Search

The single-pass, split-stream harvest of corn grain and stover has been extensively studied. Challenges for these systems include the logistics and economics of handling separate grain and stover streams. Single-pass, single-stream processes have been explored using a self-propelled forage harvester to collect whole-plant corn as a biomass feedstock. However, due to the processing done by the self-propelled forage harvester, a significant portion of the grain fraction is damaged during harvest limiting its marketability. To evaluate an alternative system, a combine harvester was modified with a rear blower to collect corn stover, facilitating the collection of the grain and stover fractions into the same wagon, creating an aggregate, whole-plant corn material. Utilizing this system, a plot study was conducted to compare it to a self-propelled forage harvester. Parameters studied for system performance were yield, grain damage, and geometric mean particle size. While the combine system reduced grain damage (p < 0.001) by 18 percentage points compared to the self-propelled forage harvester and had a similar whole plant particle size (p = 0.11), it collected 1.86 Mg DM ha−1 less biomass (p < 0.001). The combine harvester with a stover collection system provides a method to collect whole-plant corn as a biomass feedstock that maintains a large portion of the grain integrity but decreases dry matter yield. [ABSTRACT FROM AUTHOR]

An intensive rice–wheat rotation system produces high yields but leaves abundant residue in the fields after harvest, which interferes with seeding operation. This residue needs to be managed through incorporation or mulching for timely sowing of wheat. Presently, straw incorporation or direct sowing of wheat in stubble fields requires highly energy-intensive machinery achieve desired results. Therefore, a seeding attachment having concave disc furrow openers was developed for combine harvester to sow wheat simultaneously harvesting rice. The performance of the seeding attachment was evaluated at three levels of forward speeds (i.e. 1.5, 2.1, and 2.8 km/h) and stubble heights (i.e. 38, 45, and 52 cm) in terms of plant emergence, effective tillers, grain yield, fuel consumption, and field capacity of the combine harvester. The plant emergence and effective tillers were found at par as compared to other prevalent methods, whereas the average field capacity, fuel consumption, and grain yield of the developed attachment were found 0.43 ha/h, 9.2 l/h, and 4430.7 kg/ha, respectively. The total energy used for wheat crop establishment using the developed seeding attachment was 1343.2 MJ/ha and about 63.35% of the average energy demand from other methods (2113.46 MJ/ha). The use of seeding attachment may improve the utility of a combine harvesters for the sowing of wheat while rice harvesting. The current study indicated a significant gain in energy-use efficiency, and a reduction in environmental mitigation is possible with developed seeding attachment. [ABSTRACT FROM AUTHOR]

The multi‐floral oat (Avena sativa L.) inflorescence influences grain size and shape distributions, affecting the physical attributes of grain quality such as plumpness, size, and uniformity. While the grain size and shape distribution has been characterized as multi‐modal, very little is known about the genetic determinants of those distributions and their properties. The goal of this study was to model grain size and shape distribution using a finite mixture distribution approach and propose new distributional traits (i.e., emerging distributional traits) to characterize genotypes. We evaluated 47 oat genotypes in four highly replicated field experiments. Grains of three panicles per plot were individually threshed and scanned. Grain area, length, width, and roundness were obtained from each grain‐based image, while emerging distributional traits were evaluated using a finite mixture distribution approach. Finally, grain size distributions from hand‐threshed panicles (representing the full biological distribution) were compared with the grain size distributions of grains harvested with a combine harvester representing commercial harvest where small grains may be blown out. The heritability of all grain traits was high (0.89–0.94), and trait distributions differed among genotypes. Grain area and length show bi‐ and trimodal distributions, while grain width and roundness are uni‐ and bimodal. Although the full biological distribution of grains differed from the combine‐harvested grains, their genetic correlations were high, suggesting the combine‐harvested distributions can be used as a proxy for full biological distributions. This study proposes a straightforward methodological approach to model grain attributes that can aid in quality evaluations for genetic studies, breeding decisions, and industry characterization. [ABSTRACT FROM AUTHOR]

