Continuous production machine for separating and shaping Taiping Houkui tea.

In response to the challenges of low automation and a lack of a continuous processing system for Taiping Houkui tea, this study proposed a design scheme for a continuous processing line and built a continuous processing prototype for testing by combining the production requirements of Taiping Houkui tea, the characteristics of withered leaves, and the existing relevant production equipment. First, the physical properties of Taiping Houkui tea were determined. A simulation was performed using the Hertz-Mindlin model, and the motion states of the tea leaves were obtained under different conditions to define the parameter design range of the experimental platform and verify its structural rationality. Then, the response surface methodology was used to optimize the working parameter ranges and obtain the best working parameters for the feeding and kneading mechanisms. Finally, a continuous production prototype was constructed for further production verification. The experimental results show that the success rate of continuous production on this platform was 70.68%, with an average output of approximately 0.4 kg/h for Taiping Houkui dry tea on a single slide track, and the produced tea was similar to manually made tea. This demonstrates that the continuous production technique has high feasibility and provides a reference for continuous production of Taiping Houkui tea.

Continuous identification of the tea shoot tip and accurate positioning of picking points for a harvesting from standard plantations.

To address the current problems of large positioning error, low picking efficiency, and high cost of tea shoot picking, a continuous and precise harvesting scheme for tea shoots based on a two-dimensional (2D) perspective is designed in this study. A high-speed harvesting method for tea shoots in a standardized tea plantation assembly line type was proposed. First, a 2D view recognition model of tea shoot tips in a multi-disturbance environment was constructed, and accurate picking point coordinates were determined by combining a skeleton algorithm and curve growth. To avoid the losses of recognition accuracy caused by the mistaken clamping of blades and vibrations during harvester operations, accurate control of the harvester was realized by combining path planning and the S-curve speed control function. The recognition accuracy for the verification set of the recognition model was 99.9%, and the mean average precision (0.5:0.95) value was 0.97. The test results show that the error between the actual picking point position and the position determined by the model was within ± 3 mm, and the picking success rate was 83.6%. Therefore, we can realize fast and accurate picking of tea shoots and lay the foundation for continuous tea picking in the future by simplifying the identification and picking process.

Design and operation of a Peucedani Radix weeding device based on YOLOV5 and a parallel manipulator.

To avoid excessive use of herbicides in the weeding operations of Peucedani Radix, a common Chinese herb, a precision seedling avoidance and weeding agricultural robot was designed for the targeted spraying of herbicides. The robot uses YOLOV5 combined with ExG feature segmentation to detect Peucedani Radix and weeds and obtain their corresponding morphological centers. Optimal seedling avoidance and precise herbicide spraying trajectories are generated using a PSO-Bezier algorithm based on the morphological characteristics of Peucedani Radix. Seedling avoidance trajectories and spraying operations are executed using a parallel manipulator with spraying devices. The validation experiments showed that the precision and recall of Peucedani Radix detection were 98.7% and 88.2%, respectively, and the weed segmentation rate could reach 95% when the minimum connected domain was 50. In the actual Peucedani Radix field spraying operation, the success rate of field precision seedling avoidance herbicide spraying was 80.5%, the collision rate between the end actuator of the parallel manipulator and Peucedani Radix was 4%, and the average running time of the parallel manipulator for precision herbicide spraying on a single weed was 2 s. This study can enrich the theoretical basis of targeted weed control and provide reference for similar studies.

Design and Experiment of Online Detection System for Water Content of Fresh Tea Leaves after Harvesting Based on Near Infra-Red Spectroscopy.

Fresh tea leaves continuously lose water after harvesting, and the level of water content directly affects the configuration of tea processing parameters. To address this problem, this study established an online detection system for the water content of fresh tea leaves after harvesting based on near-infrared spectroscopy. The online acquisition and analysis system of the temperature and humidity sensor signal data was developed based on LabVIEW and Python software platforms. Near-infrared spectral data, environmental temperature, and humidity were collected from fresh leaves after harvesting. Spectral data were combined with PLS (partial least squares) to develop a prediction model for the water content of fresh tea leaves. Simultaneously, data communication between LabVIEW and PLC was established, laying the foundation for establishing a feedback mechanism to send the prediction results to the main platform of the lower computer. This provides a more objective and accurate basis for the detection of fresh leaves before processing and regulation during processing, thereby effectively promoting the standardisation and intelligent development of tea-processing equipment.

Detection Method for Walnut Shell-Kernel Separation Accuracy Based on Near-Infrared Spectroscopy.

