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Compared to traditional manual methods for assessing the cotton verticillium wilt (CVW) hazard level, utilizing deep learning models for foliage segmentation can significantly improve the evaluation accuracy. However, instance segmentation methods for images with complex backgrounds often suffer from low accuracy and delayed segmentation. To address this issue, an improved model, YOLO-VW, with high accuracy, high efficiency, and a light weight, was proposed for CVW hazard level assessment based on the YOLOv10n model. (1) It replaced conventional convolutions with the lightweight GhostConv, reducing the computational time. (2) The STC module based on the Swin Transformer enhanced the expression of foliage and disease spot boundary features, further reducing the model size. (3) It integrated a squeeze-and-excitation (SE) attention mechanism to suppress irrelevant background information. (4) It employed the stochastic gradient descent (SGD) optimizer to enhance the performance and shorten the detection time. The improved CVW severity assessment model was then deployed on a server, and a real-time detection application (APP) for CVW severity assessment was developed based on this model. The results indicated the following. (1) The YOLO-VW model achieved a mean average precision (mAP) of 89.2% and a frame per second (FPS) rate of 157.98 f/s in assessing CVW, representing improvements of 2.4% and 21.37 f/s over the original model, respectively. (2) The YOLO-VW model's parameters and floating point operations per second (FLOPs) were 1.59 M and 7.8 G, respectively, compressed by 44% and 33.9% compared to the original YOLOv10n model. (3) After deploying the YOLO-VW model on a smartphone, the processing time for each image was 2.42 s, and the evaluation accuracy under various environmental conditions reached 85.5%, representing a 15% improvement compared to the original YOLOv10n model. Based on these findings, YOLO-VW meets the requirements for real-time detection, offering greater robustness, efficiency, and portability in practical applications. This model provides technical support for controlling CVW and developing cotton varieties resistant to verticillium wilt. [ABSTRACT FROM AUTHOR]

Cutting-edge detection is a critical step in mechanized rice harvesting. Through visual cutting-edge detection, an algorithm can sense in real-time whether the rice harvesting process is along the cutting-edge, reducing loss and improving the efficiency of mechanized harvest. Although convolutional neural network-based models, which have strong local feature acquisition ability, have been widely used in rice production, these models involve large receptive fields only in the deep network. Besides, a self-attention-based Transformer can effectively provide global features to complement the disadvantages of CNNs. Hence, to quickly and accurately complete the task of cutting-edge detection in a complex rice harvesting environment, this article develops a Transformer Convolution Network (TCNet). This cutting-edge detection algorithm combines the Transformer with a CNN. Specifically, the Transformer realizes a patch embedding through a 3 × 3 convolution, and the output is employed as the input of the Transformer module. Additionally, the multi-head attention in the Transformer module undergoes dimensionality reduction to reduce overall network computation. In the Feed-forward network, a 7 × 7 convolution operation is used to realize the position-coding of different patches. Moreover, CNN uses depth-separable convolutions to extract local features from the images. The global features extracted by the Transformer and the local features extracted by the CNN are integrated into the fusion module. The test results demonstrated that TCNet could segment 97.88% of the Intersection over Union and 98.95% of the Accuracy in the unharvested region, and the number of parameters is only 10.796M. Cutting-edge detection is better than common lightweight backbone networks, achieving the detection effect of deep convolutional networks (ResNet-50) with fewer parameters. The proposed TCNet shows the advantages of a Transformer combined with a CNN and provides real-time and reliable reference information for the subsequent operation of rice harvesting. [ABSTRACT FROM AUTHOR]

Pineapple harvesting is a key step in pineapple field production. At present, pineapple fruits are usually picked manually. With decreasing labor resources and increasing production costs, machines have been used instead of manual picking approaches in the modern pineapple industry. This paper briefly describes the basic situation of pineapple planting worldwide. Based on the degree of automation of mechanized pineapple harvesting equipment, the main structural forms, core technologies, and operation modes of semi-automatic, automatic, and intelligent pineapple harvesting equipment are summarized. The research status and existing problems of key pineapple fruit picking robots, such as fruit recognition, maturity classification, positioning, and separation of pineapple fruits, are analyzed. Considering the problems of pineapple harvesting equipment, such as difficulty entering the ground, low harvesting efficiency, low picking success rate, and fruit damage, innovative future research directions for mechanized pineapple harvesting technology are proposed, such as combining agricultural machinery and agronomical principles, integrating mechanized, automated, and intelligent technology, and developing modular designs and generalized approaches. [ABSTRACT FROM AUTHOR]

The unmanned farm control platform is of great significance in promoting the supervision of farm production with less manpower or autonomous operation of farm machinery and the construction of farm informatization. Addressing the existing control platform for farm location information acquisition is time-consuming, labor-intensive, and lacks the whole process control of multiple types of farm machinery. In this paper, we propose an Internet of Things (IoT) control scheme for intelligent farm machinery operation of unmanned farms and design the access standards for multiple types of farm machinery, as well as realize the remote control of intelligent farm machinery operation by constructing a remote control model. A high-precision map construction method is designed to improve the DeepLabV3+ algorithm to identify fields and roads. The control models of path planning, remote task, remote control, and safety system are built to achieve the remote control of intelligent agricultural machinery operation. The proposed technology is implemented in the platform integration and application tests are carried out. The error of the constructed high-precision map is less than 3 cm, the completeness rate of the automatic boundary extraction rate is 96.71%, and the correctness rate is 95.63%, which can be used to obtain the boundary instead of manual labeling or on-site point picking. The use of the platform for the simultaneous control of three farm machinery operations reduces the number of people in operation and production and reduces the professional requirements of the personnel, which will promote the management of the entire farm by one person or even by no one in the future. [ABSTRACT FROM AUTHOR]

The air-suction precision seeder for small seeds is a planting machine, characterized by precision, high efficiency, and ease of operation, that uses air suction technology to sow small grain seeds at set intervals and depths into the soil. However, the forced vibration, enhanced by the increase in the operating speed, affects the seeding accuracy of the seeder and limits the seeding efficiency. To study the influence of vibration conditions on the seed suction performance of the air-suction precision seeder, we developed a computational fluid dynamics–discrete element coupling method to construct a bidirectional fluid–solid coupling numerical simulation model of the seed suction process under vibration conditions. Within the range of operating speeds from 0.6 km/h to 8 km/h, we quantitatively studied the population movement under different vibration frequencies, vibration amplitudes, negative pressure values, and seeding disc speeds and verified the simulation model and its analysis results through bench tests. The numerical results show that the interaction between the vibration frequency, vibration amplitude, and negative pressure value has the most significant impact on the single-seed rate. In addition, via variance analysis and response surface analysis, the optimal range of negative pressure values for achieving high single-seed rates under different vibration frequencies (4~10 Hz), vibration amplitudes (3~7.5 mm), and seeding disc speeds (4~50 rpm) was determined. The results indicate that, rather than the higher the negative pressure value, the higher the seed suction rate, the optimal negative pressure value for achieving a high seed suction rate varies with the specific vibration frequencies and amplitudes. [ABSTRACT FROM AUTHOR]

In order to enhance the efficiency of agricultural machinery in orchard rows and minimize harm to personnel caused by pesticide spraying, this study developed a GNSS-based (Global Navigation Satellite System) automatic navigation driving system for tracked orchard sprayers. The tracked sprayer was used as a platform for this research. We constructed both a crawler hydraulic platform and spraying working parts based on orchard operation requirements. Additionally, we designed the hydraulic and electrical sub-control process of the crawler platform. By utilizing the motion model of the tracked mobile platform, we designed a linear path tracking control method using position deviation and heading deviation as state quantities. This allows the research platform to automatically initiate and terminate, travel in a straight line between rows, and complete spraying operations. Experimental verification confirmed that the tracked sprayer designed in this study successfully achieves automatic driving. The best automatic driving performance is achieved at a speed of 1.0 m/s. When the sprayer's speed is 1.2 m/s, the maximum value of the straight-line path tracking accuracy of the platform's automatic driving is better than 5.6 cm, with a standard deviation of 2.8 cm. This system effectively meets the requirements of automatic operation for an automatic spraying machine, thereby establishing a foundation for the implementation of automatic spraying operations in orchards. [ABSTRACT FROM AUTHOR]

Due to factors such as a small amount of fertilizer application during rice topdressing and slow machine speed, the ordinary fertilizer discharge device fails to distribute the fertilizer uniformly and accurately as required, making it difficult to meet the needs of precise rice topdressing. This research focuses on the development of an offset spiral tooth fertilizer discharge device suitable for rice topdressing. The study analyzes the amount of fertilizer discharged in one cycle, the fertilizer force, and the motion of the fertilizer particles. In order to enhance the uniformity of the fertilizer discharge device at a low speed and small volume, the discrete element method is employed to conduct experimental research on the key structural parameters that affect the one-cycle amount of discharged fertilizer and the dynamics of the fertilizer discharge device. Through single-factor tests, it was found that the angle, height, number of spiral teeth, and diameter of the fertilizer discharge wheel are closely associated with the fertilizer discharge performance. To further investigate the impact of these four parameters on the fertilizer discharge performance, a regression combination test of the four factors is conducted based on the range optimized by the single-factor tests. A multi-objective mathematical model, considering the key parameters of fertilizer uniformity coefficient, one-cycle amount of fertilizer, and fertilizer discharge torque, is established at three speeds: 20, 55, and 90 rpm. The response surface method is utilized to analyze the influence of the interaction factors on the fertilizer discharge performance. The optimal combination of the key structural parameters was determined as follows: spiral tooth angle of 35.42°, tooth height of 9.02 mm, discharge wheel diameter of 57.43 mm, and tooth amount of 9.37. The bench test results of the device, using the optimal parameter combination and a fertilizer discharge speed of 0–90 rpm, were obtained for four commonly used rice fertilizers. The maximum variation coefficient of fertilizer discharge was found to be 10.42%. The one-cycle amount of fertilizer discharge was measured to be 19.82 ± 0.72 (A Kang), 17.20 ± 0.69 (Ba Tian), 20.34 ± 0.54 (Yaran), and 14.51 ± 0.44 (granular urea). The fertilizer discharge torque remained stable. These results indicate that the achieved optimization meets the precise fertilizer application requirements and can provide technical support for precise topdressing operations. [ABSTRACT FROM AUTHOR]

