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Agriculture
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Agricultural Machinery and Technology for Fruit Tree Management
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Agricultural Machinery and Technology for Fruit Tree Management

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Technology".

Deadline for manuscript submissions: closed (25 June 2024) | Viewed by 11006

Special Issue Editors

Prof. Dr. Zhen Li

E-Mail Website
Guest Editor
College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, China
Interests: intelligent orchard machinery; mountainous orchard management; plant protection machinery; Internet of Things; fruit tree modern cultivation techniques
Prof. Dr. Tao Wen

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha 410004, China
Interests: E-nose; spectral detection; sensors and intelligent detection technology; postharvest technology and equipment; orchard machinery
Dr. Shilei Lyu

E-Mail Website
Guest Editor
College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, China
Interests: orchard transport; smart orchard; intelligent computing; agricultural Internet of Things; computer vision

Special Issue Information

Dear Colleagues,

Fruits represent a vital dietary component due to their abundant nutrient elements, thereby serving as a crucial factor for human well-being and demonstrating notable economic significance. The global production of fruits has been steadily escalating, while simultaneously confronting mounting challenges such as labor scarcity and escalating production costs. Consequently, the mechanization of fruit tree management assumes an increasingly pivotal role. Given the geographical diversity of fruit species and the intricate and distinctive nature of fruit orchard management, numerous scholars worldwide have undertaken extensive and profound investigations. This collective scholarly effort has culminated in the development of a diverse array of machinery and equipment for fruit production, furnishing a wealth of effective solutions to mechanizing fruit tree management.

This Special Issue encompasses a topic of utmost relevance, namely, the trend towards standardized smart orchard construction. Its primary focus lies in elucidating the critical facets of fruit tree management, including transportation, weeding, pruning, flower thinning, plant protection, and harvesting. The Issue serves as a platform for sharing the latest advancements in intelligent machinery and technological research, thereby facilitating the exploration of efficacious strategies to enhance the overall management proficiency of fruit trees and orchards. For this reason, it welcomes highly interdisciplinary quality studies from disparate research fields including overall machine design, key components and parts, mechanism and simulation analysis, intelligent technology, and other related fields. We welcome the submission of original research articles and reviews.

Prof. Dr. Zhen Li
Prof. Dr. Tao Wen
Dr. Shilei Lyu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • agricultural machinery
  • information technology
  • standardized orchard
  • intelligent orchard
  • transportation machinery
  • thinning machinery
  • weeding machinery
  • plant protection machinery
  • harvesting machinery
  • orchard irrigation
  • insect information
  • growth information

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Published Papers (7 papers)

