the concentration of starch.

In the present work a review of the new multivariate techniques and why they appear especiallysuited to the personality research is presented. Emerging models of personality  and advances in the measurement  of personality and psychopathology suggest that research in this field has ente­ red a stage of advanced development. The past two decades have shown importan! developments in statistics and measurement. Refinement of multivariate statistics has been especially importan! in personality assessment because of the complexity of relations among personality variables. Multivariate procedures provide the opportunity  to examine the complexity  of these interactions by providing methods of analysis for multiple variables. On the other hand, structural equation modeling and multivariate techniques for analyzing categorical variables have been developed. Multidimensional  scaling and item response theory are the last developments. / En este trabajo se realiza una revisión de las nuevas técnicas estadísticas y de su utilidad para la investigación en personalidad. Los nuevos modelos y los avances en la medición de la personalidad y la psicopatología sugieren que la investigación en este campo y en su evaluación han entrado en un estadio avanzado de desarrollo. En las dos últimas décadas se han producido importantes desarrollos en estadística y medición. El refinamiento de las técnicas de análisis multivariado ha sido fundamental en la evaluación de la personalidad debido a la complejidad de las relaciones entre sus variables. Los procedimientos de análisis multivariado proveen la oportunidad de examinar la complejidad de esas interacciones a través de métodos de análisis para variables múltiples. Por otra parte, se han desarrollado los modelos de ecuaciones estructurales y técnicas multivariadas para analizar variables categóricas. Los últimos desarrollos corresponden al escalamiento multidimensional y a la teoría de la respuesta al ítem.

A cultura da batata-doce assume papel importante no cenário agrícola nacional por ser considerada uma espécie altamente versátil, que consegue suprir as necessidades nutricionais da população, além de atualmente ser foco da cadeia de produção do etanol, pelo seu elevado teor de amido. Apesar da importância dessa cultura, ela é pouco estudada e, no que se refere ao melhoramento genético dessa espécie, os estudos são ainda mais escassos. Essa falta de informações acerca dos genótipos mais adaptados às condições de determinada região é um dos principais problemas enfrentados pelos produtores de batata-doce que não conseguem atingir o máximo de produtividade, pois as variedades utilizadas não conseguem expressar o seu potencial. Visando a aceleração dos programas de melhoramento, surge como alternativa a realização da seleção precoce, podendo-se realizar o descarte de materiais com características desfavoráveis nas primeiras gerações clonais. Para auxiliar na seleção precoce, a utilização de técnicas multivariadas como a análise GGE Biplot é de fundamental importância para se atingir sucesso na seleção. Dessa forma, os objetivos do presente trabalho foram (a) avaliar a eficiência da seleção precoce em batata-doce, bem como identificar possíveis correlações entre características morfológicas, para auxiliar na seleção de genótipos superiores; (b) identificar genótipos produtivos e que apresentem características de raiz favoráveis para o mercado e com elevado teor de amido para serem utilizados em futuros programas de melhoramento. Os experimentos foram realizados em casa de vegetação, onde foram avaliados em três épocas distintas, além de uma vez a campo para a mensuração dos caracteres relacionados à produção e ao teor de amido. Pelos resultados observados, nota-se que a utilização da técnica de seleção precoce em batata-doce pode não ser eficiente pelo comportamento que os genótipos assumiram no decorrer das avaliações, já que a correlação entre épocas foi muito baixa ou até mesmo inexistente, o que dificulta a seleção em etapas iniciais do programa. Porém, com relação às correlações entre as características em uma mesma época, nota-se que várias delas apresentaram correlações positivas, levando à interpretação de que se selecionarmos para uma determinada característica, automaticamente selecionaremos para outra correlacionada a esta. Os resultados para os caracteres produtivos indicam que existem genótipos que apresentam elevado potencial produtivo, superior à média nacional e também apresentam características desejáveis na forma e tamanho das raízes tuberosas. Além dessas características, algumas