Canopy Volume Research Articles

Artrópodos asociados a dos especies de arbustos nativos en Playa Magagna, Chubut

Playa Magagna is a protected area located near the city of Rawson (Chubut), where urban development is increasing. Therefore, it is essential to develop strategies for the sustainable use of its natural resources. The aim of this study was to investigate the biodiversity of the area, focusing on arthropods associated with two native shrubs: Atriplex lampa (“zampa”) and Chuquiraga erinacea ssp. hystrix (“uña de gato”). The beating method was used to collect arthropods from five shrubs of each species at six sampling sites (n= 60). Additionally, architectural variables and the richness of associated plants were measured for each shrub. Variation in arthropod assemblages between the shrub species and their relationship with plant variables were analyzed. Arthropod abundance was higher in A. lampa, while the richness and diversity of families were similar in both shrub species. The assemblages were well differentiated, and their structuring was mainly explained by the canopy volume. This information enhances the understanding of regional biodiversity and will contribute to the development of a management and conservation program for Playa Magagna.

Genetic variability in macadamia rootstocks and their effects on early vigor traits of ‘HAES 741′

Early vigor in tree crops is crucial as it accelerates orchard establishment and enhances resilience to environmental stresses. Rootstocks play an essential role in determining vigor of tree crops. Macadamia is propagated through grafting, however research into rootstocks is rare. This study evaluated a range of macadamia rootstocks including cultivars, standard rootstocks, breeding selections and wild germplasm, focusing on their effects on early vigor (age 4). Phenotypic variability in the scion ‘HAES 741′ was assessed using 24 accessions of seedling and cutting rootstocks over 4 years (2018–2021), analyzing 7 early vigor traits and growth rates. Principal coordinate analysis and cluster analysis revealed high genetic diversity among accessions, clustering into 4 groups. Significant rootstock effects on early vigor were observed. Broad-sense heritability estimates of rootstock effects were moderate for scion height (H2=0.48) and total height (H2=0.44), holding promise for improvement through selection. Positive correlations among scion growth traits, particularly trunk circumference, (rg= 0.50 to 0.99) suggested their potential as indicators of early vigor. The strong genetic correlations for canopy area (rg = 0.84) and canopy volume (rg = 0.63) between scions of grafted trees and the ungrafted trees of the same rootstock accessions reflect the possibility of trait transmission from rootstock to scion. Among the studied rootstocks, ‘BHI1’, ‘BHY2’ and ‘BHI3’ imparted the highest early vigor. Compared with the current industry standard rootstocks ‘H2’ and ‘Beaumont’, the least vigorous rootstocks ‘Mjan1’ and ‘BDW3’ showed reductions of 18 % and 47% in tree height, 54 % and 74% in trunk circumference and 97 % and 210 % in canopy volume respectively. These findings suggest promising rootstock candidates for high performing orchard systems, although ongoing evaluation until maturity is crucial.

Effects of Urban Tree Species and Morphological Characteristics on the Thermal Environment: A Case Study in Fuzhou, China

Trees and their morphology can mitigate the urban heat island (UHI) effect, but the impacts of tree species and their two-dimensional (2D) and three-dimensional (3D) morphological characteristics on the thermal environment of residential spaces at the building scale have not been effectively evaluated. This research extracted the data of trees in the spatial range of a 50 m radius of the sampling sites located in a subtropical humid city’s residential area based on unmanned aerial vehicle (UAV) imagery and field measurements. It included Ficus microcarpa L. f., Cinnamomum camphora (L.) J. Presl, and Alstonia scholaris (L.) R. Br. as three typical evergreen tree species and six quantitative indicators of trees, with the number of trees (N) serving as fundamental indicator and mean canopy width (MCW), mean canopy height (MCH), mean tree height (MTH), canopy biomass (CV), and mean canopy biomass (MCV) as morphological characteristic indicators. We analyzed the impact of the six indicators above on two thermal environment parameters: Air temperature (AT) and relative humidity (RH), by correlation analysis and multiple linear regression analysis. Results showed that: (1) F. microcarpa, as a dominant local species, provided more than 65% of the tree canopy volume within the study area (50 m radius buffer zones), and its contribution to cooling and humidification effects was superior to those of C. camphora and A. scholaris. (2) The MTH and CV of F. microcarpa are the key factors influencing daytime AT and RH, respectively, with temporal fluctuation in impact intensity during the spring (May) daytime. (3) The MTH and N of F. microcarpa show the best cooling effect (adjusted R2 = 0.731, p < 0.05) during midday (13:00–14:00 p.m.), while its CV and MTH have the best humidification effect (adjusted R2 = 0.748, p < 0.05) during the morning (9:00–10:00 a.m.) among three typical tree species. The 2D and 3D morphological characteristic indicators effectively describe the impact and variation of tree species on the spring microclimate within small-scale residential spaces. This work provides new insights into the thermal benefits brought by the spatial growth features of trees at the building scale and offers reference for urban residential areas in the planning and management related to tree species selection, canopy maintenance, and the improvement of thermal comfort for inhabitants.