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Research

19 pages, 13127 KiB  
Article
Optimization of the Camellia oleifera Fruit Harvester Engine Compartment Heat Dissipation Based on Temperature Experiments and Airflow Field Simulation
by Wenfu Tong, Kai Liao, Lijun Li, Zicheng Gao, Fei Chen and Hong Luo
Agriculture 2024, 14(9), 1640; https://doi.org/10.3390/agriculture14091640 - 19 Sep 2024
Viewed by 619
Abstract
The Camellia oleifera fruit harvester, a specialized agricultural device, is engineered for efficient operation within the densely planted C. oleifera groves of China’s undulating terrains. Its design features a notably small footprint to navigate the constrained spaces between trees. With the enhancement of [...] Read more.
The Camellia oleifera fruit harvester, a specialized agricultural device, is engineered for efficient operation within the densely planted C. oleifera groves of China’s undulating terrains. Its design features a notably small footprint to navigate the constrained spaces between trees. With the enhancement of the functionality and power of the harvester, the engine compartment becomes even more congested. This, while beneficial for performance, complicates heat dissipation and reduces harvesting efficiency. In this study, experiments were initially conducted to collect temperature data from the main heat-generating components and parts susceptible to high temperatures within the harvester’s engine compartment. Subsequently, a 3D model was developed for numerical simulations, leading to the proposal of optimization schemes for the engine compartment’s structure and the validation of these schemes’ feasibility. A comparison of the experimental data, both before and after optimization, revealed a significant reduction in the surface temperatures of components within the engine compartment following optimization. As a result, the heat dissipation of the engine compartment has been greatly optimized. The harvester has demonstrated prolonged normal operation, enhancing the reliability and economy of the harvester. Full article
(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Tree Management)
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20 pages, 9123 KiB  
Article
Design and Experimental Study of Banana Bunch Transportation Device with Lifting Mechanism and Automatic Bottom-Fixing Fruit Shaft
by Weiqin Li, Zhou Yang, Xing Xu, Weixi Li, Xingkang Mo, Jiaxiang Yu and Jieli Duan
Agriculture 2024, 14(7), 1161; https://doi.org/10.3390/agriculture14071161 - 16 Jul 2024
Viewed by 979
Abstract
In addressing the challenges of high labor intensity, cost, and potential mechanical damage to banana fruit in orchards, this study presents the design of a banana bunch transport device featuring a lifting mechanism and an automatic fruit shaft bottom-fixing system. The device is [...] Read more.
In addressing the challenges of high labor intensity, cost, and potential mechanical damage to banana fruit in orchards, this study presents the design of a banana bunch transport device featuring a lifting mechanism and an automatic fruit shaft bottom-fixing system. The device is tailored to the planting and morphological characteristics of banana bunches, aiming for efficient, low-loss, and labor-saving mechanized transport. Key design considerations included the anti-overturning mechanism and the lifting system based on transportation conditions and the physical dimensions of banana bunches. A dynamic simulation was conducted to analyze the angular velocity and acceleration during the initial conveying stages, forming the basis for the fruit shaft bottom-fixation mechanism. A novel horizontal multi-point scanning method was developed to accurately identify and secure the fruit shaft bottom, complemented by an automated control system. Experimental results showed a 95.83% success rate in identification and fixation, validated by field trials that confirmed the necessity and stability of the fixation mechanism. To enhance the durability of the fruit shaft bottom-fixation mechanism, a multi-factor test was conducted, optimizing the device’s maximum travel speed and minimizing the banana bunch’s oscillation angle. Field tests showed an oscillation angle of 8.961°, closely matching the simulated result of 9.526°, demonstrating the reliability of the response surface analysis model. This study offers a practical and efficient solution for banana bunch transport in orchards, showcasing significant practical value and potential for wider adoption. Full article
(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Tree Management)
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23 pages, 5237 KiB  
Article
Design of Adaptive Grippers for Fruit-Picking Robots Considering Contact Behavior
by Bowei Xie, Mohui Jin, Jieli Duan, Zewei Li, Weisheng Wang, Mingyu Qu and Zhou Yang
Agriculture 2024, 14(7), 1082; https://doi.org/10.3390/agriculture14071082 - 5 Jul 2024
Viewed by 2078
Abstract
Adaptability to unstructured objects and the avoidance of target damage are critical challenges for flexible grippers in fruit-picking robots. Most existing flexible grippers have many problems in terms of control complexity, stability and cost. This paper proposes a flexible finger design method that [...] Read more.
