Tree Diameter Research Articles

Tree parameter extraction in Fokienia hodginsii plantation based on airborne LiDAR data.

Accurate and efficient extraction of tree parameters from plantations lay foundation for estimating individual wood volume and stand stocking. In this study, we proposed a method of extracting high-precision tree parameters based on airborne LiDAR data. The main process included data pre-processing, ground filtering, individual tree segmentation, and parameter extraction. We collected high-density airborne point cloud data from the large-diameter timber of Fokienia hodginsii plantation in Guanzhuang State Forestry Farm, Shaxian County, Fujian Province, and pre-processed the point cloud data by denoising, resampling and normalization. The vegetation point clouds and ground point clouds were separated by the Cloth Simulation Filter (CSF). The former data were interpolated using the Delaunay triangulation mesh method to generate a digital surface model (DSM), while the latter data were interpolated using the Inverse Distance Weighted to generate a digital elevation model (DEM). After that, we obtained the canopy height model (CHM) through the difference operation between the two, and analyzed the CHM with varying resolutions by the watershed algorithm on the accuracy of individual tree segmentation and parameter extraction. We used the point cloud distance clustering algorithm to segment the normalized vegetation point cloud into individual trees, and analyzed the effects of different distance thresholds on the accuracy of indivi-dual tree segmentation and parameter extraction. The results showed that the watershed algorithm for extracting tree height of 0.3 m resolution CHM had highest comprehensive evaluation index of 91.1% for individual tree segmentation and superior accuracy with R2 of 0.967 and RMSE of 0.890 m. When the spacing threshold of the point cloud segmentation algorithm was the average crown diameter, the highest comprehensive evaluation index of 91.3% for individual tree segmentation, the extraction accuracy of the crown diameter was superior, with R2 of 0.937 and RMSE of 0.418 m. Tree height, crown diameter, tree density, and spatial distribution of trees were estimated. There were 5994 F. hodginsii, with an average tree height of 16.63 m and crown diameter of 3.98 m. Trees with height of 15-20 m were the most numerous (a total of 2661), followed by those between 10-15 m. This method of forest parameter extraction was useful for monitoring and managing plantations.

Vegetative and Reproductive Responses Induced by Organo-Mineral Fertilizers on Young Trees of Almond cv. Tuono Grown in a Medium-High Density Plantation

Field experiments were conducted in three successive seasons (2019–2021) to evaluate the effects of four commercial organo-mineral fertilizers with biostimulating action (Hendophyt®, Ergostim®, and Radicon®) on the vegetative and productive performance of young almond trees (Prunus dulcis, cv. Tuono) grown in a semiarid climate in Southern Italy. Foliar treatments were applied three times during each season (at the swollen bud, beginning of flowering, and fruit set-beginning of fruit growth stages). Both 2020 and 2021 were adversely affected by late frosts, resulting in damage to the flowers and small fruits without any positive effect of the biostimulant applications. In contrast, the results obtained during the normal climate year (2019) indicated that the growth of trunk diameter and shoot length of trees tended to increase in biostimulant treatments compared to those of the control. The number of buds and flowers per unit length of the branch revealed no significant differences among years and all compared treatments. However, in 2019, the fruit set percentage, number, and weight of kernels per tree were significantly higher in the biostimulant treatments compared to those of the control. To this regard, the use of biofertilizers is suitable for maintaining soil fertility and improving crop productivity This information holds significance for almond tree growers.

Application of the Global Uncertainty and Sensitivity Analysis to assess the importance of deadwood characteristics for forest biodiversity

