Search Results (336)

In recent years, the traditional orchard sprayer has had problems, such as waste of liquid agrochemicals, low target coverage, high manual dependence, and environmental pollution. In this study, an automatic swing-arm sprayer for orchards was developed based on the standardized pear orchard in Pinggu, Beijing. Firstly, the structural principles of a crawler-type traveling system and swing-arm sprayer were simulated using finite element software design. The combination of a diffuse reflection photoelectric sensor and Arduino single-chip microcomputer was used to realize real-time detection and dynamic spray control in the pear canopy, and the sensor delay compensation algorithm was used to optimize target recognition accuracy and improve the utilization rate of liquid agrochemicals. Through the integration of innovative structural design and intelligent control technology, a vertical droplet distribution test was carried out, and the optimal working distance of the spray was determined to be 1 m; the nozzle angle for the upper layer was 45°, that for the lower layer was 15°, and the optimal speed of the swing-arm motor was 75 r/min. Finally, a particle size test and field test of the orchard sprayer were completed, and it was concluded that the swing-arm mode increased the pear tree canopy droplet coverage by 74%, the overall droplet density by 21.4%, and the deposition amount by 23% compared with the non-swing-arm mode, which verified the practicability and reliability of the swing-arm spray and achieved the goal of on-demand pesticide application in pear orchards. Full article

Background: Pinus massoniana is a significant lipid-producing tree species in China and a susceptible host for both the pine wood nematode and its insect vector, Monochamus alternatus. The basic helix–loop–helix (bHLH) family of transcription factors play a crucial role in responding to both biotic and abiotic stresses. However, the role of bHLH in terpene-induced defense in P. massoniana remains poorly studied. Results: Transcriptome sequencing using DNA Nanoball Sequencing (DNBSEQ) and PacBio Sequel platforms was performed, revealing differences in gene expression in P. massoniana branch under the simulated feeding treatment of methyl jasmonate (MeJA) spraying. Fifteen bHLH genes were cloned and analyzed, among which eight highly upregulated PmbHLH genes showed similar temporal expression after MeJA treatment and M. alternatus adult feeding. Five highly upregulated bHLH genes with nuclear localization were highly expressed in P. massoniana after M. alternatus feeding and interacted with the promoter of the terpene synthase gene Pm TPS (−)-α-pinene, confirming their involvement in the defense response of P. massoniana against the M. alternatus adult feeding. Conclusions: Our results unveil the temporal changes and the regulation of the induced defense system in P. massoniana mediated by both MeJA signaling and M. alternatus feeding treatment. The potential application for transgenic experiments and the breeding of resistant species in the future were discussed. Full article

Air-assisted spraying is the primary method of plant protection in orchards, and precision spraying according to the canopy characteristics of fruit trees can reduce waste and pollution due to pesticide drift. To facilitate targeted pesticide application in the canopy of fruit trees, this study employed a newly developed wind-speed-adjustable orchard sprayer and established a prediction model for deposition based on data from orthogonal trials using a central composite design accounting for the coupling effect of three-dimensional spatial parameters. The experimental design systematically quantified the interaction effects of spray distance (1.5–2.5 m), fan wind speed (10–20 m/s), and deposition height (0.5–3 m) on the spatial distribution of droplets. Model significance was p < 0.0001 and the misfit term was significant (p = 0.2193), supporting its validity. The research found that wind speed and distance significantly interact in influencing deposition. By adjusting fan speed and spray distance, variable applications can be achieved in different canopy zones during plant protection operations. The response surface model developed in this study can be applied to variable-rate spraying control systems, thus providing a quantitative basis for dynamic droplet control guided by canopy characteristics. Validation tests revealed that the model’s accuracy was lower in high canopy regions and upwind spraying scenarios, indicating areas for further research. Full article

