Bulletin of the Transilvania University of Brasov. Series II: Forestry • Wood Industry • Agricultural Food Engineering

Evaluation of Tensile and Compression Bending Moment of L-Type Joints With 3D Printed Connectors

2024-12-17T06:39:01+00:00

The paper investigates the bending moments under diagonal tensile and diagonal compression loads of L-type corner joints made of three wooden parts corresponding to the leg and the two stretchers used in chair construction. The wooden parts were jointed together with a 3D printed connector made of polylactic acid (PLA) filaments using Filament Fused Fabrication (FFF) as additive manufacturing technology. Larch (Larix decidua Mill.) wood was used to manufacture the wooden elements. In order to assess how the model orientation on the build platform influences the mechanical performance of the printed connector, two print positions were taken into account during the additive manufacturing (AM) process, namely horizontal and vertical. Mechanical testing under diagonal tensile and compression loads of the L-type corner joints, followed by the microscopic investigation of the fractured connectors with magnifications 50X, 80X, 100X were employed in this study. The results were compared with those of the reference L-type corner joint consisting of common mortise-tenon jointed wooden elements. The results show that the vertical orientation of the model on the build platform of the 3D printer is preferred for a better mechanical performance. The microscopy of the fractured connectors revealed the interlayer delamination of the filaments, especially in the case of the horizontal orientation of the model, which caused the wooden parts to slide out of the connector and record low values of the maximum failure loads.

Development of Mathematical Model for Predicting the Cupping of Lumber

2024-12-17T06:57:07+00:00

Deformations are a significant disadvantage of wood as a structural material for products made of it. Therefore, the purpose of this work was to determine the magnitude and nature of the deformations of lumber used for the manufacturing of laminated panels in construction. The main causes of the possible changes in the shape of the surfaces of laminated panels in construction are characterized. In this paper, a model has been developed for the theoretical study of shape change in lumber, which is proposed to be determined through the warping force, which causes the deformation of lumber. The engineering formulas for calculating the warping force that leads to lumber shape change were obtained. This force mainly depends on size, changes in moisture content and the location of the lumber in the cross-section of the log.

Performance Characteristics of Coatings Created with Alkyd and Oil- Based Materials in Wooden House Construction

2024-12-17T07:32:44+00:00

The paper deals with the issues and study of the properties of varnish-and-paint materials which are used to create protective-anddecorative coatings for joinery and building structures. The article provides an examination of comparative studies on the qualitative characteristics of alkyd varnish (PF-283) and drying linseed. Changes in the drying time of linseed oil and alkyd (pentaphthalic) varnish are determined depending on the material consumption and drying temperature. The studies have shown that the drying rate of films at the same material consumption at temperatures of 50 and 80°С is practically the same and ranges from 80 to 114 minutes. The article also presents the results of studies on the performance properties of finishing materials (coating thickness, water and heat resistance). It was found that alkyd varnish-and-paint materials form a coating of greater film thickness and hardness. In terms of water-resistance and heat-resistance, coatings based on drying oils have higher performance indicators. Recommendations are given for the use of alkyd and oil-based varnish-and-paint materials for finishing joinery and building structures made of oak wood which are used in wooden house construction.

The Influence of Commercial Starter Cultures on the Quality of Telemea Cheese

2024-12-17T07:45:43+00:00

The purpose of this scientific work was to study the influence that commercial starter cultures have on the quality of a traditional Romanian semi-hard cheese, namely Telemea. The starter cultures were thoroughly characterized prior to their application in the process, with particular attention to their impact on the food product both during and following processing. Different experimental types of cheese were obtained using two types of commercial starter cultures (MA11 and WHITE FLORA 1) in combination with a third commercial culture (MO536CRYO): MO536CRYO+MA11 and MO536CRYO+WHITE FLORA 1. The analysis focused on two factors that may influence cheese quality: the type of starter culture (mesophilic and thermophilic lactic acid bacteria) and the quantity of culture added to the milk. Starting from the same raw material, cow milk, and applying similar technological process, the cheeses inoculated with MO536CRYO+WHITE FLORA 1 exhibited superior physico-chemical, microbiological, and sensory characteristics compared to the other produced variants.