AbstractData acquisition for sustainable forest management has focused on obtaining high quality information to estimate biomass. Improving the quality of non-timber sustainability indicators, like deadwood volume, has been a minor interest. To explore how inventory approaches could be improved, we applied a Global Uncertainty and Sensitivity Analysis (GUSA) to evaluate which factors propagate more errors in deadwood modelling and how better data collection can minimize them. The impact of uncertainty on deadwood characteristics (diameter, collapse ratio, decay class, tree species, and position) was explored under stakeholders´ preferences, management actions, and climate change scenarios. GUSA showed that removing the prediction error in deadwood tree species and diameter would alter the most the total uncertainty in deadwood volume. We found that assessment of high deadwood volume was less uncertain for the scenarios where small deadwood items were left decaying on the forest floor (BAU) and for high-end climate change scenario (RCP8.5) which resulted in lower deadwood accumulation in forest stands and therefore also in lower likelihood of erroneous estimates. Reduced uncertainty in tree species and diameter class will elevate the certainty of deadwood volume to a similar level achieved in living biomass estimation. Our uncertainty and sensitivity analysis was successful in ranking factors propagating errors in estimate of deadwood and identified a strategy to minimize uncertainty in predicting deadwood characteristics. The estimation of uncertainty in deadwood levels under the scenarios developed in our study can help decision makers to evaluate risk of decreasing deadwood value for biodiversity conservation and climate change mitigation.

A planting optimization strategy to improve the carbon sink benefit for urban green-Taking the communal green of Nanjing Forestry University as an example

This research study identified the communal green at Nanjing Forestry University as an example and focused on the carbon sink benefits of the plant communities. Firstly, the representative plant communities in the communal green were investigated, and the parameters of the plant communities were established so that the carbon sink benefits of each plant community could be quantified. Secondly, by applying correlation analysis to study the influence degree of varied plant community factors on the benefits of carbon sink, it was found that the canopy closure, diameter class structure and tree density showed significant positive correlation; the correlation between community density and daily carbon sequestration per unit area was significant; the correlation between community density and carbon storage per unit area showed none significance; and the correlation between the proportion of trees and shrubs and the carbon sink benefits was of no significance. Thirdly, regression analysis was used to study the curve trends of the carbon sink benefits of the plant communities, from which it was concluded that increasing canopy density, average plant height, average crown width and tree density will improve carbon sink benefits. Increasing the average DBH would achieve positive effects for increasing daily carbon sequestration per unit area only at the early stage of the community growth. The plant community density showed positive effects on the increase of the daily carbon sequestration per unit area within a limited range. Since most regression formulas resulted in S-curves, certain threshold bottlenecks were found existed of improving the carbon sinks benefits by increasing the plant community factors. Finally, the characteristics of plant communities with high carbon sink benefit were summarized to provide theoretical references for forming a planting optimization strategy of urban green.

Tree Diameter at Breast Height (DBH) Estimation Using an iPad Pro LiDAR Scanner: A Case Study in Boreal Forests, Ontario, Canada

The aim of this study was to determine whether the iPad Pro 12th generation LiDAR sensor is useful to measure tree diameter at breast height (DBH) in natural boreal forests. This is a follow-up to a previous study that was conducted in a research forest and identified the optimal method for (DBH) estimation as a circular scanning and fitting ellipses to 4 cm stem cross-sections at breast height. The iPad Pro LiDAR scanner was used to acquire point clouds for 15 sites representing a range of natural boreal forest conditions in Ontario, Canada, and estimate DBH. The secondary objective was to determine if tested stand (species composition, age, density, understory) or tree (species, DBH) factors affected the accuracy of estimated DBH. Overall, estimated DBH values were within 1 cm of actual DBH values for 78 of 133 measured trees (59%). An RMSE of 1.5 cm (8.6%) was achieved. Stand age had a large effect (>0.15) on the accuracy of estimated DBH values, while density, understory, and DBH had moderate effects (0.05–0.14). No trend was identified between accuracy and stand age. Accuracy improved as understory density decreased and as tree DBH increased. Inertial measurement unit (IMU) and positional accuracy errors with the iPad Pro scanner limit the feasibility of using this device for forest inventories.

