Pruning Research Articles

Benchmarking of Various Flexible Soft-Computing Strategies for the Accurate Estimation of Wind Turbine Output Power

This computational study explores the potential of several soft-computing techniques for wind turbine (WT) output power (kW) estimation based on seven input variables of wind speed (m/s), wind direction (°), air temperature (°C), pitch angle (°), generator temperature (°C), rotating speed of the generator (rpm), and voltage of the network (V). In the present analysis, a nonlinear regression-based model (NRM), three decision tree-based methods (random forest (RF), random tree (RT), and reduced error pruning tree (REPT) models), and multilayer perceptron-based soft-computing approach (artificial neural network (ANN) model) were simultaneously implemented for the first time in the prediction of WT output power (WTOP). To identify the top-performing soft computing technique, the applied models’ predictive success was compared using over 30 distinct statistical goodness-of-fit parameters. The performance assessment indices corroborated the superiority of the RF-based model over other data-intelligent models in predicting WTOP. It was seen from the results that the proposed RF-based model obtained the narrowest uncertainty bands and the lowest quantities of increased uncertainty values across all sets. Although the determination coefficient values of all competitive decision tree-based models were satisfactory, the lower percentile deviations and higher overall accuracy score of the RF-based model indicated its superior performance and higher accuracy over other competitive approaches. The generator’s rotational speed was shown to be the most useful parameter for RF-based model prediction of WTOP, according to a sensitivity study. This study highlighted the significance and capability of the implemented soft-computing strategy for better management and reliable operation of wind farms in wind energy forecasting.

Boosted Poisson regression trees: a guide to the BT package in R

Abstract Thanks to its outstanding performances, boosting has rapidly gained wide acceptance among actuaries. Wüthrich and Buser (Data Analytics for Non-Life Insurance Pricing. Lecture notes available at SSRN. http://dx.doi.org/10.2139/ssrn.2870308, 2019) established that boosting can be conducted directly on the response under Poisson deviance loss function and log-link, by adapting the weights at each step. This is particularly useful to analyze low counts (typically, numbers of reported claims at policy level in personal lines). Huyghe et al. (Boosting cost-complexity pruned trees on Tweedie responses: The ABT machine for insurance ratemaking. Scandinavian Actuarial Journal. https://doi.org/10.1080/03461238.2023.2258135, 2022) adopted this approach to propose a new boosting machine with cost-complexity pruned trees. In this approach, trees included in the score progressively reduce to the root-node one, in an adaptive way. This paper reviews these results and presents the new BT package in R contributed by Willame (Boosting Trees Algorithm. https://cran.r-project.org/package=BT; https://github.com/GiregWillame/BT, 2022), which is designed to implement this approach for insurance studies. A numerical illustration demonstrates the relevance of the new tool for insurance pricing.

Antioxidative, Metabolic and Vascular Medicinal Potentials of Natural Products in the Non-Edible Wastes of Fruits Belonging to the Citrus and Prunus Genera: A Review.