There are appreciable physical losses to the header of a combine harvester operating in the fields during harvesting. To reduce these losses, it is desirable to effectively control the header height of the combine harvester. In the present study, a soil bund detection system has been developed for the header of the combine harvester using an ultrasonic sensor and tested under field conditions. In the laboratory, the best among five ultrasonic sensors (HC-SR04, US-100, JSN-SR04T, GY-US42 and MB-7092) was selected based on accuracy and response of the sensor operated for 27 treatments of soil bund height, sensor height and stubble density. Consequently, the soil bund detection system was developed using the US-100 sensor, Arduino UNO R3 microcontroller and two relays to control the actuator on prototype. The results showed that during sensor selection, the US-100 sensor had a maximum accuracy of 84.83% in BH3SH1SD1 treatment and a maximum response of 91.38 readings/sec in BH2SH2SD3 treatment. Furthermore, the developed system showed a maximum accuracy of 88.89% and 85.58% without the actuator in the field and with the actuator under laboratory conditions respectively. The highest response of 64.68 and 62.70 readings/sec was recorded for systems without the actuator in the field and with the actuator under laboratory conditions respectively. The study reveals that the increase in stubble density and sensor height causes a decrease in the accuracy, while the increase in bund height significantly increases the accuracy of the system. Moreover, an increase in vehicle speed causes a decrease in the response of the system, whereas with increasing bund height and stubble density, there is an increase in the response. [ABSTRACT FROM AUTHOR]

At present, the speed of the reel of soybean combine harvester is mainly adjusted manually, and basically does not have the ability to automatically adjust the speed of the reel according to changes in crops or working speed. In the maize-soybean strip intercropping mode, soybean plants are densely planted. During harvesting, the feeding rate increases, making it even more necessary to adjust the reel speed according to the growth status of the crops. This article uses PLC as the main control platform to design a reel speed control system for the existing combine harvester. Tests have shown that the control system can meet the requirements for reel speed control. The relative error of the reel control system's speed test is 2.6%, the relative error of the operating speed is 6.77%, and the maximum relative error of the automatic control of the reel speed is 5.38%. Compared with traditional reel, it reduces header loss by 2.12%. The soybean combine harvester reel speed control system designed in this article can realize automatic adjustment of the reel speed, reduce feeding losses caused by changes in crop height, changes in feed volume, and untimely adjustment of the reel, and can reduce header loss, increased crop yield. [ABSTRACT FROM AUTHOR]

A novel method for the mechanical detection of wheat biomass, based on the mechanical properties of wheat plants, is proposed to enable the quick assessment of wheat biomass. The mechanical model developed for the wheat plants, based on the variable cross-section beam elastic bending theory, can be used to analyse the interactive forces between the reel and wheat plants, and predict wheat biomass based on the magnitude of the force. The influence of wheat ears on deflection was incorporated into the model. The accuracy of wheat plant deflection forces obtained using the model was confirmed through theoretical analyses, simulations and experimental measurements. Moreover, deflection tests and posture analysis were performed on the wheat plants for different locations at which the deflection forces were acting and for different plant densities. Experiments focusing on reel operation demonstrated that the deflection forces exerted by the reel rod on wheat plants could be used to predict the number of bent plants, which would subsequently help in wheat biomass estimation. The study found that the influence of the wheat ear on the deflection force significantly increased as the plant deflection increased. The deflection force was most effective at two-thirds of the height of the wheat plant. Moreover, the higher the plant density, the greater the deflection force, which was closely correlated with wheat biomass. A model was established based on the results of the linear regression performed to determine the relationship between the deflection force acting on a wheat plant and its biomass. The model with a determination coefficient of 0.9155 provided a theoretical basis for detecting the feed quantity of the combine harvester. • Analysed the interaction force between the combine harvester reel and wheat plants. • A mechanical model of wheat plant deflection was established. • The method of bending theory of elastic beam with variable cross-section is used. • Prediction of wheat biomass based on interaction force. [ABSTRACT FROM AUTHOR]