The use of unmanned aerial vehicle (UAV) pesticide spraying technology in precision agriculture is becoming increasingly important. However, traditional spraying methods struggle to address the precision application need caused by the canopy differences of fruit trees in orchards. This study proposes a UAV orchard variable-rate spraying method based on canopy volume. A DJI M300 drone equipped with LiDAR was used to capture high-precision 3D point cloud data of tree canopies. An improved progressive TIN densification (IPTD) filtering algorithm and a region-growing algorithm were applied to segment the point cloud of fruit trees, construct a canopy volume-based classification model, and generate a differentiated prescription map for spraying. A distributed multi-point spraying strategy was employed to optimize droplet deposition performance. Field experiments were conducted in a citrus (Citrus reticulata Blanco) orchard (73 trees) and a litchi (Litchi chinensis Sonn.) orchard (82 trees). Data analysis showed that variable-rate treatment in the litchi area achieved a maximum canopy coverage of 14.47% for large canopies, reducing ground deposition by 90.4% compared to the continuous spraying treatment; variable-rate treatment in the citrus area reached a maximum coverage of 9.68%, with ground deposition reduced by approximately 64.1% compared to the continuous spraying treatment. By matching spray volume to canopy demand, variable-rate spraying significantly improved droplet deposition targeting, validating the feasibility of the proposed method in reducing pesticide waste and environmental pollution and providing a scalable technical path for precision plant protection in orchards. Full article

Fruit orchard canopy recognition and characteristic extraction are the key problems faced in orchard precision production. To this end, we built a fruit tree canopy detection platform based on millimeter-wave radar, verified the feasibility of millimeter-wave radar from the two perspectives of fruit orchard canopy recognition and canopy characteristic extraction, and explored the detection accuracy of millimeter-wave radar under spray conditions. For fruit orchard canopy recognition, based on the DBSCAN algorithm, an ellipsoid model adaptive clustering algorithm based on a variable-axis (E-DBSCAN) was proposed. The feasibility of the proposed algorithm was verified in the real operation scene of the orchard. The results show that the F₁ score of the proposed algorithm was 96.7%, the precision rate was 93.5%, and the recall rate was 95.1%, which effectively improves the recognition accuracy of the classical DBSCAN algorithm in multi-density point cloud clustering. Regarding the extraction of the canopy characteristics of fruit trees, the RANSAC algorithm and coordinate method were used to extract crown width and plant height, respectively, and a point cloud density adaptive Alpha_shape algorithm was proposed to extract volume. The number of point clouds, crown width, plant height, and volume value under spray conditions and normal conditions were compared and analyzed. The average relative errors of crown width, plant height, and volume were 2.1%, 2.3%, and 4.2%, respectively, indicating that the spray had little effect on the extraction of canopy characteristics by millimeter-wave radar, which could inform spray-related decisions for precise applications. Full article

Precision spraying technology has attracted increasing attention in orchard production management. Traditional chemical pesticide application relies on subjective judgment, leading to fluctuations in pesticide usage, low application efficiency, and environmental pollution. This study proposes a machine vision-based precision spraying control system for orchards. First, a canopy leaf wall area calculation method was developed based on a multi-iteration GrabCut image segmentation algorithm, and a spray volume calculation model was established. Next, a fuzzy adaptive control algorithm based on an extended state observer (ESO) was proposed, along with the design of flow and pressure controllers. Finally, the precision spraying system’s performance tests were conducted in laboratory and field environments. The indoor experiments consisted of three test sets, each involving six citrus trees, totaling eighteen trees arranged in two staggered rows, with an interrow spacing of 3.4 m and an intra-row spacing of 2.5 m; the nozzle was positioned approximately 1.3 m from the canopy surface. Similarly, the field experiments included three test sets, each selecting eight citrus trees, totaling twenty-four trees, with an average height of approximately 1.5 m and a row spacing of 3 m, representing a typical orchard environment for performance validation. Experimental results demonstrated that the system reduced spray volume by 59.73% compared to continuous spraying, by 30.24% compared to PID control, and by 19.19% compared to traditional fuzzy control; meanwhile, the pesticide utilization efficiency increased by 61.42%, 26.8%, and 19.54%, respectively. The findings of this study provide a novel technical approach to improving agricultural production efficiency, enhancing fruit quality, reducing pesticide use, and promoting environmental protection, demonstrating significant application value. Full article

