Pruning Research Articles

Effects of biochar and compost addition in potting substrates on growth and volatile compounds profile of basil (Ocimum basilicum L.).

Despite the optimal characteristics of peat, more environmental-friendly materials are needed in the nursery sector, although these must guarantee specific quantitative and qualitative commercial standards. In the present study, we evaluated the influence of biochar and compost as peat surrogates on yield and essential oil profile of two different varieties of basil (Ocimum basilicum var. Italiano and Ocimum basilicum var. minimum). In two 50-day pot experiments, we checked the performances of biochar from pruning of urban trees and composted kitchen scraps, both mixed in different proportions with commercial peat (first experiment), and under different nitrogen (N) fertilization regimes (second experiment), in terms of plant growth and volatile compounds profile of basil. Total or high substitution of peat with biochar (100% and 50% v.v.) or compost (100%) resulted in seedling death a few days from transplantation, probably because the pH and electrical conductivity of the growing media were too high. Substrates with lower substitution rates (10-20%) were underperforming in terms of plant growth and color compared to pure commercial peat during the first experiment, whereas better performances were obtained by the nitrogen-fertilized mixed substrates in the second experiment, at least for one variety. We identified a total of 12 and 16 aroma compounds of basil (mainly terpenes) in the two experiments. Partial replacement of peat did not affect basil volatile organic compounds content and composition, whereas N fertilization overall decreased the concentration of these compounds. Our results support a moderate use of charred or composted materials as peat surrogates. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Development of an automatic control system for a hydraulic pruning robot

Automatic pruning is capable of trimming trees into complex shapes efficiently and continuously. However, this technology faces more challenges under unstructured agricultural environments. In the present paper, we describe the development of a hydraulic disc-saw mounted pruning robot with a relatively low cost for automated geometric pruning of fruit trees based on a new automatic pruning scenario. A pruning control strategy based on rolling observations and continuous prediction algorithm was designed to precisely control the motion of hydraulic cylinders. A forward kinematic model was described using modified Denavit–Hartenberg (D-H) notation, and the accessible workspace for the end-effector was analyzed in the simulation. The inverse kinematics model based on geometry was established, which provided the foundation for the development of a control system together with the forward kinematics model. Performance tests showed a sufficient control accuracy within ± 1.8° of all cylinders. The results of the waypoint tracking tests suggest that an increase in the step-size from 20 mm to 60 mm not only increases the moving speed and improves tracking accuracy, but also increases the fluctuation of the end-effector in the Z-axis direction. The movement of the chassis can introduce new errors and results in a larger average absolute positional error along the X-axis. The average startup and stop lag of the control system was 0.55 s and 0.15 s, respectively. This study provides guidance for pruning robot path planning and lays the foundation for future iterations of autonomous pruning robots.

Effects of AMF inoculation on the growth, photosynthesis and root physiological morphology of root-pruned Robinia pseudoacacia seedlings.

Root pruning hinders the absorption and utilization of nutrients and water by seedlings in the short term. Arbuscular mycorrhizal fungi (AMF) are an important source of nutrient and water for seedlings except for the root system. However, the mechanism by which AMF affect the physiological growth of seedlings after root pruning has rarely been studied. In this study, a pot experiment was conducted through a three-compartment partition system to clarify the effects of Funneliformis mosseae (F. mosseae) strain BGC XJ07A on the physiological growth of root-pruned Robinia pseudoacacia seedlings. Five root pruning treatments (zero, one-fifth, one-fourth, one-third and one-half of the taproot length were removed) were applied to noninoculated seedlings and those inoculated with F. mosseae. The results showed that the presence of F. mosseae significantly increased the shoot and root biomasses, leaf photosynthetic rate, stomatal conductance and transpiration rate. The root projected area, root surface area, average root diameter, root density, root volume and number of root tips of the inoculated seedlings were higher than those without inoculation in all root pruning treatments. The root cytokinin, gibberellins and indole-3-acetic acid concentrations, but root abscisic acid concentration, were higher than those measured in the absence of inoculation in all root pruning treatments. Moreover, the changes in the root endogenous hormone concentrations of the seedlings were closely related to the root morphological development and seedling biomass. The AMF increased the soil available nitrogen, soil available phosphorus, soil available potassium and soil organic matter concentrations compared with the noninoculated treatment. These results indicate that AMF can alleviate the adverse effects of root pruning on the physiological growth of R. pseudoacacia and soil properties, and can provide a basis for AMF application to forest cultivation and the sustainable development of forest ecosystems.