contêm elevado teor de amido, o que é altamente desejável para a indústria de biocombustíveis. Pode-se concluir que a técnica de seleção precoce não é recomendável para a cultura, mas existem características altamente correlacionadas em uma época específica. Existem genótipos que podem ser utilizados em programas de melhoramento, tanto pelo seu elevado potencial produtivo e características de raiz desejáveis quanto pela concentração de amido. / The culture of sweet potato plays an important role in the national agricultural scenario because it is considered a highly versatile species that can meet the nutritional needs of the population, in addition to currently being the focus of the ethanol supply chain, for their high starch content. Despite the importance of this crop, it is little studied and, in relation to the genetic improvement of this species, studies are still more scarce. This lack of information about the genotypes most adapted to the conditions of a given region is one of the main problems faced by sweet potato producers who fail to achieve maximum productivity, as the varieties used can not express their potential. Aiming at the acceleration of plant breeding programs, the alternative of performing early selection arises, and the disposal of materials with unfavorable characteristics can be carried out in the first clonal generations. And to assist in the early selection, using multivariate techniques such as GGE Biplot analysis is crucial to achieving success. Thus, the objectives of this study were (a) to evaluate the efficiency of early selection in sweet potatoes, as well as to identify possible correlations between morphological characteristics, in order to assist in the selection of superior genotypes; (b) to identifying productive genotypes that exhibit favorable root characteristics for the market and with high starch content for use in future breeding programs. The experiments were conducted both in greenhouse and in field conditions, where the traits related to production and starch content were assessed at three different times and one time, respectively. The results indicate that the use of the early selection technique in sweet potatoes may not be efficient, on the basis of the behavior shown by the genotypes in the assessments, since the correlation between assessment times was very low or even non-existent, making it difficult for selection to be applied in the initial stages of the program. However, regarding the correlations between the characteristics in the same assessment instance, it can be noted that several of them had positive correlations, implying that, if a particular feature is selected for, that automatically selects for others correlated to this. The results for the productive characters indicate that there are genotypes that have high yield potential, higher than the national average and that also have desirable characteristics regarding the shape and size of the tuberous roots. In addition to these features, some accessions have high starch content, which is highly desirable for the biofuel industry. It can be concluded that the early selection technique is not recommended for this crop, but there are nonetheless highly correlated characters at particular times. There are genotypes that can be utilized in breeding programs, both for their high yield potential associated to desirable root characteristics and for the concentration of starch.

A batata-doce é uma das fontes de alimento mais importantes do mundo, sendo muito cultivada no Brasil por agricultores tradicionais. Os caiçaras, habitantes do litoral do Sudeste brasileiro, têm exercido enorme influência na manutenção da diversidade genética em muitas culturas, incluindo a batata-doce. Como os processos de mudanças socioeconômicas e agrícolas nesta região são muito rápidos e têm provocado alterações constantes nesses sistemas agroecológicos, pretendeu-se capturar o nível de diversidade genética mantida por estes agricultores, por meio da morfometria geométrica e caracteres morfoagronômicos, além de avaliar o potencial da cultura para a produção de etanol. Assim, 71 acessos coletados no litoral Norte e do Vale do Ribeira mais seis acessos de um antigo banco de germoplasma e três variedades comerciais de um produtor de Piracicaba foram utilizados nestas avaliações. Para a caracterização morfoagronômica, os acessos foram submetidos às avaliações, com base em 10 descritores quantitativos e 27 qualitativos. Nas avaliações quantitativas, o método de Tocher e UPGMA apresentaram concordância, indicando a produtividade como caráter fundamental na formação