Diabetes mellitus and related metabolic and vascular impairments are notable health problems. Fruits and vegetables contain phenolics that are beneficial to metabolic and oxidative health and useful in preventing associated disease. Scientific evidence has shown that some bioactive phenolics are more abundant in the non-edible parts (especially the peels) of many fruits than in their respective edible tissues. Fruits belonging to the Citrus and Prunus genera are commonly consumed worldwide, including in South Africa, and their non-edible wastes (peel and seed) have been shown to have antioxidative, metabolic and vascular pharmacological potentials and medicinal phytochemistry. It is therefore imperative to evaluate the pharmacological actions and phytochemical properties of the non-edible wastes of these fruits and understand how they could potentially be of medicinal relevance in oxidative, metabolic and vascular diseases, including diabetes, oxidative stress, obesity, hypertension and related cardiovascular impairments. In the absence of a previous review that has concomitantly presented the medicinal potentials of fruits wastes from both genera, this review presents a critical analysis of previous and recent perspectives on the medicinal potential of the non-edible wastes from the selected Citrus and Prunus fruits in metabolic, vascular and oxidative health. This review further exposes the medicinal phytochemistry, while elucidating the underlying mechanisms through the fruit wastes potentiates their therapeutic effects. A literature search was carried out on "PubMed" to identify peer-reviewed published (mostly 2015 and beyond) studies reporting the antidiabetic, antioxidative, antihypertensive, anti-hyperlipidemic and anti-inflammatory properties of the non-edible parts of the selected fruits. The data of the selected studies were analyzed to understand the bioactive mechanisms, bioactive principles and toxicological profiles. The wastes (seed and peel) of the selected fruits had antioxidant, anti-obesogenic, antihypertensive, anti-inflammatory, antidiabetic and tissue protective potentials. Some phenolic acids and terpenes, as well as flavonoids and glycosides such as narirutin, nobiletin, hesperidin, naringin, naringenin, quercetin, rutin, diosmin, etc., were the possible bioactive principles. The peel and seed of the selected fruits belonging to the Citrus and Prunus genera are potential sources of bioactive compounds that could be of medicinal relevance for improving oxidative, metabolic and vascular health. However, there is a need for appropriate toxicological studies.

Canopy Manipulation for Production of Winter Guava (Psidium guajava L.) in the Eastern Himalayan Region of India

Elimination of rainy-season crops is pivotal to encourage winter crops in guava. In general, rainy-season guava fruits are of poor fruit quality, insipid in taste, have poor shelf life, and mostly affected by many insect pests. Pruning is also considered one of the most eco-friendly methods for crop regulation. To fully comprehend the impact of pruning time and severity on flowering, fruit quality, and crop production, a field experiment was carried out. Three alternative pruning times (mid-April, mid-May, and mid-June) at different pruning levels (low, moderate and heavy pruning) were employed in the experiment, which was designed as two-factor factorial RBD. For obtaining optimal fruiting, size of fruit and quality of fruit attributes, mid-May pruning has proven to be the best time for guava pruning. Whereas, concerning pruning severity, moderate pruning (pruning 1/2 of the current season’s shoot length) showed a good response to yield and fruit quality parameters. Therefore, the present study concluded that moderate pruning of guava trees during the month of mid-May proved to be the most effective for producing winter-season guava with good yield and superior quality.

Algorithm A for distributed data Classification

Knowledge discovery is one of the key areas in predictive data mining tasks. Performing Classification tasks on a single source of data using a decision tree algorithm is a relatively straightforward process. However, the complication arises when we have distributed sources of data that yield sets of decision trees. Classifier ensembles are often created, and a decision is assigned to a new object based on a certain voting strategy. The article proposes a different approach to creating a rule-based classifier. Using a set of decision trees, a global model of decision rules is induced. It contains rules which are true for the maximum number of trees from a set of decision trees. This model is verified by data corresponding to distributed local data sources. The bootstrapping technique was used to obtain distributed data sources. Pruning of decision trees was applied to improve the accuracy of the rule-based classifier. The conducted experiments confirm the validity of using algorithm A for the learning of decision rules from a set of decision trees.

Evaluation of weed control efficacy and crop safety of the PPO-inhibiting herbicide tiafenacil in California orchard cropping systems

Abstract Tiafenacil is registered in the United States for use in annual crops such as corn and soybean, but not on orchard crops. Field studies were conducted to determine orchard crop safety and efficacy of tiafenacil on important California orchard weeds. To evaluate crop safety, tiafenacil was applied at 74, 148, and 222 g ai ha−1 alone and with 38 g ai ha−1 of tolpyralate three times per year at the base of almond, pistachio, prune, and walnut trees. The first treatment was applied 2 mo after the trees had been transplanted. In all four tree crop experiments, treatments were applied once in May 2020, then three times again during the winter of 2021 and 2022 at 21-d treatment intervals. There were no visual foliar injury symptoms or treatment-related effects on tree trunk diameter change even at the highest tested rate of tiafenacil applied seven times over three growing seasons. In a separate study of weed control, in most instances, tiafenacil applied at 12 g ai ha−1 performed similarly to that of tiafenacil plus glufosinate. Control of glyphosate-resistant hairy fleabane with tiafenacil applied alone at 25 g ai ha−1 was 65% by 14 d after treatment. Tiafenacil applied at 50 g ai ha−1 to hairy fleabane performed similarly to glufosinate plus glyphosate. In a greenhouse study, tiafenacil applied at 12 g ha−1 provided 95% to 100% control of barnyardgrass and junglerice, and there was no significant difference between tiafenacil applied alone or with glufosinate. Saflufenacil applied alone or in a mixture with glufosinate was not as effective as the tiafenacil treatments for grass weed control. Based on experiments conducted over three growing seasons in four tree fruit and tree nut crops, tiafenacil crop safety appeared to be acceptable even at up to 2- or 3-fold the expected use rate.