Obstacle avoidance control and navigation in unstructured agricultural environments are key to the safe operation of autonomous robots, especially for agricultural machinery, where cost and stability should be taken into account. In this paper, we designed a navigation and obstacle avoidance system for agricultural robots based on LiDAR and a vision camera. The improved clustering algorithm is used to quickly and accurately analyze the obstacle information collected by LiDAR in real time. Also, the convex hull algorithm is combined with the rotating calipers algorithm to obtain the maximum diameter of the convex polygon of the clustered data. Obstacle avoidance paths and course control methods are developed based on the danger zones of obstacles. Moreover, by performing color space analysis and feature analysis on the complex orchard environment images, the optimal H-component of HSV color space is selected to obtain the ideal vision-guided trajectory images based on mean filtering and corrosion treatment. Finally, the proposed algorithm is integrated into the Three-Wheeled Mobile Differential Robot (TWMDR) platform to carry out obstacle avoidance experiments, and the results show the effectiveness and robustness of the proposed algorithm. The research conclusion can achieve satisfactory results in precise obstacle avoidance and intelligent navigation control of agricultural robots. [ABSTRACT FROM AUTHOR]

Rice lodging is a crucial problem in rice production. Lodging during growing and harvesting periods can decrease rice yields. Practical lodging judgment for rice can provide effective reference information for yield prediction and harvesting. This article proposes a binocular camera-based lodging judgment method for rice in real-time. As a first step, the binocular camera and Inertial Measurement Unit (IMU) were calibrated. Secondly, Census and Grayscale Level cost features are constructed for stereo matching of left and right images. The Cross-Matching Cost Aggregation method is improved to compute the aggregation space in the LAB color space. Then, the Winner-Takes-All algorithm is applied to determine the optimal disparity for each pixel. A disparity map is constructed, and Multi-Step Disparity Refinement is applied to the disparity map to generate the final one. Finally, coordinate transformation obtains 3D world coordinates corresponding to pixels. IMU calculates the real-time pose of the binocular camera. A pose transformation is applied to the 3D world coordinates of the rice to obtain its 3D world coordinates in the horizontal state of the camera (pitch and roll angles are equal to 0). Based on the distance between the rice and the camera level, thresholding was used to determine whether the region to be detected belonged to lodging rice. The disparity map effect of the proposed matching algorithm was tested on the Middlebury Benchmark v3 dataset. The results show that the proposed algorithm is superior to the widely used Semi-Global Block Matching (SGBM) stereo-matching algorithm. Field images of rice were analyzed for lodging judgments. After the threshold judgment, the lodging region results were accurate and could be used to judge rice lodging. By combining the algorithms with binocular cameras, the research results can provide practical technical support for yield estimation and intelligent control of rice harvesters. [ABSTRACT FROM AUTHOR]

The yield and quality of rice are closely related to field management. The automatic identification of field abnormalities, such as diseases and pests, based on computer vision currently mainly relies on high spatial resolution (HSR) images obtained through manual field inspection. In order to achieve automatic and efficient acquisition of HSR images, based on the capability of high-throughput field inspection of UAV remote sensing and combining the advantages of high-flying efficiency and low-flying resolution, this paper proposes a method of "far-view and close-look" autonomous field inspection by unmanned aerial vehicle (UAV) to acquire HSR images of abnormal areas in the rice canopy. First, the UAV equipped with a multispectral camera flies high to scan the whole field efficiently and obtain multispectral images. Secondly, abnormal areas (namely areas with poor growth) are identified from the multispectral images, and then the geographical locations of identified areas are positioned with a single-image method instead of the most used method of reconstruction, sacrificing part of positioning accuracy for efficiency. Finally, the optimal path for traversing abnormal areas is planned through the nearest-neighbor algorithm, and then the UAV equipped with a visible light camera flies low to capture HSR images of abnormal areas along the planned path, thereby acquiring the "close-look" features of the rice canopy. The experimental results demonstrate that the proposed method can identify abnormal areas, including diseases and pests, lack of seedlings, lodging, etc. The average absolute error (AAE) of single-image positioning is 13.2 cm, which can meet the accuracy requirements of the application in this paper. Additionally, the efficiency is greatly improved compared to reconstruction positioning. The ground sampling distance (GSD) of the acquired HSR image can reach 0.027 cm/pixel, or even smaller, which can meet the resolution requirements of even leaf-scale deep-learning classification. The HSR image can provide high-quality data for subsequent automatic identification of field abnormalities such as diseases and pests, thereby offering technical support for the realization of the UAV-based automatic rice field inspection system. The proposed method can also provide references for the automatic field management of other crops, such as wheat. [ABSTRACT FROM AUTHOR]

The widespread use of chemical herbicides has jeopardized concerns about food safety and ecological consequences. To address these issues and reduce reliance on chemical herbicides, a physical weed control device was developed for the tillering stage in paddy fields. This device features a biomimetic duckbill-like vibration chain that effectively controls weed outbreaks. The chain penetrates the soft surface soil of the paddy field under gravity and rapidly stirs the soil through vibration, leading to the detachment of the weed roots anchored in the surface layer. Simultaneously, the device avoids mechanical damage to rice seedlings rooted in deeper soil. This study aimed to investigate the effects of chain structural parameters (the number of chain rows, vibration amplitude, and length of chains) and operational parameters (vibration frequency and working velocity) on weed control efficiency and rice seedling damage. Through a central composite regression field test, the optimal device structure and operational parameters were determined. The optimization results demonstrated that a vibration amplitude of 78.8 mm, a chain length of 93.47 cm, and 3.4 rows of chains, along with a vibration frequency and working velocity ranging from 0.5 to 1.25 m/s, achieved an optimal weeding effect. Under the optimal parameter combination, field test results demonstrated that approximately 80% of the weeds in the field were effectively cleared. This indicates that the design of the biomimetic duckbill-like vibration chain weeding device exhibits a relatively superior weeding performance, offering a practical solution for the management of weeds in rice fields. [ABSTRACT FROM AUTHOR]

The hard bottom layer of a paddy field has a great influence on the driving stability and the operation quality and efficiency of intelligent farm machinery. For paddy field machinery, continuous improvements in the accuracy and operation efficiency of unmanned precision operations are needed to realize unmanned rice farming. In the context of unmanned farm machinery operation, the complicated hard bottom layer situation makes it difficult to quantify the local characteristics of paddy fields. In this paper, an unmanned direct rice seeding machine chassis is used to maneuver the operation field and collect the hard bottom layer information simultaneously. This information is used to design a data processing method that automatically calibrates the sensor installation error and performs abnormal value rejection and 3D sample curve denoising of the contour trajectory. A hard bottom layer surface profile evaluation method based on the local sliding surface roughness is also proposed. The local characteristics of the hard bottom layer were quantified, and the results from the test plots showed that the mean value of the local roughness was 0.0065, where 68.27% of the plots were distributed in the variation range of 0.0042~0.0087 and 99.73% were distributed in the variation range of 0~0.0133. Using the test field data, the surface roughness features were verified to describe the variability in representative working conditions, such as the transport, downfield, operation, and trapping of unmanned intelligent farm machinery. When driving intelligent farm machinery, the proposed method for quantifying local features of the hard bottom layer can provide feedback on the local environmental features at any given position of the machinery. The method also provides a reference for the design optimization of unmanned systems, which can help to realize speed adaption and improve the local path tracking control accuracy of smart farming machines. [ABSTRACT FROM AUTHOR]

A distributed seed delivery system is the most important component of a pneumatic central-cylinder seeder. We performed a fluent simulation analysis for seed-drop tubes at different parameters and airflow velocities, and with an increase in air velocity, the larger the angle is, the easier it is to produce a vortex, which considerably changes the angle, with the little bend tube improving the uniformity of seeding performance. The distribution of rice seeds in the seeding furrow using seed-drop tubes of different angles was also analyzed, and with an increase in delivery airflow velocity, the rice-sowing belts aggregated toward the seeding furrow central line, and with an increase in the forward speed, the seed distribution in the forward-speed direction presented an aggregation and then dispersion trend. The field experiment and physiological indices show that the yield of germination acceleration by seed pelleting can reach 7.92 t. ha−1, which was significantly higher than the yields with other treatments. [ABSTRACT FROM AUTHOR]

