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Silva Fennica 1926-1997
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Acta Forestalia Fennica
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Articles containing the keyword 'precision'.

Category: Research article

article id 1340, category Research article
Mostafa Farhadi, Mulualem Tigabu, Per Christer Odén. (2015). Near Infrared Spectroscopy as non-destructive method for sorting viable, petrified and empty seeds of Larix sibirica. Silva Fennica vol. 49 no. 5 article id 1340. https://doi.org/10.14214/sf.1340
Highlights: Near Infrared spectroscopy discriminates filled-viable, empty and petrified seeds of Larix sibirica with 98%, 82% and 87% accuracy, respectively based on spectral differences attributed to moisture and storage reserves; The classification accuracy reached 100% when sorting seeds into viable and non-viable class; The results demonstrate that NIR spectroscopy has great potential as non-destructive sorting technique to upgrade seed lot quality.

Larix sibirica Ledeb. is one of the promising timber species for planting in the boreal ecosystem; but poor seed lot quality is the major hurdle for production of sufficient quantity of planting stocks. Here, we evaluated the potential of Near Infrared (NIR) Spectroscopy for sorting viable and non-viable seeds, as the conventional sorting technique is inefficient. NIR reflectance spectra were collected from single seeds, and discriminant models were developed with Orthogonal Projections to Latent Structure – Discriminant Analysis (OPLS-DA). The computed model predicted the class membership of filled-viable, empty and petrified seeds in the test set with 98%, 82% and 87% accuracy, respectively. When two-class OPLS-DA model was fitted to discriminate viable and non-viable (empty and petrified seeds combined), the predicted class membership of test set samples was 100% for both classes. The origins of spectral differences between non-viable (petrified and empty) and viable seeds were attributed to differences in seed moisture content and storage reserves. In conclusion, the result provides evidence that NIR spectroscopy is a powerful non-destructive method for sorting non-viable seeds of Larix sibirica; thus efforts should be made to develop on-line sorting system for large-scale seed handling.

  • Farhadi, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden ORCID ID:E-mail: mostafa.farhadi@slu.se
  • Tigabu, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden ORCID ID:E-mail: mulualem.tigabu@slu.se (email)
  • Odén, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden ORCID ID:E-mail: per.oden@slu.se
article id 459, category Research article
Tomi Tulokas, Jawdat Tannous. (2010). Research method and improvement of log rotation in sawmills. Silva Fennica vol. 44 no. 1 article id 459. https://doi.org/10.14214/sf.459
Log rotation studies were performed at 14 Finnish sawmills during the years 2003–2005. In the investigation of automatic log rotation, the materialized degree of log rotation for each log was calculated from photos captured from a digital video recording. Rotation errors (D) for individual logs and again the accuracy of the automatic log rotator was determined from optimized angle values of the log measuring system and materialized angle values calculated from the still photos. The accuracy of the log rotation varied considerably between sawmills. The rotation error average of the automatic log rotation varied from –23.6° to +11.4°. This means that in some cases the logs were under-rotated and in some they were over-rotated, on an average. Standard deviation of the rotation error (s) of the automatic rotator varied from 4.4° to 22.9°. The results of the simulation indicated that the performance of the log rotation system can be improved by adjusting the log rotator control. In addition to the zero degree error on an average rotation (or near to zero), the corrected values have a significantly smaller standard deviation of the rotation error, and the number of correct rotations was significantly higher compared to the situation before the adjusted rotation commands. At Sawmill 1, standard deviation of the rotation error was reduced by 40.9% from 14.9 degrees to 8.8 degrees. At the same time the number of correct rotations (–10°≤ D ≤ +10°) increased 4.0 fold from 20.1% to 79.4%. At Sawmill 2, standard deviation of the rotation error was reduced by 23.8% from 10.5 degrees to 8.0 degrees. At this sawmill, the rate of accepted rotations increased 1.9 fold from 42.6% to 81.0%. According to previous research, 2.5° decrease in standard deviation of the rotation error (from 10.5 to 8.0°) in square sawing means about 0.5% increase in value yield. For example with 10 million Û annual sales of sawn timber this means 50 000 Û extra profit.
  • Tulokas, Centre for Timber Engineering, Edinburgh Napier University, 10 Colinton Road, Edinburgh EH10 5DT, UK ORCID ID:E-mail: tomi.tulokas@lut.fi (email)
  • Tannous, School of Engineering and the Built Environment, Edinburgh Napier University, 10 Colinton Road, Edinburgh EH10 5DT, UK ORCID ID:E-mail:
article id 478, category Research article
Ronald E. McRoberts, Daniel G. Wendt, Greg C. Liknes. (2005). Stratified estimation of forest inventory variables using spatially summarized stratifications. Silva Fennica vol. 39 no. 4 article id 478. https://doi.org/10.14214/sf.478
Large area natural resource inventory programs typically report estimates for selected geographic areas such as states or provinces, counties, and municipalities. To increase the precision of estimates, inventory programs may use stratified estimation, with classified satellite imagery having been found to be an efficient and effective basis for stratification. For the benefit of users who desire additional analyses, the inventory programs often make data and estimation procedures available via the Internet. For their own analyses, users frequently request access to stratifications used by the inventory programs. When data analysis is via the Internet and stratifications are based on classifications of even medium resolution satellite imagery, the memory requirements for storing the stratifications and the online time for processing them may be excessive. One solution is to summarize the stratifications at coarser spatial scales, thus reducing both storage requirements and processing time. If the bias and loss of precision resulting from using summaries of stratifications is acceptably small, then this approach is viable. Methods were investigated for using summaries of stratifications that do not require storing and processing the entire pixel-level stratifications. Methods that summarized satellite image-based 30 m x 30 m pixel stratifications at spatial scales up to 2400 ha produced stratified estimates of the mean that were generally within 5-percent of estimates for the same areas obtained using the pixel stratifications. In addition, stratified estimates of variances using summarized stratifications realized nearly all the gain in precision that was obtained with the underlying pixel stratifications.
  • McRoberts, North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510 ORCID ID:E-mail: rmcroberts@fs.fed.us (email)
  • Wendt, Region 9, USDA Forest Service, 626 East Wisconsin Avenue, Milwaukee, Wisconsin 53202, USA ORCID ID:E-mail:
  • Liknes, North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510 ORCID ID:E-mail:

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