Crop canopy volume weighted by color parameters from UAV-based RGB imagery to estimate above-ground biomass of potatoes

Current techniques to estimate crop aboveground biomass (AGB) across the multiple growth stages mainly used optical remote-sensing techniques. However, this technology was limited by saturation of the canopy spectrum. To meet this problem, this study used digital images obtained by an unmanned aerial vehicle to extract the spectral and structural indicators of the crop canopy in three key potato growth stages. We took the color parameters (CP) of assorted color space transformations as the canopy spectral information, and crop height (CH), crop coverage (CC), and crop canopy volume (CCV) as the canopy structural indicators. Based on the complementary advantages of CP and CCV, we proposed a new metric: the color parameter-weighted crop-canopy volume (CCVCP). Results showed that the CH, CCV, and CCVCP correlated more strongly with potato AGB during the multi-growth stages than do CP and CC. The hue-weighted crop-canopy volume (CCVH) correlated most strongly with the potato AGB among all structural indicators. Using CH was more accurate in estimating potato AGB compared to CP and CC. Combining indicators (CP + CC/CH, CP + CC + CH) improved the accuracy of potato AGB estimation over the multi-growth stages. Except for the CP + CC + CH model, other AGB estimation models produced inaccurate AGB estimation than the models based on CCV and CCVH. The AGB estimation accuracy produced by the univariate-based CCVH model (R2 = 0.65, RMSE = 281 kg/hm2, and NRMSE = 23.61 %) was comparable to that of the complex model [CP + CC + CH using random forest (RF) or multiple stepwise regression (MSR)]. Compared with CP + CC + CH using RF and MSR, the RMSE decreased and increased by 0.35 % and 4.24 %, respectively. Compared with CP, CP + CC, CP + CH, and CCV, the use of CCVH to estimate AGB decreased the RMSE by 10.24 %, 7.42 %, 6.36 %, and 6.33 %, respectively. Meanwhile, the performance of CCVH was verified at different stages and among varieties. Thus, this indicator can be used for monitoring potato growth to help guide field production management.

Ladder fuels rather than canopy volumes consistently predict wildfire severity even in extreme topographic-weather conditions

Drivers of forest wildfire severity include fuels, topography and weather. However, because only fuels can be actively managed, quantifying their effects on severity has become an urgent research priority. Here we employed GEDI spaceborne lidar to consistently assess how pre-fire forest fuel structure affected wildfire severity across 42 California wildfires between 2019–2021. Using a spatial-hierarchical modeling framework, we found a positive concave-down relationship between GEDI-derived fuel structure and wildfire severity, marked by increasing severity with greater fuel loads until a decline in severity in the tallest and most voluminous forest canopies. Critically, indicators of canopy fuel volumes (like biomass and height) became decoupled from severity patterns in extreme topographic and weather conditions (slopes >20°; winds > 9.3 m/s). On the other hand, vertical continuity metrics like layering and ladder fuels more consistently predicted severity in extreme conditions – especially ladder fuels, where sparse understories were uniformly associated with lower severity levels. These results confirm that GEDI-derived fuel estimates can overcome limitations of optical imagery and airborne lidar for quantifying the interactive drivers of wildfire severity. Furthermore, these findings have direct implications for designing treatment interventions that target ladder fuels versus entire canopies and for delineating wildfire risk across topographic and weather conditions.