Toward presenting an ensemble meta‐model for evaluation of pozzolanic mixtures incorporating industrial by‐products

AbstractUnsustainable development in the industry has increased the challenge of proper disposal of industrial by‐products and has caused environmental pollution on a large scale. Furthermore, minimizing the carbon dioxide emissions due to industrial and environmental activities is a crucial challenge to controlling the global warming crisis and climate change. The use of industrial by‐product‐based supplementary cementitious materials (SCMs) can reduce fossil fuel consumption through the reduction in cement production and contribute to suitable waste management. In this research, a meta‐model was developed using integration of the decision tree‐based method named reduced error pruning tree (REPtree) and ensemble approaches (boosting and bagging) to improve the pruning phase for strength simulation of concrete mixtures incorporating industrial by‐products. Then, ensemble multiple learning algorithms were applied to develop a meta‐model using the artificial neural network and Gaussian process regression. A comprehensive experimental‐based database incorporating 3836 records from short‐term to long‐term compressive strength (CS) was collected from the literature. Performance measures present that the proposed ensemble boosting‐REPtree model outperforms other benchmark and ensemble models with a correlation coefficient of 0.960 and root mean square error of 7.884 MPa. Also, uncertainty evaluation was done based on the Monte Carlo simulation algorithm in the modeling process. The FAST and SOBOL methods, as global sensitivity analysis, presented water‐to‐binder (W/B) ratio, curing time, and SCMs to binder ratio (SCM/B) as critical components to estimate the CS of concrete mixtures. The computational simulation of the influential parameters on concrete mixtures incorporating industrial by‐products revealed that the experimental factors yielding the highest CS of the mixtures were calculated as follows: cement content of 584 kg/m3, W/B ratio of 0.17, superplasticizer‐to‐cement ratio of 1.88%, and SCM/B ratio of 0.15.

Valorization of Prunus Seed Oils: Fatty Acids Composition and Oxidative Stability.

Prunus fruit seeds are one of the main types of agri-food waste generated worldwide during the processing of fruits to produce jams, juices and preserves. To valorize this by-product, the aim of this work was the nutritional analysis of peach, apricot, plum and cherry seeds using the official AOAC methods, together with the extraction and characterization of the lipid profile of seed oils using GC-FID, as well as the measurement of the antioxidant activity and oxidative stability using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) free-radical scavenging method. Chemometric tools were required for data evaluation and the obtained results indicated that the main component of seeds were oils (30-38%, w). All seed oils were rich in oleic (C18:1n9c) and linoleic (C18:2n6c) acids and presented heart-healthy lipid indexes. Oil antioxidant activity was estimated in the range IC50 = 20-35 mg·mL-1, and high oxidative stability was observed for all evaluated oils during 1-22 storage days, with the plum seed oil being the most antioxidant and stable over time. Oxidative stability was also positively correlated with oleic acid content and negatively correlated with linoleic acid content. Therefore, this research showed that the four Prunus seed oils present interesting healthy characteristics for their use and potential application in the cosmetic and nutraceutical industries.

Decision Tree-Based Modeling of the Aeration Effectiveness of Circular Plunging Jets.

