Leptographium is an anamorph genus within the Ophiostomatoid group of fungi and represents a unique case for molecular applications. The genus has a near complete sequence data available for three genes across all known species. This characteristic makes it a perfect test group for investigating applications of new diagnostic techniques within ascomycetes. Probes and primers, for microarrays, are designed from phylogenetically useful gene regions and are fabricated onto a solid substrate using printing technology. The sample is prepared using PCR and is hybridised to the probes under stringent conditions. The resulting fluorescent pattern is rigorously analysed to distinguish species from each other. Diagnostic PCR uses primers that are designed in similar way to the way probes are designed for microarrays and indicate the presence of a species through positive amplification. This research methodology will be applied to Leptographium to evaluate the efficacy of microarray technology for discriminating species within that genus. The data gained from this research study will be used in applications for other genera using microarray technology. / Dissertation (MSc)--University of Pretoria, 2009. / Genetics / Unrestricted

Probabilistic models have been successfully applied for a wide variety of problems, such as but not limited to information retrieval, computer vision, bio-informatics and speech processing. Probabilistic models allow us to encode our assumptions about the data in an elegant fashion and enable us to perform machine learning tasks such as classification and clustering in a principled manner. Probabilistic models for bio-acoustic data help in identifying interesting patterns in the data (for instance, the species-specific vocabulary), as well as species identification (classification) in recordings where the label is not available. The focus of this thesis is to develop efficient inference techniques for existing models, as well as develop probabilistic models tailored to bioacoustic data. First, we develop inference algorithms for the supervised latent Dirichlet allocation (LDA) model. We present collapsed variational Bayes, collapsed Gibbs sampling and maximum-a-posteriori (MAP) inference for parameter estimation and classification in supervised LDA. We provide an empirical evaluation of the trade-off between computational complexity and classification performance of the inference methods for supervised LDA, on audio classification (species identification in this context)as well as image classification and document classification tasks. Next, we present novel probabilistic models for bird sound recordings, that can capture temporal structure at different hierarchical levels, and model additional information such as the duration and frequency of vocalizations. We present a non-parametric density estimation technique for parameter estimation and show that the MAP classifier for our models can be interpreted as a weighted nearest neighbor classifier. We provide an experimental comparison between the proposed models and a support vector machine based approach, using bird sound recordings from the Cornell Macaulay library. / Graduation date: 2011 / Access restricted to the OSU Community at author's request from Dec. 30, 2010 - Dec. 30, 2011

The larvae (wireworms) of some click beetle genera inhabit the soil in agricultural land and are crop pests. In the UK, a pest complex of Agriotes species, A. obscurus, A. sputator and A. lineatus, has been identified as the cause of the majority of damage. However, studies on their ecology are lacking, despite knowledge of this being important for the development of sustainable risk assessment and pest management strategies, in part due to the morphologically cryptic nature of wireworms. The ecology of economically important click beetle species was investigated, focusing on UK Agriotes species. The relationship between sex pheromone trapped male Agriotes adults and wireworms, identified using a molecular tool (T‐RFLP), was influenced by sampling method, and some environmental variables significantly correlated with species distributions. Scale of sampling influenced the observed distribution of wireworms and other soil insect larvae. Other wireworm species were trapped together with Agriotes species, but mitochondrial 16S rRNA sequences could not be matched to those of other UK species. Sequences from Canadian wireworm samples revealed possible cryptic species. Differences in adult movement rates were found in laboratory tests (A. lineatus > A. obscurus > A. sputator). Molecular markers (AFLPs) were developed to assess dispersal in adult male Agriotes but further protocol optimisation is required. The results show the importance of identifying wireworms to species for assessing adult and wireworm distributions, since the Agriotes pest complex may not be present or as 3 widespread as previously assumed. Sex pheromone trapping of adults may not be appropriate for risk assessment as the relationship between aboveground adult and belowground wireworm species distribution is not straightforward. The differences observed in Agriotes species’ ecology have implications for the implementation of pest management strategies. The techniques used here can be applied in future studies to provide information on other economically important click beetle species worldwide.

