Current issue: 58(1)

Under compilation: 58(2)

Scopus CiteScore 2021: 2.8
Scopus ranking of open access forestry journals: 8th
PlanS compliant
Silva Fennica 1926-1997
1990-1997
1980-1989
1970-1979
1960-1969
Acta Forestalia Fennica
1953-1968
1933-1952
1913-1932

Articles containing the keyword 'sorting'

Category : Article

article id 5120, category Article
Pentti Sepponen. (1981). Kivennäismaan raekoon tunnuksista ja niiden käyttökelpoisuudesta eräiden maan ominaisuuksien kuvaamiseen. Silva Fennica vol. 15 no. 2 article id 5120. https://doi.org/10.14214/sf.a15061
English title: Particle size distribution characteristics of mineral soil and their applicability for describing some soil properties.
Original keywords: metsämaa; maaperä; lajitekoostumut; raekoko; kenttäkapasiteetti; kationinvaihtokapasiteetti
English keywords: forest soil; particle size distribution; field capacity; degree of sorting; cation exchange capacity
Abstract | View details | Full text in PDF | Author Info

The particle size distribution affects several properties of the soil, thus, the ability to define the texture type of the soil as accurately as possible in field conditions is essential. The soil particle size classification devised by Atterberg (1912) is used in Finnish forestry. The study is based on a small laboratory material. The correlation between some characteristics of the soil particle size distribution, field capacity and cation exchange capacity were determined.

The particle size characteristics such as the relative proportion of different particle sizes, average particle size (Md) and parameters depicting the degree of sorting were determined. The relative proportion of soil particles below 0.06 mm correlated best with both field capacity and cation exchange capacity. Similarly, the average particle size and the degree of sorting correlated well with the field capacity and the cation exchange capacity.

The use of sorting characteristics is not well-suited to the type of soil sample material containing a high proportion of particles of varying size as was used in this material. Such characteristics are probably more easily applicable to the fine sand and sand sediments which are predominant in Finnish forest soils. The most useful particle size distribution characteristics in soils having a great variation in particle sizes were the average particle size and the relative proportion of silt and clay. Thus, the nutrient and water status of the soil can be predicted to some extent by examining the percentage of silt and clay, average particle size and the degree of sorting.

The PDF includes a summary in English.

  • Sepponen, E-mail: ps@mm.unknown (email)

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
Keywords: larch; NIRS; OPLS; precision sowing; seed sorting; seed quality
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.
Abstract | Full text in HTML | Full text in PDF | Author Info

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 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 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 E-mail: per.oden@slu.se
article id 1334, category Research article
Abolfazl Daneshvar, Mulualem Tigabu, Asaddollah Karimidoost, Per Christer Oden. (2015). Single seed Near Infrared Spectroscopy discriminates viable and non-viable seeds of Juniperus polycarpos. Silva Fennica vol. 49 no. 5 article id 1334. https://doi.org/10.14214/sf.1334
Keywords: NIRS; OPLS; seed sorting; Iran; juniper; near infrared spectroscopy
Highlights: Near Infrared (NIR) Spectroscopy discriminates viable and non-viable (empty, insect-attacked and shriveled) seeds of J. polycarpos with 98% and 100% accuracy, respectively; The origins of spectral differences between non-viable and viable seeds were attributed to differences in seed coat chemical composition and storage reserves; The results demonstrate that NIR spectroscopy has great potential as seed sorting technology to ensure precision sowing.
Abstract | Full text in HTML | Full text in PDF | Author Info

A large quantity of non-viable (empty, insect-attacked and shriveled) seeds of Juniperus polycarpos (K. Koch) is often encountered during seed collection, which should be removed from the seed lots to ensure precision sowing in the nursery or out in the field. The aims of this study were to evaluate different modelling approaches and to examine the sensitivity of the change in detection system (Silicon-detector in the shorter vis-a-vis InGsAs-detector in the longer NIR regions) for discriminating non-viable seeds from viable seeds by Near Infrared (NIR) spectroscopy. NIR reflectance spectra were collected from single seeds, and discriminant models were developed by Partial Least Squares – Discriminant Analysis (PLS-DA) and Orthogonal Projection to Latent Structures – Discriminant Analysis (OPLS-DA) using the entire or selected NIR regions. Both modelling approaches resulted in 98% and 100% classification accuracy for viable and non-viable seeds in the test set, respectively. However, OPLS-DA models were superb in terms of model parsimony and information quality. Modelling in the shorter and longer wavelength region also resulted in similar classification accuracy, suggesting that prediction of class membership is insensitive to change in the detection system. The origins of spectral differences between non-viable and viable seeds were attributed to differences in seed coat chemical composition, mainly terpenoids that were dominant in non-viable seeds and storage reserves in viable seeds. In conclusion, the results demonstrate that NIR spectroscopy has great potential as seed sorting technology to upgrade seed lot quality that ensures precision sowing.

  • Daneshvar, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53, Alnarp, Sweden; (permanent address) Department of Natural Resources, Gonbad Kavous University, Shahid Fallahi Street, P.O. Box 163, Gonbad, Iran E-mail: abolfazl.daneshvar@slu.se
  • Tigabu, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53, Alnarp, Sweden E-mail: mulualem.tigabu@slu.se (email)
  • Karimidoost, Agriculture and Natural Resources Research Center of Golestan Province, Beheshti Ave. P.O. Box 4915677555, Gorgan, Iran E-mail: karimidoost@yahoo.com
  • Oden, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53, Alnarp, Sweden E-mail: per.oden@slu.se
article id 388, category Research article
Jacob Edlund, Mats Warensjö. (2005). Repeatability in automatic sorting of curved Norway spruce saw logs. Silva Fennica vol. 39 no. 2 article id 388. https://doi.org/10.14214/sf.388
Keywords: Picea abies; compression wood; stem form; bow; scanner; sorting
Abstract | View details | Full text in PDF | Author Info
Sawn wood from curved logs is prone to have cross grain and contain compression wood, both of which affect the dimensional stability. Different types of curvature can, however, have different effects on both the sawing process and board quality, which is why a standard measure of bow height alone is not enough to sort logs or set the log quality. The aim of this study was to evaluate the repeatability when sorting curved saw logs using a 3D log scanner. In the study, 56 logs were categorized into five different curvature types and four different degrees of curvature severity. The logs were run through a Rema 3D log scanner four times, and the external geometry was recorded. From the geometry data, variables describing log shapes were calculated and used to develop models using linear discriminant analysis, which was used to classify the logs according to curvature type. The accuracy and repeatability were evaluated for the classifications with Cohen’s simple Kappa coefficient. The results of this study showed that it is possible to sort logs by curve type using a 3D log scanner, although sorting by curve type was largely dependent on curve severity. The repeatability test determined that the chance of a curved log being graded identically two consecutive times was 0.40, measured as kappa.
  • Edlund, SLU, Department of Forest Products and Markets, P.O. Box 7060, SE-750 07 Uppsala, Sweden E-mail: jacob.edlund@spm.slu.se (email)
  • Warensjö, SLU, Department of Forest Products and Markets, P.O. Box 7060, SE-750 07 Uppsala, Sweden E-mail: mw@nn.se

Register
Click this link to register to Silva Fennica.
Log in
If you are a registered user, log in to save your selected articles for later access.
Contents alert
Sign up to receive alerts of new content
Your selected articles