997 resultados para Tree traits


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Rootstock has profound effects on traits such as yield and tree size in various horticultural industries, however relatively little is known about rootstock effects for macadamia. In this study, 12 cultivars were propagated as open-pollinated seedling and clonal rootstocks, and own-rooted cuttings. The same cultivars were also used as scions, and grafted to a subset of rootstocks, then planted at four trial locations. In this preliminary analysis, rootstock accounted for 19% of the variance in yield compared with 72% for scion, and 23% in height compared with 72% for scion. There was no interaction between rootstock and scion for yield, and only a small effect for height. The interaction between rootstock and propagation method (seedling, clonal, own roots) was not significant for height. A small effect was observed for yield, with the own roots treatment producing significantly lower yield than grafted trees for all rootstock cultivars except 'HAES 849'. 'H2' seedling rootstock produced a cumulative yield to age 10 years of 11.1 kg tree -1 compared to the highest yield of 13.6 kg tree -1 for 'Beaumont' clonal rootstocks. 'H2' seedling rootstock produced 4.8 m trees at age 11 years, compared to the smallest grafted tree which was 'HAES 849' seedling at 4.7 m.

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Ten growth or wood-quality traits were assessed in three nearby Corymbia citriodora subsp. variegata (CCV) open-pollinated family-within-provenance trials (18 provenances represented by a total of 374 families) to provide information for the development of a breeding program targeting both pulp and solid-wood products. Growth traits (diameter at breast high over bark [DBH], height and conical volume) were assessed at 3 and 7 years of age. Wood-quality traits (density [DEN], Kraft pulp yield [KPY], modulus of elasticity [MoE] and microfibril angle [MfA]) were predicted using near-infrared spectroscopy on wood samples collected from these trials when aged between 10 and 12 years. The high average KPY, DEN and MoE, and low average MfA observed indicates CCV is very suitable for both pulp and timber products. All traits were under moderate to strong genetic control. In across- trials analyses, high (>0.4) heritability estimates were observed for height, DEN, MoE and MfA, while moderate heritability estimates (0.24 to 0.34) were observed for DBH, volume and KPY. Most traits showed very low levels of genotype × site interaction. Estimated age–age genetic correlations for growth traits were strong at both the family (0.97) and provenance (0.99) levels. Relationships among traits (additive genetic correlation estimates) were favourable, with strong and positive estimates between growth traits (0.84 to 0.98), moderate and positive values between growth and wood-quality traits (0.32 to 0.68), moderate and positive between KPY and MoE (0.64), and high and positive between DEN and MoE (0.82). However, negative (but favourable) correlations were detected between MfA and all other evaluated traits (−0.31 to −0.96). The genetic correlation between the same trait expressed on two different sites, at family level, ranged from 0.24 to 0.42 for growth traits, and from 0.29 to 0.53 for wood traits. Therefore simultaneous genetic improvement of growth and wood property traits in CCV for the target environment in south-east Queensland should be possible, given the moderate to high estimates of heritability and favourable correlations amongst all traits studied, unless genotype × site interactions are greater than was evident. © 2016 NISC (Pty) Ltd

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We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

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Counselling children often requires the use of supplementary strategies in order to interest and engage the child in the therapeutic process. One such strategy is the Metaphorical Fruit Tree (MFT); an art metaphor suited to exploring and developing self-concept. Quantitative and qualitative data was used to explore the relationships between children’s ability to use metaphor, age, gender, and level of emotional competence (N = 58). Quantitative and qualitative analyses revealed a significant negative relationship between self-reported emotional competence and ability to use the MFT. It is proposed that children rely on different processes to understand self and as children’s ability to cognitively report on their emotional capabilities via the Emotional Competence Questionnaire (ECQ) increases, their ability to report creatively on those capabilities via the MFT is undermined. It is suggested that the MFT may be used, via creative processes and as an alternative to cognitive processes, to increase understanding and awareness of intrapersonal and interpersonal concepts of self in the child during counselling.

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This paper describes the approach taken to the XML Mining track at INEX 2008 by a group at the Queensland University of Technology. We introduce the K-tree clustering algorithm in an Information Retrieval context by adapting it for document clustering. Many large scale problems exist in document clustering. K-tree scales well with large inputs due to its low complexity. It offers promising results both in terms of efficiency and quality. Document classification was completed using Support Vector Machines.

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The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

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Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering.

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The Thai written language is one of the languages that does not have word boundaries. In order to discover the meaning of the document, all texts must be separated into syllables, words, sentences, and paragraphs. This paper develops a novel method to segment the Thai text by combining a non-dictionary based technique with a dictionary-based technique. This method first applies the Thai language grammar rules to the text for identifying syllables. The hidden Markov model is then used for merging possible syllables into words. The identified words are verified with a lexical dictionary and a decision tree is employed to discover the words unidentified by the lexical dictionary. Documents used in the litigation process of Thai court proceedings have been used in experiments. The results which are segmented words, obtained by the proposed method outperform the results obtained by other existing methods.

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This article discusses the design of a memorial space of the Tree of Knowledge, located in Oak Street, Barcaldine, Queensland designed by Brian Hooper Architect and M3 Architecture. Features of the design include the dead tree trunk underneath pieces of timber hanging down to show the original size of the tree in the 1890s and the root ball visible under a glass floor.

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This paper describes the approach taken to the clustering task at INEX 2009 by a group at the Queensland University of Technology. The Random Indexing (RI) K-tree has been used with a representation that is based on the semantic markup available in the INEX 2009 Wikipedia collection. The RI K-tree is a scalable approach to clustering large document collections. This approach has produced quality clustering when evaluated using two different methodologies.

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Habitat models are widely used in ecology, however there are relatively few studies of rare species, primarily because of a paucity of survey records and lack of robust means of assessing accuracy of modelled spatial predictions. We investigated the potential of compiled ecological data in developing habitat models for Macadamia integrifolia, a vulnerable mid-stratum tree endemic to lowland subtropical rainforests of southeast Queensland, Australia. We compared performance of two binomial models—Classification and Regression Trees (CART) and Generalised Additive Models (GAM)—with Maximum Entropy (MAXENT) models developed from (i) presence records and available absence data and (ii) developed using presence records and background data. The GAM model was the best performer across the range of evaluation measures employed, however all models were assessed as potentially useful for informing in situ conservation of M. integrifolia, A significant loss in the amount of M. integrifolia habitat has occurred (p < 0.05), with only 37% of former habitat (pre-clearing) remaining in 2003. Remnant patches are significantly smaller, have larger edge-to-area ratios and are more isolated from each other compared to pre-clearing configurations (p < 0.05). Whilst the network of suitable habitat patches is still largely intact, there are numerous smaller patches that are more isolated in the contemporary landscape compared with their connectedness before clearing. These results suggest that in situ conservation of M. integrifolia may be best achieved through a landscape approach that considers the relative contribution of small remnant habitat fragments to the species as a whole, as facilitating connectivity among the entire network of habitat patches.