Impact of Thermal, Ultraviolet and Ultrasonic Treatment on Mechanical, Physicochemical and Sensory Characteristics of Pear Jelly

2024-12-17T08:06:18+00:00

The purpose of this study is to evaluate the influence of thermal, ultraviolet, and ultrasonic processing by examining the mechanical, physicochemical, and sensory characteristics of pear fruit jelly. Samples were processed using thermal pasteurization (TP), ultraviolet light (UV-C,) and ultrasound (US) at 65°C/50 min for all methods. US increases the most mechanical performance values compared to TP and UV-C treatment which reduces them. TP does not statistically significantly alter most physicochemical characteristics except for sugars, where it exhibits a slight reducing effect. UV-C irradiation increases water activity and moisture content the most compared to other treatments and has the least reducing effect on sugars. The US treatment significantly reduces the glucose, fructose, and sucrose in the highest amount and increases total solids and soluble solids contents. In terms of color characteristics, TP treatment makes the color of the samples darker, UV-C irradiation more saturated, and US preserves the original colour best. The strongest correlations between physicochemical and colour parameters have positive and statistically significant Pearson coefficients. Different processing methods had different effects on the sensory characteristics, with UV-C improving aroma, US taste, and texture, and TP having no significant effect on these.

Phospholipids in Cottonseed Oil and Degumming Methods

2024-12-17T08:14:04+00:00

Phospholipids are categorized into two types: hydratable phospholipids and non-hydratable phospholipids. This study examines the hydratable and non-hydratable phospholipids in cottonseed oil, as well as the types of degumming and their impact on the content of phosphorus, calcium, and magnesium. During water degumming, hydratable phospholipids are removed, but non-hydratable phospholipids remain. Water-hydratable phospholipids constitute 78-83% of the total phospholipids in cottonseed oil. However, water degumming does not sufficiently reduce the cottonseed oil’s phosphorus, calcium, and magnesium content. Acid degumming reduced the phosphorus content by 17.1 mg.kg^-1, calcium by 11.1 mg.kg^-1, and magnesium by 14.2 mg.kg^-1. The total degumming process significantly reduced the levels of accompanying substances in cottonseed oil. After the total degumming process, the phosphorus content was less than 12.4 mg.kg^-1, calcium was 7.4 mg.kg^-1, and magnesium was reduced to 1.1 mg.kg^-1.

Analyzing the Adaptive Reaction of European Beech Provenances from the Perspective of Quality Traits

2024-12-16T19:38:55+00:00

The morphological structure of a tree's stem determines its economic value and can also indicate its level of adaptation to specific environments. Given the current concerns for resilient tree populations, the present survey aims to evaluate the adaptative reaction of European beech in the Carpathian region of Romania from the perspective of quality traits. Four European beech provenance trials, which are part of two international networks, were tested for Stem quality (Sq), Forking (Fk), and Branch diameter (Bd) at the ages of 24 and 27 after planting. The variation of the studied traits across environments and provenances was tested using the Chi-squared test for categorical variables and a linear model for the numerical variables. In the 1995 series, in the more favourable environmental conditions, there was a significantly lower presence of forked trees and lower values for Bd compared to the less favourable site, where the number of trees with severe defects was notably higher. Regarding the 1998 series, there were significantly fewer trees with multiple base stem forks in the warm-humid environment, as well as considerably lower Bd, and a significantly higher number of trees with straight stems, compared with the hot-dry site. The environment significantly conditioned the quality of the stem morphotype of the provenances. The warm-humid and hot-humid environments favoured the adaptation process of the international provenances. Assisted transfer of provenances may be a feasible solution for increasing the quality of Romanian beech stands.

Predicting Willow Planting Events by Conventional Machine Learning from GPS Data: Accuracy, Generalization Ability, and Potential for Improvement

2024-12-16T20:05:19+00:00

Willow cultivation is an important activity that can provide greater amounts of cleaner and renewable energy. To support the development of this farming sector, data is required on the spatial distribution of planted plots, as well as on the performance of operations typically required in willow crop management. Unfortunately, this kind of data is largely unavailable, while documenting it is a challenging task. GPS data, which may be feasibly collected during operations, may be a good carrier of information not only to document the spatial location of plots, but also to learn about the frequency of typical events as specific to willow operational management. Based on a GPS dataset characterizing two plots, which was collected during planting operations and labelled manually (8,385 observations), a neural network was used in this study to spatially classify events such as driving (hereafter called D), maneuvering (hereafter called M), planting (hereafter called P), and being stopped (hereafter called S). Three models were trained and validated based on features such as GPS speed (hereafter called model S), GPS speed and leg length (hereafter called model S&L), and GPS speed, leg length, and heading (hereafter called model S&L&H), respectively. Classification performance was found to be impressive, with an overall accuracy of 92.0 (S), 92.1 (S&L), and 93.3% (S&L&H), respectively. The quality of the models was then checked visually using a dataset containing unseen data characterizing two plots of different cardinal orientation, indicating an acceptable generalization ability. The methods described in the paper may be useful when dealing with large datasets and limited resources and expertise in labelling the data manually, as they provide location and event specific data with high accuracy. Improvements in accuracy are possible by integrating the raw data in deep learning, an approach that should be explored further.