Honey bees and other pollinators are key to functioning natural and managed ecosystems. However, their health is threatened by many factors, including pesticides. Spraying fungicides during flowering of fruit trees is widespread even though it directly exposes pollinators to these fungicides. Here, we report a series of experiments designed to understand how the combination of propiconazole and carbendazim, marketed in China as Chunmanchun^®, affects honey bee health. With an acute oral toxicity of 23.8 μg a.i./bee over 24 h in the laboratory, we considered the acute mortality risk from normal Chunmanchun^® applications as relatively low. However, our comprehensive studies revealed other diverse effects: Chunmanchun^® reduced memory after classic conditioning by approximately 25% and altered the activity of protective enzymes and the composition of the honey bees’ gut microbiota. Specifically, the genus Lactobacillus was decreased by ~13%, and Bartonella and Snodgrassella were increased by ~10% and ~7.5%, respectively. The gut metabolome was also disrupted in diverse ways, possibly as a functional consequence of the microbiome changes. Thus, we demonstrated numerous sublethal effects of the combination of propiconazole and carbendazim, which adds to the growing evidence that agrochemicals and fungicides in particular can harm pollinator health in subtle ways that are not captured in simple mortality assays. Full article

Smoke tree (Cotinus coggygria) is an important component of the urban landscape and represents red-leaf scenery in Beijing; however, Verticillium wilt, caused by Verticillium dahliae, has caused high mortality of smoke trees. Traditional control methods, such as chemical root irrigation and trunk injection, are problematic due to environmental pollution and potential plant damage. This study aimed to explore effective prevention and control methods for Verticillium wilt of smoke tree across different regions of red-leaf scenery in Beijing. In 2023, 240 smoke trees from the Pofengling Park of Beijing were selected for the study. Four different fungicides, a plant growth regulator and a biocontrol agent were tested. Three application methods (root irrigation, trunk spraying, and a combination of both) were used in the different trials. Based on the results of the 2023 trial, control trials were conducted under the disease classification in 2024 at key red-leaf scenery regions, such as Xiangshan Park, Xishan Park, and Pofengling Park. The bioagents of Bacillus subtilis root irrigation combined with the trunk spraying treatment group showed the best disease control effects. Calculated by the change in disease index in the treatment and blank groups, the corrective control effect in the treatment group reached 104.55%, and 60% of the plants remained healthy, indicating that this method of disease control was the most effective. Propiconazole root irrigation also had a significant effect on diseased smoke trees. Furthermore, validation experiments conducted in 2024 confirmed that various combinations of root irrigation and trunk spraying provided strong preventive and therapeutic effects on Verticillium wilt. In conclusion, the graded control measures demonstrated effective control of wilt at different disease index grades. This study offers an effective and practical solution for controlling Verticillium wilt, benefiting both environmental sustainability and landscape health. Full article

During the flowering period of mango trees, pests often hide in the inflorescences to suck sap, affecting fruit formation. By accurately detecting the number and location of mango inflorescences in the early stages, it can help target-specific spraying equipment to perform precise pesticide application. This study focuses on mango panicles and addresses challenges such as high crop planting density, poor image quality, and complex backgrounds. A series of improvements were made to the YOLOv8 model to enhance performance for this type of detection task. Firstly, a mango panicle dataset was constructed by selecting, augmenting, and correcting samples based on actual agricultural conditions. Second, the backbone network of YOLOv8 was replaced with FasterNet. Although this led to a slight decrease in accuracy, it significantly improved inference speed and reduced model parameters, demonstrating that FasterNet effectively reduced computational complexity while optimizing accuracy. Further, the GAM (Global Attention Module) attention mechanism was introduced as an attention module in the backbone network to enhance feature extraction capabilities. Experimental results indicated that the addition of GAM improved the average precision by 2.2 percentage points, outperforming other attention mechanisms such as SE, CA, and CBAM. Finally, the model’s bounding box localization ability was enhanced by replacing the loss function with WIoU, which also accelerated model convergence and improved the mAP@.5 metric by 1.1 percentage points. Our approach demonstrates a discrepancy of less than 10% compared to manual counted results. Full article