The Effect of Tree Pruning on Growth and Potential of Carbon Storage in Aboveground Biomass in Royal Park Rajapruek in Chiang Mai Province

The Effect of Tree Pruning on Growth and Potential of Carbon Storage in Aboveground Biomass in Royal Park Rajapruek in Chiang Mai Province

A study of the current status of the quality of teacher-child interactions in preschools based on mathematical statistics multiple regression modeling

Abstract In group teaching activities, teacher-child interaction occupies a dominant position, and its quality has a significant impact on children’s interpersonal communication, language expression, and problem-handling. This study first designed a relevant questionnaire to assess the current quality of teacher-child interactions in preschools and then developed a stepwise regression algorithm based on decision trees to investigate the factors that influence the quality of these interactions. Firstly, we remove a certain number of irrelevant variables from all the input variables to reduce interference. Next, we establish stepwise regression equations between the input variables and output variables selected by decision tree pruning. Finally, we eliminate the variables with covariance. The study found that the average score of the quality of teacher-child interactions in preschools is 4.2381, which is relatively low, and the highest score in the dimension of “classroom organization” is only 4.8908. The highest score in the dimension of “classroom organization” was only 4.8908. The average scores of “emotional support”, “classroom management,” and “educational support” in the dimensions of small class and life activities were 4.76746, 4.10562, 2.8455, and 5.562, respectively, 2.8455) and (5.01564, 4.99567, 3.75402) respectively. Teacher-child interaction quality = 4.012 + 0.145 × emotional expression, i.e., emotional expression has a significant positive effect on the quality of teacher-student interaction, and the independent variable, emotional expression, can significantly and positively predict the dependent variable teacher-child interaction quality. This paper provides a useful exploration for improving the professional abilities level of kindergarten teachers and the quality of their interactions with children.

Sustainable reduction of sulfate contained in gypsum waste: perspectives and applications for agroforestry waste and sanitary sewage

This review article explores sustainable biotechnological strategies for converting sulfate compounds and lignocellulosic waste, focusing on using sulfate-reducing bacteria (SRB) and the valorization of agroforestry residues and sanitary sewage. SRB show potential in effluent treatment, mine drainage, and the removal of sulfate and heavy metals from wastewater, with their metabolic activity being influenced by factors such as pH, temperature, and chemical oxygen demand/sulfate (COD/SO4=) ratio. In the context of a sustainable bioeconomy, the challenge of converting lignocellulosic waste into value-added products is addressed through physical pretreatment techniques such as milling, extrusion, microwave irradiation, and ultrasound, which are efficient in valorizing waste from urban tree pruning. The article highlights the importance of bioreactors in transforming raw materials into desirable biochemical products, discussing different types of bioreactors, such as batch, continuous stirred tank, airlift, fluidized bed, upflow anaerobic sludge blanket (UASB), and bubble column, and their specific advantages and disadvantages. Sustainable sulfate reduction is the central focus, integrating the application of SRB and the conversion of lignocellulosic waste in a way that complements the objectives of the work and promotes a more cohesive flow in the summary. Thus, the interrelationship between effluent treatment strategies and waste valorization is emphasized from an environmental sustainability perspective, highlighting the relevance of this study in the broader context of a sustainable bioeconomy.