dos grupos, por outro lado, não existiu consistência na formação dos grupos entre os métodos ADCP e UPGMA, com base nos caracteres qualitativos. A maior parte da variabilidade encontrada ficou entre os acessos e não se observou qualquer estruturação espacial da varibilidade. A análise elíptica de Fourier (AEF) realizada em 1.437 folhas permitiu a extração dos seis primeiros componentes principais para explicar a maior parte da variabilidade existente nas amostras. A reconstrução do contorno foliar indicou que os dois primeiros componentes principais descreveram as variações quanto ao índice de lobação do limbo e as diferenças na profundidade do seio peciolar, sendo estes caracteres provavelmente de herança qualitativa e quantitativa, respectivamente. A análise multivariada de variância (MANOVA) revelou diferenças significativas entre os acessos avaliados, indicando a presença de variabilidade genética. O método UPGMA demonstrou a existência de grupos com folhas cordiformes, com três lóbulos e com cinco ou mais lóbulos. Na identificação do potencial de etanol foram avaliados os caracteres teor de amido, produtividade (t.ha-1), rendimento de amido, rendimento de etanol em litros por hectare (L.ha-1) e rendimento de etanol em litros por tonelada (L.t-1). O método de Tocher possibilitou a formação de nove grupos. Os acessos mais dissimilares e com média elevada para os caracteres indicaram a possibilidade de seleção de genótipos superiores. Os resultados obtidos nestas avaliações permitem inferir que (1) existe uma alta diversidade genética mantida pelos caiçaras, (2) a AEF pode ser utilizada com sucesso na avaliação da diversidade nesta espécie e (3) a batata-doce apresenta-se como fonte alternativa para geração de bioetanol. / Sweet potato is one of the most important food sources in the world and is widely cultivated in Brazil by traditional farmers. The native human population of the southeastern Brazilian coast, has exerted enormous influence in maintaining genetic diversity in many crops, including sweet potato. As the processes of socioeconomic and agricultural change in this region are very fast and have caused constant changes in their agroecological system, it was intended to capture the genetic diversity level maintained by these farmers through the geometric morphometrics and morphological traits, to evaluate the potential of the crop for the production of ethanol. Thus, 71 accessions collected in the Northern Coast of São Paulo State and in the coast of the Ribeira Valley region, in Southern São Paulo State, plus six accessions from a former germplasm bank and three commercial varieties from a farm in Piracicaba, SP, were used in these assessments. For morphoagronomic characterization, accessions were subjected to evaluation using 10 quantitative and 27 qualitative descriptors. In quantitative assessments, Tocher and UPGMA method showed agreement, indicating productivity as fundamental in the formation of groups. On the other hand, there was no consistency in the groups between the DAPC and UPGMA methods, based on qualitative characters. Most of the variability was found among the accessions and the genetic variability had no spatial structure. The elliptical Fourier analysis (EFA) performed on 1,437 leaves allowed the extraction of the first six principal components and explained most of the variability of the samples. The reconstruction of the leaf outline indicated that the first two principal components described the variation in the leaf blade lobation index and the differences in the depth of the petiole sinus, and these characters probably have qualitative and quantitative inheritance, respectively. Multivariate analysis of variance (MANOVA) revealed significant differences among accessions, indicating the presence of genetic variability. The UPGMA method showed the existence of groups with heart-shaped leaves, both with three lobes and five or more lobes. The potential for ethanol production was evaluated through the starch content, starch yield (t.ha-1), ethanol yield in liters per hectare (L.ha-1) and ethanol yield in liters per tonne (L.t-1). Tocher\'s method made possible the formation of nine groups. The most dissimilar accessions with high average for the traits indicated the possibility of selection of superior genotypes. The results obtained in these assessments allow us to infer that (1) there is a high genetic diversity maintained by the native population, (2) EFA can be successfully used in the evaluation of diversity in this species and (3) the sweet potato is presented as an alternative source to generate bioethanol.