Since soft computing has gained a lot of attention in hydrological studies, this study focuses on predicting aeration efficiency (E20) using circular plunging jets employing soft computing techniques such as reduced error pruning tree (REPTree), random forest (RF), and M5P. The study undertaken required the development and validation of models, which were achieved using 63 experimental data values with input variables, such as angle of inclination of tilt channel (α), number of plunging jets (JN), discharge of each jet (Q), hydraulic radius of each jet (HR), and Froude number (Fr. No), to evaluate the aeration efficiency (E20), which served as the output variable. To evaluate the effectiveness of the developed models, three different statistical indices were used such as the coefficient of correlation (CC), root-mean-square error (RMSE), and mean absolute error (MAE), and it was found that all of the applied techniques possessed good forecasting ability since their correlation coefficient values were greater than 0.8. Upon testing, it was discovered that the M5P model outperformed other soft computing-based models in its ability to predict E20, as demonstrated by its correlation coefficient value of 0.9564 and notably low values of MAE (0.0143) and RMSE (0.0193).

Rectangle packing with a recursive Pilot Method

We propose a deterministic tree search procedure for the Rectangle Packing Problem, where a set of rectangular items must be packed into a rectangular container such that the unoccupied area of the container is the minimum possible. The tree search is based on two literature methods whose strong points complement each other. First, a skyline-based heuristic strongly restricts the number of items that must be evaluated and the number of positions where they may be placed. Also, a generalization of the Pilot Method meta-heuristic expands the search tree gradually, iteratively increasing the tree size within a given time limit. We also devise tree pruning strategies to further reduce the exploration size. Empirical results surpass state-of-the-art solutions on most benchmark data sets, subject to computation time limits comparable to those of the literature, and we analyze how the quality of the solutions varies depending on the geometry of the items.

Multiple energy resources integration in the food industry: A technoeconomic analysis

This study focuses on exploring sustainable energy solutions for the industrial sector, with a particular emphasis on meeting the electrical and thermal needs of the local bakery industry. Several alternative energy sources were proposed in this study, including solar irradiation, and the utilization of agricultural residues (such as olive tree pruning and residues of tomato crop). An anaerobic digestion (AD) reactor, a photovoltaic (PV) system, wind turbines (WT), a gasification system, and a combined heat and power (CHP) unit were used as parts of the developed hybrid renewable energy system (HRES). The objective was to optimize the system's performance by considering renewable energy sources (RES) penetration, energy cost, and ecological footprint.Furthermore, this investigation identified research gaps in the supply of thermal energy demand using renewable energy sources in an industrial setting and evaluated the integration of waste-to-energy technologies in HOMER Pro. Through modelling, optimization, and evaluation, different HRES configurations were assessed to determine the most cost-effective and optimal system for the bakery industry. The optimal suggested HRES showed a 65% reduction (from 0.4362 €/kWh to 0.1533 €/kWh) in the levelized cost of electricity (LCOE). Gasification achieved better results than AD, with the addition of a gasifier leading to a 40% decrease in the LCOE. The renewable fraction for the optimal HRES was 87.9%. There was a reduction in carbon dioxide emissions by 63%, while the HRES had a payback time of 3.17 years. Overall, the findings of this study show that utilizing local biomass and waste can play a significant role in the energy transition, leading to cost reduction and improved economic performance.

Effect of different levels of pruning and nitrogen fertilizer on vegetative traits and chemical content of Rosmarinus officinalis L.

