Journal of Renewable Natural Resources Research
Year:2020 | Volume:11 | Issue:1 (SERIAL NUMBER 33 )|Papers Count:6

To investigate the effect of melamine resin impregnated paper waste on physical and mechanical properties of medium-density fiberboard (MDF), a mixture of melamine resin impregnated paper waste and wood fibers in the ratio of 0. 100, 10/90, 20/80, 70. 30 was used. After gluing the fibers with urea-formaldehyde adhesive in 10% (relative to the dry weight of the fibers), the fiber cake in a laboratory press at a temperature of 170 ° C, under the pressure of 35-40 bar and pressing time of 6 min to they were compressed to a thickness of 15 mm. The results obtained from measuring the physical and mechanical properties of the boards showed that increasing the amount of melamine resin impregnated paper waste in the boards led to increase the modulus of rupture, modulus of elasticity, internal bonding, while the thickness swelling after 2 and 24 hours of immersion was decreased. Therefore, the findings of the present study statistical analysis showed that the best treatment in this study is the use of 20% melamine resin impregnated paper waste in the production of medium-density fiberboard, while achieving the desired levels of physical and mechanical properties specified in the standard range related to this type of board, can be prevent waste loss and environmental pollution.

Today, remote sensing with high spatial and spectral resolutions along with the use of a variety of plant indices has provided the possibility of more accurate analysis and classification of satellite data in the identification and structural resolution of natural phenomena. Accordingly obtain information from the structure of forests using satellite data to help the management of forest renewable resources is of interest to managers and researchers. In this research, maps of the development stages of natural forests in the north of the country were prepared using GeoEye-1 satellite data and different classification algorithms in pixel-based, object-based, and model-based methods. The ultimate accuracy of the classification maps was calculated with the overall accuracy parameters and the Kappa coefficient. The results of this study showed that maximum accuracy (78%) in the object-based method was estimated on the basis of the segmentation of the NDVI and the maximum likelihood algorithm. Also, the algorithms that follow the structural patterns for the classification of the pixel distribution provided a higher accuracy. Overall, the results showed the high potential of GeoEye-1 data in mapping forest development stages.

This study aimed to investigate the possibility of making reed plant flour-high density polyethylene composite using oxidized poly-propylene as a compatibilizer. For this purpose, reed plant flour, high density polyethylene, and oxidized poly-propylene compatibilizer in the specified value were mixed into the internal mixer for 6 min and after that, the resulting amorphous materials turned to the granules using a laboratory mill. Finally, the granules turned to reed-plastic plates using a hot press. Mechanical tests such as bending and tensile resistances and their modulus and physical properties such as water absorption and thickness swelling in 2 and 24 h were measured. A fourier transform infrared spectroscopy machine was used to check the modification of oxidized poly-propylene and the morphology of the composites was studied by electron microscopy images. The results demonstrated that with increasing the compatibilizer, the mechanical properties were linearly increased, while the water absorption and thickness swelling were decreased. Electron microscopy images showed that improved adhesion at the interface between the reed plant flour and polymer fibers. The Fourier-transform infrared spectroscopy also showed that due to the oxidation of polypropylene, hydrophilic regions are formed in it.

Having accurate information about the efficiency of skidding machines in order to reduce transportation costs in forest engineering studies using modern statistical models is very valuable. In this study, the prediction of the skidding time in steel tracked skidder and agriculture tractor was performed using an artificial neural network and multiple linear regression model and then the efficiency of the models was compared. The variables of skidding distance, slope, and volume in each skidding cycle as independent variables (input variable) and time of each skidding cycle as the dependent variables (response variable) were entered into the model. The results showed the prediction in skidding time of steel tracked skidder, the explanation coefficient of the MLP neural network and regression model were 0. 78 and 0. 55, respectively and the error rate of models was 0. 19 and 0. 42, respectively. Also, in the agricultural tractor system, the explanation coefficient of MLP neural network and regression model were 0. 70 and 0. 62, respectively, and the error rate of models was 0. 18 and 0. 28, respectively. Therefore, in both skidding systems, MLP neural network is more efficient in predicting skidding time than the multiple linear regression model. Sensitivity analysis of the artificial neural network and regression showed that the skidding distance variable in the steel tracked skidder chain wheel and the skidding path slope variable in the agricultural tractor are the most important.

Due to the lack of studies on the effect of forest harvesting on lichen species in Hyrcanian forests, this research aimed to compare the indicator species in harvested and control stands of beech forests. This study was carried out in three parcels 209, 234 and 241 of Shurab section 2 of Golband forestry plan in Nowshahr region (Mazandaran province). Sampling was made from all trees using 40 × 60 cm frames to record lichens type and frequency. The results of this study showed that 8 species of lichen belonging to 7 genera and 5 families were recorded in harvested beech forests while in control forests, 15 lichen species belong to 13 genera and 10 families were recorded. According to the findings of this study, five species of lichen included Graphis scripta, Pertusaria albescens, Opegrapha vulgata, Lepraria lobificans and Parmotrema perlatum in control stands and Lecanora thysanophora, Flavoparmelia caperata and Ramalina thrausta in harvested stands have been introduced as indicator species of beech forests. So, the assessment of human interference in beech forests can be ascertained by examining these species and their presence or absence. In conclusion, it can be stated that the index species differed in both forests, indicating that forest utilization has caused changes in them.

This study was aimed to determine the impact of social and economical factors on the participation rate of ranchers in rangeland management projects of Kojour in Nowshahr city. The research method was a survey-field study. The statistical population of the study included 54 ranchers in the pastures of Hamze Chal, Leman Sofla and Olia of Kojour, and the sample size was determined for 45 individuals based on Cochran formula and 28 of them collaborated in the research. Samples were selected by a simple random sampling method and the essential information was collected through a questionnaire. Data analysis was done by SPSSv19 using Pearson and Spearman's correlation coefficient, Spearman, and multivariate regression. The results of the research showed that the rate of participation in rangeland projects was high, but no significant correlation was observed between the age of respondents and the level of their education with the rate of participation in rangeland projects. Besides, there is a significant and positive correlation between the rate of income and the rate of participation in rangeland projects with a probability of more than 95% and there was a significant relationship between the level of trust in government promises and participation in rangeland projects. Regression analysis indicated that the variable of knowledge in rangeland management projects had a greater contribution in predicting the participation rate in rangeland management projects compared to other variables. Also, holding training-extension classes led to an increase in the motivation of participation and also raising problems and issues by experts and managers for rangeland projects caused to reduce the rate of participation in rangeland projects. According to the results of this study, increasing the awareness of ranchers, increasing the level of trust to the government, reducing problems, and increasing the income of ranchers can be suggested as a solution.