To achieve high-frequency and effective inter-vehicle communication between harvesters and transport vehicles during cooperative harvesting, a protocol for wireless communication was designed by analyzing actual communication requirements. Two different wireless communication modes (radio and 4G) were selected for the hardware design; then, a Kalman Filter was designed based on real-time Dead-reckoning and inter-vehicle Communication data after delay Compensation (KFDCC). Finally, the relative longitudinal deviation between two vehicles was obtained and updated steadily at a 10 Hz frequency. By using the relative longitudinal deviation of two vehicles, calculated after aligning the UTC stamp with the local GNSS data from the harvester and transport vehicle as a comparative metric, accuracy evaluation experiments were conducted regarding radio and 4G. The maximum absolute errors of the KFDCC output value were 0.03783 and 0.07381 m, respectively, and the mean square errors were 0.00392 and 0.01317 m, respectively. Compared with systems without the KFDCC method, the mean square errors were reduced by 88.76% and 90.60%, respectively. The KFDCC method can also effectively solve the problems of data delay, packet loss, blockage, error, and so on, in wireless communication, and has short-time breakpoint endurance capabilities. Field experiments showed that the proposed method can provide accurate data support for the dynamic alignment and unloading processes of harvesters and transport vehicles, and it can also provide algorithmic support for real-time communication data fusion between different wireless communication modes. Overall, the inter-vehicle communication mode and data-processing method designed in this paper have good effects and adaptability, and they can guarantee that the whole process of autonomous harvesting operates properly. [ABSTRACT FROM AUTHOR]

Discrete element modelling (DEM) parameters are of great importance for the accurate prediction of soil properties and disturbance. This study aimed to provide an efficient method for accurately determining the DEM parameters of a paddy soil with a high moisture content (45.66%). The DEM parameters of the paddy soil modelled using the Hertz–Mindlin with JKR contact model were determined by using the Plackett–Burman (PB), steepest ascent, and central composite tests. The accuracies of the developed DEM models were evaluated using actual slumping tests. Based on the PB test, the surface energy of soil, coefficients of soil–soil rolling friction, and coefficients of soil–steel static friction exerted larger influences on the overall relative error (δZH). The optimization results showed that to achieve a minimum δZH (5.96%), the surface energy of soil, the coefficients of soil–soil rolling friction, and the coefficients of soil–steel static friction should be 0.808 J m−2, 0.11, and 0.6, respectively. The optimized DEM model had an overall relative error of 7.27% with a coefficient of variation of 1.32%, indicating that the DEM parameters of the calibrated paddy soil had good accuracy. [ABSTRACT FROM AUTHOR]

The identification method of rice seedling rows based on machine vision is affected by environmental factors that decrease the accuracy and the robustness of the rice seedling row identification algorithm (e.g., ambient light transformation, similarity of weed and rice features, and lack of seedlings in rice rows). To solve the problem of the above environmental factors, a Gaussian Heatmap-based method is proposed for rice seedling row identification in this study. The proposed method is a CNN model that comprises the High-Resolution Convolution Module of the feature extraction model and the Gaussian Heatmap of the regression module of key points. The CNN model is guided using Gaussian Heatmap generated by the continuity of rice row growth and the distribution characteristics of rice in rice rows to learn the distribution characteristics of rice seedling rows in the training process, and the positions of the coordinates of the respective key point are accurately returned through the regression module. For the three rice scenarios (including normal scene, missing seedling scene and weed scene), the PCK and average pixel offset of the model were 94.33%, 91.48%, 94.36% and 3.09, 3.13 and 3.05 pixels, respectively, for the proposed method, and the forward inference speed of the model reached 22 FPS, which can meet the real-time requirements and accuracy of agricultural machinery in field management. [ABSTRACT FROM AUTHOR]

The distribution of airflow field in the pneumatic centralized cylinder metering device cavity, airstream distributor and different angle seed feeding tubes was investigated based on the pneumatic centralized cylinder direct-seeding metering device to study the effect on the movement law of rice seed. In total, three suction hole sizes (1.5 mm, 2 mm and 2.0 mm 45° wedge) were used for CFD simulation. The results showed that under the same inlet vacuum, the pressure at the 1.5 mm hole is higher than the other two types of holes, and the five measurement points of the 2 mm hole are more stable than the other two types of holes. At the positive pressure seed feeding area, the inlet pressure was set as 1.5 kPa, and the outlet pressure was set as 0 Pa. The pressure distribution at different measuring points showed that the 2 mm 45° wedge had the most uneven positive pressure distribution, and the 1.5 mm hole had higher positive pressure distribution than the 2 mm hole in general. Three different structured airflow distributors were designed. CFD simulation experiments showed that the arc transition type presented better uniformity than the other two types. The uniformity experiments at the ends of the seed-feeding tubes indicated that the airflow velocity had the trend of large in the middle and small at two sides. Finally, the movement law of the rice seeds in seed feeding tubes at different angles was obtained by using high-speed photography. The results showed that the rice seeds in tube C (maximum angle) presented a movement posture of falling sector a and kept falling after colliding in sector b; the rice seeds in tube B (the second angle) presented a movement posture of falling in sector a and kept falling after colliding in sector b. The above research provides a reference for the optimal design of a pneumatic centralized cylinder metering device. [ABSTRACT FROM AUTHOR]

Background: Functional ankle instability (FAI) of college football players is an important risk factor affecting their training and competition. Physical therapy and appropriate sports intervention can improve the stability of FAI patients. Previous studies have shown that Tai Chi (TC) and Kinesio taping (KT) can improve the posture control ability of FAI patients. However, whether Tai Chi combined with Kinesio taping effect patch can be used as an effective exercise for rehabilitation of college football players with FAI is not yet proven.Methods/design: Fifty-three FAI college football players were randomly assigned to 3 groups: TC+KT (n = 20); TC+KTp (placebo Kinesio taping, KTp, placebo) (n = 17), and KT (n = 16). The TC+KT group received TC and KT functional correction technical intervention, the TC+KTp group received TC and placebo KT technical intervention, and the KT group received KT functional correction technical intervention. Each of the three groups received 30 min each time, 3 times a week, for a total of 6 weeks of intervention training. Star Excursion Balance Test (SEBT) and UniPedal Stance Test (UST) at baseline (before), 4 weeks after intervention (middle), and 6 weeks after intervention (after) and Toe Touch Test (TTT) were evaluated.Discussion: For the first time in this trial, the impact will be evaluated. If the results are the same as expected, they will provide evidence that Tai Chi combined with Kinesio taping sticking intervention can promote the posture control of college football players with FAI.Trial Registration: Chinese Clinical Trial Registry ChiCTR1900027253 . Registered on 6 November 2019. [ABSTRACT FROM AUTHOR]

This paper proposes an optical tracking system to realize the clustering of multiple unmanned aerial vehicles (UAVs). The system uses a laser spot as a visual recognition target to realize cluster flight operations in a complex environment. To reduce the interference of sunlight in the optical visual navigation and obtain the optimal combination of laser receiving devices, we selected lasers in a variety of spectrum bands and filter films with different light transmittances to conduct a comprehensive test. By performing a fluid simulation of the UAVs with the related modules mounted in different positions, the optimal installation position was selected to enhance the effect of the UAV wind field. An online learning tracking framework based on the multi-feature extraction of convolutional networks was developed to realize robust long-term visual tracking. In the tracking process, the tracking algorithm could train the detector online according to the status of the target and adaptively initialize the target. Finally, to verify the practical application performance of the clustering system, a group of UAVs was tested in flight. We verified that the proposed method and device exhibit a high feasibility and reliability. [ABSTRACT FROM AUTHOR]

Global climate change and socio-economic development have led to a shortage of water and labour resources, which has had a significant impact on rice cultivation. In this study, the application of micro-ridge-furrow planting technology and degradable film mulching in dry direct-seeded rice was investigated to address the factors restricting the development of the rice industry and reduce the impact of rice production on the environment. The effects of a micro-ridge-furrow planting pattern and degradable film mulching on soil temperature, seedling growth, and yield of dry direct-seeded rice in a semiarid region of China were studied through three field experiments: micro-ridge-furrow mulching with traditional plastic film (T1); micro-ridge-furrow mulching with degradable film (T2); and traditional flat-cropping mulching with traditional plastic film (CK). The experimental results demonstrated that the micro-ridge-furrow mulching film planting pattern promoted the germination of rice seeds and improved the soil temperature, plant height, leaf area, dry mass, and grain yield. T2 had the highest average soil temperature (14.68–17.83 ℃ during the day; 14.4–15.74 ℃ at night), leaf area (41.85 cm2 plant−1), root dry mass (45.32 mg plant−1), shoot dry mass (58.46 mg plant−1), root–shoot ratio (0.821), and yield (8.112 t ha−1). In summary, the micro-ridge-furrow mulching with degradable film (T2) is recommended as an efficient planting and mulching pattern for sustainably solving environmental problems and improving grain yield in semiarid regions of China. [ABSTRACT FROM AUTHOR]