Evaluating forest aboveground biomass estimation model using simulated ALS point cloud from an individual-based forest model and 3D radiative transfer model across continents

Area-based approach (ABA) has been widely employed for estimating forest aboveground biomass (AGB) using airborne laser scanning (ALS) data. However, its scalability is limited due to challenges in model generalization across different forest types and regions. The selection of sensitive variables from ALS data is crucial for constructing robust forest AGB estimation models, yet this selection varies significantly among forest types and regions. Traditionally, assessing the influence of variable selection is hindered by the lack of accurate reference forest AGB values. Computer simulation-based method provides a perspective for exploring these challenges. This study employs an individual-based forest growth process model, FORMIND, coupled with a 3D radiative transfer model (RTM), LESS, to evaluate the transferability of ABA-based forest AGB estimation models and the generalization of ALS-derived variables. We used six virtual 3D forest scenes and two real-world forest sites, representing a range of global forest types, along with their simulated ALS data, to develop a forest AGB estimation model using the random forest algorithm, which allowed us to analyze the importance of various variables. We assessed model transferability through cross-comparison. Additionally, we validated the model using field plots and ALS data collected from two distinct regions. The results showed that the canopy surface area and volume extracted using the α-shape algorithm and parameters fitted from the Weibull distribution are vital variables when using ALS for forest AGB estimation across forest types and regions. Incorporating these variables into the model significantly improves the accuracy of forest AGB estimation. The optimized model achieved a R2 of 0.945, a RMSE of 34.22 t/ha, and a MAE of 20.53 t/ha. Our study not only deepens the understanding of the relationship between forest vertical structural metrics and AGB but also highlights the potential of computer simulation as a tool for refining the estimation of forest structural parameters.

Comparing the accuracy of 3D urban olive tree models detected by smartphone using LiDAR sensor, photogrammetry and NeRF: a case study of ’Ascolana Tenera’ in Italy

Abstract. Rapid urban growth makes green space management crucial to improve citizens’ well-being. Urban olive trees characterize the Italian landscapes and their culture. This study explores different methodologies for urban tree assessment in this context, using an iPhone 14 Pro Max. These included: 1) its integrated Light Detection and Ranging (LiDAR) sensor using the Recon3D app, 2) its camera with Structure from Motion (SfM) techniques, and 3) its camera for generating 3D models using Neural Radiance Fields (NeRF). Additionally, a professional Mobile Laser Scanner (MLS), was used for comparison. Total height (H), canopy base height (CBH) and canopy volume (CV) measurements were extracted using both CloudCompare and allometric formulas. The main aim of this paper is to compare the 3D models of olive trees obtained from low-cost sensors with those generated from the MLS, which is a more accurate device but comes with significantly higher costs. The results, in terms of RMSE (iPhone LiDAR - H: 0.46 m, CBH: 0.12 m, CV: 15.66 m3; iPhone-SfM - H: 0.95 m, CBH: 0.19 m, CV: 25.85 m3; iPhone-NeRF - H: 1.26 m, CBH: 0.31 m, CV: 33.79 m3), bias and volume differences, reveal that the smartphone, in all the methodologies, tends to underestimate measurements as the size of the trees increases. This is due to the higher MLS range of acquisition. Despite these limitations, low-cost solutions like smartphone-based methods can be a viable alternative given their economic accessibility.

Exploring the correlation between tree structure characteristics and carbon storage in historic gardens using TLS technology: a case study of Jian Xin Pavilions at Jingyi Park, Fragrant Hills Park