Previous studies have shown that foliar spraying with a 0.3% CaCl₂ + 0.3% MgCl₂ solution can mitigate the “sugar receding” phenomenon in fruit pulp, partly by regulating sugar conversion in the pulp of ‘Feizixiao’ litchi (Litchi chinensis Sonn.). Given that calcium-dependent protein kinases (CDPKs) in plants regulate sugar metabolism by modulating the activity of key sugar conversion enzymes, this study investigated the expression response of CDPK genes in ‘Feizixiao’ litchi pulp to foliar calcium–magnesium nutrient treatment and their regulatory characteristics on sugar conversion. After the fruit set, ‘Feizixiao’ litchi trees were subjected to three consecutive foliar spray applications of 0.3% CaCl₂ + 0.3% MgCl₂, with water spraying as the control. The dynamic changes in peel h values and soluble sugar and monosaccharides, water-soluble calcium (Ca²⁺) and magnesium (Mg²⁺), plant hormones, and the concentration of CDPKs in the pulp were compared throughout fruit development. Key differentially expressed members of the CDPK gene family were screened through real-time quantitative PCR analysis. The results showed that the peel color transition occurred earlier in the control (CK) than in the treatment (T), but the coloration process accelerated in the treated fruit, leading to no significant difference in peel h values between the groups at 76 days after anthesis (DAA), when both reached the lowest levels. The total of soluble sugar in the pulp peaked at 70 DAA in both groups, but while the CK exhibited a significant decline thereafter, T maintained stable sugar levels, thereby mitigating the “sugar receding” phenomenon. Water-soluble calcium and water magnesium levels were significantly higher in the T at 42 and 63 DAA, with water calcium remaining significantly higher at 70 DAA. Furthermore, sucrose, glucose, fructose, abscisic acid (ABA) contents, and CDPK concentration were significantly higher in the T at 70 and 76 DAA. The CDPK gene family members LcCDPK1, LcCDPK2, LcCDPK3, LcCDPK4, LcCDPK5, LcCDPK9, LcCDPK15, and LcCDPK17 were upregulated in response to T. Among them, LcCDPK1, LcCDPK4, LcCDPK5, LcCDPK9, and LcCDPK17 were identified as key structural genes due to their significant correlation with soluble sugar content and CDPK concentration, as well as their differential expression between T and CK. In conclusion, foliar calcium–magnesium nutrient treatment upregulates the expression of these five CDPK gene family members by increasing the ABA levels in the pulp, leading to more CDPK accumulation. This accumulation inhibits sugar conversion and promotes sucrose and fructose accumulation, thereby mitigating the “sugar receding” phenomenon in ‘Feizixiao’ litchi pulp. Full article

To address uneven airflow distribution and pesticide deposition coverage in orchard pesticide application, we developed a double-flexible duct spraying device. Utilizing FLUENT 2022 software for airflow field simulation, we analyzed various structural parameters to identify optimal configurations for the air duct type, diameter, and nozzle outlet diameter. The results indicated that the nozzle outlet diameter most significantly influences wind field uniformity, followed by the air duct diameter and type. The optimal settings were identified as follows: C-Type air duct, 100 mm duct diameter, and 50 mm nozzle outlet diameter. Validation tests confirmed these settings, with simulated and actual wind speed measurements, showing no more than a 10% relative error, affirming the simulation’s accuracy. Field tests demonstrated an average droplet density of 35.38 droplets/cm² within tree canopies, indicating strong penetration ability. Droplet distribution followed a lower > middle > upper pattern in the canopy’s vertical direction, fulfilling technical requirements for high spindle-shaped fruit trees and providing a foundation for achieving a uniform canopy coverage. Full article

Chile contributes 4% of global hazelnut (Corylus avellana L.) production, mainly developed in temperate regions with high autumn rainfall and humidity during harvest, which can compromise nut quality and increase postharvest losses. Thus, synchronizing harvests has become a critical aspect for growers in the southern region of Chile. This study focused on the effects of ethephon (ETH) spraying on trees to optimize nut drop timing and assess its impact on yield optimization and its influence on vegetative growth and inflorescence activity. From the 2020/2021 to the 2022/2023 seasons, experiments were conducted on a commercial hazelnut orchard of Tonda di Giffoni (TDG) planted in southern Chile. Four ETH (0, 250, 500, 1000 mg L⁻¹) treatments were sprayed 15 days preharvest and denoted as ETHA (sprayed 2020/2021) and ETHB (sprayed twice, in 2020/2021 and 2021/2022). Nut drop synchronization was periodically monitored at 7, 15, 21, 28, and 35 days after application (DAA), along with industrial quality parameters (nut weight, kernel yield) and inflorescence activity. In the first season, ETH significantly synchronized nut drops, achieving optimal results at 15–28 DAA with ETH 250 and 500, while ETH 1000 induced earlier drops but reduced yields. Total nut yield varied among seasons and demonstrated consistent performance of ETH 250, identified as the most efficient treatment for balancing nut drop timing. Industrial parameters showed seasonal differences but no adverse effects on nut quality. Conversely, the inflorescence activity remained unaffected by ETH concentrations. ETHA and ETHB treatments influenced tree shoot length variably across three seasons, showing significant concentration and seasonal interaction effects. These results demonstrate that ETH effectively synchronizes hazelnut harvests under temperate conditions, reducing post-harvest losses and optimizing logistics without compromising yield or quality. Full article