The brown rice planthopper (Nilaparvata lugens Stal) is one of the main pests of rice. The rapid and accurate detection of brown rice planthoppers (BRPH) can help treat rice in time. Due to the small size, large number and complex background of BRPHs, image detection of them is challenging. In this paper, a two-layer detection algorithm based on deep learning technology is proposed to detect them. The algorithm for both layers is the Faster RCNN (regions with CNN features). To effectively utilize the computing resources, different feature extraction networks have been selected for each layer. In addition, the second layer detection network was optimized to improve the final detection performance. The detection results of the two-layer detection algorithm were compared with the detection results of the single-layer detection algorithm. The detection results of the two-layer detection algorithm for detecting different populations and numbers of BRPHs were tested, and the test results were compared with YOLO v3, a deep learning target detection network. The test results show that the detection results of the two-layer detection algorithm were significantly better than those of the single-layer detection algorithm. In the tests for different numbers of BRPHs, the average recall rate of this algorithm was 81.92%, and the average accuracy was 94.64%; meanwhile, the average recall rate of YOLO v3 was 57.12%, and the average accuracy rate was 97.36%. In the experiment with different ages of BRPHs, the average recall rate of the algorithm was 87.67%, and the average accuracy rate was 92.92%. In comparison, for the YOLO v3, the average recall rate was 49.60%, and the average accuracy rate was 96.48%. [ABSTRACT FROM AUTHOR]

Traveling along straight lines and headland turning are two common motions during the automatic guidance of agricultural machines. However, most studies focus on accurately following parallel tracks in the field and seldom consider the maneuvers at the end of each row. Moreover, numerous studies have mainly focused on planning the global trajectories in the entire field to increase field efficiency, and very few works are related to maneuver generation and vehicle control in headlands. In this study, a feedforward-plus-proportional–integral–derivative controller for a differential drive robot in headland turning was developed. The feedforward-plus-proportional–integral–derivative controller consisted of a feedforward and a feedback loop. The feedforward loop was designed based on the heading errors of a lookahead point on the planning path. The feedback loop was designed based on radial errors to improve the tracking accuracy. Field comparison tests of feedforward, feedback, and feedforward-plus-proportional–integral–derivative controllers were conducted. Experimental results showed that the feedforward-plus-proportional–integral–derivative had better tracking results and took less turning time. [ABSTRACT FROM AUTHOR]

Grain qualities including milling, appearance, cooking and nutritional quality, are important traits that have aroused rice researchers' attention worldwide. Head rice rate, an important milling quality together with grain yield affects head rice yield. The head rice yield is directly related to economic value of the grains, and has significant impacts on income of rice producers. Precision rice hill-drop drilling is a simplified technique, which can achieve high yield while is applied at appropriate rice growth regions. The precision rice hill-drop drilling technique has been applied in many rice growth regions in China. Previously, precision rice hill-drop drilling technique has been proven to influence rice yield, agronomic performances and grain qualities in small region only and assessing the effect of precision rice hill-drop drilling technique on grain qualities in national wide is therefore important. In order to investigate the influence of precision rice hill-drop drilling technique on grain qualities in multiple rice growth regions in China, the comparison experiment were carried out. In this study, comparisons of the grain qualities between precision rice hill-drop drilling and machanical transplanting were investigated in the mainly planting areas (viz: Anhui, Shanghai, Guangdong, Sichuan, Xinjiang and Shandong) of precision rice hill-drop drilling in China. Results showed that precision rice hill-drop drilling technique was beneficial to improve head rice yield. Rice by using precision rice hill-drop drilling had higher head rice yield than that by using machanical transplanting in Nanling Anhui, Mianzhu Sichuan, Wensu Xinjiang, and Gaoqing Shandong regions, which increased by 9.11%, 27.02%, 4.08%, and 11.11% significantly. Moreover, the effects of precision rice hill-drop drilling technique on protein content and amylose content in grains from different investigated regions were different because of the difference in cultivars and environmental conditions, and the decrease in protein content and amylose content in grains were detected for some investigated regions. Furthermore, precision rice hill-drop drilling technique significantly decreased chalky rice rate in grains in Gaoqing Shandong, while showed no significant effect on appearance qualities of grains for other investigated regions. This study have investigated the impact of precision rice hill-drop drilling technique on grain quality of the rice varieties planted in large areas of the rice planting regions in China, this work is beneficial to further promotion to the popularization and application of precision rice hill-drop drilling technique in appropriate areas. [ABSTRACT FROM AUTHOR]

Automation of images registration and stitching is one of the most important key technologies to the wide use of the low-altitude remote sensing by Micro-UAVs (unmanned aerial vehicles) in rice growing. In order to overcome the limitations, i.e. the thresholds need to be artificially determined for the traditional Harris corner detection algorithm, this paper proposed a self-adaptive algorithm for Harris corner detection, which was used in image registration and stitching of the rice low-altitude remote sensing. The algorithm was improved based on the traditional Harris corner detection algorithm by using a self-adaptive threshold determination method, which calculated from the standard deviation of image pixel gray-scale value. And then the characteristics of image were described by corners, and the images were registered by using the Euclidean distance among descriptors. In order to verify the effectiveness of the algorithm and optimize the relevant parameters, a verification test was conducted based on low-altitude remote sensing images, which were gained by a multispectral camera mounted on a multi-rotor unmanned helicopter during rice tillering stage. Four indices, the repetition rate (a measure of the stability of corner detection), the recognition rate (a measure of corner recognizable description operator), the registration rate (a measure of the accuracy of image registration and stitching) and running time of algorithm (a measure of computing speed of the algorithm), were proposed to evaluate the results of registration and stitching. Sixty images were randomly divided into 3 groups for verification test. Test results showed that the average registration rate reached 98.95%, and also the average repetition rate reached 96%, which indicated that the proposed algorithm had high accuracy. The repetition rate and the difference in image registration rates among the groups were not significant (at 0.05 significance level), which indicated that the proposed algorithm was stable and reliable. And the recognition rate among the groups was significant, and it indicated that the proposed algorithm had higher distinguishability to the remote sensing images, which was conducive to the precision of the automation of images registration and stitching. Threshold value of the proposed algorithm, which is the standard deviation of the image pixel gray values after standardization, here is set to 1 and 2 for optimization test. Test results showed that the registration rate was not significant, namely there was no significant difference (at 0.05 significance level) when the threshold value was equal to 1 or 2. However, comparing the average running time of the proposed algorithm, it showed that the running time when the threshold value was 1, is 2.5 times that when the threshold value was 2. Based on comprehensive consideration of the registration rate, the running time and the efficiency, the threshold value of 2 can be set as the optimum parameter of the proposed algorithm. [ABSTRACT FROM AUTHOR]

At present three-dimensional (3D) reconstruction of crop images and binocular vision guidance of agricultural robot are still important hot research contents in the related field, in which the feature extraction and matching of green crops is one of key technologies for monitoring crop growth state or providing 3D guiding information for agricultural robot because they directly affect the accuracy of obtained 3D information of crops. A feature extraction and matching method of the green crops is proposed in this paper. We focus on the crop regions in an image that can provide enough crop information. Firstly, a pre-treatment process of the image in RGB (red, green and blue) space is employed to segment the green crop from the backgrounds. Then the morphology opening operation with an optimal size is used to filter the noises including some isolated points or small areas caused by weeds, small stone, shadows and residue etc. Considering the field application conditions, the SURF is adopted to obtain the featuring points because of its attractive performance including repeatability, distinctiveness and robustness without bad time consumption. And the reason is that its detector and descriptor are scale invariance and rotation invariance with the length of 64 dimensions. There are 2 steps to get the featuring points: the first step is to employ Hessian matrix to detect the featuring points, and then, the non-maxima suppression is used to search the extreme points and the interpolation arithmetic is to position them; in the second step, the featuring points are extracted by using a main direction vector which is the main factor of the invariance property. Finally, the Euclidean distances between each searching points are calculated in the left and right image to measure the similarity of searching point pair. The ratio of the nearest distance to the sub-nearest is used to determine whether the point is the matching one or not. If the ratio is larger than the set threshold, the matching is right otherwise wrong. At the same time, for improving the accuracy of matching, the complete constraint matching is implemented to restrain the wrong matching points. The constraint consists of 3 components: the first is the local epipolar line constraint, which requests the matching points must be located in a certain region; the second is left-right constraint that is the x coordinate of the point in left image must be larger than that of the corresponding point in right image; the third is a point of the left image is allowed to only match sole one of the right image. The experimental results show that each of the 3 constraints makes the accuracy of matching decrease when the ratio rises; but when the complete constraint matching is applied, the accuracy of matching has an inconspicuous variation. After the constraint procedure is implemented, the corresponding pairs will be sorted according to their distances. And the smaller the distance is, the more the probability of correct matching is. Thirteen groups of images under various illumination conditions about celeries, vegetables and cabbages are used to test the algorithm in this paper. The experimental results show that SURF is superior to SIFT and can be used to obtain the 3D information of crops for agricultural machinery vision system. And the mean of the extraction rate of featuring points for SURF and SIFT is 1.2%, 3.3%, respectively; and the mean of the accurate rate of matching of them is 94.8%, 92.4%, respectively; the time consumption is 4.6 s, 4.8 s, respectively. [ABSTRACT FROM AUTHOR]