Historic gardens contain a greater number and variety of ancient trees, which are older, have unique forms, and larger volumes. These trees hold significant value in both natural ecosystems and cultural heritage. However, current research on the carbon sequestration value of ancient and non-ancient trees in historical gardens is relatively lacking. Based on the unique morphology and carbon storage estimation needs of ancient trees in historic gardens, this paper proposes a morphology-based point cloud single-tree segmentation method. This method can precisely extract the morphological structures of various tree species and accurately estimate their carbon storage. From the perspective of carbon sequestration, it evaluates the correlation between the structural characteristics and carbon storage of trees in historic gardens, as well as the potential changes in their carbon storage capacity.Using the Jing Yi Park’s Jian Xin Pavilions in Fragrant Hills Park as a case study, this method was applied to extract structural indicators of 116 ancient and non-ancient trees. The total carbon storage was found to be 19,171.13 kg, with an average carbon storage of 165.27 kg per tree. Among these, ancient trees accounted for 13,178.32 kg, or 68.74% of the total carbon storage. The study revealed that the correlation between tree age and carbon storage varied by species, and there were significant positive correlations between carbon storage and tree height, DBH, and canopy volume. Notably, there was a significant linear growth trend between DBH, canopy volume, and carbon storage. By 2030, the total carbon storage is projected to increase to 21,924.96 kg, with an annual average increase of 393.40 kg, representing a growth rate of 14.4%.The results indicate that studying the correlation between structural characteristics and carbon storage of aged trees in historical gardens can shed light on the important role of trees in sustainable carbon sequestration. The precise extraction of tree information through 3D digital technology and the prediction of carbon storage potential not only offer new perspectives for the conservation of cultural heritage in historical gardens, urban microclimate planning and design, and spatial management of carbon sinks and emissions but also have significant value for promoting the scientific management and protection of urban green spaces.

Application of a Multi-Spectral UAV Imagery in Germplasm Characterization: Prediction of Forage Biomass and Growth Patterns of Cicer Milkvetch (Astragalus cicer L.) Populations

Unmanned aerial vehicles (UAV)-based multi-spectral imaging could reduce the intensive labour required in phenotyping germplasm in crop breeding. The objectives of this study were to examine if UAV-based imaging could differentiate cicer milkvetch (Astragalus cicer L.) germplasm and identify UAV-based vegetation indices with correlations to its dry matter yield (DMY). A spaced nursery from 27 cicer milkvetch populations was established near Saskatoon, SK, Canada, in 2019. From 1 June to 15 October in 2020 and 2021, phenotypic traits including maximum stem length, leaf number per stem, rhizome spread rate, and stem density, along with two UAV-measured traits, green area and canopy volume, were measured bi-weekly. Forage DMY was determined in late June and mid-October of each year. In this study, normalized difference vegetation index (NDVI) green area and NDVI canopy volume data differentiated the three selected populations. NDVI green area had the highest correlation with forage DMY among the traits (June harvest: r = 0.91, October harvest: r = 0.77). Among measured phenotypic traits, maximum stem length had the highest correlation with forage DMY (June harvest: r = 0.74, October harvest: r = 0.83), which was significantly correlated to NDVI green area. The results indicated potential use of UAV-phenotyping in single plant evaluation in plant breeding.

Effect Of Different Doses Of IBA On Success, Survivability And Growth Of Lemon Using Leaf Cut Method Under Glass House And Field Condition

An experiment was conducted at the Horticulture division of Bangladesh Institute of Nuclear Agriculture (BINA), Mymensingh during the period from March, 2024 to June, 2024 to evaluate the quick propagation techniques from lemon leaves by using IBA under glass house and field condition. The experiment was consisted of two factors such as Environmental condition: (i) glass house and field condition and (ii) Different doses of IBA: D0 (Control), D1 (1000ppm IBA for 3mins) D2 (1500ppm IBA for 3mins) and D3 (2000ppm IBA for 3mins). Mature leaves were collected from BINA Lebu-1 mother plants. Collected leaves were exposed by different doses of IBA solution separately and also a control. The experiment was laid out in RCBD with three replications. Total 24 treatment combinations of the environmental condition and IBA levels. IBA exposed leaves of lemon were planted in the unit plots on 8 March, 2024 in the afternoon with spacing of 15cmx15cm (row to row and leaf to leaf distance). Different environmental condition showed significantly influenced on almost all the mentioned parameters studied concerned with growth and growth contributing characteristics. The highest percentage of success (66.34%), survivability (56.86 and %) and canopy volume (0.055m3) were found in glass house condition and the lowest % success (50.35%) % survivability ( 44.26%) and canopy volume (0.028m3) were found in field condition. The glasshouse condition took the minimum time for root and shoot (43.22 and 70.82 days respectfully) initiation. The application of 1500ppm IBA for 3mins took the minimum time for root and shoot (21.83 and 31.00 days respectfully) initiation and the maximum success ( 97.70 %), survivability (92.77%) and canopy volume (0.088m3).The maximum time took for root and shoot (51.08 and 66.08 days respectfully) initiation and the minimum success ( 48.35 %), survivability (45.59%) and canopy volume (0.008m3) were found from control treatment. The combined effect of environmental condition and IBA was statistically significant on the success, survivability and growth of lemon. The treatment in glasshouse condition with 1500ppm IBA solution for 3mins took the minimum time for root and shoot (18.00 and 51.44 days respectfully) initiation and the maximum success (98.70 %), survivability (96.90%) and canopy volume (0.015m3) as compare to control. Therefore, the overall results indicate that glasshouse condition with 1500ppm IBA solution for 3 mins might be an efficient and eligible practice for developing mutant from leaves. Therefore, the overall results indicate that glasshouse condition with 1000ppm IBA solution for 3mins might be an efficient and eligible practice for quick propagation techniques from leaves