Multivariate Analysis of the Community Composition of Tidal Freshwater Forests on the Altamaha River, Georgia

Situated in the transitional zone between non-tidal forests upstream and tidal freshwater marshes downstream, tidal freshwater forests (TFF) occupy a unique and increasingly precarious habitat due to the threat of saltwater intrusion and sea level rise. Salinization causes tree mortality and forest-to-marsh transition, which reduces biodiversity and carbon sequestration. The Altamaha River is the longest undammed river on the United States East Coast and has extensive TFF, but there have been only limited field studies examining TFF along the entire gradient of salinity and flooding. We surveyed thirty-eight forest plots on the Altamaha River along a gradient of tidal influence, and measured tree species composition, diameter, and height. Hierarchical clustering and indicator species analysis were used to identify TFF communities. The relationship of these communities to elevation and river distance was assessed using non-metric multidimensional scaling (NMDS). We identified six significantly different forest communities: Oak/Hornbeam, Water Tupelo, Bald Cypress/Tupelo, Pine, Swamp Tupelo, and Bald Cypress. Both elevation and river distance were significantly correlated with plot species composition (p = 0.001). Plots at the downstream extent of our study area had lower stem density, basal area, and species diversity than those further upstream, suggesting saltwater intrusion. This study demonstrates the importance of and need for thorough and robust analyses of tidal freshwater forest composition to improve prediction of TFF response to sea level rise.

Ecosystem carbon fluxes are tree size-dependent in an Amazonian old-growth forest

Tropical forests are important carbon sinks as they store huge amounts of carbon and are thus essential players within the global carbon cycle. While good estimates of the gross and net primary productivity (GPP and NPP, respectively) of tropical forests exist, we still lack a cohesive study on the contribution of different tree sizes to the overall forest carbon fluxes and their seasonal variation. Here, we model GPP based on xylem sap flux and eddy covariance data for an old-growth moist lowland forest in Central Amazon for the year 2013 (Jan-Dec). The model uses canopy transpiration and vapor pressure deficit as covariates and enables GPP partitioning into fluxes from canopy, subcanopy, and understory trees. Net primary productivity was calculated from forest inventory data. Carbon use efficiency (CUE) was computed as the ratio between NPP and GPP. GPP was 28.46 MgC ha−2 yr−1 at our study site. Canopy trees (diameter > 30 cm; average height of 28 m) were responsible for 21.47 MgC ha−2 yr−1 of the overall GPP, whereas subcanopy and understory trees contributed 3.95 MgC ha−2 yr−1 and 3.04 MgC ha−2 yr−1, respectively. Canopy trees allocated only 23% of their photosynthetic products towards growth and were responsible for more than 50% of NPP. Subcanopy and understory trees were more efficient by allocating 67% and 59% of their carbon assimilates towards biomass growth, respectively. GPP showed distinct seasonal patterns, with canopy trees doubling monthly GPP with the progressing dry season, whereas understory and subcanopy trees had a 60% higher GPP than in the wet season. This study provides evidence for the importance of large trees in tropical forests and highlights their crucial role in forest carbon cycling. Due to high drought-related mortality, large trees make up a critical component of the response of tropical forests to climate change.

Tree Crown Segmentation and Diameter at Breast Height Prediction Based on BlendMask in Unmanned Aerial Vehicle Imagery

The surveying of forestry resources has recently shifted toward precision and real-time monitoring. This study utilized the BlendMask algorithm for accurately outlining tree crowns and introduced a Bayesian neural network to create a model linking individual tree crown size with diameter at breast height (DBH). BlendMask accurately outlines tree crown shapes and contours, outperforming traditional watershed algorithms in segmentation accuracy while preserving edge details across different scales. Subsequently, the Bayesian neural network constructs a model predicting DBH from the measured crown area, providing essential data for managing forest resources and conducting biodiversity research. Evaluation metrics like precision rate, recall rate, F1-score, and mAP index comprehensively assess the method’s performance regarding tree density. BlendMask demonstrated higher accuracy at 0.893 compared to the traditional watershed algorithm’s 0.721 accuracy based on experimental results. Importantly, BlendMask effectively handles over-segmentation problems while preserving edge details across different scales. Moreover, adjusting parameters during execution allows for flexibility in achieving diverse image segmentation effects. This study addresses image segmentation challenges and builds a model linking crown area to DBH using the BlendMask algorithm and a Bayesian neural network. The average discrepancies between calculated and measured DBH for Ginkgo biloba, Pinus tabuliformis, and Populus nigra varitalica were 0.15 cm, 0.29 cm, and 0.49cm, respectively, all within the acceptable forestry error margin of 1 cm. BlendMask, besides its effectiveness in crown segmentation, proves useful for various vegetation classification tasks like broad-leaved forests, coniferous forests, and grasslands. With abundant training data and ongoing parameter adjustments, BlendMask attains improved classification accuracy. This new approach shows great potential for real-world use, offering crucial data for managing forest resources, biodiversity research, and related fields, aiding decision-making processes.