Adaptability to unstructured objects and the avoidance of target damage are critical challenges for flexible grippers in fruit-picking robots. Most existing flexible grippers have many problems in terms of control complexity, stability and cost. This paper proposes a flexible finger design method that considers contact behavior. The new approach incorporates topological design of contact targets and introduces contact stress constraints to directly obtain a flexible finger structure with low contact stress and good adaptability. The study explores the effects of design parameters, including virtual spring stiffness, volume fraction, design domain size, and discretization, on the outcomes of the flexible finger topology optimization. Two flexible finger structures were selected for comparative analysis. The experimental results verified the effectiveness of the design method and the maximum contact stress was reduced by about 70%. An adaptive two-finger gripper was developed. This design allows the gripper to achieve damage-free grasping without additional sensors and control systems. The adaptive and contact performances of the grippers with different driving modes were analyzed. Practical grasping tests were also performed, including evaluation of adaptive performance, stability, and maximum grasping weight. The results indicate that gripper 2 with flexible finger 2 excelled in contact stress and adaptive wrapping, making it well-suited for grasping unstructured and fragile objects. This paper provides valuable insights for the design and application of flexible grippers for picking robots, offering a promising solution to enhance adaptability while minimizing target damage. Full article
(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Tree Management)
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15 pages, 9695 KiB  
Article
A Lightweight Algorithm for Recognizing Pear Leaf Diseases in Natural Scenes Based on an Improved YOLOv5 Deep Learning Model
by Jianian Li, Zhengquan Liu and Dejin Wang
Agriculture 2024, 14(2), 273; https://doi.org/10.3390/agriculture14020273 - 7 Feb 2024
Cited by 2 | Viewed by 1321
Abstract
The precise detection of diseases is crucial for the effective treatment of pear trees and to improve their fruit yield and quality. Currently, recognizing plant diseases in complex backgrounds remains a significant challenge. Therefore, a lightweight CCG-YOLOv5n model was designed to efficiently recognize [...] Read more.
The precise detection of diseases is crucial for the effective treatment of pear trees and to improve their fruit yield and quality. Currently, recognizing plant diseases in complex backgrounds remains a significant challenge. Therefore, a lightweight CCG-YOLOv5n model was designed to efficiently recognize pear leaf diseases in complex backgrounds. The CCG-YOLOv5n model integrates a CA attention mechanism, CARAFE up-sampling operator, and GSConv into YOLOv5n. It was trained and validated using a self-constructed dataset of pear leaf diseases. The model size and FLOPs are only 3.49 M and 3.8 G, respectively. The [email protected] is 92.4%, and the FPS is up to 129. Compared to other lightweight indicates that the models, the experimental results demonstrate that the CCG-YOLOv5n achieves higher average detection accuracy and faster detection speed with a smaller computation and model size. In addition, the robustness comparison test CCG-YOLOv5n model has strong robustness under various lighting and weather conditions, including frontlight, backlight, sidelight, tree shade, and rain. This study proposed a CCG-YOLOv5n model for accurately detecting pear leaf diseases in complex backgrounds. The model is suitable for use on mobile terminals or devices. Full article
(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Tree Management)
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21 pages, 4219 KiB  
Article
Optimization and Experimental Study of Structural Parameters for a Low-Damage Packing Device on an Apple Harvesting Platform
by Zixu Chen, Hongjian Zhang, Huawei Yang, Yinfa Yan, Jingwei Sun, Guangze Zhao, Jinxing Wang and Guoqiang Fan
Agriculture 2023, 13(9), 1653; https://doi.org/10.3390/agriculture13091653 - 22 Aug 2023
Viewed by 1364
Abstract
To address the issues of low efficiency and high damage rates during apple harvesting and packing, a parameter optimization experiment was conducted on a low-damage packing device for an apple harvesting platform based on Adams 2019 software. The aim was to reduce the [...] Read more.
To address the issues of low efficiency and high damage rates during apple harvesting and packing, a parameter optimization experiment was conducted on a low-damage packing device for an apple harvesting platform based on Adams 2019 software. The aim was to reduce the mechanical damage to apples during the packing process. Firstly, kinematics and energetics analyses of the apple packing process were performed, and a mathematical model for damage energy was established to identify the main factors and their ranges that influence the mechanical damage to apples. Secondly, using the fruit damage rate and packing efficiency as the evaluation criteria, a second-order orthogonal rotating regression experiment was conducted with the inclination angle of the fruit conveying tube, the inner wall radius of the fruit conveying tube, and the length of the fruit conveying tube as the experimental factors. Regression mathematical models were established to assess the relationship between the evaluation criteria and the experimental factors. Finally, the impact of each experimental factor on the evaluation criteria was analyzed to determine the optimal structural parameters for the low-damage packing device of the apple harvesting platform, and validation experiments were conducted. The results showed that when the inclination angle of the fruit conveying tube was 47°, the inner wall radius of the fruit conveying tube was 84 mm and the length of the fruit conveying tube was 0.12 m, the average fruit damage rate was minimized at 7.2%, and the average packing efficiency was maximized at 1925 kg/h. These results meet the requirements for apple harvesting operations, and the research findings can serve as a reference for the structural design and packing operation parameter optimization of apple harvesting platforms. Full article