Development Of Mutant From Lemon Leaves By Using Gamma Radiation And Leaf Cut Method Under Glass House And Field Condition

An experiment was conducted at the Horticulture division of Bangladesh Institute of Nuclear Agriculture (BINA), Mymensingh during the period from March 2024 to September 2024 to develop mutants from lemon leaves by using gamma radiation and leaf cut method under glasshouse and field conditions to find out the appropriate combination of irradiation dose and suitable environment on success, survivability, and growth of lemon. The experiment was consisted of two factors such as Environmental condition: (i) glass house and field condition and (ii) Nine gamma radiation levels (0 GY, 60 GY,80Gy,100Gy, 120 GY,140 GY,160 GY,180 GY and 200 GY).Mature leaves were collected from BINA Lebu-1 mother plants.Collected leaves were exposed by different doses of gamma radiation separately with 60 GY, 80GY, 100 GY, 120 GY, 140 GY, 160 GY,180 GY, 200 GY, and also a control at BINA from 60Co gamma radiation sources. The experiment was laid out in RCBD with three replications. Total 18 treatment combinations of the environmental condition and radiation levels. Irradiated leaves of lemon were planted in the unit plots on 8 March 2023 in the afternoon with spacing of 15cmx15cm (row to row and leaf to leaf distance). Different environmental condition showed significantly influenced on almost all the mentioned parameters studied concerned with growth and growth contributing characteristics. The highest percentage of success and survivability was found in glass house condition and the lowest % success and %survivability was found in field condition.The glasshouse condition producedhigher number of roots(4.77), longer root length(9.24cm), diameter of shoot( 4.95mm), higher number of leaves per plant(50.66) and field condition produced lower number of roots(3.55), smallest longer root length(7.14cm), lower diameter of shoot(2.26mm), lower number of leaves(43.00) per plant compared to the field condition. The application of 120GY irradiation level produced the highest number of roots (8.50), longest root length (16.1cm),the highest diameter of shoot (5.65mm), andthe highest number of leaves per plant (70.00) as compared to control. The combined effect of environmental condition and gamma radiations was statistically significant on the success, survivability and growth.120GY irradiation level in glasshouse condition produced the maximum roots (7.00), the longest root length (17.5.cm), the largest diameter of shoot (4.80mm), highest canopy volume (0.12m3 ) and the maximum leaves per plant (73.00). Similarly, the lowest values were in respect of almost all the mentioned parameters were found at field condition with control treatment. Therefore, the overall results indicate that glasshouse condition with 120 GY might be an efficient and eligible practice for developing mutant from leaves

Estimation of Strawberry Canopy Volume in Unmanned Aerial Vehicle RGB Imagery Using an Object Detection-Based Convolutional Neural Network.

Estimating canopy volumes of strawberry plants can be useful for predicting yields and establishing advanced management plans. Therefore, this study evaluated the spatial variability of strawberry canopy volumes using a ResNet50V2-based convolutional neural network (CNN) model trained with RGB images acquired through manual unmanned aerial vehicle (UAV) flights equipped with a digital color camera. A preprocessing method based on the You Only Look Once v8 Nano (YOLOv8n) object detection model was applied to correct image distortions influenced by fluctuating flight altitude under a manual maneuver. The CNN model was trained using actual canopy volumes measured using a cylindrical case and small expanded polystyrene (EPS) balls to account for internal plant spaces. Estimated canopy volumes using the CNN with flight altitude compensation closely matched the canopy volumes measured with EPS balls (nearly 1:1 relationship). The model achieved a slope, coefficient of determination (R2), and root mean squared error (RMSE) of 0.98, 0.98, and 74.3 cm3, respectively, corresponding to an 84% improvement over the conventional paraboloid shape approximation. In the application tests, the canopy volume map of the entire strawberry field was generated, highlighting the spatial variability of the plant's canopy volumes, which is crucial for implementing site-specific management of strawberry crops.