It is generally recognized that the magnitude of recreation resource impacts should be judged by their severity and spatial qualities, including extent, distribution, and association. Previous investigations, however, have primarily focused on assessing the severity of impacts, with limited examination of spatial qualities. The goal of this dissertation was to expand our understanding of the spatial dimension of recreation resource impacts and their assessment and evaluation. Two empirical data sets collected from a comprehensive recreation impact assessment and monitoring project in Great Smoky Mountains National Park provided the basis for the analyses. Three spatial issues were examined and presented as three papers, designed for journal submission. The purpose of the first paper was to improve our understanding of the dimensional structure and spatial patterns of camping impacts by means of multivariate analyses and mapping. Factor analysis of 195 established campsites on eight impact indicator variables revealed three dimensions of campsite impact: land disturbance, soil and groundcover damage, and tree-related damage. Cluster analysis yielded three distinctive campsite types that characterize both the intensity and areal extent of camping impacts. Spatial patterns and site attributes of these three campsite types and an additional group of primitive campsites were illustrated and discussed. The purpose of the second paper was to examine the influence of sampling interval on the accuracy of selected trail impact indicator estimates for the widely applied systematic point sampling method. A resampling-simulation method was developed and applied. Simulation results indicated that using systematic point sampling for estimating lineal extent of trail impact problems can achieve an excellent level of accuracy at sampling intervals of less than 100 m, and a reasonably good level of accuracy at intervals between 100 and 500 m. The magnitude of accuracy loss could be higher when the directions of loss are not considered. The responses of accuracy loss on frequency of occurrence estimates to increasing sampling intervals were consistent across impact types, approximating an inverse asymptotic curve. These findings suggest that systematic point sampling using an interval of less than 500 m can be an appropriate method for estimating the lineal extent, but not for estimating occurrence of trail impacts. Further investigations are called for to examine the generalizability of these results to other areas. The purpose of the third paper was to expand the scope of indices used for evaluating recreation resource impacts. Two specific objectives were to synthesize the recreation ecology and recreation resource management literature on the use of spatial indicators and indices, and to propose and apply selected spatial indices that are mostly lacking in the literature. Three spatial indices primarily adapted from the geography and ecology literature were proposed for application in recreation impact evaluation. Application results demonstrated that the Lorenz curve and associated Gini coefficient, and the linear nearest-neighbor analysis and associated LR ratio were effective in quantifying the spatial distribution patterns of trail impacts at landscape and trail scales, respectively. Application results of the third index, the impact association index, were less promising and require further refinements. Management implications and future directions of research were discussed in light of the findings of this dissertation. As the field of recreation ecology is emerging, this dissertation has demonstrated: (1) the value of recreation impact assessment and monitoring programs in providing data for examining the spatial dimension of impacts, and (2) the utility of spatial analytical approaches in understanding recreation impact assessment and evaluation. / Ph. D.

The risks associated with a soil contaminated by polycyclic aromatic hydrocarbons (PAHs) are generally assessed by measuring individual PAHs in the soil and correlating the obtained amounts to known adverse biological effects of the PAHs. The validity of such a risk estimation is dependent on the presence of additional compounds, the availability of the compounds (including the PAHs), and the methods used to correlate the measured chemical data and biological effects. In the work underlying this thesis the availability, chemical composition and biological effects of PAHs in samples of soils from PAH-contaminated environments were examined. It can be concluded from the results presented in the included papers that the PAHs in the studied soils from industrial sites were not generally physically trapped in soil material, indicating that the availability of the PAHs was not restricted in this sense. However, the bioavailable fraction of the PAHs, as assessed by bioassays with the earthworm Eisenia Fetida, could not be assessed by a number of abiotic techniques (including: solid phase micro extraction, SPME; use of semi-permeable membrane devices, SPMDs; leaching with various solvent mixtures, leaching using additives, and sequential leaching) and it seems to be difficult to find a chemical method that can accurately assess the bioavailability of PAHs. Furthermore, it was shown that PAH-polluted samples may be extensively chemically characterized by GC-TOFMS using peak deconvolution, and over 900 components can be resolved in a single run. The chemical characterization also revealed that samples that appeared to be similar in terms of their PAH composition were heterogeneous in terms of their overall composition. Finally, single compounds from this large set of compounds, which correlated with different biological effects, could be identified using the multivariate technique partial least squares projections to latent structures (PLS). This indicates that PLS may provide a valid alternative to Effect Directed Analysis (EDA), an established method for finding single compounds that correlate to the toxicity of environmental samples. Thus, the instrumentation and data evaluation tools used in this thesis are clearly capable of providing a broad chemical characterization as well as linking the obtained chemical data to results from bioassays. However, the link between the chemical analyses and the biological tests could be improved as as an organic solvent that solubilised virtually all of the contaminants was used during the chemical analysis while the biological tests were performed in an aqueous solution with limited solubility for a number of compounds. Consequently the compounds probably have a different impact in the biological tests than their relative abundance in profiles obtained by standard chemical analyses suggests. The availability and bioavailability of contaminants in soil also has to be studied further, and such future studies should focus on the molecular interactions between the contaminants and different compartments of the soil. By doing so, detailed knowledge could be obtained which could be applied to a number of different contaminants and soil types. Such studies would generate the data needed for molecular-based modelling of availability and bioavailability, which would be a big step forward compared to current risk assessment practices.