Developing an AI Tool for Forest Monitoring: Introducing SylvaMind AI

2024-12-16T20:17:54+00:00

Global forests face increasing threats from deforestation, biodiversity loss, and climate change, necessitating innovative tools for effective monitoring and management. Traditional forest monitoring methods, which rely heavily on manual fieldwork and labor-intensive data processing, are often inadequate for addressing the scale and complexity of these challenges. Advanced tools leveraging artificial intelligence (AI) and remote sensing have emerged as critical solutions, offering timely, accurate, and actionable insights to enable efficient ecosystem monitoring, threat detection, and sustainable management practices. This paper introduces SylvaMind AI, an advanced platform that integrates satellite imagery, deep learning frameworks, and geospatial analysis within a user-friendly interface, which was built using Python for backend systems and deep learning pipelines, alongside tools like Pandas, Rasterio, and TensorFlow for data preprocessing and predictive modelling. The platform processes high-resolution data from Sentinel-2 and Landsat missions for feature extraction and predictive modelling. SylvaMind AI offers two modelling approaches: an automated option for non-technical users and a customizable feature for researchers with specialized needs. Using these approaches, we developed a predictive canopy height model for a study area. The results demonstrated the platform's ability to capture underlying forest patterns and provide detailed insights into canopy height distribution, particularly for medium to high canopies (>25m). This underscores its strength in modeling structural complexity in dense forests. However, the model showed limitations in representing smaller trees, attributed to insufficient training data. SylvaMind AI holds immense potential in transforming forest monitoring by leveraging advanced geospatial data, AI, and intuitive design to address critical challenges in sustainable forest management.

Quantifying Forest Disturbances and Lanscape Level Over Half a Century Using Cold War SPY Satellite and Contemporary Imagery. Case Study Pecineagu Watershed, Romania

2024-12-16T20:29:09+00:00

This study examines disturbances in the Pecineagu watershed forests over the last 50 years. The primary objective of this study is to comprehensively assess the intensity and consequences of canopy disturbances in the Pecineagu watershed forests over the past half-century. Utilizing meta-analysis and advanced remote sensing techniques, including satellite imagery from Corona Spy, Landsat, and Sentinel-2, we identified significant changes in forest cover and structure. The analysis revealed 142 hectares of disturbed forest between 1986 and 1996, with a notable portion undergoing clearcutting and afforestation. Despite these disturbances, our findings show high forest connectivity and low fragmentation, predominantly in the dominant forest layer. However, two areas, i.e. Berevoiu – Valea Coltilor and Manastire – Valea Comisului, experienced substantial fragmentation in different periods, indicating variable impacts across the watershed. These results underscore the importance of continuous monitoring and sustainable forest management to maintain forest connectivity and minimize fragmentation. The study also highlights the need for accurate data recording in forest management plans for effective resource management, offering crucial insights into forest conservation strategies amid environmental changes.

A 30-Year Analysis of Forest Cover and Land Surface Temperature in Attapeu Province, Lao PDR

2024-12-16T20:40:06+00:00

Changing forest areas can have a complex range of impacts on ground temperatures, from increasing temperatures due to loss of shade to creating drier and hotter local climate environments. This study aims to identify spatiotemporal changes in forest cover and retrieve land surface temperature (LST) using thermal infrared sensor (TIRS) data in Attapeu province, Lao PDR from 1994 to 2024. Geographic information system (GIS) techniques were employed to extract spatiotemporal changes in land use and land cover (LULC) and Normalized Difference Vegetation Index (NDVI). The analysis of LULC change revealed a notable decrease of 18.43% in dense forest areas, accompanied by an increase of 7.87% in sparse forest and 11.35% in cropland, indicating a transition from dense forest to sparse forest and cropland for the study area. The analysis of LST utilizing TIRS revealed a consistent negative correlation with NDVI. The coefficient of determination (R2) indicated values of 0.5896 in 1994, 0.5691 in 2009, and 0.4344 in 2024. By correlating remotely-sensed thermal data with in situ observations, this research delineated the prolonged alterations in LST due to fluctuations in forest cover. The urgency of enacting policies is underscored to mitigate the ongoing loss of forest cover. These findings emphasize the need for immediate policy actions, such as enhanced forest conservation and reforestation programs, to mitigate rising temperatures and ensure ecological sustainability in Attapeu province. The insights garnered from this investigation hold significant implications for the conservation endeavors aimed at preserving the forests of Attapeu province.