Scale-Dependent Effects of Urban Canopy Cover, Canopy Volume, and Impervious Surfaces on Near-Surface Air Temperature in a Mid-Sized City

Cities are significantly warmer than their surrounding rural environments. Known as the ‘urban heat island effect’, it can affect the health of urban residents and lead to increased energy use, public health impacts, and damage to infrastructure. Although this effect is extensively researched, less is known about how landscape characteristics within cities affect local temperature variation. This study examined how tree canopy cover, canopy volume, and impervious surface cover affect daytime near-surface air temperature, and how these effects vary between different scales of analysis (10, 30, 60, 90 m radii), ranging from approximate street corridor to city block size. Temperature data were obtained from a car-mounted sensor, with traverse data points recorded during morning, afternoon, and evening times, plotted throughout the city of Portland, OR. The variability in near-surface air temperature was over 10° F during each traverse period. The results indicate that near-surface air temperature increased linearly with impervious surface cover and decreased linearly with tree canopy cover, with canopy volume reducing the temperature by 1° F for every 500 cubic feet of canopy volume for evening temperatures. The magnitude of the effect of tree canopy increased with spatial scale, with 60 and 90 m scales having the greatest measurable effect. Canopy volume had a positive relationship on presumed nighttime and early-morning temperatures at 60 and 90 m scales, potentially due to the impacts of wind fluctuation and air roughness. Canopy cover still contributed the largest overall decrease in street-scale temperatures. Increasing tree canopy cover and volume effectively explained the lower daytime and evening temperatures, while reducing impervious surface cover remains critical for reducing morning and presumed nighttime urban heat. The results may inform strategies for urban foresters and planners in managing urban land cover and tree planting patterns to build increased resiliency towards moderating urban temperature under warming climate conditions.

Effect of Foliar Application of Humic Acid on Vegetative Growth Attributes of Jamun (Syzygium cumini (L.) Skeels.) cv. Goma Priyanka

A field experiment was carried out at Instructional Farm, Department of Fruit Science, College of Horticulture and Forestry in Jhalarapatan, Jhalawar during 2021-22 and 2022-23 with the object of assessing the response of foliar application of humic acid on growth attributes of Jamun (Syzygium cumini (L.) Skeels) cv. Goma Priyanka. The experiment comprised of 4 treatment combinations in randomized block design with three replications consisted of HA0: [Control], HA1: [1000ppm humic acid], HA2: [2000 ppm humic acid], and HA3: [3000 ppm humic acid]. On the basis of the results emanated from present investigation, it could be concluded that foliar application of humic acid HA3 (3000 ppm) was significantly superior plant growth parameters viz. rootstock girth, scion girth, plant height, canopy volume, canopy spread E-W, N-S, of Jamun cv. Goma Priyanka plants.

Effect of Tree Density on Yield and Fruit Quality of the Grafted Hazelnut Cultivar 'Tonda Francescana®'.

Optimizing planting density is crucial for balancing resource competition, light penetration, and tree productivity in orchard systems. This study investigateed the impact of planting density on the yield and fruit quality of the hazelnut cultivar 'Tonda Francescana®' grafted onto Corylus colurna L. rootstocks. The research aimed to assess how different planting densities influenced light penetration, canopy volume, yield, and the nutritional profile of hazelnuts during their sixth growing season. Three planting densities were tested: 625, 1250, and 2500 trees per hectare (low, medium, and high density, respectively). The results show that medium-density planting provided the best balance between light availability, canopy development, and yield efficiency. The synthesis of monounsaturated fatty acids (MUFA) and α-tocopherol (vitamin E) was more prominent in the medium-density system (80.2% and 10.3%, respectively), suggesting a favorable metabolic response to moderate competition for resources. In contrast, high-density planting yielded the most per hectare (2898 kg/ha) but exhibited lower individual tree productivity (1.16 kg). Low-density planting had the highest light penetration (53%) but lower overall yield (822 kg/ha) and quality, with greater starch accumulation in the fruit. In general, medium-density planting optimized both yield and kernel quality, with potential implications for orchard management and breeding strategies to enhance hazelnut production and nutritional value.