(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Tree Management)
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18 pages, 4954 KiB  
Article
Detection and Classification of Citrus Fruit Infestation by Bactrocera dorsalis (Hendel) Using a Multi-Path Vis/NIR Spectroscopy System
by Dapeng Li, Jiang Long, Ziye Tang, Longbo Han, Zhongliang Gong, Liang Wen, Hailong Peng and Tao Wen
Agriculture 2023, 13(8), 1642; https://doi.org/10.3390/agriculture13081642 - 21 Aug 2023
Cited by 1 | Viewed by 1755
Abstract
In this study, a multi-path Vis/NIR spectroscopy system was developed to detect the presence of Bactrocera dorsalis (Hendel) infestations of citrus fruit. Spectra were acquired for 252 citrus fruit, 126 of which were infested. Two hundred and fifty-two spectra were acquired for modeling [...] Read more.
In this study, a multi-path Vis/NIR spectroscopy system was developed to detect the presence of Bactrocera dorsalis (Hendel) infestations of citrus fruit. Spectra were acquired for 252 citrus fruit, 126 of which were infested. Two hundred and fifty-two spectra were acquired for modeling in their un-infested stage, slightly infested stage, and seriously infested stage. The location of the infestation is unclear, and considering the impact of the light path on the location of the infestation, each citrus fruit was tested in three orientations (i.e., fruit stalks facing upward (A), fruit stalks facing horizontally (B), and fruit stalks facing downward (C)). Classification models based on joint X-Y distance, multiple transmittance calibration, competitive adaptive reweighted sampling, and partial least squares discriminant analysis (SPXY-MSC-CARS-PLS-DA) were developed on the spectra of each light path, and the average spectra of the four light paths was calculated, to compare their performance in infestation classification. The results show the classification result changed with the light path and fruit orientation. The average spectra for each fruit orientation consistently gave better classification results, with overall accuracies of 92.9%, 89.3%, and 90.5% for orientations A, B, and C, respectively. Moreover, the best model had a Kappa value of 0.89, and gave 95.2%, 80.1%, and 100.0% accuracy for un-infested, slightly infested, and seriously infested citrus fruit. Furthermore, the classification results for infested citrus fruits were better when using the average spectra than using the spectrum of each single light path. Therefore, the multi-path Vis/NIR spectroscopy system is conducive to the detection of B. dorsalis infestation in citrus fruits. Full article
(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Tree Management)
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13 pages, 2263 KiB  
Article
Parameters Optimization and Performance Evaluation Model of Air-Assisted Electrostatic Sprayer for Citrus Orchards
by Xiuyun Xue, Kaixiang Zeng, Nengchao Li, Qin Luo, Yihang Ji, Zhen Li, Shilei Lyu and Shuran Song
Agriculture 2023, 13(8), 1498; https://doi.org/10.3390/agriculture13081498 - 27 Jul 2023
Cited by 1 | Viewed by 1512
Abstract
Citrus orchards in Southeast Asia are commonly grown in hilly areas, where the terrain is unsuitable for the operation of crop protection machinery. Conventional spraying equipment used in hilly orchards have a poor deposition effect. In this paper, a new air-assisted electrostatic sprayer [...] Read more.
Citrus orchards in Southeast Asia are commonly grown in hilly areas, where the terrain is unsuitable for the operation of crop protection machinery. Conventional spraying equipment used in hilly orchards have a poor deposition effect. In this paper, a new air-assisted electrostatic sprayer was designed for hilly citrus orchards. The orthogonal method was conducted to determine the optimal spray parameters of the sprayer. To evaluate the spray performance of the optimized air-assisted electrostatic sprayer, field tests were carried out on a citrus orchard with various cultivation patterns. Based on the data of the field tests, a comprehensive evaluation model was constructed to quantitatively analyze the performance of the sprayer. Results indicate that the optimal parameters are a spray pressure of 0.5 MPa, applied voltage of 9 kV and air flow velocity of 10 m/s. The optimized air-assisted electrostatic sprayer has the best performance in the citrus under dense fence cultivation pattern, followed by dense dwarf cultivation pattern. Comparing to the other sprayers tested, the air-assisted electrostatic sprayer greatly improves the spray coverage on the leaf surfaces (abaxial and adaxial) under various cultivation patterns. Full article
(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Tree Management)
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