Gene Diversity In Seed Crop Of Taurus Cedar (Cedrus Libani A. Rich.) Over An Altitudinal Range

There could be many environmental and biological impacts such as edaphic, geographic, climatic, age, tree structure and population on morphological, physiological and genetically seed quality in plant species. Gene diversity is an important mirror of genetically seed quality. Gene diversity in seed crops were estimated based on female and male strobili productions of fifty trees (N) randomly chosen from each population sampled over an altitudinal range as low (1200-400 meters ≤ altitude), middle (1400 m < altitude ≤ 1600 m), high (1600 m < altitude ≤ 1800 m), and very high (1800 m < altitude) in Taurus cedar also known as cedar of Lebanon (Cedrus libani A. Rich.) for two consecutive years (2021&2022). The variation in strobilus production was subjected to estimation of female and male fertility variation. The total fertility variation (Ψ) was estimated from the female and male fertility variation. Impacts of some growth characteristics (tree height and diameter at breast height) on strobili productions were also investigated. Strobili productions varied among the populations and individuals within population, and between years. The differences for populations and years were also found for coefficient of variations which were mirror of fertility variation of the strobili productions. Tree height and diameter at breast height seemed more reasonable predictor than age for number of strobili. Fertility variations of female parents were generally higher than that of male in both years. First year showed generally higher parental variations in individual populations. Gene diversity (GD=1-0.5Ψ/N) ranged from 0.967 to 0.974 for the populations and years. The loss of highest gene diversity was 0.004 in low population (0.967 & 0.971) between years. Results of the study indicated that altitudinal gene diversity of seed crop could be used to produce genetically quality seed and their grading. Moreover, data sets can be used to fill the Forest Landscape Restoration library (FLR-Library).

Grey alder at the regeneration stage: Long-term effects on soil nitrogen and carbon pools and Norway spruce growth

Increasing soil N availability is an effective way to enhance soil organic carbon (SOC) sequestration and biomass production in N-limited ecosystems such as boreal Norway spruce forests. Alder has a root nodule symbiosis with Frankia, an N2-fixing bacterium, and can thus add considerable amounts of N to soil mainly through its N-rich leaf litter. The objective of this study was to determine whether the presence of grey alder at the regeneration stage had any long-term effects on soil C and N cycling and stocks and spruce growth. The study sites were two relatively fertile 40-year-old Norway spruce stands (Luhdansuo and Porkkola) in Southern Finland. At both study sites, half the spruce stand had an admixture of grey alders for approximately 10–15 years after regeneration (alder treatment), but no alder had been present in the other half (control treatment). Alders were cut from the alder treatment 25 (Luhdansuo) or 30 (Porkkola) years before the measurements. At Porkkola, alder treatment received ash fertilisation 13 years ago. We observed no significant differences in the plant-available N fluxes, measured with a microdialysis technique, or SOC stocks between treatments. The total N stock (organic horizon + 0–30 cm mineral soil) and organic horizon thickness were larger, while the microbial biomass C:N and C mineralisation rate were lower in the alder versus the control treatment at Luhdansuo. The annual ring widths of spruces were larger in the alder versus the control treatment for up to six years after alder removal at both sites, but no differences were observed in the current tree diameters or diameter increments. In conclusion, most of the current soil or tree properties did not differ significantly between treatments, possibly because the effect of alder had faded out over the 25–30 years since its removal, and because the sites were initially relatively fertile.