Influence of spraying nutrients and bioregulators on vegetative growth, flowering and productivity of litchi

Aim: To investigate the influence of nutrients and bioregulators on the vegetative growth, flowering and productivity of Litchi. Methodology: The vegetative growth, flowering and productivity of litchi cv. Bombai was assessed through application of nutrients and bioregulators. Results: The plants receiving treatment with @ 0.5% Borax (T1) showed the highest percentage increase in canopy volume (7.56 %) and plant height (2.46 %) in litchi, outperforming all other treatments. The maximum productivity (38.69 kg per plant) was registered in plants under treatment T2 (0.3% Borax), which was found to be statistically at par (36.68 kg per plant) with plants treated with 0.1% Seaweed extract (T10) . The percentage increase in the plant height, plant spread in East-West and North-South direction, canopy volume, , fruit weight and fruit set capture positive correlation in both PC-1 and PC-2. The total contribution of PC-1 and PC-2 was 60.857 %. Interpretation: Among all the treatments, T2 (0.3% borax) and T4 (ZnSO4 @ 0.4%) treatments proved superior over other treatements with respect to vegetative growth, flowering and productivity parameters in litchi. However, further investigation need to be carried out with combination of these applied nutrients and bioregulators for getting acceptable results. Key words: Bioregulators, Flowering, Growth, Litchi, Nutrients

The microclimatic effects of the native shrub Ephedra californica (Mormon tea) in California drylands.

The impacts of climate change can be profound in many ecosystems worldwide, including drylands such as arid and semi-arid scrublands and grasslands. Foundation plants such as shrubs can provide microclimatic refuges for a variety of taxa. These shrubs can directly influence micro6 environmental measures, and indirectly increase the local environmental heterogeneity as a result. We examined the hypothesis that, in comparison to an open gap, foundation shrubs improve the microclimate beneath their canopy and that microclimate is in turn a significant predictor of annual vegetation. The following predictions were made: 1) mean air temperature (NSAT), ground temperature (SGT), and vapour pressure deficit (VPD) will be significantly lower under the shrubs than in the open microsites; 2) shrub canopy size predicts microclimate; 3) site-level aridity estimates and percent shrub cover influence annual plant abundance and richness; and 4) the site13 level mean of NSAT and VPD predict annual plant abundance and richness. Our study took place in Southwestern California, U.S.A. We used a handheld device with a probe to measure microclimatic variables such as near-surface air temperature (NSAT), near-surface relative humidity (NSRH), and surface ground temperature (SGT) at the shrub species Ephedra californica and in the open gap, across six sites in California, United States. Air temperature and RH were then used to calculate VPD. The mean number of vascular plant species across each site was also recorded. Only SGT was significantly reduced under shrub canopies. Canopy volume was not a significant predictor of all three microclimatic variables, demonstrating that even small, low-stature shrubs can have facilitative effects. Furthermore, total shrub cover and aridity at sites significantly predicted mean plant richness and abundance. There were significantly more plants associated with shrubs and there were significantly more species associated with the open. Mean air temperature and VPD at the site-level significantly predicted vegetation abundance and richness, though microsite-level differences were only significant for richness. Foundation shrubs are a focal point of resiliency in dryland ecosystems. Understanding their impact on microclimate can inform us of better management, conservation, and restoration frameworks.

ALS-Based, Automated, Single-Tree 3D Reconstruction and Parameter Extraction Modeling