This research focuses on designing and evaluating ergonomic self‐propelled machinery seats to reduce whole‐body vibration (WBV) exposure among male and female agricultural workers. Subjects without musculoskeletal disorders were selected, and their anthropometric parameters were analyzed. An ergonomically refined seat, considering anthropometric dimensions and vibration reduction, was developed and tested. Vibration isolators using piezoelectric material enhanced operator comfort. In a laboratory experiment, real‐time one‐third octave band WBV data were collected using various seat types and engine speeds. At 1200 rpm, female operators experienced WBV levels between 3.42 and 13.40 m/s², while males ranged from 3.13 to 12.20 m/s². At 1600 rpm, females (T‐1) had WBV levels of 20.20–42.39 m/s², and males recorded 18.90–40.12 m/s². At 2000 rpm (T‐1), female operators WBV ranged from 246.71 to 303.45 m/s², and males from 248.10 to 300.13 m/s². At 2400 rpm (T‐1), female operators experienced WBV from 385.29 to 457.87 m/s², and males from 381.57 to 445.50 m/s². An integrated approach with artificial neural networks and genetic algorithms optimized machine operating parameters, resulting in minimum WBV levels. The highly accurate Multilayer Feed‐Forward Artificial Neural Network model (2‐10‐1) had a correlation (R) of 0.996 and a low mean‐squared error of 0.198. This research underscores the effectiveness of seat isolators in reducing vibrations and highlights the importance of considering both seat design and engine speed, especially concerning gender‐specific differences in vibration tolerance. It provides valuable insights for improving the comfort and safety of self‐propelled machinery operators in agriculture. [ABSTRACT FROM AUTHOR]

The wheat harvesting boundary line is vital reference information for the path tracking of an autonomously driving combine harvester. However, unfavorable factors, such as a complex light environment, tree shade, weeds, and wheat stubble color interference in the field, make it challenging to identify the wheat harvest boundary line accurately and quickly. Therefore, this paper proposes a harvest boundary line recognition model for wheat harvesting based on the MV3_DeepLabV3+ network framework, which can quickly and accurately complete the identification in complex environments. The model uses the lightweight MobileNetV3_Large as the backbone network and the LeakyReLU activation function to avoid the neural death problem. Depth-separable convolution is introduced into Atrous Spatial Pyramid Pooling (ASPP) to reduce the complexity of network parameters. The cubic B-spline curve-fitting method extracts the wheat harvesting boundary line. A prototype harvester for wheat harvesting boundary recognition was built, and field tests were conducted. The test results show that the wheat harvest boundary line recognition model proposed in this paper achieves a segmentation accuracy of 98.04% for unharvested wheat regions in complex environments, with an IoU of 95.02%. When the combine harvester travels at 0~1.5 m/s, the normal speed for operation, the average processing time and pixel error for a single image are 0.15 s and 7.3 pixels, respectively. This method could achieve high recognition accuracy and fast recognition speed. This paper provides a practical reference for the autonomous harvesting operation of a combine harvester. [ABSTRACT FROM AUTHOR]

Based on patent data, we revealed the global technical distribution, research topics and competition trend of grain combine harvester technology. It provided reference for the technology mining and industrialization development of grain combine harvester in China. Based on IncoPat patent database, we analyzed the global innovation layout and competitiveness of grain combine harvester from the perspectives of patent overall layout, patent application trend, patent applicant and its research topics. The results showed that the technology of combine harvester entered a new round of innovation activities in recent years. The patents from China, the United States, Japan and Germany accounted for 86. 95% of the total world. The gap between China and advanced technology countries in patent application narrowed. International agricultural machinery giants, such as Kubota, Iseki, Deere Company, CNH Industrial, were the main enterprises of grain combine harvester technology innovation. Great attention had been paid to the control and measurement devices of combine harvesters in China, and further research were needed to catch up with the world’s advanced level in grain separation and cleaning. In addition, China’s grain combine harvester innovation was facing problems like patent blockade from international agricultural machinery giants, low share of high-value patents, insufficient patents distribution overseas, and weak technological innovation competitiveness of domestic enterprises. In the future, China should take the advantage of backwardness, and carry out patent layout with invalid patents. Furthermore, cooperation among universities, research institutions and enterprises should be strengthened to promote the transformation of technological achievements. [ABSTRACT FROM AUTHOR]