Σκοπός της εργασίας αυτής είναι να εφαρμόσουμε την Παραγοντική Ανάλυση στο δείγμα μας, έτσι ώστε να ανιχνεύσουμε και να περιγράψουμε τις καταναλωτικές συνήθειες του Ελληνικού πληθυσμού ως προς την κατανάλωση 9 κατηγοριών αλκοολούχων ποτών. Η εφαρμογή της μεθόδου γίνεται με την χρήση του στατιστικού προγράμματος SPSS. Στο πρώτο κεφάλαιο παρουσιάζεται η οικογένεια μεθόδων επίλυσης του προβλήματος και στο δεύτερο η μέθοδος που επιλέχτηκε για την επίλυση, η Παραγοντική Ανάλυση. Προσδιορίζουμε το αντικείμενο, τα στάδια σχεδιασμού και τις προϋποθέσεις της μεθόδου, καθώς και τα κριτήρια αξιολόγησης των αποτελεσμάτων. Τα κεφάλαια που ακολουθούν αποτελούν το πρακτικό μέρος της εργασίας. Στο 3ο κεφάλαιο αναφέρουμε την πηγή των δεδομένων μας και την διεξαγωγή του τρόπου συλλογής τους. Ακολουθεί ο εντοπισμός των «χαμένων» απαντήσεων και εφαρμόζεται η Ανάλυση των Χαμένων Τιμών (Missing Values Analysis) για τον προσδιορισμό του είδους αυτών και την αποκατάσταση τους στο δείγμα. Στην συνέχεια παρουσιάζουμε το δείγμα μας με τη βοήθεια της περιγραφικής στατιστικής και τέλος δημιουργούμε και περιγράφουμε το τελικό μητρώο δεδομένων το οποίο θα αναλύσουμε παραγοντικά. Στο 4ο και τελευταίο κεφάλαιο διερευνάται η καταλληλότητα του δείγματος για την εφαρμογή της Παραγοντικής Ανάλυσης με τον έλεγχο της ικανοποίησης των προϋποθέσεων της μεθόδου. Ακολουθεί η παράλληλη μελέτη του δείγματος συμπεριλαμβάνοντας και μη στην επίλυση τις ακραίες τιμές (outliers) που εντοπίστηκαν. Καταλήγοντας στο συμπέρασμα ότι οι ακραίες τιμές δεν επηρεάζουν τα αποτελέσματα της μεθόδου, εφαρμόζουμε την Παραγοντική Ανάλυση με τη χρήση της μεθόδου των κυρίων συνιστωσών και αναφέρουμε αναλυτικά όλα τα βήματα μέχρι να καταλήξουμε στα τελικά συμπεράσματα μας. / The purpose of this paper is to apply the Factor Analysis to our sample in order to detect and describe patterns concerning the consumption of 9 categories of alcoholic beverages by the Greek population. For the application of the method, we use the statistical program SPSS. The first chapter presents the available methods for solving this problem and the second one presents the chosen method, namely Factor Analysis. We specify the objective of the analysis, the design and the critical assumptions of the method, as well as the criteria for the evaluation of the results. In the third chapter we present the source of our data and how the sampling was performed. Furthermore, we identify the missing values and we apply the Missing Values Analysis to determine their type. We also present our sample using descriptive statistics and then create and describe the final matrix which we analyze with Factor Analysis. In the fourth and last chapter we investigate the suitability of our samples for applying Factor Analysis. In the sequence, we perform the parallel study of our sample both including and not including the extreme values that we identified (which we call “outliers”). We conclude that the outliers do not affect the results of our method and then apply Factor Analysis using the extraction method of Principal Components. We also mention in detail all steps until reaching our final conclusions.

