To improve fungal identification using a single DNA sequence, I introduce the Barcode Similarity Group (BSG) defined as a cluster of sequences that share greater than or equal to a threshold amount of genetic similarity with each other. As a test case, I created 393 BSGs from 2463 Cortinarius ITS sequences using a 94% similarity cut-off value in DOTUR. Some BSGs may contain multiple species. The BSG database was used to label environmental sequences, find misidentified or mislabeled sequences, and find potential cryptic species and novel species. Expert taxonomists will be needed to perform detailed morphological and phylogenetic studies to identify the individual species within each BSG. The main advantage of using BSGs is that it clusters together sequences using total genetic relatedness and does not rely on any taxonomy for identification. A website was created where the RDP Classifier is used to classify a query sequence into a BSG.

To improve fungal identification using a single DNA sequence, I introduce the Barcode Similarity Group (BSG) defined as a cluster of sequences that share greater than or equal to a threshold amount of genetic similarity with each other. As a test case, I created 393 BSGs from 2463 Cortinarius ITS sequences using a 94% similarity cut-off value in DOTUR. Some BSGs may contain multiple species. The BSG database was used to label environmental sequences, find misidentified or mislabeled sequences, and find potential cryptic species and novel species. Expert taxonomists will be needed to perform detailed morphological and phylogenetic studies to identify the individual species within each BSG. The main advantage of using BSGs is that it clusters together sequences using total genetic relatedness and does not rely on any taxonomy for identification. A website was created where the RDP Classifier is used to classify a query sequence into a BSG.

Orientador: Ana Maria Goulart de Azevedo Tozzi / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-09T03:16:51Z (GMT). No. of bitstreams: 1 Meireles_JoseEduardodeCarvalho_M.pdf: 5457639 bytes, checksum: 2254e34efd86c3760ca5a245abf9eaf6 (MD5) Previous issue date: 2007 / Resumo: Poecilanthe (Leguminosae, Papilionoideae, Brongniartieae) é em gênero sul-americano que inclui atualmente dez espécies. A heterogeneidade morfológica e química encontrada em Poecilanthe dificulta sua circunscrição e coloca em dúvida sua monofilia. Além disso, limites interespecíficos imprecisos e falta de chave de identificação dificultam o reconhecimento das espécies. Este trabalho tem como objetivos testar a monofilia de Poecilanthe e estabelecer as relações entre suas espécies, bem como revisar a taxonomia do gênero. Para tanto, uma análise filogenética de máxima parcimônia baseada em caracteres morfológicos e seqüências de ITS/5.8S (nrDNA) foi realizada. Como subsídio para a análise cladística, foi feito um estudo sobre a morfologia das sementes e embriões de Poecilanthe, que resultou no reconhecimento de quatro padrões distintos de morfologia. Os resultados da filogenia mostram que Poecilanthe não é um gênero monofilético, sendo composto por três clados parafiléticos em relação à tribo. Estes três clados foram caracterizados morfologicamente e considerados como gêneros distintos. Poecilanthe é recircunscrito para incluir apenas as espécies extra-amazônicas (Poecilanthe s.s.), compreendendo então seis espécies. O gênero Amphiodon é restabelecido, e P. ovalifolia combinada neste. Um gênero novo é descrito para incluir P. amazonica e P. hostmannii. Cada um destes gêneros foi tratado taxonomicamente, constando em cada tratamento descrições, ilustrações e chave para a identificação das espécies / Abstract: The genus Poecilanthe (Leguminosae, Papilionoideae, Brongniartieae) currently comprises ten South-American species. The morphological and chemical diversity that is found within this genus renders its circumscription imprecise and brings Poecilanthe¿s monophyly into question. This work aims to test the monophyly of Poecilanthe and to revise the taxonomy of the genus. A parsimony analysis based on both morphological and ITS/5.8S data was carried out. In order to provide characters to the cladistic analysis, the morphology of the seeds and embryos of Poecilanthe was analyzed, and resulted in the identification of four different morphological patterns. The phylogeny does not support Poecilanthe as monophyletic, but resolves three different well-supported lineages that are paraphyletic with respect to the tribe. These clades are morphologically characterized and ranked at the generic level. Poecilanthe is recircumscribed to include the six extra-Amazonian species only. The genus Amphiodon is reinstated and P. ovalifolia is combined. Poecilante amazonica and P. hostmannii are segregated into a new genus. Each genus was revised and descriptions, illustrations and identification key for the species are presented. / Mestrado / Biologia Vegetal / Mestre em Biologia Vegetal

