Silva Fennica vol. 53 no. 2 | 2019
Category : Editorial
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Heräjärvi,
Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland
E-mail:
henrik.herajarvi@luke.fi
Category : Research article
Crane work is the most time-consuming work element in forwarding. Hence, assist systems like boom-tip control are of interest. The first commercially available boom-tip control for forwarders was introduced in 2013. In this study we analysed whether replacing conventional boom control (CBC) with John Deere’s version of boom-tip control (named Intelligent Boom Control, IBC), increases crane-work productivity. We used data automatically gathered from 10 final-felling stands, covering typical logging conditions for southern, central and northern Sweden. Two John Deere 1510E and two John Deere 1910G forwarders were operated by seven experienced operators during the follow-up study, covering 1238 loads in total. A split-plot design was applied to isolate effects of the boom-control system being used (CBC, IBC). We found that using IBC for loading work (crane work and driving included) saved 5.2% of productive machine time compared to using CBC (p ≤ 0.05). The corresponding saving when using IBC for unloading work was 7.9% (p ≤ 0.05). Depending on geophysical factors, this corresponds to approximately 4% savings in productive machine time for forwarding as a whole, including pure transport (with and without load). Moreover, the study introduced in cut-to-length context a novel field-study design to collect a large follow-up dataset in the course of ordinary forwarding operations. We found the study design to be a cost-efficient way to combine the representativeness of conventional follow-up datasets with the ability to establish causal relationships. Establishment of causal relationships has traditionally been possible only through observational time studies or standardized experiments.
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Manner,
The Forestry Research Institute of Sweden (Skogforsk), Uppsala Science Park, SE-751 83 Uppsala, Sweden
http://orcid.org/0000-0002-4982-3855 E-mail: jussi.manner@skogforsk.se
- Mörk, The Forestry Research Institute of Sweden (Skogforsk), Uppsala Science Park, SE-751 83 Uppsala, Sweden E-mail: anders.mork@skogforsk.se
- Englund, The Forestry Research Institute of Sweden (Skogforsk), Uppsala Science Park, SE-751 83 Uppsala, Sweden E-mail: martin.englund@skogforsk.se
Accurate mapping of the spatial distribution of understory species from spectral images requires ground reference data which represent the prevailing phenological stage at the time of image acquisition. We measured the spectral bidirectional reflectance factors (BRFs, 350–2500 nm) at varying view angles for lingonberry (Vaccinium vitis-idaea L.) and blueberry (Vaccinium myrtillus L.) throughout the growing season of 2017 using Finnish Geospatial Research Institute’s FIGIFIGO field goniometer. Additionally, we measured spectra of leaves and berries of both species, and flowers of lingonberry. Both lingonberry and blueberry showed seasonality in visible and near-infrared spectral regions which was linked to occurrences of leaf growth, flowering, berrying, and leaf senescence. The seasonality of spectra differed between species due to different phenologies (evergreen vs. deciduous). Vegetation indices, normalized difference vegetation index (NDVI), moisture stress index (MSI), plant senescence reflectance index (PSRI), and red-edge inflection point (REIP2), showed characteristic seasonal trends. NDVI and PSRI were sensitive to the presence of flowers and berries of lingonberry, while with blueberry the effects were less evident. Off-nadir observations supported differentiating the dwarf shrub species from each other but showed little improvement for detection of flowers and berries. Lingonberry and blueberry can be identified by their spectral signatures if ground reference data are available over the entire growing season. The spectral data measured in this study are reposited in the publicly open SPECCHIO Spectral Information System.
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Forsström,
Aalto University, School of Engineering, Department of Built Environment, FI-00076 Aalto, Finland
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Peltoniemi,
Finnish Geospatial Research Institute (FGI), Department of Geodesy and Geodynamics, Geodeetinrinne 2, FI-02430 Masala, Finland
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Rautiainen,
Aalto University, School of Engineering, Department of Built Environment, FI-00076 Aalto, Finland; Aalto University, Department of Electronics and Nanoengineering, FI-00076 Aalto, Finland
Factors affecting soil disturbance caused by harvester and forwarder were studied on mid-grained soils in Finland. Sample plots were harvested using a one-grip harvester. The harvester operator processed the trees outside the strip roads, and the remaining residues were removed to exclude the covering effect of residues. Thereafter, a loaded forwarder made up to 5 passes over the sample plots. The average rut depth after four machine passes was positively correlated to the volumetric water content at a depth of 0–10 cm in mineral soil, as well as the thickness of the organic layer and the harvester rut depth, and negatively correlated with penetration resistance at depths of both 0–20 cm and 5–40 cm. We present 5 models to predict forwarder rut depth. Four include the cumulative mass driven over a measurement point and combinations of penetration resistance, water content and the depth of organic layer. The fifth model includes harvester rut depth and the cumulative overpassed mass and provided the best fit. Changes in the penetration resistance (PR) were highest at depths of 20–40 cm. Increase in BD and VWC decreased PR, which increased with total overdriven mass. After four to five machine passes PR values started to stabilize.