The experiment was performed in a greenhouse belonging to the Department of Horticulture and Landscaping gardening, College of Agriculture, Tikrit University for the period from November 2021 - May 2022. The experiment included two factors: the level of pruning (without pruning, moderate pruning, and severe pruning); the addition of nitrogen fertilizer at two levels (73.4 and 146.7 g N.L-1 in the form of urea (46% N) according to the randomized complete block design (RCBD), with three replicates and three plants for each experimental unit. The results showed that the treatment of severe pruning (H2) and moderate pruning (H1) were significantly superior in the trait of the branches number (26.65 and 24.61 plants.branches-1), respectively. The treatment without pruning (H0)) was significantly superior in the leaves content of chlorophyll of (0.36 mg.g-1). The nitrogen fertilization treatment of the first concentration (F1) had a significant effect on the trait of plant height, which amounted to 37.28 cm. As for the nitrogen fertilization treatment of the second concentration (F2), it was significantly superior in the percentage of nitrogen 1.31%, phosphorous 0.24%, and potassium 1.43%. As for the interaction, the treatment (S1H0) was significantly superior in the leaves content of chlorophyll, and the treatments (H0F1) and (H0F2) also gave a significant superiority in the leaves content of chlorophyll. The interference treatment (H2F2) also led to a significant superiority in the leaves content of phosphorous. As for potassium

A Function-Based Approach to Interactive High-Precision Volumetric Design and Fabrication

We present a novel function representation (F-Rep) based geometric modeling kernel tailor-made to support computer aided design (CAD) and fabrication of high resolution volumetric models containing hundreds of billions of voxel grid elements. Our modeling kernel addresses existing limitations associated with evaluating, storing, and accessing volumetric data produced by F-Reps in contexts outside of rendering. The result is an F-Rep modeling kernel well suited for CAD-based applications. Our kernel utilizes a sparse volume data structure to manage F-Rep data while efficient F-Rep evaluation is achieved through a combination of interval arithmetic (IA), just-in-time (JIT) compilation of user-defined functions, and massively parallel evaluation on the GPU. We employ IA as the basis for local pruning of the function evaluation tree to minimize total function evaluations, we use a novel JIT compilation scheme to optimize function execution, and we take advantage of GPU-parallelism to enhance computational throughput. We illustrate the kernel’s effectiveness in visualizing and slicing models with complex defining functions and detailed geometry, and utilize the geometry kernel to manufacture a physical part. Additionally, we present performance metrics across multiple hardware configurations demonstrating significant performance improvements over existing F-Rep geometry kernels, and we examine how our geometry kernel scales with computing power.

ERGONOMIC ANALYSIS OF PRUNING TREES IN CONFLICT WITH POWER LINES

Ergonomic analysis of pruning trees in conflict with power lines. Pruning trees in conflict with power lines is associated with several ergonomic risks due to postural issues and exposure to environmental conditions, such as noise and vibration in work activities. Additionally, there are life-threatening risks from falls or contact with power lines. The objective of this work was to apply the Ergonomic Workplace Analysis (EWA) method and assess the exposure of workers involved in pruning of trees conflicting with power lines to noise and vibration. The survey was conducted considering outsourced employees that provide services to an electric utility company in the state of Bahia, Brazil. The results obtained through EWA showed a regular risk rate, with concerning aspects, such as verbal communication (dialogue among workers regarding technical/operational issues), irregular posture of back, arms, and shoulders, high attention demand, and activity limitations. Quantitative analysis showed 84.9 dB (A-weighted) for noise and 2.440 m s-2 for vibration, both close to the action level. The pole saw vibration reached 3.703 m s-2, exceeding the tolerance limit. The importance of breaks, at-work exercises, and training is emphasized as ergonomic measures. A rotation system should be implemented in tree pruning activities to reduce exposure to vibration.

Re-discovering Prunus fruit varieties as antiangiogenic agents by metabolomic and bioinformatic approach

In this work, a comparative chemical-biological study of nine plum varieties (Prunus domestica L. and Prunus salicina Lindl.) with two commercial ones was carried out to improve their cultivation and use in the agri-food chain. The chemical quali-quantitative fingerprint by HR-Orbitrap/ESI-MS showed similar profiles, being ‘Rossa Casa Velasco’ the richest in phenols and anthocyanins. All the extracts were investigated for their in vitro antioxidant as well as antiangiogenic activity by two in vivo models, chick chorioallantoic membrane and zebrafish embryos. Among investigated varieties ‘Scarrafona’, ‘Rusticano’, ‘Marisa’, ‘Rossa Casa Velasco’, ‘Verdone’, and ‘Sangue di Drago’ showed the best antiangiogenic activities (30–50 % inhibition). Finally, the chemical/biological datasets processed with a bioinformatic approach revealed that a large group of flavonoids, procyanidins, and anthocyanins significantly correlated with all the three antioxidant tests (DPPH, FRAP, and ABTS), while quinic acid and icariside F2 resulted positively correlated with CAM at both 100 and 200 μg/egg.