In this study, Near-infrared (NIR) spectroscopy was adopted for the collection of 1200 spectra of three types of walnut materials after breaking the shells. A detection model of the walnut shell-kernel separation accuracy was established. The preprocessing method of de-trending (DT) was adopted. A classification model based on a support vector machine (SVM) and an extreme learning machine (ELM) was established with the principal component factor as the input variable. The effect of the penalty value (C) and kernel width (g) on the SVM model was discussed. The selection criteria of the number of hidden layer nodes (L) in the ELM model were studied, and a genetic algorithm (GA) was used to optimize the input layer weight (W) and the hidden layer threshold value (B) of the ELM. The results revealed that the classification accuracy of SVM and ELM models for the shell, kernel, and chimera was 97.78% and 97.11%. The proposed method can serve as a reference for the detection of walnut shell-kernel separation accuracy.

Optimization of Roasted Green Tea Winnowing via Fluid-Solid Interaction Experiments and Simulations.

In the tea industry, achieving a high winnowing accuracy to produce high-quality tea is a complex challenge. The complex shape of the tea leaves and the uncertainty of the flow field lead to the difficulty in determining the wind selection parameters. The purpose of this paper was to determine the accurate wind selection parameters of tea through simulation and improve the precision of tea wind selection. This study used three-dimensional modeling to establish a high-precision simulation of dry tea sorting. The simulation environment of the tea material, flow field, and wind field wall were defined using a fluid-solid interaction method. The validity of the simulation was verified via experiments. The actual test found that the velocity and trajectory of tea particles in the actual and simulated environments were consistent. The numerical simulations identified wind speed, wind speed distribution, and wind direction as the main factors affecting the winnowing efficacy. The weight-to-area ratio was used to define the characteristics of different types of tea materials. The indices of discrete degree, drift limiting velocity, stratification height, and drag force were employed to evaluate the winnowing results. The separation of tea leaves and stems is best in the range of the wind angle of 5-25 degrees under the same wind speed. Orthogonal and single-factor experiments were conducted to analyze the influence of wind speed, wind speed distribution, and wind direction on wind sorting. The results of these experiments identified the optimal wind-sorting parameters: a wind speed of 12 m s-1, wind speed distribution of 45%, and wind direction angle of 10°. The larger the difference between the weight-to-area ratios of the tea leaves and stems, the more optimized the wind sorting. The proposed model provides a theoretical basis for the design of wind-based tea-sorting structures.

Yupingfeng polysaccharides enhances growth performance in Qingyuan partridge chicken by up-regulating the mRNA expression of SGLT1, GLUT2 and GLUT5.

The ban on the use of antibiotic in feed encouraged nutritionists to using alternatives to maintain growth performance and intestinal function of broilers. This study was conducted to evaluate the effects of Yupingfeng polysaccharides (YP) supplementation on growth performance and expression of SGLT1, GLUT2 and GLUT5 in Qingyuan partridge chicken. Experiment 1: a total of 540 chickens were randomly allocated to five groups with six replication. Dietary treatments were: (1) CON (control group), basal diet; (2) T1, CON + 0.5 g kg-1 YP; (3) T2, CON + 1 g kg-1 YP; (4) T3, CON + 2 g kg-1 YP; (5) T4, CON + 4 g kg-1 YP. Experiment 2, a total of 162 were randomly allocated to three groups with three replication. Dietary treatments were: (1) CON, basal diet; (2) T1, CON + 0.5 g kg-1 YP; (3) T2, CON + 1 g kg-1 YP. From days 1 to 14 and overall, chicken fed T1 diet had higher ADG. On day 42, there was increased villus height of jejunum in T1 group. On days 14 and 28, there was decreased villus height of duodenum and jejunum in T2 group. In duodenum, the expression of SGLT1 (days 21, 35 and 42), GLUT2 (days 7, 14, 21, 28, 35 and 42) and GLUT5 (days 7, 14, 21 and 28) was increased with YP supplementation. In jejunum, the expression of SGLT1 (days 7, 14, 21, 28 and 35), GLUT2 (days 14, 21, 28, 35 and 42) and GLUT5 (days 7, 14, 21, 28, 35 and 42) was increased with YP supplementation. In ileum, the expression of SGLT1 (days 7, 21, 35 and 42), GLUT2 (days 7, 14, 21 and 42) and GLUT5 (days 7, 14, 21, 28, 35 and 42) was increased with YP supplementation. Dietary YP supplementation improves growth performance and expression of SGLT1, GLUT2 and GLUT5 in intestine.