Toward Answering Federated Spatial Range Queries Under Local Differential Privacy

Federated analytics (FA) over spatial data with local differential privacy (LDP) has attracted considerable research attention recently. Existing solutions for this problem mostly employ a uniform grid (UG) structure, which recursively decomposes the whole spatial domain into fine‐grained regions in the distributed setting. In each round, the sampled clients perturb their locations using a random response mechanism with a fixed probability. This approach, however, cannot encode the client’s location effectively and will lead to ill‐suited query results. To address the deficiency of existing solutions, we propose LDP‐FSRQ, a spatial range query algorithm that relies on a hybrid spatial structure composed of the UG and quad‐tree with nonuniform perturbation (NUP) probability to encode and perturb clients’ locations. In each iteration of LDP‐FSRQ, each client adopts the quad‐tree to encode his/her location into a binary string and uses four local perturbation mechanisms to protect the encoded string. Then, the collector prunes the quad‐tree of the current round according to the clients’ reports and shares the pruned tree with the clients of the next round. We demonstrate the application of LDP‐FSRQ on Beijing, Landmark, Check‐in, and NYC datasets, and the experimental results show that our approach outperforms its competitors in terms of queries’ utility.

Poda de verão e dobramento de galhos de pessegueiros em região subtropical

Abstract The objective of this work was to quantify peach (Prunus persica) tree production in the Y-training and open-vase management systems, subjected to three summer pruning methods. The experiment was set up in a 2x3 factorial arrangement, with two management systems and three summer pruning methods (no summer pruning, summer pruning, and branch bending). The plants were arranged in two spacings: 1.5×5.0 m for the Y-training system, with 1,334 plants per hectare; and 4.0×5.0 m for open-vase system, with 500 plants per hectare. In the early summer of 2019, summer pruning was performed, being repeated in the three following years. In the branch bending treatment, new branches were twisted manually until reaching an angle of 110°. In the treatment without summer pruning, the branches were not removed. The Y-training system increases peach production. The methods of branch bending in summer and no prunning in summer provide an equivalent peach production, whereas the summer pruning treatment results in the lowest production.

Silvicultural Practices for Diversity Conservation and Invasive Species Suppression in Forest Ecosystems of the Bundala National Park, Sri Lanka.

Forest ecosystems in Sri Lanka are under pressure from intensive human activity and climate change. Invasive species are one of the greatest threats to autochthonous species and ecosystems. In Bundala National Park of Sri Lanka, there are efforts to control and limit the spreading of unwanted invasive Prosopis juliflora (Sw.) DC. and Opuntia dillenii (Ker-Gawl.) Haw., which poses a significant risk to natural ecosystem conservation. Nine different treatment variants (four replications) were used to test which management approach provides the control of Prosopis juliflora. This research is based on nine repeated measurements from 2017 to 2021 on 36 permanent research plots (each 625 m2) with 27 observed plant species and a total of 90,651 recorded plant individuals. The results confirmed that the dynamics of species richness, heterogeneity, and evenness showed significant differences between treatments during the five years of dynamics. The lowest species diversity was found in the control variant, followed by treatments based on the hard pruning and thinning of Prosopis juliflora trees. In contrast, strategies emphasizing the complete uprooting of Prosopis juliflora trees, replanting, and support of the natural regeneration of native species showed high species diversity and a high overall number of plant species. Generally, treatments had a significant effect on species diversity and the number of individuals of Prosopis juliflora, while changes in the overall number of plant species were more affected by time and succession. Silvicultural treatments including pruning, uprooting, and thinning have proven to be essential tools for nature conservation across various sites, aimed at enhancing habitat diversity in the face of ongoing climate change.