Early treatment effects on plantation growth and biodiversity in mature ponderosa pine forest

We address the concerns that managed forest plantations may cause reductions of diversity of understory vegetation. We performed inventories of two mature ponderosa pine plantations in which multiple treatments were applied during plantation establishment. At stand age 35, we measured tree heights and diameters, understory plant cover and diversity, soil nutrients and chemical properties, and soil microbial biomass and diversity with phospholipid fatty acid. We found a significant, positive effect from both herbicide (H) and fertilizer (F) applications on subsequent overstory tree growth and development ( P < 0.05); insecticide (I) effect was minimal. We observed negative effects on understory plant diversity decades later when herbicide was applied during stand establishment. However, lower plant diversity and ground cover appeared to have been caused primarily from overstory canopy closure, supported by the increased understory cover and diversity observed in the HI and HFI plots that had been thinned at age 12. Similarly, while fertilizer increased tree growth at both sites, it only negatively affected understory plants at the higher quality site. We did not find significant influence of treatment effects on soil nutrients and microbial communities. Therefore, to mitigate the potential loss of understory biodiversity in plantations, foresters can manage overstory trees with traditional pre-commercial thinning techniques and early tending.

Species-specific allometric models for reducing uncertainty in estimating above ground biomass at Moist Evergreen Afromontane Forest of Ethiopia

An allometric equation is used to convert easily measured tree variables into biomass. However, limited species-specific biomass equations are available for native tree species grown in various biomes of Ethiopia. The available pantropic generic equation has resulted in biases owing to the uncertainty of the generic model estimation due to the difference in tree nature and response to growth conditions. The objective of the study is, thus, to develop a species-specific allometric equation for reducing uncertainty in biomass estimation at the Moist Evergreen Afromontane Forest in south-central Ethiopia. Five tree species were selected for model development, these selected trees were harvested and weighed in the field. The measured above-ground biomass data related to easily measured tree variables: diameter at stump height, diameter at breast height (dbh), crown diameter, and total tree height. The developed model evaluated and compared with previously published model by using measures of goodness of fit such as coefficient of determination (R2), total relative error, mean prediction error, root mean square error, and Akaike information criteria. The analysis showed that a model with dbh as a single predictor variable was selected as the best model for the estimation of above-ground biomass. It gives the highest R2 for Syzygium guineense (0.992) and the lowest for Bersama abyssinica (0.879). The additions of other tree variables did not improve the model The pantropic model by Brown overestimates the biomass by 9.6–77.8% while both Chave models resulted in an estimation error of 12–50.3%. Our findings indicated that species-specific allometric equations outperformed both site-specific and pantropic models in estimating above-ground biomass by giving 0.1% up to 7.9% estimation error for the respective tree species.

A comparison of initial harvest results from four partial harvest systems at the Blue Heron Demonstration Forest

Demonstration forests have been established across the northern hardwoods of the United States to assess the economic and environmental implications of partial harvest systems, such as single tree selection and diameter limit cutting. Single tree selection has been studied at several sites in the northern hardwoods of Canada, but there has not been a structured comparison of partial harvest systems within one site. We assessed the initial harvest results at the Blue Heron Demonstration Forest, in which four partial harvest systems – single tree selection (STS), financial maturity selection (FMS), diameter limit cutting (DLC), and crop tree release (CROP) – and a control treatment were implemented with multiple replicates within a typical northern hardwood forest in central Ontario. DLC harvested the most volume as well as basal area, followed closely by FMS. STS harvested the least basal area and volume and generated the lowest product values as well as the lowest stumpage revenue. However, STS did not harvest significantly more low vigour trees, nor did it significantly increase the proportion of basal area that is high vigour, suggesting that alternative partial harvest systems like FMS may achieve silvicultural objectives while yielding superior financial results over multiple cutting cycles.

A novel forestry information-collecting mobile system

Automatic forestry mobile system is needed to perform the information-collecting tasks, which could not only improve the efficiency but also free the mankind from the heavy labour. In this paper, a set of automatic system is proposed. It consists of a novel multi-mode robot and a visual information-collecting system. The multi-mode robot is designed by utilizing the Schatz linkage, and it could surmount obstacles to traverse the rough terrain in the forest. The switch between the mobile modes is realised by the shape of the touchdown link of the robot, which avoid the inconvenience of switching mechanism. The visual information-collecting system is built with an RGB-D camera, a mechanical arm and a lower computer. The system could collect the forestry information from the images captured by the camera. A prototype of the system is fabricated and assigned the task to measure the breast diameters (DBH) of the experimental trees. The data is compared with the data that measured manually, and the results verify that the system could traverse the rough terrain in the forest and perform the forestry information-collecting task precisely.