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Sirén,
Natural Resources Institute Finland (Luke) c/o Aalto University, P.O. Box 15600, FI-00076 Aalto, Finland
E-mail:
matti.siren@luke.fi
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Ala-Ilomäki,
Natural Resources Institute Finland (Luke) c/o Aalto University, P.O. Box 15600, FI-00076 Aalto, Finland
- Lindeman, Natural Resources Institute Finland (Luke), Korkeakoulunkatu 7, FI-33720 Tampere, Finland E-mail: harri.lindeman@luke.fi
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Uusitalo,
Natural Resources Institute Finland (Luke), Korkeakoulunkatu 7, FI-33720 Tampere, Finland
- Kiilo, Versowood, Teollisuuskatu 1, FI-11130 Riihimäki, Finland E-mail: kalle.kiilo@versowood.fi
- Salmivaara, Natural Resources Institute Finland (Luke), P.O. Box 2, FI-00791 Helsinki, Finland E-mail: aura.salmivaara@luke.fi
- Ryynänen, Natural Resources Institute Finland (Luke), Kaironiementie 15, FI-39700 Parkano, Finland E-mail: ari.ryynanen@luke.fi
Colchicine is widely used as a mutagen to induce production of diploid gametes in plants. However, whether colchicine affects induced pollen viability remains unclear. To clarify whether colchicine affected the viability of induced pollen, we induced production of diploid pollen by colchicine, followed by pollen germination in vitro and crossing induced pollen with normal gametes to produce triploid in Populus tomentosa Carrière. The results showed that the predominant meiotic stages and the number of colchicine injections had significant effects on the occurrence rates of induced 2n pollen. When the colchicine injection was given at diakinesis, a significant decrease in the pollen production per bud was observed (p < 0.001). The morphology of the colchicine-induced 2n pollen was similar to that of the natural 2n pollen in its ectexine structure. The pollen germination experiments revealed that there was also no significant difference in germination rates between the induced diploid pollen and natural 2n pollen grains, and 68 triploids were created by crossing colchicine-induced pollen. Our findings revealed that colchicine injection could induce P. tomentosa to produce 2n pollen and will not lead to dysfunction of induced diploid pollen.
- Liu, National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing 100083, China; College of Bioscience and Biotechnology, Beijing Forestry University, Beijing 100083, China E-mail: 342767649@qq.com
- Zhang, National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing 100083, China; College of Bioscience and Biotechnology, Beijing Forestry University, Beijing 100083, China E-mail: 409192881@qq.com
- Zhou, National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing 100083, China; College of Bioscience and Biotechnology, Beijing Forestry University, Beijing 100083, China E-mail: 876034493@qq.com
- Wu, National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing 100083, China; College of Bioscience and Biotechnology, Beijing Forestry University, Beijing 100083, China E-mail: 1269485709@qq.com
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Zhang,
National Engineering Laboratory for Tree Breeding, Beijing Forestry University, Beijing 100083, China; College of Bioscience and Biotechnology, Beijing Forestry University, Beijing 100083, China
E-mail:
zhangpd@bjfu.edu.cn
The aim of this study was to estimate economic losses, which are caused by forest inventory errors of tree species proportions and site types. Our study data consisted of ground truth data and four sets of erroneous tree species proportions. They reflect the accuracy of tree species proportions in four remote sensing data sets, namely 1) airborne laser scanning (ALS) with 2D aerial image, 2) 2D aerial image, 3) 3D and 2D aerial image data together and 4) satellite data. Furthermore, our study data consisted of one simulated site type data set. We used the erroneous tree species proportions to optimise the timing of forest harvests and compared that to the true optimum obtained with ground truth data. According to the results, the mean losses of Net Present Value (NPV) because of erroneous tree species proportions at an interest rate of 3% varied from 124.4 € ha–1 to 167.7 € ha–1. The smallest losses were observed using tree species proportions predicted using ALS data and largest using satellite data. In those stands, respectively, in which tree species proportion errors actually caused economic losses, they were 468 € ha–1 on average with tree species proportions based on ALS data. In turn, site type errors caused only small losses. Based on this study, accurate tree species identification seems to be very important with respect to operational forest inventory.