An integrated GIS-based multivariate adaptive regression splines-cat swarm optimization for improving the accuracy of wildfire susceptibility mapping

A hybrid machine learning method is proposed for wildfire susceptibility mapping. For modeling a geographical information system (GIS) database including 11 influencing factors and 262 fire locations from 2013 to 2018 is used for developing an integrated multivariate adaptive regression splines (MARS). The cat swarm optimization (CSO) algorithm tunes the parameters of the MARS in order to generate accurate susceptibility maps. From the Pearson correlation results, it is observed that land use, temperature, and slope angle have strong correlation with the fire severity. The results demonstrate that the prediction capability of the MARS-CSO model outperforms model tree, reduced error pruning tree and MARS. The resulting wildfire risk map using MARS-CSO reveals that 20% of the study areas is categorized in the very low wildfire risk class, whereas 40% is under the very high class of fire hazard.

Design of a Biogas Power Plant That Uses Olive Tree Pruning and Olive Kernels in Achaia, Western Greece

In Greece, agricultural residues form a significant part of available biomass resources. This study focuses on exploring energy production potential from olive tree pruning and kernels via anaerobic digestion in the Achaia region of Western Greece. It aims to address environmental challenges by analyzing anaerobic digestion of these residues. The study evaluates qualitative and quantitative attributes, including composition analysis and energy content assessment. Detailed design considerations for an anaerobic digestion system tailored for these residues are presented, laying the groundwork for practical implementation. By integrating scientific analysis with engineering principles, this research aims to optimize anaerobic digestion systems for a more sustainable agricultural landscape in Greece.

THE IMPACT OF THE PRUNING TIME ON THE BIOLOGICAL PROPERTIES OF CHERRY VARIETIES GRAFTED ON MAXMA 14

Pruning is a basic procedure in the sweet cherry trees cultivation, which significantly affects the yield and quality of the fruit. The objective of this study was to examine the influence of the pruning time on the biological properties of sweet cherry trees (Prunus avium L.). The orchard in which the research was carried out was established in the central area of the Republic of Moldova in the fall of 2012. The Kordia and Regina sweet cherries, grafted on MaxMa 14, whose crowns had a naturally improved reduced volume, were planted at a distance of 5 x 3 m. The maintenance and fruiting pruning of the sweet cherry trees were done during the dormant and vegetation phases as follows. The flowering and fruit ripening time, the trunk cross-sectional area (TCSA), the number of fruiting buds and the fruit weight and yield were studied. The results showed that the pruning time had had a significant impact on the yield. The data on the yield of the Kordia and Regina sweet cherry varieties grafted on MaxMa 14 are promising and prove that the pruning done in the first decade of September has a positive effect on the fruit yield.

Delineating flood-prone areas using advanced integration of reduced-error pruning tree with different ensemble classifier algorithms

Delineating flood-prone areas using advanced integration of reduced-error pruning tree with different ensemble classifier algorithms

Evolution of microbiome composition, antibiotic resistance gene loads, and nitrification during the on-farm composting of the solid fraction of pig slurry using two bulking agents

Composting is a nature-based method used to stabilize organic matter and to transform nitrogen from animal farm manure or solid fraction of slurry (SFS). The use of composted material as source of nutrients for agriculture is limited by its potential to facilitate the propagation of biological hazards like pathogens and antibiotic-resistant bacteria and their associated antibiotic-resistance genes (ARG). We show here an experimental on-farm composting (one single batch) of pig SFS, performed under realistic conditions (under dry continental Mediterranean climate) for 280 days, and using two different bulking agents (maize straw and tree pruning residues) for the initial mixtures. The observed reduction in potentially pathogenic bacteria (80–90%) and of ARG loads (60–100%) appeared to be linked to variations in the microbiome composition occurring during the first 4 months of composting, and concurrent with the reduction of water-soluble ammonium and organic matter loads. Nitrification during the composting has also been observed for both composting piles. Similar patterns have been demonstrated at small scale and the present study stresses the fact that the removal can also occur at full scale. The results suggest that adequate composition of the starting material may accelerate the composting process and improve its global performance. While the results confirm the sanitization potential of composting, they also issue a warning to limit ARG loads in soils and in animal and human gut microbiomes, as the only way to limit their presence in foodstuffs and, therefore, to reduce consumers' exposure.