A multilayered urban tree dataset of point clouds, quantitative structure and graph models

The significance of urban trees in promoting human health and well-being has been amplified by urbanization and the climate change effects. Simultaneously, advancements in remote sensing techniques have enhanced the opportunities for studying urban trees. The TreeML-Data has been compiled to support these efforts. It consists of labelled point clouds of 40 scanning projects of streets in Munich, 3,755 leaf-off (scans in winter) point clouds of individual trees, quantitative structure models (QSM), tree structure measurements, and tree graph structure models of these trees. The dataset offers valuable data for generating and evaluating models in various scientific disciplines, which include remote sensing, computer vision, machine learning, urban forestry, urban ecosystem, green architecture, and graph analysis. To ensure its quality, the tree structure measurements and QSM have been crosschecked. For instance, the tree diameter at breast height (DBH) in the sample dataset exhibits a deviation of approximately 1.5 cm (4.3%) when compared to manual measurements. In conclusion, the quality checks confirm its reliability for subsequent studies when compared to manual measurements.

Compositional changes at neighborhood and stand scales during recovery of a tropical lowland rainforest after shifting cultivation on Hainan Island, China

Understanding compositional changes during secondary forest recovery is crucial for effective restoration efforts. While previous research has predominantly focused on shifts in species composition at the stand scale, this study delves into the recovery dynamics in three compositional aspects of location (neighbor distances), size (tree diameters), and species (tree species) at both stand and neighborhood scale. The investigation spans nine chronosequence plots within a tropical lowland rainforest ecosystem after shifting cultivation, including three each for young-secondary forests (18–30 years), old-secondary forests (60 years), and old-growth forests (without obvious human interference). The quantification of location, size, and species composition involved categorized neighbor distances (Near, Moderate, Far-distance), tree diameters (Small, Medium, Large-tree), and tree species (Pioneer, Intermediate, Climax-species) into three groups, respectively. Compositional changes at the stand scale (plot) were directly based on these groups, while at the neighborhood scale, assessment involved combination types of these groups within a neighborhood (comprising three adjacent trees). At the stand scale, neighbor distances shifted from Near to Moderate and Far, tree diameters transitioned from Small to Medium and Large, and tree species of Pioneer gave way to Climax. Meanwhile, at the neighborhood scale, there was a notable decline in the aggregations of Near-distance (N), Small-tree (S), and Pioneer-species (P), while the mixtures of Far and Moderate-distance (F-M), Large and Small-tree (L-S), and Climax and Intermediate-species (C–I) experienced a marked increase. The compositional change exhibited a recovery pattern, with the fastest recovery in neighbor distances, followed by tree diameters and tree species. Moreover, compositional recovery in tree diameters and tree species at the neighborhood scale generally lagged behind that at the stand scale. The study suggests that rapid restoration of secondary forest can be achieved by different targeted cutting according to the recovery stages, aimed at reduce the Pioneer-species, Small-tree and Near-distance in neighborhood. Our findings underscore that analyzing the compositional changes in three aspects at two scales not only provides a profound understanding of secondary forest recovery dynamics, but also offers valuable insights for guiding practices in the restoration of degraded forest ecosystems.