Hyalopterus pruni (Geoffroy)'nin morfolojik ve moleküler teşhisi üzerine araştırma

Aphids are one of the most important groups of insects that cause damage to agricultural crops, ornamental plants, as well as herbaceous and woody plants in their natural habitats. Aphids that feed on plant sap can cause significant crop losses worldwide, ranging from 70% to 80%, due to stunted growth, deformation, wilting, and other detrimental effects on plants. Despite the chemical, biological, and integrated pest management methods applied against these damages, aphids have rapidly expanded their distribution areas and their damages have been increasing in recent times. Hyalopterus Koch (Hemiptera: Aphididae), a genus of aphids, are known worldwide as pests that infest Prunus trees, which are stone fruit trees. They cause damage by feeding on the trees and also by transmitting plant viruses. Subsequently, improper and indiscriminate use of chemical control methods negatively impacts both human and environmental health. Accurate identification of aphids, especially in terms of invasive species, is crucial for early detection of their damages in the initial stages. The mitochondrial cytochrome c oxidase subunit I (COI) gene is an effective gene region used in the identification of many economically important plant pests worldwide. In this study, a total of 50 individuals of Hyalopterus pruni (Geoffroy) were collected from three localities Şarköy (Ulaman, Bulgurlu, Gölcük, Cumhuriyet, Mürefte, Hoşköy, Gaziköy, Tepeköy, Palamut), Süleymanpaşa (Yüzüncüyıl, Altınova, Banarlı, Barboros, Bıyıkali, Çınarlı, Değirmenaltı, Ferhadanlı, Hürriyet, Karacakılavuz, Karaevli, Naip, Namık Kemal and Marmaraereğlisi (Bahçelievler, Cedit Ali Paşa, Dereağzı, Mustafa Kemal Paşa, Sultanköy, Türkmenli, Yakuplu and Yeniçiftlik) in Tekirdağ province. The species H11, H41, and H61, which were selected to represent three counties, were sequenced, and the molecular sequence results revealed that H. pruni, as morphologically described, showed 99% consistency at the molecular level.

Monitoring water quality metrics of ponds with IoT sensors and machine learning to predict fish species survival

Aquaculture involves cultivating various marine and freshwater aquatic creatures within regulated environments. Monitoring the aquatic environmental conditions in real-time is crucial for successful fish farming. The Internet of Things (IoT) offers significant potential for real-time monitoring, and this paper introduces an IoT framework designed for efficient monitoring and effective control of various water-related aquatic environmental parameters. The proposed system is implemented as an embedded system utilizing sensors and an Arduino microcontroller. In cultivating pond water, diverse sensors such as pH, temperature, and turbidity sensors are deployed, with each sensor connected to an Arduino Uno-based microcontroller board. These sensors collect data from the water, which is then stored as a CSV file in an IoT cloud platform called ThingSpeak through the Arduino microcontroller. To gather data for analysis, we conducted measurements across five ponds, varying in size and environmental conditions. After getting the real-time data, we compared our experimental results with the standard reference values. As a result, we could take the decision of whether a pond is suitable for cultivating fish or not. After that, we labeled the data with 11 fish categories: Katla, sing, prawn, shrimp, rui, tilapia, pangas, karpio, magur, silver carp, and koi. The data was analyzed using 10 machine learning (ML) algorithms, including J48, Random Forest, K Nearest Neighbors (K-NN), K*, Logistic Model Tree (LMT), Reduced Error Pruning Tree (REPTree), Jumping Rule Inference with Pruned Search (JRIP), Partial Decision Trees (PART), Decision Table, and Logit boost. After experimental analyses, it was discovered that only three of the five ponds were ideal for fish farming, and those three ponds only met the required standards for pH, Temperature, Turbidity, and Conductivity. Among the state-of-art machine learning algorithms, Random Forest achieved the highest score of performance metrics as accuracy 94.42%, kappa statistics 93.5%, and Avg. TP Rate 94.4%. In addition, we calculated the Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Dissolved Oxygen (DO) for one scenario. This study includes prototype hardware details of the proposed IoT system.