Technoeconomic assessment for the viable exploitation of biomass residues by an innovative pyrolysis-anaerobic digestion processing plant

In Greece, there is no organized practice in agricultural and animal wastes management. Their exploitation is still set aside, due mainly to economic reasons and lack of incentives for their efficient utilization. Therefore, in the present work a technoeconomic assessment for the environmentally friendly useful exploitation of biomass residues produced in the Prefectures of Ilia and Achaia (Western Greece) for the generation of energy by an integrated anaerobic digestion (AD)-pyrolysis processing plant was carried out. The processed biomass of the AD unit is corn residues and cattle manure, while the feedstock of pyrolysis unit is olive tree prunings. The residues will be transferred to collection areas by field tractors. Then an integrated harvester is used and afterwards, the residues are discharged from the lifting bin of the harvester to trucks and are transported to the processing unit. The total fixed capital for a capacity of 328,716 t/y is equal to 11.5 M€, while the initial working capital is equal to 2.1 M€. The total operational cost of this investment is estimated at 18.3 M€/y, the projected revenues amount to 21.4 M€/y and the net profit is equal to 3.1 M€/y. The return on investment is estimated at 23% and the payback period becomes equal to 4.4 years. From the sensitivity analysis becomes apparent that the capacity, the incentive cost, the fuel price, the products price and the total fixed capital affect significantly the investment characteristics of the proposed AD-pyrolysis processing unit. The amount of the expected profit is considered quite significant, and the evaluation criteria (return on investment and payback period) advocate for a more detailed examination of the investment plan, in the direction of undertaking the project.

An image-based system for locating pruning points in apple trees using instance segmentation and RGB-D images

Intelligent pruning is an effective way to improve the efficiency of fruit tree pruning and reduce production costs, where the positioning of fruit tree pruning points is the key. In this study, a pruning point localisation method based on deep learning and red-green-blue-depth (RGB-D) is proposed for dormant tall spindle apple trees, which can quickly and accurately identify the pruning points on the primary branches. Firstly, red-green-blue (RGB) images and depth images of apple trees were acquired by using the Realsense D435i depth camera, and the SOLOv2 instance segmentation model was used to segment the trunks, branches, and supports in RGB images. Secondly, the manual pruning rules were adapted to improve the pruning methods; then using OpenCV image processing method, the junction points of branches and trunk and potential pruning points were gained, and the world coordinates of the points were obtained according to the coordinate transformation to calculate the length of branch diameter and spacing. Finally, the pruning points were determined according to the pruning rules. The results show that SOLOv2 has better segmentation effect compared with Mask R–CNN and Cascade Mask R–CNN. The mean absolute error between the estimated and manually measured values of branch diameter and spacing are 1.10 mm and 16.06 mm, and the recognition accuracy of pruning points is 87.2%, with a recognition time of about 3.8 s for each image. It is shown that the method can measure branch diameter and spacing and quickly locate pruning points with high reliability and accuracy, and the study provides a basis for the development of apple tree pruning robots.

Pruning terms and techniques affect vigour and flower formation of Ukrainian sweet cherry trees

Excessive tree vigour and late entrance into full production, inherent to sweet cherry trees, are major challenges in the intensive cultivation of this crop. Possible ways to reduce the vigour and stimulate flower induction include shifting the term of pruning and reducing its severity. However, the reaction of the trees may differ depending on specific cultivar, soil and climatic conditions. Therefore, the aim of the study was to determine the effect of various techniques and terms of pruning on young sweet cherry trees in order to adapt the intensive cultivation technology to the arid conditions of southern Ukraine. The results showed a strong cultivar-specific reaction to various pruning treatments. Pruning young sweet cherry trees in late summer contributed to a reduction of trunk and canopy indices by 11-22% on one of the cultivars and an increase in the number of flowers per tree by 1.4-1.7 times on both cultivars, compared to dormant pruning. Low severity pruning reduced 1-year-old shoot length by 9-25% and increased the number of flowers by 1.5-2.5 times compared to more aggressive pruning. The effect of pruning treatments on tree vigour was more pronounced during the first and second year of their application.