La nutrition est un facteur de risque modifiable pour le cancer puisqu'environ un tiers des cas pourraient être évités en adoptant une meilleure alimentation. La relation entre nutrition et cancer est complexe, et son étude est enrichie par de nouveaux défis apportés par les récentes avancées technologiques dans le domaine des « -omiques ». Cette thèse a pour but de développer de nouvelles approches biostatistiques afin d'étudier la relation entre nutrition et cancer au sein de la cohorte EPIC. Pour ce faire, l'applicabilité de nouvelles méthodologies multivariées dans le domaine de l'épidémiologie nutritionnelle a été étudiée.Une nouvelle méthode multivariée pour la réduction de la dimensionnalité, le Treelet Transform (TT), a été examinée afin d'extraire des patterns de nutriments issus de questionnaires. Les patterns ainsi obtenus par le TT étaient plus facilement interprétables que par les méthodes classiques. Ensuite, un cadre analytique pour implémenter le concept du « meeting-in-the-middle » (MITM) a été développé et appliqué dans 2 études cas-témoin nichées sur le cancer hépatocellulaire avec des données métabolomiques. Le MITM cherche à identifier des biomarqueurs qui soient à la fois des marqueurs de certaines expositions passées et des prédicteurs de maladies. L'implémentation s'est focalisée sur l'application de la PLS et de l'analyse de médiation.Enfin, nous avons examinés la relation entre les niveaux plasmatiques de 60 acides gras issus de biomarqueurs et le risque de cancer du sein dans une étude cas-témoin nichée dans EPIC.Cette thèse servira de base pour des applications épidémiologiques futures examinant la relation nutrition-cancer / Diet is a modifiable risk factor for many cancers. It has been estimated that about a third of cancer cases can be prevented by complying with a healthy diet and adhering to the recommendations in terms of nutrition. The nutrition-cancer relationship is a complex one, and its study is currently at a turning point with the opportunity and challenges brought by the recent technological advances in the fields of « -omics ».This thesis aims to develop new biostatistical approaches to investigate the nutrition-cancer relation within the European Prospective Investigation into Cancer and nutrition (EPIC) study. To do so, the applicability of new methodologies in the field of nutritional epidemiology has been examined.First, a new multivariate dimension reduction method, the Treelet Transform (TT) was applied to extract nutrient patterns relying on questionnaire data. The extracted patterns were more easily interpretable than those obtained with more classical methods.Then, an analytical framework was conceived for the « meeting-in-the-middle » (MITM) principle and applied to two nested case-control studies on hepatocellular carcinoma, with targeted and untargeted metabolomics data. The MITM aims to identify overlap biomarkers of certain exposures that are at the same time predictive of disease outcomes. The implementation focused on the application of partial least squares and mediation analyses. Last, the association between 60 plasma fatty acids levels assessed from biomarkers and breast cancer risk was examined in a nested case-control study in EPIC. This thesis will serve as a basis for future epidemiological applications looking into the nutrition-cancer relation

[ES] Esta tesis doctoral se centra en el estudio, implementación y aplicación de técnicas de aprendizaje automático y estadística multivariante en el emergente campo de la analítica deportiva, concretamente en el fútbol. Se aplican procedimientos comunmente utilizados y métodos nuevos para resolver cuestiones de investigación en diferentes áreas del análisis del fútbol, tanto en el ámbito del rendimiento deportivo como en el económico. Las metodologías empleadas en esta tesis enriquecen las técnicas utilizadas hasta el momento para obtener una visión global del comportamiento de los equipos de fútbol y pretenden ayudar al proceso de toma de decisiones. Además, la metodología se ha implementado utilizando el software estadístico libre R y datos abiertos, lo que permite la replicabilidad de los resultados. Esta tesis doctoral pretende contribuir a la comprensión de los modelos de aprendizaje automático y estadística multivariante para la predicción analítica deportiva, comparando su capacidad predictiva y estudiando las variables que más influyen en los resultados predictivos de estos modelos. Así, siendo el fútbol un juego de azar donde la suerte juega un papel importante, se proponen metodologías que ayuden a estudiar, comprender y modelizar la parte objetiva de este deporte. Esta tesis se estructura en cinco bloques, diferenciando cada uno en función de la base de datos utilizada para alcanzar los objetivos propuestos. El primer bloque describe las áreas de estudio más comunes en la analítica del fútbol