Boosting cost-complexity pruned trees on Tweedie responses: the ABT machine for insurance ratemaking

This paper proposes a new boosting machine based on forward stagewise additive modeling with cost-complexity pruned trees. In the Tweedie case, it deals directly with observed responses, not gradients of the loss function. Trees included in the score progressively reduce to the root-node one, in an adaptive way. The proposed Adaptive Boosting Tree (ABT) machine thus automatically stops at that time, avoiding to resort to the time-consuming cross validation approach. Case studies performed on motor third-party liability insurance claim data demonstrate the performances of the proposed ABT machine for ratemaking, in comparison with regular gradient boosting trees.

Bidirectional pruned tree-based efficient minimum cut acceleration in dense graph

The minimum cut (min-cut) problem has been extensively investigated, and the corresponding algorithms have been used in many related problems. The recently proposed acceleration strategy based on tree-cut mapping has been shown to be an effective alternative, with a slight loss in acceleration accuracy. However, the existing method requires a large number of ineffective traversal passes in the high-overhead preprocessing step, which has the potential to be significantly improved in mapping effective graphs, i.e. dense graphs. To solve the problem, we propose to use bidirectional pruned tree for tree-cut mapping, which combines pruned depth-first traversal tree and bidirectional traversal paths to enumerate as many different tree instances as possible. Thus, it can help find the min-cut of any node pair efficiently. Theoretical analysis also shows its potential. For its serial implementation in a graph with M edges, after a preprocessing step with a time complexity as low as O(M), 99.9% of sampled node pairs can obtain their exact min-cut value in various types of dense graphs with degrees greater than 8 in experiments. In addition, the same precision can be obtained in sparse graphs in case of unit capacity. Per-pair running time in a million-node graph can be several orders of magnitude faster than existing methods and as low as several microseconds, so can be used as an effective complement to existing methods.

The effect of summer pruning time and severity on antioxidant capacity and storage quality of Hayward kiwifruit

BACKGROUND Summer pruning of kiwifruit has an important effect on fruit quality and storability. OBJECTIVE: The present study was conducted to investigate the effects of summer pruning time and severity on some quantitative and qualitative characteristics and storability of Hayward kiwifruit. METHODS: The present study was conducted to evaluate summer pruning time (one week after fruit set [1WAFS] and four weeks after fruit set [4WAFS]) and pruning severity (1 - no pruning [control], 2 - shoot pruning after the third or fourth leaf after the last fruit [common pruning], 3 - tip squeezing, and 4 - zero leaf pruning in 20% of fruit-bearing shoots with unlimited growth) on Hayward kiwifruit in 2020 and 2021. RESULTS: The results showed that, at harvest time, the highest average fruit weight and total acid were 124.00 g and 1.74% in the tip squeezing treatment observed in the 4WAFS pruning time in 2021. Zero leaf pruning produced fruits with the highest firmness and antioxidant capacity in 2020 and the highest vitamin C and total phenols in 2021. At the end of 90 days of cold storage, in the tip squeezing treatment, fruit firmness at 4WAFS pruning time was higher than in 1WAFS pruning time in the second year, and the highest antioxidant capacity was in 1WAFS pruning time in the first year. In the second year, the highest vitamin C, firmness, and dry matter were obtained in the zero leaf pruning treatment. In this treatment, the highest total phenols and antioxidant capacity were 133.96 mg GAE/100 g FW and 86.75%, respectively, observed in 4WAFS pruning time in the second year. CONCLUSIONS: Overall, tip squeezing and zero leaf pruning at the time of 4WAFS improved the quantitative and qualitative characteristics at the harvest and cold storage.