Compared to rice mechanistic metering device, rice pneumatic metering device has advantages of low number of sowing seeds, high precision of seed metering and low seed-injuring rate. Because the precision of seed metering is difficult to control and the performance of hill sowing is poor, rice pneumatic metering device is difficult to be widely used in field direct-seeding. The control of the precision of seed metering is the key to design metering device. Analysis of the process of dropping seeds helps improve the precision of seed metering and the performance of hill sowing, providing a basis for the design of metering device. Seeds were taken away from sowing disc under positive pressure for blowing seeds. The dropping trajectories and hill sowing performance of rice seeds were studied in this article. A high-speed photography technology was introduced to investigate how the dropping trajectories of rice seeds varied and what influenced the dropping trajectories, on which the equations of the rice's movement were formed. The theory equations were optimized through the average horizontal displacements of actual dropping trajectories and the optimization equations under the different conditions were obtained. The diameter of hill sowing was also measured. As seeds were taken away from sowing disc under positive pressure, seeds gained an initial velocity, which was called Vz and was vertical to the sowing disc. Because seeds moved along with sowing disc rotating before seeds were blown away, the seeds gained the other initial velocity, which was called Vr and was parallel to the disc. Seeds also gained acceleration of gravity under the gravity. In the above factors, the dropping trajectories were spatial parabolic, which was more complicated than the plane parabolic trajectories of rice mechanistic metering device. In order to investigate and count the dropping trajectories of rice pneumatic metering device, a coordinate system was established. Indic hybrid Peizataifeng was taken as research subject in this article, of which water content and average length, width and thickness were 20.5% and 8.97, 2.34 and 1.90 mm respectively. There were 2 dropping trajectories, the trajectory of frontal dropping seed and the trajectory of profile dropping seed. The dropping trajectories and diameters of hill sowing were analyzed by multi-factor experiment under different rotation rates and positive pressures for blowing seeds. The experimental results showed horizontal displacements of the trajectory of frontal dropping seed increased with the increasing of rotation rate, which were less than 5 mm. The frontal trajectory had good stability under positive pressure of 0.1 kPa, and horizontal displacements were stabilized within the range of 45-65 mm. Under positive pressure of 0.2 kPa, the frontal trajectory was unevenly distributed with bad stability. Trajectory of profile dropping seed was little affected by rotation rate. Horizontal displacements of trajectory of profile dropping seed increased with the increasing of positive pressure for blowing seeds. The profile trajectories were stabilized within the range of 0-15 mm under positive pressure of 0.1 kPa. Under positive pressure of 0.2 kPa, the profile trajectories were unevenly distributed. Diameters of the hill less than 50 mm were deemed as qualified, while diameters more than 50 mm were deemed as substandard. The probability of substandard diameter increased with the increased rotation rate and positive pressure. Performance of hill sowing was best with the rotating speed of 30 r/min and positive pressure of 0.1 kPa, of which qualified rate was 96.9%. The optimum height of dropping seeds was 10 cm. This article analyzed dropping trajectories in theory and got the optimal conditions of performance of hill sowing, providing the basis for optimal conditions of hill sowing and the reference for the design of seeding tubes of rice pneumatic metering device. [ABSTRACT FROM AUTHOR]

The technology of rice's mechanical direct seeding can significantly reduce the consumption of manpower and material resources, and meanwhile maintain the production of rice. Super hybrid rice is a kind of hybrid rice and its tillering ability is stronger than the general hybrid rice. Due to the characteristics of high tillering capacity of super hybrid rice, the sowing quantity is required to be 1-3 seeds for each hole when super hybrid rice seeds are directly seeded to the field by the drilling machine, so as to ensure the high precision of seeding and high rate of field seedling emergence. In order to meet the requirement of 1-3 seeds for each hole using the precise hill-drop drilling technique, a seed-filling stratified room was designed, which was between the seed-metering device and the seed box on pneumatic feed mechanism for precision rice hill-drop sowing. It also aimed at improving the liquidity of seeds and raising the seeding precision, the liquidity of rice seed would reduced after accelerating germination. This the reduction of the liquidity of rice seed after accelerating germination had so bad effects on filling process that it limited the improvement of metering performance. Indic hybrid Peizataifeng was taken as the research object, and the impacts of the seed-filling stratified room on the performance of the pneumatic feed mechanism was studied by the single-factor experiment and orthogonal experiment in this paper. These experiments were carried out under different negative pressures for sucking seeds and positive pressures for blowing seeds. The experimental results showed that there existed an optimization condition on the capability of the metering device to meet the needs of the production. The probability about the quantity for each hill was used to evaluate the capability of the pneumatic precise metering device. The seed-filling stratified room consisted of a barrel and two seed-guiding plates. The cross-section of the barrel was the square with 50 mm per side. There were the chutes on the lining of the barrel, which were 1.1 mm wide. Seed-guiding plates were 1 mm thick, which were connected with the barrel by chutes. The two seed-guiding plates formed an angle of 45 degrees. The optimization condition was that the sucking plate's rotation speed was 30 r/min, the negative pressure for sucking seeds was 1.6 kPa and the positive pressure for blowing seeds was 0.1 kPa. With the seed-filling stratified room, the probability of 1-3 seeds per hill for the metering device was 95.4%; in addition, the probability of empty seed was 1.53%, and the probability of greater than or equal to 4 seeds was 3.07%. Under the same condition, the probability of one seed per hill for the metering device was 17.32%; in addition, the two-seed probability was 58.72% and three-seed probability was 19.36%. Compared with the existed researches, the results showed that the seed-filling stratified room between the seed-metering device and the seed box on pneumatic feed device, had a good influence on the precision of the pneumatic seed-metering device, improved the fluidity of the seeds and decreased the friction force and extrusion force among the seeds. This study provides an important reference for the structure optimization and the performance improvement of the pneumatic metering device. [ABSTRACT FROM AUTHOR]

The technology of rice's mechanical direct seeding can significantly reduce the consumption of manpower and material resources, and meanwhile maintain the production of rice. Super hybrid rice is a kind of hybrid rice and its tillering ability is stronger than the general hybrid rice. Due to the characteristics of high tillering capacity of super hybrid rice, the sowing quantity is required to be 1-3 seeds for each hole when super hybrid rice seeds are directly seeded to the field by the drilling machine, so as to ensure the high precision of seeding and high rate of field seedling emergence. In order to meet the requirement of 1-3 seeds for each hole using the precise hill-drop drilling technique, a seed-filling stratified room was designed, which was between the seed-metering device and the seed box on pneumatic feed mechanism for precision rice hill-drop sowing. It also aimed at improving the liquidity of seeds and raising the seeding precision, the liquidity of rice seed would reduced after accelerating germination. This the reduction of the liquidity of rice seed after accelerating germination had so bad effects on filling process that it limited the improvement of metering performance. Indic hybrid Peizataifeng was taken as the research object, and the impacts of the seed-filling stratified room on the performance of the pneumatic feed mechanism was studied by the single-factor experiment and orthogonal experiment in this paper. These experiments were carried out under different negative pressures for sucking seeds and positive pressures for blowing seeds. The experimental results showed that there existed an optimization condition on the capability of the metering device to meet the needs of the production. The probability about the quantity for each hill was used to evaluate the capability of the pneumatic precise metering device. The seed-filling stratified room consisted of a barrel and two seed-guiding plates. The cross-section of the barrel was the square with 50 mm per side. There were the chutes on the lining of the barrel, which were 1.1 mm wide. Seed-guiding plates were 1 mm thick, which were connected with the barrel by chutes. The two seed-guiding plates formed an angle of 45 degrees. The optimization condition was that the sucking plate's rotation speed was 30 r/min, the negative pressure for sucking seeds was 1.6 kPa and the positive pressure for blowing seeds was 0.1 kPa. With the seed-filling stratified room, the probability of 1-3 seeds per hill for the metering device was 95.4%; in addition, the probability of empty seed was 1.53%, and the probability of greater than or equal to 4 seeds was 3.07%. Under the same condition, the probability of one seed per hill for the metering device was 17.32%; in addition, the two-seed probability was 58.72% and three-seed probability was 19.36%. Compared with the existed researches, the results showed that the seed-filling stratified room between the seed-metering device and the seed box on pneumatic feed device, had a good influence on the precision of the pneumatic seed-metering device, improved the fluidity of the seeds and decreased the friction force and extrusion force among the seeds. This study provides an important reference for the structure optimization and the performance improvement of the pneumatic metering device. [ABSTRACT FROM AUTHOR]

For centuries, strip compound planting system has been widely adopted in the southwestern part of China, and is mainly farmed by hand up to date. It is commonly believed that the compound planting system results to the low level of mechanization. The traditional strip compound planting system, "wheat-maize-sweet potato" (WMP) relay cropping system was once the main cropping pattern on dry land in this area. However, in recent years, along with the demand decrease of sweet potato as swine feed and the demand increase of soybean, soybean has been taking the place of sweet potato in the WMP system for its economic benefits; then the main compound planting system has gradually transformed into "wheat-maize-soybean" (WMS), which is now one of the key technologies the nation has been endeavoring to popularize. In the WMS relay cropping system, several rows of wheat are usually drilled with 20cm row space at the beginning of November of the first year relay-cropping with several rows of maize which are usually hill-dropped with 40cm row space at the end of March of the next year; when the wheat is harvested in the middle of May, several rows of soybean are then seeded with 40cm row space in the wheat stubble relay-cropping with maize at the beginning of June of the second year. In practice, there are usually three types of strip width configuration of Wheat-Maize: narrow (40-73 cm), medium (100-100cm, 117-83cm, 100-67 cm) and wide (200-200 cm). Different crop width configuration has different room available for mechanization operation; the nonstandard crop strip width hazards the adoption of mechanization; so the strip width configuration needs to be standardized firstly in line with the demands of mechanization. In order to realize the mechanized production of the WMS model as well as to improve the level of mechanization by popularizing the mechanized relay cropping system, the machine and agriculture measures for the WMS system should both be taken into account as a whole. On the condition of achieving the maximum annual yield of the three crops in the WMS system, field experiments have been carried out at several sites in the hilly areas of Sichuan Province since 2003 to acquire the optimal width configuration and agricultural measures. By the results, the "100-100" WMS model was selected as the optimal pattern to be mechanized with. Thereafter, mechanization operations were carried out in the chosen system by employing mini-, small- and medium-sized machinery system, respectively and the maize and soybean harvesters developed intentionally for the chosen pattern. According to the results, the mechanization of strip compound planting system is feasible; the compound planting system is not the root cause that leads to the low mechanization level in the hilly areas; "100-100" WMS model is the reliable carrier for developing dry land mechanization in the hilly areas of Sichuan; the Mini-four-wheeled tractor and its implements system is applicable for the strip compound planting system as well as the small-sized plots in hilly areas; so the popularization of the mechanized "100-100" WMS model shall facilitate the mechanization of the hilly areas. [ABSTRACT FROM AUTHOR]