y las clasifica en función de los datos utilizados. Esta parte contiene un estudio exhaustivo del estado del arte de la analítica del fútbol. Así, se recopila parte de la literatura existente en función de los objetivos alcanzados, conjuntamente con una revisión de los métodos estadísticos aplicados. Estos modelos son los pilares sobre los que se sustentan los nuevos procedimientos aquí propuestos. El segundo bloque consta de dos capítulos que estudian el comportamiento de los equipos que alcanzan la Liga de Campeones o la Europa League, descienden a segunda división o permanecen en mitad de la tabla. Se proponen varias técnicas de aprendizaje automático y estadística multivariante para predecir la posición de los equipos a final de temporada. Una vez realizada la predicción, se selecciona el modelo con mejor precisión predictiva para estudiar las acciones de juego que más discriminan entre posiciones. Además, se analizan las ventajas de las técnicas propuestas frente a los métodos clásicos utilizados hasta el momento. El tercer bloque consta de un único capítulo en el que se desarrolla un código de web scraping para facilitar la recuperación de una nueva base de datos con información cuantitativa de las acciones de juego realizadas a lo largo del tiempo en los partidos de fútbol. Este bloque se centra en la predicción de los resultados de los partidos (victoria, empate o derrota) y propone la combinación de una técnica de aprendizaje automático, random forest, y la regresión Skellam, un método clásico utilizado habitualmente para predecir la diferencia de goles en el fútbol. Por último, se compara la precisión predictiva de los métodos clásicos utilizados hasta ahora con los métodos multivariantes propuestos. El cuarto bloque también comprende un único capítulo y pertenece al área económica del fútbol. En este capítulo se aplica un novedoso procedimiento para desarrollar indicadores que ayuden a predecir los precios de traspaso. En concreto, se muestra la importancia de la popularidad a la hora de calcular el valor de mercado de los jugadores, por lo que este capítulo propone una nueva metodología para la recogida de información sobre la popularidad de los jugadores. En el quinto bloque se revelan los aspectos más relevantes de esta tesis para la investigación y la analítica en el fútbol, incluyendo futuras líneas de trabajo. / [CA] Aquesta tesi doctoral se centra en l'estudi, implementació i aplicació de tècniques d'aprenentatge automàtic i estadística multivariant en l'emergent camp de l'analítica esportiva, concretament en el futbol. S'apliquen procediments comunament utilitzats i mètodes nous per a resoldre qu¿estions d'investigació en diferents àrees de l'anàlisi del futbol, tant en l'àmbit del rendiment esportiu com en l'econòmic. Les metodologies emprades en aquesta tesi enriqueixen les tècniques utilitzades fins al moment per a obtindre una visió global del comportament dels equips de futbol i pretenen ajudar al procés de presa de decisions. A més, la metodologia s'ha implementat utilitzant el programari estadístic lliure R i dades obertes, la qual cosa permet la replicabilitat dels resultats. Aquesta tesi doctoral pretén contribuir a la comprensió dels models d'aprenentatge automàtic i estadística multivariant per a la predicció analítica esportiva, comparant la seua capacitat predictiva i estudiant les variables que més influeixen en els resultats predictius d'aquests models. Així, sent el futbol un joc d'atzar on la sort juga un paper important, es proposen metodologies que ajuden a estudiar, comprendre i modelitzar la part objectiva d'aquest esport. Aquesta tesi s'estructura en cinc blocs, diferenciant cadascun en funció de la base de dades utilitzada per a aconseguir els objectius proposats. El primer bloc descriu les àrees d'estudi més comuns en l'analítica del futbol i les classifica en funció de les dades utilitzades. Aquesta part conté un estudi exhaustiu de l'estat de l'art de l'analítica del futbol. Així, es recopila part de la literatura existent en funció dels objectius aconseguits, conjuntament amb una revisió dels mètodes estadístics aplicats. Aquests models són els pilars sobre els quals se sustenten els nous procediments ací proposats. El segon bloc consta de dos capítols que estudien el comportament dels equips que aconsegueixen la Lliga de Campions o l'Europa League, descendeixen a segona divisió o romanen a la meitat de la taula. Es proposen diverses tècniques d'aprenentatge automàtic i estadística multivariant per a predir la posició dels equips a final de temporada. Una vegada realitzada la predicció, se selecciona el model amb millor precisió predictiva per a estudiar les accions de joc que més discriminen entre posicions. A més, s'analitzen els avantatges de les tècniques proposades enfront dels mètodes clàssics utilitzats fins al moment. El tercer bloc consta d'un únic capítol en el