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Haara,
Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, Finland
E-mail:
arto.haara@luke.fi
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Kangas,
Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 68, FI-80101 Joensuu, Finland
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Tuominen,
Natural Resources Institute Finland (Luke), Bioeconomy and environment, P.O. Box 2, FI-00791 Helsinki, Finland
The aim of this study was to determine the effect of leaching of heavy metals (Cr, As, Cd, Cu, Ni, Pb, Zn, Co, Mo) and earth-alkaline metal, barium (Ba), on the percolation and ditch water quality from the forest roads that contained ash in the road structures. Water quality was studied in the immediate vicinity below the ash layers as well as deeper in the road structure. Water quality was also determined in the drainage water in ditches that crossed the forest roads. A mixture of wood and peat based fly ash was used in the road structures. The treatments were: 1) no ash, 2) a 15 cm layer of ash/gravel mixture, 3) a 20 cm layer of ash/gravel mixture, 4) a 25 cm layer of ash, and 5) a 50 cm layer of ash. Large variation in the concentrations of Cr, As, Cu, Ni, Pb, Mo and Ba in the percolation water, even within the same treatment, caused difficulties to generalize the results. The concentrations of Cr, As, Ni, Pb, Mo and Ba in water samples were high in some treatment plot lysimeters containing ash compared to the control (no ash). On the other hand, many lysimeters had low and similar concentrations in water samples in the treatment plots containing ash compared to concentrations in the control plots. The ash in the roads did not affect the concentrations in the ditches. The leaching is uneven and seems to take place only from some parts of the ash layer. Risk for leaching is minimal if such parts are not widely spread.
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Lindroos,
Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland
E-mail:
antti.lindroos@luke.fi
- Ryhti, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: kira.ryhti@helsinki.fi
- Kaakkurivaara, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: tomi.kaakkurivaara@gmail.com
- Uusitalo, Natural Resources Institute Finland (Luke), Korkeakoulunkatu 7, FI-33720 Tampere, Finland E-mail: jori.uusitalo@luke.fi
- Helmisaari, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: helja-sisko.helmisaari@helsinki.fi
The stoniness index of forest soil describes the stone content in the upper soil layer at depths of 20–30 centimeters. This index is not available in any existing map databases, and traditional measurements for the stoniness of the soil have always necessitated laborious soil-penetration methods. Knowledge of the stone content of a forest site could be of use in a variety of forestry operations. This paper presents a novel approach to obtaining automatic measurements of soil stoniness during an excavator-based mounding operation. The excavator was equipped with only a low-cost inertial measurement unit and a satellite navigation receiver. Using the data from these sensors and manually conducted soil stoniness measurements, supervised machine learning methods were utilized to build a model that is capable of predicting the stoniness class of a given mounding location. This study compares different classifiers and feature selection methods to find the most promising solution for this learning problem. The discussion includes a proposition for a meaningful measurement resolution of the soil’s stoniness, and a practical method for evaluating the variability of the stone content of the soil. The results indicate that it is possible to predict the soil stoniness class with 70% accuracy using only the inertial and location measurements.
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Melander,
Automation Technology and Mechanical Engineering, Tampere University, FI-33014 Tampere University, Finland
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Ritala,
Automation Technology and Mechanical Engineering, Tampere University, FI-33014 Tampere University, Finland
- Strandström, Metsäteho Oy, Vernissakatu 1, FI-01300 Vantaa, Finland E-mail: markus.strandstrom@metsateho.fi
It is commonly accepted that the period of early-spring xylem sap exudation marks a stage during which a positive pressure builds inside the tree trunks. This state changes when leaves appear, initiating water transport within the trunk. It is unknown, however, how the wood anatomical structure and its mechanical resistance influences the sap. We present the results of research on the relationship between exudation of sap from Betula pendula Roth trees from the interior of a forest stand and from its edge, and the anatomical structure of the trunk wood and its bending strength. During the period between March 21 and April 18, we performed five sets of measurements of sap exudation from trees at the edge of the stand and from the forest interior. The resulting radial wood samples were tested for bending strength using a fractometer. We tested the sap for electrolytic conductivity and sugars content. For the anatomical analysis of the wood, we determined the number of vessels per 1 mm2, average vessel lumen area and potential conductivity index. We found that the trees along the edge of the stand exude more sap, but it is less concentrated than the sap from the trees from the interior. Bending strength perpendicular to wood fibres is higher in the trees from the stand edge and in the western side of the trunk, where the number of vessels per 1 mm2 and conductivity index are smaller. Seemingly, this is the result of western winds, which are dominant in Poland.
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Zajączkowska,
Department of Forest Botany, Faculty of Forestry, Warsaw University of Life Sciences, 159 Nowoursynowska St., 02-776 Warsaw, Poland
E-mail:
urszula.zajaczkowska@wl.sggw.pl
- Kaczmarczyk, Department of Forest Botany, Faculty of Forestry, Warsaw University of Life Sciences, 159 Nowoursynowska St., 02-776 Warsaw, Poland E-mail: karina.kaczmarczyk@wl.sggw.pl
- Liana, Department of Forest Botany, Faculty of Forestry, Warsaw University of Life Sciences, 159 Nowoursynowska St., 02-776 Warsaw, Poland E-mail: janusz.liana@wl.sggw.pl