The real-time monitoring of corn yield by a combine harvester is a critical data source for constructing the yield histogram, which significantly benefits precision management and decision-making in modern precision agriculture. While widely used, the current photoelectric sensor-based yield monitoring method has limitations. It detects the corn height on each scraper and calculates the yield through a geometric formula. However, it neglects the noticeable difference in the corn stacking patterns affected by factors such as feeding volume, terrain, and driving speed. This oversight often results in low accuracy and poor stability in the prediction of corn yield, highlighting the need for a more advanced approach. To resolve this, we employ EDEM discrete element simulation to demonstrate the large difference of corn stacking patterns on the scraper of the elevator corresponding to feeding volume. Then, we develop a real-time monitoring system on our selfdeveloped double elevator testing rig for carrying out a composite dataset for training three machine learning algorithm-based models, namely Deep Neural Networks (DNN), Gradient Boosting Machine (GBM), and Random Forest (RF). Importantly, these models have undergone rigorous validation under various feeding volumes, ensuring their robustness and reliability. The auxiliary elevator speed is meticulously set at 150r/min, 225r/min, and 450r/min, providing a comprehensive performance assessment. The results denote that the DNN model performs best and is stable, with a coefficient of determination (R²) of 0.998, root mean square error (RMSE) of 0.526, and mean absolute error (MAE) of 0.425. The paper also performs field experiments to test the proposed three prediction models and the system. The results also denote the DNN-based prediction model's best performance for the lowest relative error of 2.29% and the highest average accuracy of 97.85%. Consequently, the proposed real-time corn yield monitoring system achieves high accuracy and reliability for the combine harvester applications. [ABSTRACT FROM AUTHOR]

To reduce grain loss during pickup and prevent stalk entanglement in buckwheat harvesters, thereby improving the quality of mechanized harvesting, a three-stage pickup conveyor roll with a ground-level rotary knife-type pickup header was designed and tested. This paper, based on the growth characteristics of buckwheat, determined the three-stage pickup conveying process and the overall structure of the ground-level rotary knife-type pickup header. Kinematic analysis and parameter design of the rotary knife-type pickup roll were conducted. Finally, a physical prototype was fabricated, and field performance tests were carried out, using machine forward speed and pickup roll rotational speed as influencing factors and pickup loss rate as an evaluation metric. Results showed that the interaction between pickup roll rotational speed and forward speed had a significant effect on the pickup loss rate, with forward speed having a greater impact than pickup roll rotational speed. Under consideration of their interaction, when the pickup roll rotational speed was within the range of 396–457 r/min, and the forward speed was between 0.9–1.0 m/s, the pickup loss rate was minimized. Based on the regression equation model, the predicted optimal conditions were a forward speed of 1.0 m/s and a roll pickup speed of 396 rpm. Under these conditions, the test results showed a pickup loss rate of 5.235%, indicating good pickup performance. This research provides a reference for the design of pickup devices in grain combine harvesters. [ABSTRACT FROM AUTHOR]

Cereal grain crops are used as main food and raw feed materials all over the world. Among cereal crops, wheat occupies a leading place as the most valuable crop. Harvesting is the most energy-intensive stage in wheat cultivation. Therefore, improving technologies and tools to reduce energy costs in this process is an urgent task. A new stripping and threshing unit for harvesting cereal crops has been developed, allowing the harvesting of grain at both full maturity and in the early stages of maturity, when the grain has an increased content of protein and amino acids and is a valuable raw feed material. The new unit consists of a stripping and threshing unit. The stripping unit consists of a stripping drum and stripping combs. The threshing unit contains replaceable decks that collide with the grain, separating it from the ear; an auger for transporting the heap to the unloading device; and a blade beater with a cut-off shield. Wheat grain in the early stages of maturity has a strong connection with the ear, as a result of which harvesting such grain can be energy-intensive and impractical. In this regard, the purpose of this research was to study the dynamics of changes in the energy intensity of the wheat grain harvesting process during ripening and to compare the energy intensity of the harvesting process with the new unit with the energy intensity of a combine harvester. The methodology is based on measuring torque on the shaft of the stripping and threshing unit. The results show that the power required for stripping by the new unit is reduced from 8–10 kW to 2–4 kW, which is 2.5–4 times lower. The difference in power values between harvesting at the hard wax ripeness stage and full ripeness is only 1–1.5 kW, indicating the feasibility of harvesting grain at this stage. [ABSTRACT FROM AUTHOR]

