Shanjun Li

Design of the filling device for citrus seedling pot based on turnover box

An automatic feeding device for substrate filling was designed to address the challenges of difficult feeding and low efficiency in the citrus seedling pot filling and transferring machine. The device comprises a framework, tracks, overturning frame, drive system, etc. In order to ensure optimal performance, the frame’s turning angle was set at a minimum of 110° and the angle between the frame’s horizontal plane and slope was determined to be 120°. Following optimization, the number and intensity of sudden changes in velocity, angular velocity, and thrust were reduced, thereby prolonging the device’s service life. The prototype test demonstrated that the device has an average feeding time of 9.86 s, is capable of raising 0.14 m³ of substrate in a single cycle, and has a handcart turning angle of 111°. Furthermore, no residual substrate remained in the handcart, and the handcart fixing mechanism operated correctly. The torque measurement results of the motor output shaft were found to be consistent with the simulation results in ADAMS, with a maximum force difference of only 298 N. The simulation was found to be accurate, with an error rate of only 3.67%. This model can be utilized as a dependable reference for the optimization of the design of the automatic feeding device.

In order to address the problem of citrus seedling pot filling and transporting which is time-consuming and labor-intensive in China, a scheme for seedling pot filling and placing was proposed, and a self-propelled citrus seedling pot filling and placing machine was designed which can fill and place 48 pots at one time. Firstly, the rotary hopper door mechanism was designed, the movement of the hopper door was analyzed, and the connection between the opening size and the movement time of the hopper door was determined. Then, the transmission system of the machine was designed, the power consumption of the hopper movement and substrate stirring were calculated, and the power requirement of the transmission system was determined. The lifting structure of the seedling pots frame was analyzed, the size of the flipping structure of the cover plate was calculated, and the seedling pots frame was designed. After that, the substrate flow rate curve was measured through the substrate flow rate experiments, and the hopper-controlled movement speed was calculated. Furthermore, the experimental prototype was manufactured and tested. The test results indicate that the filling number of pots was 48 one time, the filling time was 30 s, and the seedling pots were fully filled and placed in order. The average filling mass of the seedling pots was 2.23 kg, and the average mass variation coefficient was 2.7%. The substrate mass which is scraped out is 0.81 kg, accounting for 0.76% of the total filling mass at one time. This designed machine had a reasonable structure and high filling efficiency. The reseach can provide a reference for the development and optimization of the citrus seedling pots filling and transporting machine. Keywords: agricultural machinery, design, experiments, fillingmachine, placing machine DOI: 10.25165/j.ijabe.20231601.7817 Citation: Xu Q C, Li S J, Zhang J, Zhu J T, Pan H B. Design and test of self-propelled citrus seedling pots filling and placing machine. Int J Agric & Biol Eng, 2023; 16(1): 104–110.

In Southeast Asia, many varieties of citrus are grown in hilly areas. Compared with plain orchards, it is difficult for large spraying equipment to move in hilly orchards. Small spraying equipment can enter hilly orchards, but their spraying power cannot make droplets penetrate into the canopy, resulting in low deposition rates within the canopy. As a kind of unstructured narrow space, the branches within the canopy are interlaced, thus a flexible manipulator that can move within the canopy is required. In this paper, a novel remote-controlled, cable-driven target spray robot (CDTSR) was designed to achieve a precise spray within the canopy. It consisted of a small tracked vehicle, a cable-driven flexible manipulator (CDFM), and a spray system. The CDFM had six degrees of freedom driven by a cable tendon. The forward and inverse kinematics model of the CDFM were established and then the semispherical workspace was calculated. Furthermore, while considering precise control requirements, the dynamics equations were derived. The experimental results demonstrated that the CFDM could move dexterously within the canopy with interlacing branches to reach pests and diseases areas in the canopy. The entire operation took 3.5 s. This study solved the problem of a low spray deposition rate within a canopy and has potential applications in agricultural plant protection.

