Pruning Research Articles

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.

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.

Olive leaf protein: Extraction optimization, in vitro digestibility, structural and techno-functional properties

Olive leaf, as an important by-product of olive farming, is generated from the pruning and harvesting of olive trees and represents >10 % of the total olive weight. The present study was conducted to evaluate the composition, functional and structural characterizations, as well as the in vitro digestibility of olive leaf proteins isolated from ultrasonic-assisted extraction, comparing to classical and industrial techniques. The ultrasound-assisted extraction of olive leaf protein was optimized by the simultaneous maximization of the yield and purity of protein using a Box-Behnken design (BBD) of response surface methodology (RSM). The results indicated that the optimal extraction conditions were as follows: pH of 10.99, temperature of 40.48 °C, sonication time of 47.25 min, and solvent/solid ratio of 24.08 mL/g. Under these conditions, the extraction yield and protein content were 11.67 and 51.2 %, respectively, which were significantly higher than those obtained by the conventional techniques. Regarding the functionality of protein, extraction technique had significant impacts on the structural and functional properties of proteins. In general, ultrasound assisted extraction had higher solubility, and better foaming and thermal properties and in vitro digestibility but lower emulsifying stability and fluid binding capacity compared to conventional ones. Ultrasound-assisted alkaline extraction has great potential to produce edible olive leaf protein with modified functional properties that can be used for various aims in the food applications.

Seasonal Susceptibility of Sweet Cherry Pruning Wounds to Calosphaeria pulchella, Cytospora sorbicola, and Eutypa lata.

Fungal canker pathogens commonly infect trees at pruning wounds leading to branch dieback and loss of productivity in sweet cherry orchards. However, the seasonal susceptibility of sweet cherry pruning wounds to Calosphaeria pulchella, Cytospora sorbicola, and Eutypa lata is not well understood. This study compared the susceptibility of sweet cherry pruning wounds made during the dormant season (January) and the postharvest season (late May to June) to infection by main canker pathogens in California. Field trials were conducted in three cherry orchards and trees were pruned at the different periods over 2 years. Fresh pruning wounds were inoculated with spores of each pathogen, and pathogen recovery was assessed through microbiological isolations at 3 to 4 months after inoculations. Pruning wounds made in late May and June resulted in significantly higher infection by Cal. pulchella compared to pruning wounds made in January. Pruning wounds made during both seasons were generally equally susceptible to Cyt. sorbicola and E. lata infections. However, there was one orchard where dormant pruning wounds were more susceptible to infection by E. lata and there was one particularly cold winter where Cyt. sorbicola did not infect pruning wounds. Overall, our findings suggest that Cal. pulchella infections of cherry pruning wounds are more likely to occur during periods of warm temperatures such as late spring and early summer. However, infections by Cyt. sorbicola and E. lata can occur year-round if inoculum is present and if winter temperatures are not abnormally low for California. Finally, our results suggest that the emergence of Cal. pulchella as a major canker pathogen of sweet cherry in California may be the result of a shift from dormant to after-harvest pruning of sweet cherry trees.

Light efficacy estimation for fruit trees based on LIDAR point clouds: A case study on pear trees

It is important to evaluate the effect of fruit-tree pruning based on canopy-structure characteristics so as to keep appropriate illumination for tree growth. However, current pruning and evaluation mainly rely on manual experience due to lacking a convenient and automatic approach to obtain such features. This paper proposes a method for estimating light efficacy based on layered canopy point-clouds, where leaf-area was selected as the canopy characteristic. LIDAR was utilised to scan pear trees in three dimensions to acquire initial point clouds, and preprocess was conducted to obtain the point-cloud images of different canopy layers. Then, an optimised algorithm based on Freeman Chain was developed to accurately draw the outlines of point-cloud clusters in the images, and pixel proportion was used to calculate the real leaf-area of each layer. Finally, based on Deep Neural Network, an estimation model was established between different layer leaf-areas and their average illumination acquired in tests. The proposed method was applied to estimate the illumination of a random pear tree to evaluate the variation of light intensity. The results showed that: 1) the average relative error of leaf-area calculation of the optimised Freeman Chain method was about 6.74 %, although the running duration was longer than the conventional one, 2) the overall correlation coefficient, R, of the model was more than 0.95, while that of validation and test sets were more than 0.94, and 3) the illumination estimation was accurate and precise with an average relative error of 1.42 % and a standard deviation of relative errors of 1.19. The validation indicated that this method could achieve the prediction of illumination based on different leaf-area characteristics. The study is expected to give a technical solution for the illumination evaluation before and after tree pruning.

Obtaining Cellulose Nanocrystals from Olive Tree Pruning Waste and Evaluation of Their Influence as a Reinforcement on Biocomposites

The objective of this work is to improve the mechanical properties of polylactic acid (PLA) by incorporating cellulose nanocrystals (CNC) previously obtained from a cellulose pulp extracted from olive tree pruning (OTP) waste. Composites were manufactured by melt processing and injection moulding to evaluate the effect of the introduction of CNC with conventional manufacturing methods. This OTP-cellulose pulp was subjected to a further purification process by bleaching, thus bringing the cellulose content up to 86.1%wt. This highly purified cellulose was hydrolysed with sulfuric acid to obtain CNCs with an average length of 267 nm and a degradation temperature of 300 °C. The CNCs obtained were used in different percentages (1, 3, and 5%wt.) as reinforcement in the manufacture of PLA-based composites. The effect of incorporating CNC into PLA matrix on the mechanical, water absorption, thermal, structural, and morphological properties was studied. Maximum tensile stress and Young’s modulus improved by 87 and 58%, respectively, by incorporating 3 and 5%wt. CNC. Charpy impact strength increased by 21% with 3%wt. These results were attributed to the good dispersion of CNCs in the matrix, which was corroborated by SEM images. Crystallinity index, glass transition, and melting temperatures were maintained.