Tree canopy area-dependent changes in soil properties: a comparative study in the southern limit of boreal forest distribution

The forest distribution in relation to mountain slope position and the relationships between forest canopy area and soil physical and chemical properties in Mongolia attract the attention of scientists. In this study, we aimed to determine (1) how the slope aspect affects the forest soil physical and chemical properties, (2) how the soil variables correlate with projected canopy area. For comparative study, we established a total of 18 (20 × 25 m2 sized) sample plots in upper forest edge (UFE), upper slope of the forest (USF), lower slope of the forest (LSF), lower forest edge (LFE), sparse forest (SF), and degraded forest area (DFA) stand types with three replications. We measured the tree height, diameter and crown projection area of each growing tree in the sample plots, and collected soil samples for further soil physical and chemical analyses in the laboratory. Our results showed a high variation in growing stock (p < 0.0001), stand density and projected canopy area (p < 0.0001) in relation to mountain slope position and land-use management. We found that the slight changes in stand canopy area projection cause a high variation in soil physical and chemical properties. Among studied stand types higher means of soil temperature and bulk density and lower moisture content were observed on SF and DFA stand types. Contrary, relatively higher content of soil moisture and nutrient elements were recorded in USF, LSF, LFE. We conclude that tree canopy area becomes key determinant factor that positively influences forest soil moisture and fertility by increasing organic matter content in Mongolia.

Complete signed graphs with largest maximum or smallest minimum eigenvalue

In this paper, we deal with extremal eigenvalues of the adjacency matrices of complete signed graphs. The complete signed graphs with maximal index (i.e. the largest eigenvalue) with n vertices and m≤⌊n2/4⌋ negative edges have been already determined. We address the remaining case by characterizing those with m>⌊n2/4⌋ negative edges. We also identify the unique signed graph with maximal index among complete signed graphs whose negative edges induce a tree of diameter at least d for any given d. This extends a recent result by Li, Lin, and Meng [Discrete Math. 346 (2023), 113250] who established the same result for d=2. Finally, we prove that the smallest minimum eigenvalue of complete signed graphs with n vertices whose negative edges induce a tree is −n2−1−1+O(1n).

Trends in radial growth of Scott pine trees in geographical crops

The purpose of the research is to identify trends in the change in radial growth, the width and structure of annual rings in forest-steppe and steppe pine ecotypes in 59-61-year-old geographical cultures. To achieve the intended goal, according to the methodology adopted in forest inventory, 32 trial plots were laid, on which the diameter of trees at a height of 1.3 m with an accuracy of 0.1 cm and the height with a Blume-Leiss altimeter with an accuracy of 0.1 m were measured with a measuring fork. area (PP) from 3 trees of average diameter and height, radial wood cores were taken with a Haglof-60 age borer at a height of 1.3 m. After dating the growth rings of wood, their width was measured at the Lintab-6 complex, divided into early and late. The obtained data were statistically processed using the programs Statistica 8.2 and Excel-10. In the forest-steppe and steppe ecotypes, the trends of radial growth were determined and their features with age were revealed. So, up to 10 years it increases, then sharply decreases and after 20 years it stabilizes.

Prediction of essential oil content in C. sintoc Leaves based on the direction of vegetation slope in Mount Ciremai National Park using ANFIS Artificial Neural Network.

C. sintoc is a plant that has a high essential oil content. Essential oils have many health benefits. Mount Ciremai National Park is an area that has abundant vegetation, especially C. sintoc. The purpose of this study was to predict the volume of oil contained in the leaves of C. sintoc based on its growing location in Mount Ciremai National Park (TNGC), West Java. Sampling was carried out in two stages, namely field samples and laboratory samples. Field samples with a single plot measuring 20 x 20 meters. Extraction of laboratory samples by steam distillation method. Data analysis using ANFIS method to predict the volume of essential oil. The results showed that the volume of essential oil in the leaves was largest on the western slope (1,96 ml), northern slope (2,01 ml), eastern slope (1,55 ml) and southern slope (1,37 ml) while the essential oil yield of extract oil in the leaves is found on the western slope (0,08%), northern slope (0,07 %), eastern slope (0,06 %) and southern slope (0,04), On the western slope (1,82 ml), northern slope (1,73 ml). The ANFIS analysis results showed a prediction accuracy of 90,99% with the highest tree productivity when C. sintoc BL grows at an altitude of 650-700 meters above sea level, tree diameter of 42 cm, height of 12 m, growing on sand-textured land and at a humidity of 75 and at a growing temperature range of 25-270C. The value of essential oil production volume is influenced by each variable such as tree diameter, tree height, soil texture, altitude, temperature and humidity.