qual es desenvolupa un codi de web scraping per a facilitar la recuperació d'una nova base de dades amb informació quantitativa de les accions de joc realitzades al llarg del temps en els partits de futbol. Aquest bloc se centra en la predicció dels resultats dels partits (victòria, empat o derrota) i proposa la combinació d'una tècnica d'aprenentatge automàtic, random forest, i la regressió Skellam, un mètode clàssic utilitzat habitualment per a predir la diferència de gols en el futbol. Finalment, es compara la precisió predictiva dels mètodes clàssics utilitzats fins ara amb els mètodes multivariants proposats. El quart bloc també comprén un únic capítol i pertany a l'àrea econòmica del futbol. En aquest capítol s'aplica un nou procediment per a desenvolupar indicadors que ajuden a predir els preus de traspàs. En concret, es mostra la importància de la popularitat a l'hora de calcular el valor de mercat dels jugadors, per la qual cosa aquest capítol proposa una nova metodologia per a la recollida d'informació sobre la popularitat dels jugadors. En el cinqué bloc es revelen els aspectes més rellevants d'aquesta tesi per a la investigació i l'analítica en el futbol, incloent-hi futures línies de treball. / [EN] This doctoral thesis focuses on studying, implementing, and applying machine learning and multivariate statistics techniques in the emerging field of sports analytics, specifically in football. Commonly used procedures and new methods are applied to solve research questions in different areas of football analytics, both in the field of sports performance and in the economic field. The methodologies used in this thesis enrich the techniques used so far to obtain a global vision of the behaviour of football teams and are intended to help the decision-making process. In addition, the methodology was implemented using the free statistical software R and open data, which allows for reproducibility of the results. This doctoral thesis aims to contribute to the understanding of the behaviour of machine learning and multivariate models for analytical sports prediction, comparing their predictive capacity and studying the variables that most influence the predictive results of these models. Thus, since football is a game of chance where luck plays an important role, this document proposes methodologies that help to study, understand, and model the objective part of this sport. This thesis is structured into five blocks, differentiating each according to the database used to achieve the proposed objectives. The first block describes the most common study areas in football analytics and classifies them according to the available data. This part contains an exhaustive study of football analytics state of the art. Thus, part of the existing literature is compiled based on the objectives achieved, with a review of the statistical methods applied. These methods are the pillars on which the new procedures proposed here are based. The second block consists of two chapters that study the behaviour of teams concerning the ranking at the end of the season: top (qualifying for the Champions League or Europa League), middle, or bottom (relegating to a lower division). Several machine learning and multivariate statistical techniques are proposed to predict the teams' position at the season's end. Once the prediction has been made, the model with the best predictive accuracy is selected to study the game actions that most discriminate between positions. In addition, the advantages of our proposed techniques compared to the classical methods used so far are analysed. The third block consists of a single chapter in which a web scraping code is developed to facilitate the retrieval of a new database with quantitative information on the game actions carried out over time in football matches. This block focuses on predicting match outcomes (win, draw, or loss) and proposing the combination of a machine learning technique, random forest, and Skellam regression model, a classical method commonly used to predict goal difference in football. Finally, the predictive accuracy of the classical methods used so far is compared with the proposed multivariate methods. The fourth block also comprises a single chapter and pertains to the economic football area. This chapter applies a novel procedure to develop indicators that help predict transfer fees. Specifically, it is shown the importance of popularity when calculating the players' market value, so this chapter is devoted to propose a new methodology for collecting players' popularity information. The fifth block reveals the most relevant aspects of this thesis for research and football analytics, including future lines of work. / Malagón Selma, MDP. (2023). Machine Learning and Multivariate Statistical Tools for Football Analytics [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/197630