The wear failure of traction wheels in orchard transport severely restricts the stability of orchard conveyors and impedes the mechanization of orchard work. In this study, the thermal-diffusion chromizing method was employed to increase the hardness of a traction wheel for the enhancement of wear resistance. The results show that a uniform and dense chrome coating with a thickness of 16 μm was formed on the surface. The coating was revealed to have a hardness of 1752.7 HV and benefited from the formation of Cr-C compounds. A friction test and a wear simulation test under both dry-friction and lubrication conditions were conducted to assess the enhanced wear resistance based on the friction coefficient and wear loss. The friction coefficient of QT400 and that of the chrome coating were 0.37 and 0.36, respectively, under dry conditions. Additionally, the friction coefficient of QT400 decreased to 0.12, while that of the chrome coating remained at 0.35, under lubrication conditions. In the wear simulation test, the wear loss of the chromed traction wheel was about 1/28 of that of the QT400 traction wheel under dry-friction conditions. In addition, the wear loss of the chromed traction wheel was about 1/24 of that of the QT400 traction wheel under lubrication conditions. Moreover, the wear mechanism was analyzed with a microstructure study and finite element analysis (FEA). The synergetic effect between fatigue wear and abrasive wear was likely responsible for the wear failure of the traction wheel. The method proposed in this study may be a promising way to enhance the wear resistance of QT400 traction wheels through the application of a chrome coating without sacrificing the loading capacity, and this work contributes to the understanding of the wear failure mechanism of traction wheels.

How to non-destructively and quickly estimate the storage time of citrus fruit is necessary and urgent for freshness control in the fruit market. As a feasibility study, we present a non-destructive method for storage time prediction of Newhall navel oranges by investigating the characteristics of the rind oil glands in this paper. Through the observation using a digital microscope, the oil glands were divided into three types and the change of their proportions could indicate the rind status as well as the storage time. Images of the rind of the oranges were taken in intervals of 10 days for 40 days, and they were used to train and test the proposed prediction models based on K-Nearest Neighbors (KNN) and deep learning algorithms, respectively. The KNN-based model demonstrated explicit features for storage time prediction based on the gland characteristics and reached a high accuracy of 93.0%, and the deep learning-based model attained an even higher accuracy of 96.0% due to its strong adaptability and robustness. The workflow presented can be readily replicated to develop non-destructive methods to predict the storage time of other types of citrus fruit with similar oil gland characteristics in different storage conditions featuring high efficiency and accuracy.

The abrasion failure is the key factor for prolonging the service life and energy saving of furrow openers. The hardness enhancement was reported to be an effective strategy to increase the wear resistance against the soil abrasion. D517 coatings were deposited on Q235 steel by electric spark to improve the wear-resistant property with an affordable cost for farmers. The wear behavior of the coatings was characterized in a pin on disk friction equipment and a homemade soil abrasion simulation system. The soil adhesion, which is highly related to energy consumption, was also evaluated. Results showed that D517 coatings revealed dendrite structure with some randomly distributed carbides. The electric current exerted a great influence on the microstructure, hardness, friction coefficient, and soil wear rate. The wear rate of samples deposited with 80 A and 90 A reduced to 79% and 84%, respectively, as compared with the normalized heat-treated 65 Mn steel after 6 h in soil. This work provides a promising solution to increase the wear resistance of furrow openers. It needs to be noted that the coating would increase the soil adhesion of the opener, which needs to be further explored to decrease the energy consumption.

Defective citrus fruits are manually sorted at the moment, which is a time-consuming and cost-expensive process with unsatisfactory accuracy. In this paper, we introduce a deep learning-based vision system implemented on a citrus processing line for fast on-line sorting. For the citrus fruits rotating randomly on the conveyor, a convolutional neural network-based detector was developed to detect and temporarily classify the defective ones, and a SORT algorithm-based tracker was adopted to record the classification information along their paths. The true categories of the citrus fruits were identified through the tracked historical information, resulting in high detection precision of 93.6%. Moreover, the linear Kalman filter model was applied to predict the future path of the fruits, which can be used to guide the robot arms to pick out the defective ones. Ultimately, this research presents a practical solution to realize on-line citrus sorting featuring low costs, high efficiency, and accuracy.