Use of Balanced Fertilizer Doses and Pruning Methods to Increase Growth and Yield of Rice Plants in Acidic Sulphate Lands in West Borneo

The provision of appropriate technology for farmers was necessary to optimize the productivity of rice plants, especially in acidic sulfate fields. The purpose of study were to determine optimal dose of NPK fertilizer and right pruning time to increase growth and yield of rice plants in acidic sulfate fields. Research was conducted in acidic sulfate fields of Rasau Jaya Tiga village, Kubu Raya district, from August to December 2022. This experiment utilized a factorial randomized design group, with two factors namely: factor I and factor II. Factor I was NPK fertilizer (N): N1 = 0.9 kg/plot, N2 = 1.8 kg/plot, N3 = 2.7 kg/plot, N4 = 4.5 kg/plot. Factor II was leaf pruning (P): P0 = No Pruning, P1 = Pruning 30 days after planting (dap), P2 = Pruning 37 dap, P3 = Pruning 44 dap, P4 = Pruning 51 dap, and P5 = Pruning 58 dap. Observed variables were plant height, number of tillers, number of productive tillers, number of grains per panicle, amount of grain contained per panicle, and dry weight of grain per plot. Data were analyzed using F and Tukey tests at a 5% level of significance. The interaction of pruning treatment and NPK has an unsignificant effect on all observed parameters. NPK treatment and pruning singularly have a significant effect on all observed parameters. Pruning of the plant at 44 dap (P3) and NPK fertilizer dose of 4.5 kg/plot (N4) yielded the best results in all observed variables. Keywords: Acidic Sulphate Lands, Fertilizer, Productivity, Pruning, Rice

Renewal Pruning Alone or in Combination with Thinning Pruning Affects Growth, Fruit Yield and Fruit Quality of Aroniaberry

Aroniaberry (Aronia mitschurinii) produces small pome fruits that possess health promoting compounds. Management practices for orchards are lacking, since aroniaberry is a relatively new crop. Pruning is an important cultural practice to optimize fruit yield in orchards. The response of an established aroniaberry orchard to pruning was evaluated over three years (2020 to 2022). Pruning treatments were as follows: 1) renewal pruning (removal of shoots to the base) only in year 1; 2) renewal pruning in year 1 + thinning to 18 shoots in year 2; 3) renewal pruning in year 1 + thinning to 9 shoots in year 2; and 4) no-pruning (control). In response to renewal pruning, plants grew uniformly and vigorously, producing 28 new vegetative primary shoots with an average length of 66 cm by the end of the first growing season. Limited flowering and fruiting occurred in the second season for plants receiving pruning treatments. Fruit yield on pruned plants was significantly less than for unpruned controls. In season 2, increased thinning of renewal-pruned plants negatively affected the number of inflorescences per plant, but positively affected individual fruit fresh weight and fruit °Brix:titratable acidity ratios. Fruits from all treatments had similar monomeric anthocyanins, total phenolics and mineral content. In season 3, flower production and predicted fruit yield from pruned plants and unpruned controls were similar, even though pruned plants were substantially smaller. In the third season, there were no longer any differences between renewed + thinned plants and those that received only renewal pruning, making shoot thinning an unnecessary practice. The results of this study demonstrate that renewal pruning can be an effective way to manage and rejuvenate an aging aroniaberry orchard.

Composite Tiles Produced from Granite Dust and Tree Pruning Using a Sandwiched Method

Composite Tiles Produced from Granite Dust and Tree Pruning Using a Sandwiched Method