The small size and low cost micro-UAV information acquisition technology platforms have been widely applied in agricultural field in recent years. It has become the inevitable trend of development of precision agriculture and has offered a fast and flexible way to acquire data for crop management and monitoring, capable of timely provision of high resolution images. The key technology for remote Sensing information acquisition based on micro UAV in the world, which includes the development of micro UAV remote sensing platforms, information acquisition technology, image processing, and analysis and application of crop management, is reviewed in this paper. Micro UAV mainly has two types: rotor helicopter and fixed-wing aircraft. The rotor helicopter has been used more widely in acquiring information of the field, because it has the ability of taking off and landing vertically, fixed-point hovering, and slow cruising. Japan was the first country that has used the micro-UAV in agricultural production, and is one of the countries that have the best and most mature technologies in using remote UAV in agriculture today. The United States, Netherlands, Israel, and the United Kingdom also have a very good development all over the world. The beginning of research and development of micro UAV in China was much later than the other developed countries, but it has a booming development and grows rapidly. In this paper, parameters and characteristics of different models of the micro UAVs from eight companies in China have been listed for comparison. In remote sensing information acquiring systems, due to the limited load capacity of micro-UAV, digital camera and light-weight multispectral camera are two main instruments that are used on micro UAV for remote sensing information acquiring. How to adjust the posture of airborne remote sensors quickly and accurately so that the detecting target is always in the center of monitoring view, and how to realize remote controlling, image and information capturing, and transmission wirelessly are some of the focuses of UAV remote sensing technology at present. Limited by the stability and load capacity of the micro UAV, the remote sensing image always appears with the defects including a small view, large angle inclination, and serious irregular image overlap. So, solving the problem of correction, matching, mosaicing, fusing, and analyzing of the remote sensing images is one of the most important research work in this field. Nowadays, the main application of micro UAV focuses on the detection of growing nitrogen levels and the generation of fertilization strategy for rice, cotton, and other staple crops. However, the usage of micro UAV is limited due to the following defects: 1) its small size, making it easily influenced by wind, and short battery life; 2) poor accuracy of navigation system and balance control system; 3) serious leakage or reduplication of capturing images caused by the imprecise heading overlapping and routes bending; 4) difficulty of image correcting, matching, mosaicing, fusing, and analyzing for the remote sensing images; 5) the error of UAV equipment and usage is difficult to control. According the review, the further research on key technology focusing on high stability, big load capacity, long life time, and high resolution data for crop management have been proposed. The micro UAV information acquisition platform is a good complement of satellite and aerial remote sensing technologies for monitoring agricultural information and generating prescription maps for precision agriculture. [ABSTRACT FROM AUTHOR]

Deep fertilizing is a high efficiency fertilization method in rice fields. In order to realize deep fertilizing, according to the requirement of rice planting, a synchronous side deep fertilizing technique is developed on the base of a precision rice hill-drop drilling technique. By ditching, ridging, deep fertilizing, and seeding joint operations, the fertilizing ditch openers prescribe fertilizing ditches, and the fertilizer apparatus puts fertilizers into the fertilizing ditches which are between two seeding ditches, to provide fertility of the necessary growth for rice in the two seeding ditches. At the same time, the fertilizing ditches are covered by the skateboard. After covering, fertilizers can reduce the loss due to volatilization, denitrification, and leaching. And then the seeding ditch openers prescribe seeding ditches, and the seed-falling devices take rice into the seeding ditches, at the same time the water ditch openers prescribe water ditches, and the water in the water ditches will be provided for the rice in the seeding ditches. In order to explore the distribution of the depth of deep fertilizing and fertilizer in different soil layers, this paper investigated the special distribution of the rice root system in different planting patterns and rice varieties. The 80% rice root is in a 0-10 cm soil layer. Technical parameters for synchronous side deep fertilizing were studied based on the special distribution of the rice root system in that soil layer (0-10 cm). The optimum fertilization depth was identified as 10 cm. And according to the special distribution of the rice root in the 0-5 and 5-10 cm soil layers, fertilization distribution for the rice varieties of 'Peizataifeng' and 'Yuxiangyouzhan' in the 0-5 cm and 5-10 cm soil layers was researched. The field experiment results showed that the precision rice hill-drop drilling machine with synchronous side deep fertilizing developed in SCAU meets the requirements of the synchronous side deep fertilizing technique, which can be used as the implementation of a synchronous side deep fertilizing technique with precision rice hill-drop drilling. The field experiment results in rice production indicated that the technique can increase the yield and reduce the cost. Compared with the artificial fertilizing on the same fertilizing level, the higher effective panicle, grains per panicle, and seed setting rate were achieved with the synchronous side deep fertilizing technique. The rice yield increased by 418.5-957 kg/hm2 with an improvement of 5.86%-13.41%. The research results could provide the references for the design synchronous side deep fertilizing machine. [ABSTRACT FROM AUTHOR]

Because of its high efficiency and leveling precision, the laser leveler for paddy fields has received widespread attention in the mechanization of rice planting. The laser receiver is the elevation sensor component of a laser leveler for paddy fields, and the effective distances of the laser leveler for paddy fields are mainly decided by the noise-rejection performance of the photoelectric conversion and amplifier circuit. In extension work, due to strong solar irradiance and vibration the laser receiver may output wrong height position information, reducing leveling precision and work efficiency. In order to improve the reliability of elevation measurements, the photoelectric conversion and amplifier circuit of the laser receiver were optimized by using the experimental methods in this study. Laser receiving distance, energy conversion, and the noise and frequency characteristics of the laser receiver were selected as experimental variables. 2CR93 silicon photoelectric cells were selected as the laser photoelectric conversion element in this research. The laser pulse energy received by the silicon photocell was converted to an electrical signal. The signal energy is determined by the optical filter mode, laser spot and sweeping duration across the silicon photocell. As the receiving distance increases, the diameter of the laser spot expands, and both the sweeping duration across the silicon photocell and the laser energy received by the silicon photocell decrease. With increasing receiver distance, the short circuit current and open circuit voltage of the silicon photocell were obtained by experiments under two optical filter modes. When the receiving distance was over 175 meters, the short circuit current of the silicon photocells were approximately equal under each filter mode. When the receiving distance was over 50 meters, the open circuit voltages of the silicon photocells were also approximately equal. The bare 2CR93 silicon photocell was used as direct photoelectric converting device. With a 100 μH external inductance, the photoelectric conversion signal was modulated into a sinusoidal signal. With 4 parallel silicon photoelectric cells, the modulation frequency was 63.9 kHz. With 8 cells, the frequency was 43.5 kHz. The 2CR93 silicon solar cell equivalent diode capacitance was 16 nF. The laser receiver receives the laser signal and other external noise, including the mechanical vibration noise, solar irradiance noise and various electrical noises. The photoelectric conversion noise experiment result shows that with increasing background solar power, the laser signal peak value decreases and the noise peak value rises. Vibration noise affected only the low-frequency system. According to the test results, the photoelectric conversion circuit and amplification circuit parameters were optimized in this paper. The appropriate 100 μH inductance was selected; the photoelectric conversion signal was modulated into a sinusoidal signal. A smaller bandwidth could reduce the solar noise interference on the laser receiver; with an optimized, infinite-gain, multiple negative feedback, two-order bandpass amplifier circuit parameters could reduce vibration noise. Field testing results showed that when the transmitter was a Futian KF308, rotating frequency was 600 r/min, a multilevel, narrow-band amplifier can reduce the noise caused by solar irradiance, and the bandpass amplifier can reduce the noise caused by mechanical vibrations. The optimized laser receiver met height position requirements of a laser leveler for paddy fields. [ABSTRACT FROM AUTHOR]