DNA barcoding is a valuable tool for fish species identification by food regulators, however, it does not perform well when multiple species are present within the same food product. PCR cloning has high potential to be used in combination with DNA barcoding to overcome this challenge. The objective of this study was to examine the use of PCR cloning combined with DNA barcoding to identify fish in a mixed-species product that cannot be identified with standard DNA barcoding. A total of 15 fish ball mixtures were prepared with known amounts of Nile tilapia (Oreochromis niloticus), Pacific cod (Gadus macrocephalus), and walleye pollock (Gadus chalcogrammus). The fish balls underwent DNA extraction in triplicate, followed by DNA barcoding across the full barcode (655 bp) and SH-E mini-barcode (226 bp) of the cytochrome c oxidase subunit 1 (CO1) region. Samples that did not pass sequencing according to regulatory standards were further analyzed with PCR cloning. Full barcoding enabled identification of at least one species in 80% of the fish ball mixtures compared to 51% for minibarcoding. The results of PCR cloning with samples that did not pass DNA barcoding showed identification success rates of 61% for clones (54 of 90) that underwent full barcoding and 51% for clones (111 of 220) that underwent mini-barcoding. All fish balls made of just one species tested positive for that species (i.e., tilapia, cod, or pollock).. The combination of standard full barcoding and PCR cloning enabled identification of Nile tilapia in all 12 mixed-species fish balls and Pacific cod in 6 of 12 (50%) of mixed-species fish balls. In comparison, the combination of standard mini-barcoding and PCR cloning enabled identification of Nile tilapia in all 12 mixed-species fish balls and Pacific cod in 9 of 12 (75%) of mixed-species fish balls. Overall, the results of this study show that PCR cloning may be an effective method to identify certain fish in mixed-species products when standard DNA barcoding fails. However, additional research is needed to understand the limitations associated with primer bias.

No description available.

The objectives of studies undertaken here were to identify the species of Colletotrichum associated with coffee berry anthracnose in PNG, gain an understanding of the infection process and factors affecting it, assess the impact, if any, of anthracnose on coffee quality and identify suitable chemicals for anthracnose control. A total of 40 isolates were collected from PNG and their cultural and morphological characteristics on PDA were studied and used to identify the species. Species identification was further confirmed by molecular characterisation using RFLP and DNA sequencing of the ITS region of the rDNA. After species identification only two isolates were selected to represent C. gloeosporioides and C. acutatum for further studies. Studies on conidia germination and the effects of conidia concentration, temperature, relative humidity and pH affecting germination were done on TWA, followed by studies on the infection process on coffee berries and the influence of temperature on germination and appressoria formation in vivo. For assessment of effect of anthracnose on coffee quality, 100 samples of ripe berries were assessed for disease incidence, followed by processing of the berries to green bean and data on bean defects (black bean) together with anthracnose incidence subjected to appropriate statistical analysis. A similar procedure was followed using disease severity but the samples were from one farm only. The closing work on chemical control was done by screening 16 different fungicides for the control of C. gloeosporioides and C. acutatum. With the 40 isolates, 29 were identified as C. gloeosporioides and 11 as C. acutatum. This is the first report of C. acutatum on coffee in PNG. Identification of the species was further confirmed by RFLP groupings where C. gloeosporioides and C. acutatum were separated at 574bp and 584bp respectively and DNA sequence homology identified the PNG isolates with C. gloeosporioides and C. acutatum accessions. Optimum conditions for conidia germination in relation to spore concentration, temperature, and pH are 1 x 106 spores/ml, 21 - 29°C and pH 5 - 7 respectively for C. acutatum and for C. gloeosporioides 1 x 106 spores/ml, 25 - 31°C and pH 5 - 7 respectively. Humidity is not a limiting factor for activity of both species. Infection process for both species is similar where conidia germinate to produce the germ tube which swells at the tip to form the appressoria. The appressoria produce an infection peg which is responsible for berry cuticle penetration and cell colonisation (resulting in typical anthracnose symptom expression) and eventual sporulation. C. acutatum has not been reported elsewhere as a pathogen of coffee and this is the first report of C. acutatum causing infections on both ripe and mature green berries. Anthracnose incidence did not correlate well with coffee bean defects, but anthracnose severity v suggested that coffee quality could be affected by anthracnose. The most effective fungicide for anthracnose control is thiram alone or thiram alternating with propiconazole.

