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Articles containing the keyword 'New Zealand'

Category : Article

article id 7516, category Article
Euan G. Mason, A. Graham D. Whyte. (1997). Modelling initial survival and growth of radiata pine in New Zealand. Acta Forestalia Fennica no. 255 article id 7516. https://doi.org/10.14214/aff.7516
Keywords: Pinus radiata; New Zealand; growth modelling; young corps; radiata pine
Abstract | View details | Full text in PDF | Author Info

A sensitive framework has been developed for modelling young radiata pine (Pinus radiata D. Don) survival, its growth and size class distribution, from time of planting to age 5 or 6 years. The data and analysis refer to the Central North Island region of New Zealand. The survival function is derived from a Weibull probability density function, to reflect diminishing mortality with the passage of time in young stands. An anamorphic family of trends was used, as very little between-tree competition can be expected in young stands. An exponential height function was found to fit best the lower portion of its sigmoid form. The most appropriate basal area/ha exponential function included an allometric adjustment which resulted in compatible mean height and basal area/ha models. Each of these equations successfully represented the effects of several establishment practices by making coefficients linear functions of site factors, management activities and their interactions. Height and diameter distribution modelling techniques that ensured compatibility with stand values were employed to represent the effects of management practices on crop variation. Model parameters for this research were estimated using data from site preparation experiments in the region and were tested with some independent data sets.

  • Mason, E-mail: em@mm.unknown (email)
  • Whyte, E-mail: aw@mm.unknown
article id 7608, category Article
Peitsa Mikola. (1969). Comparative observations on the nursery technique in different parts of the world. Acta Forestalia Fennica no. 98 article id 7608. https://doi.org/10.14214/aff.7608
Keywords: Finland; New Zealand; substrate; forest nurseries; nurseries; methods; Africa; potted seedlings; greenhouses; Mediterranean countries; Australia; Latin America
Abstract | View details | Full text in PDF | Author Info

This paper is a report of the authors visits to over 80 forestry nurseries in 20 countries mostly in the tropics or subtropics. The article aim is to describe the methods used in the various countries and compares them to the conventional methods of cool and temperate countries. The article introduces nurseries of Africa south of the Sahara, Mediterranean area, Australian and New Zealand and Latin America.

A complete revolution has taken place in the Finnish nursery practice, which used to raise the seedlings in natural field soil in open-air nurseries. The seedlings were usually transplanted into transplant beds at the age of two years. Now the use of plastic greenhouses of light construction and an artificial soil substrate (fertilized peat) are essential. The new technique has some similarities to the practises of the tropical and subtropical nurseries. In Finland cultivation in greenhouses has hastened the development of the seedlings and shortened the nursery rotation from four to two years, and provided better control of watering and fertilization.

Peat beds in greenhouses are used also in Swaziland. The advantage of peat is that it is free of weed seeds, which eliminates weeding. Peat substrate gives also better yield of seedlings, which decreases the need of seeds, which is important in Finland. Another technique common with tropical silviculture is the production of potted seedlings, which are easy to handle and transport. In tropics, peat pots (jiffy pots) have made it possible to grow plantable seedlings in one season without transplanting. The present Finnish technique means a decreased degree of mechanization compared to the conventional technique of modern European and American nurseries.

  • Mikola, E-mail: pm@mm.unknown (email)

Category : Research article

article id 212, category Research article
Sandhya Samarasinghe. (2009). Exploration of fracture dynamics properties and predicting fracture toughness of individual wood beams using neural networks. Silva Fennica vol. 43 no. 2 article id 212. https://doi.org/10.14214/sf.212
Keywords: Pinus radiata; wood properties; cracks; initiation; New Zealand; peak stress; speed; video imaging
Abstract | View details | Full text in PDF | Author Info
In this study, the time to crack initiation (Tinit), duration of crack propagation (Tfrac), crack initiation stress, peak stress as well as crack speed and fracture toughness were investigated for three Rates of Loading (ROL) and four sizes of notched wood beams using high-speed video imaging and neural networks. Tinit was consistent for all volumes and the average Tinit was nonlinearly related to volume and ROL. For the smallest ROL, there was a distinct volume effect on Tinit and the effect was negligble at the largest ROL. However, the stress at crack initiation was not consistent. Contrasting these, Tfrac for all volumes appeared to be highly variable but the peak stress carried prior to catastrophic failure was consistent. The crack propagation was a wave phenomenon with positive and negative (crack closure) speeds that varied with the ROL. As accurate estimation of crack initiation load (or stress) and its relationship to peak load (or stress) is important for determining fracture toughness, Artificial Neural Networks (ANN) models were developed for predicting them from volume, Young’s modulus, face and grain angles, density, moisture content and ROL. Models for crack initiation load and peak load showed much higher predictive power than those for the stresses with correlation coefficients of 0.85 and 0.97, respectively, between the actual and predicted loads. Neural networks were also developed for predicting fracture toughness of individual wood specimens and the best model produced a statistically significant correlation of 0.813 between the predicted and actual fracture toughness on a validation dataset. The inputs captured 62% of variability of fracture toughness. Volume and Young’s modulus were the top two contributing variables with others providing lesser contributions.
  • Samarasinghe, Centre for Advanced Computational Solutions (C-fACS), Lincoln University, Canterbury, New Zealand E-mail: sandhya.samarasinghe@lincoln.ac.nz (email)
article id 309, category Research article
Sandhya Samarasinghe, Don Kulasiri, Tristan Jamieson. (2007). Neural networks for predicting fracture toughness of individual wood samples. Silva Fennica vol. 41 no. 1 article id 309. https://doi.org/10.14214/sf.309
Keywords: Pinus radiata; New Zealand; video imaging; strain energy release rate; Neural Networks; fracture toughness
Abstract | View details | Full text in PDF | Author Info
Strain energy release rate (GIc) of Pinus radiata in the TL opening mode was determined using the compliance crack length relationship. A total of 123 specimens consisting of four sizes of specimen with each size having four different crack lengths were tested. For each specimen, grain and ring angles, density and moisture content were measured. Video imaging, was used to measure crack length during propagation. Since cracks extended in stages, full compliance-crack length relationship was developed for each specimen based on their initial and subsequent crack lengths. No significant differences in GIc, between initial and subsequent crack lengths were found for the smaller specimens by paired sample t-tests, but differences were significant for the largest specimen size. The Average fracture toughness was calculated from GIc and it was 215 kPa.m0.5. Three artificial neural networks were developed to predict the: 1) force required to propagate a crack, 2) crack extension, and 3) fracture toughness of an individual specimen. Each was successful, producing respective R2 of 0.870, 0.865, and 0.621 on validation data. A sensitivity analysis of the networks revealed that the crack length was the most influential with 21% contribution followed by grain angle with 14% contribution for predicting the applied force. This was followed by volume and physical properties. For predicting the crack extension, density had the greatest contribution (20%) followed by previous crack length and force contributing 16% equally. Fracture toughness was dominated by the dimensional parameters of the specimen contributing (42%) followed by anisotropy and physical properties.
  • Samarasinghe, Centre for Advanced Computational Solutions (C-fACS), Lincoln University, New Zealand E-mail: ss@nn.nz (email)
  • Kulasiri, Centre for Advanced Computational Solutions (C-fACS), Lincoln University, New Zealand E-mail: dk@nn.nz
  • Jamieson, Centre for Advanced Computational Solutions (C-fACS), Lincoln University, New Zealand E-mail: tj@nn.nz

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