Quinoa (Chenopodium quinoa Willd.) is a pseudocereal native to the Andean region of South America and a staple crop for subsistence farmers in the altiplano of Bolivia and Peru. Downy mildew is the most significant disease of quinoa caused by the pathogen Peronospora farinosa f.sp. chenopodii Byford. This disease greatly impacts quinoa crops with yield losses up to 99%. As fungicides are expensive for farmers, the development of resistant cultivars appears to be the most efficient means for controlling downy mildew. The quinoa germplasm bank contains high amounts of genetic diversity, some of which exhibit mildew resistance. Methods for evaluating mildew severity are important for finding resistant genotypes that are useful in breeding programs. The main objectives of this study were to evaluate and investigate downy mildew resistance in quinoa through several different methods. A simple inoculation method was developed for downy mildew disease assessment by placing a damp piece of cheesecloth on a leaf, pipetting a known spore solution onto the cloth, and subjecting the plants to specific humidity cycles in a growth chamber. After inoculation of five quinoa-breeding lines in a growth chamber, accession 0654 was found to be the most resistant, while genotypes NL6 and Sayana showed moderate resistance. Each of these genotypes displayed some potential for resistance breeding programs. Investigation of the growth and development of P. farinosa through resistant and susceptible quinoa genotypes revealed fewer sporangiophores, hyphal strands, and haustoria among leaf tissues of accession 0654 than in the susceptible Chucapaca cultivar. Peronospora farinosa growth was detected in leaf, petiole, and stem tissues with polymerase chain reaction (PCR) using ITSP primers designed from the internal transcribed spacer (ITS) region of the pathogen. Scanning electron microscopy (SEM) also revealed that P. farinosa penetrated stomata via appressoria, secreted extracellular matrices during sporangia germination, grew intercellularly in leaf and petiole tissues, and exited leaf tissue through stomata. Future research requiring knowledge of resistant quinoa genotypes, P. farinosa growth and development, or inoculation methods for large numbers of small quinoa plants would benefit from this report.

Molecular and morphologic studies were used to determine the evolution, classification and differentiation of Nymphaea odorata. Molecular analyses of the nuclear internal transcribed spacer (ITS) region, the chloroplast trnL-F region, and inter-simple sequence repeat (ISSR) markers determined the variation present between and within two species of Nymphaea. The ITS region resulted in a phylogeny depicting strong separation between species (N. mexicana and N. odorata) and some separation between N. odorata's subspecies. The ITS region contained polymorphisms, which upon SAHN clustering and principle coordinate (PCOA) and minimum spanning tree (MST) analyses produced groups similar to the clades in the ITS phylogeny. Sixteen accessions were chosen for trnL-F analysis, where a subspecies-specific molecular marker was found. In most accessions the marker confirmed the original subspecies classification. Molecular analyses using ISSRs characterized among population variation in N. odorata and N. mexicana using five primers. ISSR markers among populations were highly variable within a species and were used in UPGMA, PCOA and MST analysis, which resulted in separation between the subspecies. Both univariate and multivariate analyses were performed on quantitative and qualitative morphological characters. An analysis of variance resulted in six morphological characteristics that were statistically significant (P< 0.05), the majority being leaf blade characteristics. Multivariate statistics of principle component analysis and discriminate analysis resulted in groups for each subspecies, both emphasized the importance of quantitative leaf blade characteristics. Overall, both morphology and molecular characteristics supported the classification of subspecies for ssp. odorata and ssp. tuberosa, due a lack of strong segregation of characteristics. / Master of Science

No description available.

No description available.