Biodiversity across the globe is threatened. Rapid surveying and monitoring techniques are required to understand the origin of the threats to biodiversity and to enable conservation actions to be undertaken. Kuwait is an arid desert country with a small flora of only 402 species. This flora is endangered by environmental factors, overgrazing, and human activities. DNA barcoding the flora and using Next Generation Sequencing (NGS) technologies allowed us to identify plants to species level, conduct a molecular taxonomic revision, and distinguish plant diversity found in soil environmental DNA samples. After investigating the discriminatory power of five commonly used DNA markers from plastid (matK, rbcL, trnH-psbA, trnL) and a nuclear genome (ITS2) on four largest genera of the flora using phylogenetics reconstruction tree based methods, two barcoding markers (rbcL and ITS2) were assigned to build a DNA reference library of the flora. Furthermore, the DNA reference library was tested to identify the plant diversity found below-ground level and comparing it with that above-ground, using environmental soil samples collected from both species rich and poor habitats in Kuwait by applying high-throughput sequencing methods. The DNA database provided in this study could be used as a reference library for the identification process and contribute towards the future of molecular taxonomy, biodiversity and ecological research in Kuwait.

abstract: Two critical limitations for hyperspatial imagery are higher imagery variances and large data sizes. Although object-based analyses with a multi-scale framework for diverse object sizes are the solution, more data sources and large amounts of testing at high costs are required. In this study, I used tree density segmentation as the key element of a three-level hierarchical vegetation framework for reducing those costs, and a three-step procedure was used to evaluate its effects. A two-step procedure, which involved environmental stratifications and the random walker algorithm, was used for tree density segmentation. I determined whether variation in tone and texture could be reduced within environmental strata, and whether tree density segmentations could be labeled by species associations. At the final level, two tree density segmentations were partitioned into smaller subsets using eCognition in order to label individual species or tree stands in two test areas of two tree densities, and the Z values of Moran's I were used to evaluate whether imagery objects have different mean values from near segmentations as a measure of segmentation accuracy. The two-step procedure was able to delineating tree density segments and label species types robustly, compared to previous hierarchical frameworks. However, eCognition was not able to produce detailed, reasonable image objects with optimal scale parameters for species labeling. This hierarchical vegetation framework is applicable for fine-scale, time-series vegetation mapping to develop baseline data for evaluating climate change impacts on vegetation at low cost using widely available data and a personal laptop. / Dissertation/Thesis / M.A. Geography 2013

North American bats face multiple threats, prompting an increase in bat research and conservation efforts in recent decades. Researchers often use acoustic monitoring, which entails recording bats? echolocation calls and subsequently identifying them to species, typically using automated software. Chapter 1 describes an acoustic monitoring program at eight U.S. national parks that aims to assess changes in bat populations over time. Data collected in 2016-2017 showed that activity levels of the little brown bat (Myotis lucifigus) decreased significantly while other species remained stable. Little brown bats have undergone similar population declines elsewhere due to the disease white-nose syndrome. Chapter 2 investigates whether different versions of bat call identification software are comparable to each other and how accurate they are. For the two software programs tested, agreement among versions was variable and species-dependent. Furthermore, newer versions were more conservative in assigning identifications, though not, on average, more accurate.

No description available.