Compare with uniaxial single-rotor electric unmanned helicopter (USREUH), the structure of round multi-axis multi-rotor electric unmanned helicopter (RMMEUH) is very different to USREUH, and thus its wind field parameters on rice canopy which formed by rotor airflow are also different. To explore the optimization parameters when the RMMEUH conducted supplementary pollination, in this study orthogonal tests of three factors (including flight operating load, altitude and speed) and three levels were carried out to measure the wind field. The tested RMMEUHs include two 8-rotors electric unmanned helicopters and an 18-rotors electric unmanned helicopter. The measured wind directions included parallel to the direction of flight heading (X), perpendicular to the direction of flight heading (Y), and the vertical direction (Z). The battery's voltage drop was also measured at each takeoff and landing of RMMEUH to estimate its economy. A wireless wind speed sensor network measurement system (WWSSN) was used to measure the wind field parameters of the RMMEUH. The WWSSN consists of several wireless wind speed sensors (WWSS, numbered 1#-10#), a flight global position system (FGPS), and an intelligent control focus node (ICFN). The WWSS was used to measure the wind field parameters on rice canopy. FGPS was used to measure the pose information of the RMMEUHs when they fly over the rice canopy. ICFN was used to control and record the wind field parameters. 1#-9# WWSSs were used to measure the wind field parameters which mixed with natural wind and RMMEUH produced wind. And another one, 10#, was set up far from 9#, was mainly used to measure the natural wind speed. In order to reduce the effect from natural wind speed, treatment rules about natural wind speed were adopted before wind field data analysis. The test results showed that: the width of the wind field at X direction was significantly wider than Y direction; Unlike USREUH, there were only one peak wind speed center at X direction of RMMEUH, while two at Y direction, this phenomena might be caused by the superimposition of multiple rotors of RMMEUH, and the lateral flow of the aircraft was also one of the interferences, as a result, narrowed the width of the wind field at Y direction. Comprehensively considered about the width of wind field and battery electricity consumption, the order of the three influence factors was flight speed, takeoff weight, and flight height. Flight speed of 1.30m/s, takeoff weight of 18.85 kg, and flight height of 2.40 m were suggested as the optimization of the operation parameters for supplementary pollination in hybrid rice breeding using RMMEUH. The results provide references to develop a series of specifications of supplementary pollination in hybrid rice breeding using unmanned helicopter. [ABSTRACT FROM AUTHOR]

The wind field parameters on rice canopy which formed by rotor airflow are significantly difference among different structure of unmanned helicopter. There are direct influence among the seed setting rate, operating efficiency, and the parameters of wind field on rice canopy. To explore the optimization parameters when the uniaxial single-rotor electric unmanned helicopter (USREUH) conducted supplementary pollination, orthogonal tests of three factors (including flight operating load, altitude and speed) and three levels was developed to measure the wind field which produced by USREUH in this study. The mass of tested USREUH is 9.3 kg, its rotor diameter is 2 m, and its maximum payload is 15 kg. The measured parameters of wind field included the following: wind speed at X direction (parallel to the direction of flight heading), Y direction (perpendicular to the direction of flight heading), and Z direction (the vertical direction), and also the battery's voltage drop at each takeoff and landing of USREUH to estimate its economy. The wind field parameters of the USREUH were measured by a wireless wind speed sensor network measurement system (WWSSN), which consists of several wireless wind speed sensors (WWSS), a flight global position system (FGPS), and an intelligent control focus node (ICFN). The WWSSN is a star topology, which can realize multi-point, multi-direction, mobile, and real-time measurement for wind field parameters on rice canopy, and also can record the pose information of the USREUH when the supplementary pollination is conducted. In order to reduce the affect from natural wind speed, serveral treatment rules about natural wind speed were adopted before wind field data analysis. The test results showed that: the maximum width of wind field produced by USREUH (peak wind speed >1 m/s at Y direction) was reached 8.1 m, it was indicated that this model of USREUH could meet the basic needs of supplementary pollination of hybrid rice under the designed test conditions. The peak wind speed which produced by USREUH was mainly affected by the following factors: flight operating load, altitude and speed. The lower altitude and flight speed, along with the increasing payload, it the higher peak wind speed was expected. Considering the width of wind field and battery electricity consumption, the order of the three influence factors is flight speed, takeoff weight, and flight height. And the optimal operation parameters for supplementary pollination in hybrid rice breeding are flight speed of 1.56 m/s, takeoff weight of 14.05 kg, and flight height of 1.93 m, respectively. The conclusions provide the important reference for the studies of operation parameters optimization based on any other kinds of USREUH, which are useful to the form of specifications for supplementary pollination in hybrid rice breeding using USREUH. [ABSTRACT FROM AUTHOR]

The bionic electronic nose, a machine detection method based on bionic olfaction, enjoys a good application prospect in rice varieties classification and recognition. There are many differences between hybrid and inbred rice. In order to understand the feasibility by using an electronic nose to classify and recognize hybrid and inbred rough rice varieties, the samples' volatiles of 3 inbred rough rice varieties (Zhongxiang 1, Xiangwan 13, Yaopingxiang) and 3 hybrid rough rice varieties (Wufengyou T025, Pin 36, Youyou 122), which grow in the same area and the same season, were collected in this article by using an electronic nose (PEN3). Firstly, the contribution rates of sensors, which in sampling rough rice volatile, were analyzed by using loadings analysis, and the electronic nose's sensors in the array were selected based on feature value extraction and rough rice volatile detection. It is indicated that the sensors are keenly sensitive to sulfur-containing organics, nitrogen oxides, aromatics, and sulfur- and chlorine-containing organics, and it should be mainly used in classified rough rice varieties. After that, classification and recognition algorithms of Hybrid and Inbred Rough Rice, including PCA (principal component analysis), LDA (linear discriminant analysis), and BP neural network analysis, were developed. Results show that PCA and LDA analysis for the classification between 6 rough rice varieties did not achieve the ideal results. Neither did the classification between hybrid and inbred rough rice. There are some overlapping regions between the classification groups. It is easy to cause a blur in practical application. Compared with PCA and LDA, BP neural network has better performance in the classification of 6 different rough rice varieties, the same effect in the classification between hybrid and inbred rough rice. By using BP neural network, test results show that the accuracy of classification between 6 different rough rice varieties reaches 90% in testing samples test. For classification between hybrid and inbred rough rice, it reaches 96.7% in testing samples test. It is indicated that the bionic Electronic Nose could be a new approach, which can conduct a rapid and non-destructive classification of hybrid and inbred rough rice varieties. [ABSTRACT FROM AUTHOR]

The environmental factors during the rice growing process have wide changes and most of the energy consumption of the sensor node is used for transmitting data. Meantime, wireless sensor networks on the basis of reliable communication consuming the lowest energy, has been a hot research topic. In order to establish a long time, stable and highly reliable wireless sensor network, a node for working on the rice fields was designed. The basis experiments study the relationship between plant height, leaf area, and the growth days and the impact on the radio channel. The basis results showed that the relationship of the plant height of the rice and the growth days caused attenuation to exist according to a logarithmic model, and the regression coefficient R2 was in the range of 0.9604 and 0.9485. Plant height and leaf area increase reduced the radio signal strength and communication success rate. The experimental results also showed that increasing the transmitting power could improve communication quality because of the rice growth factor for adverse wireless channel impact. First, sensor nodes use sleeping waking up as a working mechanism to reduce power consumption. Second, to extend the working time and improve communication quality, the node uses under rice growth cycle, the communication distance, the received signal strength, the average packet loss rate and other factors, automatically adjusts the transmitting power of the energy adaptive mechanisms. The experiments demonstrated that the larger transmitting power had the effective communication distance farther and rice density and height had important impact on the wireless communication. Finally, the verification experiments results proved that if the transmitting power was less than 5 dBm, the transmitting power changes had little effect on the working current of the node. Meantime, the verification experiments showed the node operating current was less than 40 mA. Moreover, with increasing transmit power the communication success rate improved dramatically. The node reducing the transmitting power in the allowable range still resulted in a high communication success rate. With this power adaptive strategy, the wireless node working in rice tiller and heading time, the impact of transmitting power changing on the communication quality was finished. The results showed that the average packet loss rate was 5% or less, and that the received signal strength stayed within acceptable range. In short, the node designing achieved the desired purpose. [ABSTRACT FROM AUTHOR]

An impedance immunosensor was developed recently for the rapid detection of a H5 subtype avian influenza virus (AIV). The important step was to have a magnetic nanobead separator (MNS) to separate and concentrate the streptavidin-coated magnetic nanobeads which were captured with the avian influenza virus H5N1. This paper describes a compact and portable magnetic nanobead separator designed for the rapid detection of an avian influenza virus and the series of experiments for confirming the separation efficiency. These ideas came from several tries of different MNS separator designs and experiments. There were six separation holes constructed by tile-shaped NdFeBs in this MNS. It was built up of a cylinder shell with 6 cylinder containers, pairs of tile-shaped magnets, a piece of metal magnetizer, and 6 separation holes. The design was aided by Pro/Engineer software to simulate and analyze. From the measurements, the maximum magnetic induction intensity of each separation area (hole) reached 1166.2mT and its maximum grads reached 152.7T/m. Also, the ingenious configuration of MNS could be suitable for other requirements by minor amendment. The experiments on separating H5N1 virus and E. coli O157:H7 were conducted to confirm the separation efficiency of the MNS with the nanobeads in different sizes. The results showed that the MNS could separate 30, 100, and 180nm nanobeads entirely, while the separation duration was no less than 60min, 60, and 40s respectively, and the separation efficiency was higher than 96.5% under the controlled experimental condition, without any residual bead in supernatant liquid. The experiments for separation efficiency of the MNS included: a multi-point magnetic induction intensity measurement, a preliminary separation observation, a transmission electron microscope observation, a Dot-ELISA experiment, and an enumeration by a plate count experiment. All the repeatable experimental data showed that the MNS system was stable and efficient. The relative standard deviation (RSD) of the magnetic induction intensity measurement was around 3%. [ABSTRACT FROM AUTHOR]