The 3D reconstruction of point cloud trees and the acquisition of stand factors are key to supporting forestry regulation and urban planning. However, the two are usually independent modules in existing studies. In this work, we extended the AdTree method for 3D modeling of trees by adding a quantitative analysis capability to acquire stand factors. We used unmanned aircraft LiDAR (ALS) data as the raw data for this study. After denoising the data and segmenting the single trees, we obtained the single-tree samples needed for this study and produced our own single-tree sample dataset. The scanned tree point cloud was reconstructed in three dimensions in terms of geometry and topology, and important stand parameters in forestry were extracted. This improvement in the quantification of model parameters significantly improves the utility of the original point cloud tree reconstruction algorithm and increases its ability for quantitative analysis. The tree parameters obtained by this improved model were validated on 82 camphor pine trees sampled from the Northeast Forestry University forest. In a controlled experiment with the same field-measured parameters, the root mean square errors (RMSEs) and coefficients of determination (R2s) for diameters at breast height (DBHs) and crown widths (CWs) were 4.1 cm and 0.63, and 0.61 m and 0.74, and the RMSEs and coefficients of determination (R2s) for heights at tree height (THs) and crown base heights (CBHs) were 0.55 m and 0.85, and 1.02 m and 0.88, respectively. The overall effect of the canopy volume extracted based on the alpha shape is closest to the original point cloud and best estimated when alpha = 0.3.

Omitting the Application of Nitrogen or Potassium Reduced the Growth of Young Chestnut (Castanea sativa) Trees, While a Lack of Boron Decreased Fruit Yield

The chestnut tree (Castanea sativa Mill.) is gaining importance in the mountainous regions of southern Europe due to the high value of its fruits. It is essential to establish effective cultivation protocols, considering that this species is still relatively understudied. In this study, we present the outcomes of the initial establishment of a chestnut orchard conducted through a nutrient omission trial for four years. The treatments included a fertilization plan with nitrogen, phosphorus, potassium, and boron (NPKB), the control, and four other treatments corresponding to the omission of each nutrient (-NPKB, N-PKB, NP-KB, NPK-B). The -NPKB and NP-KB treatments showed significantly lower trunk circumferences and canopy volumes compared to the other treatments. The NPK-B treatment resulted in the lowest fruit production, with a total accumulated yield (2020–2022) of 0.56 kg tree–1, a value significantly lower than that of NPKB (1.12 kg tree–1) and N-PKB (1.19 kg tree–1). The assessment of nutrient concentrations in the leaves revealed plants with deficient levels of B and K in treatments that did not receive these nutrients. Conversely, N levels in the leaves in the -NPKB treatment fell within the sufficiency range (20 to 28 g kg–1). This suggests that the sufficiency range should be adjusted to higher values, given the treatment’s effect on tree growth. It was also observed that the -NPKB treatment led to lower soil organic matter compared to the other treatments, likely due to reduced herbaceous vegetation development under the canopy, leading to decreased organic substrate deposition in the soil. The main findings of this study are that N and K were crucial elements for the optimal growth of chestnut trees, while B played a significant role in fruit production.

Design and Testing of a Fruit Tree Variable Spray System Based on ExG-AABB

This paper addresses the issue of pesticide waste and low utilization rates resulting from traditional plant protection via spraying operations, which apply equal dosages to different targets or to different parts of the same target. To tackle this problem, we designed a variable fruit tree spraying system based on the ExG-AABB (excess green and axis-aligned bounding box) algorithm. We used a Kinect depth camera to capture information about the fruit tree canopy and constructed a spray flow model using pulse width modulation and variable spray control technology. Variable multi-nozzle spraying was guided by combining this canopy data. We evaluated the accuracy of each model in calculating canopy volume by comparing the coefficient of determination (R2) and root mean square error (RMSE) of the ExG-AABB with the slice convex hull method, voxel method, three-dimensional alpha-shape method, and QuickHull method. The ExG-AABB algorithm had the highest R2 value (0.9334) and the lowest RMSE value (0.0353 m3) among the five models, indicating that it most accurately reflects the true volume of the fruit tree canopy. This validates the effectiveness of the ExG-AABB algorithm in calculating canopy volume. We established a correlation model between canopy volume and spray volume, designed a canopy-adaptive layering method based on point cloud processing, and achieved precise calculation of nozzle flow. Comparative field experiments were conducted to analyze the spray coverage rate and observed flow, thereby evaluating the spraying effect of this variable spraying system. The experimental results showed that compared to conventional continuous spraying, this variable spraying system not only achieves more uniform spray coverage but also significantly reduces pesticide usage by 48.1%. Furthermore, through system optimization, the average coverage rate of the middle layer of the canopy decreased by 17.53%, effectively reducing the phenomenon of overlapping spraying from multiple nozzles and improving spraying efficiency.