The present work aims to determine the physiological and sanitary quality of Sweet sorghum (Sorghum bicolor (L.) Moench) seeds, as well as to identify pathogens associated with seed, their transmission to seedlings and the subsequent pathogenicity of isolates obtained, In addition, molecularly identify the fungal species pathogenic to this crop. The experiments were carried out in the Teaching and Seed Research Laboratory (TSRL), of the Plant Engineering Department; In the Elocy Minussi Phytopathology Laboratory, Department of Plant Protection, and at the Biological Institute of São Paulo. Sweet sorghum seeds were used, all without chemical treatment. Sanitary quality was evaluated by sanity test, and physiological characteristics by germination and vigor tests (seedling length, dry mass, emergence, rate of emergence and accelerated aging). It was performed the test of transmission of the pathogens associated to the seeds and the subsequent pathogenicity of the obtained isolates, culminating with the molecular characterization of the identified pathogens, in which were sequenced the Internal Transcribed Spacer (ITS) genomic regions and the Elongation Factor 1 - alpha (TEF1-α) gene. The design used was the completely randomized design, with four cultivars of Sweet sorghum (BRS 506, F19, BRS 511 and BRS 509); For the evaluation of pathogenicity, the factorial scheme is represented by four cultivars and three isolates of Fusarium spp., besides the witness. The seeds of the BRS 509 cultivar were considered to have lower physiological quality than the other cultivars. The DNA sequencing allowed identifying the Fusarium thapsinum species as a pathogenic agent in the sweet sorghum crop, and proven its transmission via seeds. / O presente trabalho teve como objetivo determinar a qualidade fisiológica e sanitária de sementes de cultivares de sorgo sacarino (Sorghum bicolor (L.) Moench), bem como identificar os patógenos associados à semente, sua transmissão às plântulas e a posterior patogenicidade de isolados obtidos, além disso, identificar molecularmente as espécies fúngicas patogênicas a esta cultura. Os experimentos foram realizados no Laboratório Didático e de Pesquisas em Sementes (LDPS), do Departamento de Fitotecnia; no Laboratório de Fitopatologia Elocy Minussi, do Departamento de Defesa Fitossanitária e, no Instituto Biológico de São Paulo. Foram utilizadas sementes de sorgo sacarino, todas sem tratamento químico. A qualidade sanitária foi avaliada pelo teste de sanidade, e as características fisiológicas por meio dos testes de germinação e de vigor (comprimento de plântulas, massa seca, emergência, índice de velocidade de emergência e envelhecimento acelerado). Foi realizado o teste de transmissão dos patógenos associados à semente e a posterior patogenicidade dos isolados fúngicos obtidos, culminando com a caracterização molecular dos patógenos identificados, na qual foram sequenciadas as regiões genômicas Internal Transcribed Spacer (ITS) e o gene do fator de elongação 1-α (TEF1α). O delineamento utilizado foi o inteiramente casualizado com quatro cultivares de sorgo sacarino (BRS 506, Fepagro 19, BRS 511 e BRS 509); já para a avaliação da patogenicidade, o esquema fatorial foi representado pelas quatro cultivares e três isolados de Fusarium sp., além da testemunha. As sementes da cultivar BRS 509 foram consideradas de qualidade fisiológica inferior as demais cultivares. O sequenciamento de DNA permitiu identificar a espécie Fusarium thapsinum como agente patogênico na cultura do sorgo sacarino, sendo comprovada sua transmissão via sementes.

The range of applications for high-quality automatic speech recognition (ASR) systems has grown dramatically with the advent of smart phones, in which speech recognition can greatly enhance the user experience. Currently, the languages with extensive ASR support on these devices are languages that have thousands of hours of transcribed speech corpora already collected. Developing a speech system for such a language is made simpler because extensive resources already exist. However for languages that are not as prominent, the process is more difficult. Many obstacles such as reliability and cost have hampered progress in this regard, and various separate tools for every stage of the development process have been developed to overcome these difficulties. Developing a system that is able to combine these identified partial solutions, involves customising existing tools and developing new ones to interface the overall end-to-end process. This work documents the integration of several tools to enable the end-to-end development of an Automatic Speech Recognition system in a typical under-resourced language. Google App Engine is employed as the core environment for data verification, storage and distribution, and used in conjunction with existing tools for gathering text data and for speech data recording. We analyse the data acquired by each of the tools and develop an ASR system in Shona, an important under-resourced language of Southern Africa. Although unexpected logistical problems complicated the process, we were able to collect a useable Shona speech corpus, and develop the first Automatic Speech Recognition system in that language. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2014

The range of applications for high-quality automatic speech recognition (ASR) systems has grown dramatically with the advent of smart phones, in which speech recognition can greatly enhance the user experience. Currently, the languages with extensive ASR support on these devices are languages that have thousands of hours of transcribed speech corpora already collected. Developing a speech system for such a language is made simpler because extensive resources already exist. However for languages that are not as prominent, the process is more difficult. Many obstacles such as reliability and cost have hampered progress in this regard, and various separate tools for every stage of the development process have been developed to overcome these difficulties. Developing a system that is able to combine these identified partial solutions, involves customising existing tools and developing new ones to interface the overall end-to-end process. This work documents the integration of several tools to enable the end-to-end development of an Automatic Speech Recognition system in a typical under-resourced language. Google App Engine is employed as the core environment for data verification, storage and distribution, and used in conjunction with existing tools for gathering text data and for speech data recording. We analyse the data acquired by each of the tools and develop an ASR system in Shona, an important under-resourced language of Southern Africa. Although unexpected logistical problems complicated the process, we were able to collect a useable Shona speech corpus, and develop the first Automatic Speech Recognition system in that language. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2014