This study focused on addressing the issue of delayed root system development in mulberry trees during aerosol cultivation, which is attributed to the asynchronous growth of branches and buds. To tackle this challenge, we propose an intelligent foliar fertilizer spraying system based on deep learning. The system incorporates a parallel robotic arm spraying device and employs trinocular vision to capture image datasets of mulberry tree branches. After comparing YOLOv8n with other YOLO versions, we made several enhancements to the YOLOv8n model. These improvements included the introduction of the Asymptotic Feature Pyramid Network (AFPN), the optimization of feature extraction using the MSBlock module, the adoption of a dynamic ATSS label assignment strategy, and the replacement of the CIoU loss function with the Focal_XIoU loss function. Furthermore, an artificial neural network was utilized to calculate the coordinates of the robotic arm. The experimental results demonstrate that the enhanced YOLOv8n model achieved an average precision of 94.48%, representing a 6.05% improvement over the original model. Additionally, the prediction error for the robotic arm coordinates was maintained at ≤1.3%. This system effectively enables the precise location and directional fertilization of mulberry branches exhibiting lagging growth, thereby significantly promoting the synchronous development of mulberry seedlings. Full article

Efficient pest control in orchards is crucial for preserving crop quality and maximizing yield. A key factor in optimizing automated variable-rate spraying is accurate tree canopy size estimation, which helps reduce pesticide overuse while minimizing environmental and health risks. This study evaluates the performance of two advanced convolutional neural networks, PP-LiteSeg and fully convolutional networks (FCNs), for segmenting tree canopies of varying sizes—small, medium, and large—using short-term dense-connection networks (STDC1 and STDC2) as backbones. A dataset of 305 field-collected images was used for model training and evaluation. The results show that FCNs with STDC backbones outperform PP-LiteSeg, delivering superior semantic segmentation accuracy and background classification. The STDC1-based model excels in precision variable-rate spraying, achieving an Intersection-over-Union of up to 0.75, Recall of 0.85, and Precision of approximately 0.85. Meanwhile, the STDC2-based model demonstrates greater optimization stability and faster convergence, making it more suitable for resource-constrained environments. Notably, the STDC2-based model significantly enhances canopy-background differentiation, achieving a background classification Recall of 0.9942. In contrast, PP-LiteSeg struggles with small canopy detection, leading to reduced segmentation accuracy. These findings highlight the potential of FCNs with STDC backbones for automated apple tree canopy recognition, advancing precision agriculture and promoting sustainable pesticide application through improved variable-rate spraying strategies. Full article

The spraying time of nitrogen fertilizer is a key factor to consider when fertilizing with an intelligent micro-sprinkler irrigation system. This study aims to investigate the impact of nitrogen fertilizer spraying time on the seed oil quality of tree peony, with the expectation of providing theoretical support for the application of intelligent micro-sprinkler irrigation systems in the production of tree peony. In 2022 and 2023, foliar nitrogen application was conducted on Paeonia ostii ‘Fengdan’ utilizing an intelligent micro-spray irrigation system, with four distinct nitrogen fertilizer spraying times (3:00–4:00, 7:00–8:00, 14:00–15:00, and 19:00–20:00). Based on this, the study assessed nitrogen metabolism indicators in leaves and seeds at various growth stages and the fatty acid composition of seed oil in Paeonia ostii ‘Fengdan’. The results revealed that foliar nitrogen application between 14:00 and 15:00 significantly enhanced the levels of free amino acids (FAA), nitrate reductase (NR), glutamine synthetase (GS), and glutamate synthase (GOGAT) activity in both leaves and seeds. Furthermore, the ratio of α-linolenic acid in the seed oil was significantly increased. Correlation analysis demonstrated a positive or highly significant positive correlation between the levels of nitrogen metabolism indicators and the ratio of unsaturated fatty acids. In conclusion, foliar nitrogen application between 14:00 and 15:00 significantly enhances the FAA content and the activity of nitrogen metabolism enzymes within the leaves and seeds and promotes the synthesis of unsaturated fatty acids in seed oil. This study contributes to the efficient and high-quality cultivation of tree peony. Full article