Current issue: 54(4)
Under compilation: 54(5)
Expertise in the cost-efficient utilization and treatment of brushwood on forest roadside sites is limited. In the present study, the productivity of brushwood clearing and harvesting on forest roadside sites was defined by creating time-consumption models or parameters for the aforementioned working methods. Compiled time consumption models and parameters for the brushwood clearing and harvesting can be used as a basis for evaluating alternative management practices and to determine when brushwood biomass should be harvested and when it should be left to decay. The harvesting of brushwood was based on the harwarder system and the clearing of brushwood was done with a spiral cutter, which is a novel accessory for cutting roadside vegetation. Based on the study results, the average volume of harvested brushwood and forwarding distance are the key elements that have an effect on harvesting productivity with harwarders. Correspondingly, stump diameter has a strong impact on the clearing productivity of brushwood. The plot-wise productivity of the spiral cutter in brushwood clearings varied in the range of 0.19–0.61 ha per PMh. An increase in stump diameter slowed down the clearing productivity of the spiral cutter and there was a clear step downward in clearing productivity as the average diameter increased from 30 mm to 40 mm. The machinery under study operated well and there were no interruptions due to machine breakdowns.
In wintertime, the payload capacity of a timber truck is reduced by snow that accumulates on the structures of the truck. The aim of this study was to quantify the potential payload loss due to snow and winter accessories and to predict the loss with weather variables. Tare weights of eight timber trucks were collected at mill receptions in Finland over a one-year period. Monthly and annual loss of potential payload was estimated using the tare measurements in summer months as a reference. Each load was also connected with weather data at the location and time of delivery and payload loss explained by the weather data with the aid of regression models. The maximum loss of payload varied between 1560 kg and 3100 kg. On a monthly basis, the highest losses occurred in January, when the median values varied between 760 kg and 2180 kg. Over the year, the payload loss ranged between the trucks from 0.5% to 1.5% (from 1.9% and 5.1% in January) of the total number of loads in the study. Payload loss was found to increase with decreasing temperature, increasing relative humidity and increasing precipitation. Although the average payload loss was not very high, the biggest losses occur just during the season of highest capacity utilization. Big differences were also found in the tare weights between the trucks. The results of the study give incentive to develop truck and trailer structures that reduce the adherence of snow.