All authors edited and revised the manuscript. B Correction to: Trials 23, 162 (2022) b B https://doi.org/10.1186/s13063-022-06083-5 b Following the publication of the original article [[1]], we were notified that the "Funding information" and "Author contribution" sections need to be updated. [Extracted from the article]

Smart farming uses advanced tools and technologies such as intelligent agricultural machines, high-precision sensors, navigation systems, and sophisticated computer systems to increase the economic benefits of agriculture and reduce the associated human effort. With the increasing demands of individualized farming operations, the internet of things is a crucial technique for acquiring, monitoring, processing, and managing the agricultural resource data of precision agriculture and ecological monitoring domains. Here, an internet of things-based system scheme integrating the most recent technologies for designing a management platform for agricultural machines equipped with automatic navigation systems is proposed. Various agricultural machinery cyber-models and their corresponding sensor nodes were constructed in a pre-production phase. Three key enabling technologies—multi-optimization of agricultural machinery scheduling, development of physical architecture and software, and integration of the controller-area-network with a mobile network—were addressed to support the system scheme. A demonstrative prototype system was developed and a case study was used to validate the feasibility and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper describes the physical and tensile properties of corn bracts during a whole harvest period by using two corn cultivars, aiming to realize efficient peeling with minimum energy performance and decrease the incidence of ear damage. The value range and change rule of tensile properties were obtained by combining mechanical experiments and numerical statistics. Meanwhile, mathematical models were established for tensile properties depending on bract moisture content and bract thickness. The experimental results show that the tensile properties of leaf blade were affected by the orientation between pulling force and longitudinal vein, and that parallel orientation was greater than perpendicular. Further, the tensile properties of leaf sheaths depended on the angle between pulling force and natural growth direction of the bract in the following order: 0° > 90° > 180°. A larger pulling force angle can improve the probability of bract fracturing at the root of leaf sheaths, which helps reduce bract residue on the peduncle. In addition, the fracture mechanisms of leaf blades and sheaths were expressed from physiological and morphological perspectives. The experimental results are believed to be able to provide theoretical guidance by which to design and optimize corn-peeling devices. [ABSTRACT FROM AUTHOR]

Cloud cover hinders the effective use of vegetation indices from optical satellite-acquired imagery in cloudy agricultural production areas, such as Guangdong, a subtropical province in southern China which supports two-season rice production. The number of cloud-free observations for the earth-orbiting optical satellite sensors must be determined to verify how much their observations are affected by clouds. This study determines the quantified wide-ranging impact of clouds on optical satellite observations by mapping the annual total observations (ATOs), annual cloud-free observations (ACFOs), monthly cloud-free observations (MCFOs) maps, and acquisition probability (AP) of ACFOs for the Sentinel 2 (2017–2019) and Landsat 8 (2014–2019) for all the paddy rice fields in Guangdong province (APRFG), China. The ATOs of Landsat 8 showed relatively stable observations compared to the Sentinel 2, and the per-field ACFOs of Sentinel 2 and Landsat 8 were unevenly distributed. The MCFOs varied on a monthly basis, but in general, the MCFOs were greater between August and December than between January and July. Additionally, the AP of usable ACFOs with 52.1% (Landsat 8) and 47.7% (Sentinel 2) indicated that these two satellite sensors provided markedly restricted observation capability for rice in the study area. Our findings are particularly important and useful in the tropics and subtropics, and the analysis has described cloud cover frequency and pervasiveness throughout different portions of the rice growing season, providing insight into how rice monitoring activities by using Sentinel 2 and Landsat 8 imagery in Guangdong would be impacted by cloud cover. [ABSTRACT FROM AUTHOR]

Existing devices for dry direct-seeded rice with film mulching in northern China have limitations such as imprecise sowing, unadjustable sowing depth, and seeding device blocking. In this regard, this study proposes a combined seeding method of 'mini shovel + telescopic pipe' for dry direct-seeded rice with film mulching. A precision seeder for dry direct-seeded rice with film mulching was developed through theoretical calculations, discrete element modelling (DEM) simulations, and field experiments. The configuration and diameter of the rollers were obtained. Twelve telescopic pipes were evenly distributed on the circumference of the roller, with a contact ratio exceeding one. This ratio reduced the slip rate of the roller effectively. Subsequently, DEM was used to develop a 33 central composite design. The response surface was established with the sowing depth as the response value. According to agronomic requirements, the sowing depth was set to 20 mm. The optimal combination of working parameters was obtained by optimizing the regression equation. The field experiments showed that the performance of the precision seeder for dry direct-seeded rice with film mulching satisfied the requirements of agricultural production, working stably and reliably. The developed device represents a useful solution for dry direct-seeded rice with film mulching. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) remote sensing platforms allow for normalized difference vegetation index (NDVI) values to be mapped with a relatively high resolution, therefore enabling an unforeseeable ability to evaluate the influence of the operation parameters on the quality of the thus acquired data. In order to better understand the effects of these parameters, we made a comprehensive evaluation on the effects of the solar zenith angle (SZA), the time of day (TOD), the flight altitude (FA) and the growth level of paddy rice at a pixel-scale on UAV-acquired NDVI values. Our results show that: (1) there was an inverse relationship between the FA (≤100 m) and the mean NDVI values, (2) TOD and SZA had a greater impact on UAV–NDVIs than the FA and the growth level; (3) Better growth levels of rice—measured using the NDVI—could reduce the effects of the FA, TOD and SZA. We expect that our results could be used to better plan flight campaigns that aim to collect NDVI values over paddy rice fields. [ABSTRACT FROM AUTHOR]

The elevation detection accuracy of the laser receiver in the laser levelling control system directly affects land-levelling operations. To effectively improve the effect of levelling operations and meet the requirements for the accuracy of elevation detection in different industries, this study optimization designed a multilevel adjustable laser receiver. First, we examined the laser signal detection technology and processing circuit, designed the photoelectric conversion array for the detection of the rotating laser, and converted it into a photocurrent signal. We also designed the filter, amplifier, and shaping and stretching circuits for analogue-to-digital conversion of the photocurrent signal. The digital signal was calculated based on the deviation of the elevation by using a microprocessor and was output by a controller area network (CAN) bus. The laser beam spot diameter transmission and diffusion were then studied, and with the detectable spot diameters were compared and analyzed. Accordingly, an algorithm was proposed to calculate the deviation of laser receiver elevation. The resolution of the elevation deviation was set to ±3 mm; however, this value could be adjusted to ±6 mm, ±9 mm, ±12 mm, and ±15 mm, according to the requirements. Finally, the laser receiver was tested and analyzed, and the test results of the elevation detection accuracy showed that when the laser receiver was within a radius of 90 m, the elevation detection accuracy was within the ±3 mm range. The outcomes of the farmland-levelling test showed that the standard deviation S d of the field surface decreased from 9.54 cm before levelling to 2.42 cm after levelling, and the percentage of sampling points associated with absolute errors of ≤3 cm was 84.06%. These outcomes meet the requirements of high-standard farmland construction. The test results of concrete levelling showed that within a radius of 30 m, the standard deviation S d of the elevation adjustment of the left laser receiver was 1.389 mm, and the standard deviation S d of the elevation adjustment of the right laser receiver was 1.316 mm. Furthermore, the percentage of the sampling points associated with absolute elevation adjustment errors of ≤3 mm in the cases of the two laser receivers was 100% after levelling, whereas the standard deviation S d of the sand bed surface was 0.881 mm. Additionally, the percentage of the sampling points associated with absolute errors of ≤3 mm was 100%. This met the construction standards of the concrete industry. [ABSTRACT FROM AUTHOR]

Droplet characteristics are identified as essential factors in agricultural spray application. The aims of this study were to analyse the influence of spray parameters on droplet characteristics and to determine possible candidate sprays that would produce the same droplet size categorizations as the American Society of Agricultural and Biological Engineers (ASABE) standard S-572.1 for air induction nozzles (AINs). Six different orifice sizes of the Billericay Farm Services (BFS) air induction (AI) flat fan hydraulic nozzles (the air bubblejet) were examined at different spray pressures (200 kPa, 300 kPa, 400 kPa, 500 kPa, 600 kPa and 700 kPa) and concurrent air velocities (2 m/s, 3 m/s, 4 m/s and 5 m/s). The influences of spray parameters on the droplet characteristics were analysed using analysis of covariance (ANCOVA) and analysis of variance (ANOVA). Results showed that: (1) The values of droplet characteristics and the results of ANOVA were significantly different before and after eliminate the influence of dynamic surface tension (DST) on droplet characteristics by ANCOVA; (2) (a) the reduction rates of the droplet diameter sizes decreased with increasing spray pressure; (b) air velocities of 2 m/s and 5 m/s resulted in smaller droplets reports, and air velocities of 3 m/s and 4 m/s are more suitable for agricultural spray applications; (c) a larger nozzle orifice size not always result in a larger droplet size and (3) Fine, Medium, Coarse, Very Coarse and Extremely Coarse droplet classification categories as the ASABE S-572.1 standard categorizations were determined to classify AINs. [ABSTRACT FROM AUTHOR]