Lumajang is one of the districts in East Java where the majority of farmers grow rice. One of the causes of the decrease in productivity is due to the delay in harvest time due to the lack of rice harvesting labor and the type of harvesting machine used is inefficient. The purpose of this study is to measure the factors that influence farmers' interest in using Combine Harvester. The sample needed in this study is 93 respondents. The data analysis technique used is descriptive quantitative analysis using Structural Equation Modelling Partial Least Square (SEM-PLS). There are four exogenous variables, including the characteristics of farming, counseling and information, farmer characteristics, and the role of credit. The results of the study show that there are three factors that have a significant influence on farmers' interest, namely innovation, behavior control and attitude. The most significant result was the attitude factor with a P value of 0.012. Meanwhile, the factor that does not have a significant effect is the subjective norm. [ABSTRACT FROM AUTHOR]

To address the issue of header loss in millet combine harvesters, a double-chain millet harvester header was designed based on the principles of contact mechanics and tribology. Key component parameters of the header were determined, with the divider length and width measuring 0.56 m and 0.30 m, respectively. The divider angle was 40°, and the spiral angle was also 40°. A prototype was manufactured, and field performance tests were conducted. The results showed that the total header loss rate of the double-chain header was lower than that of the single-chain header under various combinations of header height and harvesting speed. The lowest total header loss rate, 3.12%, occurred when the header height was 0.2 m and the harvesting speed was 1.667 m/s, with a grain loss rate of 0.55% and a spike loss rate of 2.57%. This research provides a theoretical foundation for the development of low-loss, high-efficiency millet combine harvesters. [ABSTRACT FROM AUTHOR]

Aiming at the current peanut pickup combine harvester seedling vines crushing mechanism operation qualified seedling length rate is low, the impurity rate is high, and the seedling vines crushing mechanism is optimized design. On the basis of the material characteristics of peanut seedling vines, taking the crushing mechanism as the research carrier, the interaction mechanism of the seedling vine mechanism was analyzed. Establish the mechanical model and motion trajectory model in the crushing process, simulate the peanut seedling vines crushing process based on the discrete element method, analyze the influence of the cutter shaft rotational speed, movement speed, and bending angle on the crushing of peanut seedling vines, and establish the regression model, and the results of the research show that the influence factors in the main order of priority are: knife shaft speed > movement speed > bending angle The optimal parameter combination is knife shaft speed 2171.94 r/min, movement speed 0.79 m/s, and bending angle 45°. According to the field test conditions, it is determined that the knife shaft rotational speed of 2170 r/min, movement speed of 0.8 m/s, and bending angle of 45° can make the peanut seedling vines crushing mechanism of the work performance to achieve a qualified seedling length rate of 97.292%, the rate of impurity content of 2.746%, and the error with the predicted value is less than 2%, which indicates that this study can provide a reference for the optimal design of the seedling vines crushing mechanism of the peanut pickup combine harvester. [ABSTRACT FROM AUTHOR]

Aiming at the problems of poor passability of a tracked chassis due to small plots, complicated road conditions and steep slopes during mechanized potato harvesting in hilly and mountainous areas. To design a potato combine harvester and take the tracked chassis of the harvester as the research object to study its driving performance under typical road conditions in mountainous areas. Firstly, mechanical analysis and theoretical calculation are carried out on the tracked chassis to obtain the relevant parameters of key components, and secondly, its driving performance is analyzed to obtain the driving limit values of passing performance under different working conditions; RecurDyn software was used to establish the dynamics simulation and analysis model of the whole machine, and the driving limit values of the harvester were determined under five different road conditions through simulation. The results show the following: the driving limit gradient angle is 20° in cross-gradient conditions, 25° in longitudinal up-gradient conditions, 25° in longitudinal down-gradient conditions, the limiting height of the chassis that can be overpassed in obstacle-crossing conditions is 450 mm, and the limiting width of the chassis that can be spanned in trench-crossing conditions is 1200 mm. The simulation results were verified through field tests, and the results of the field tests showed that the harvester met the requirements of stable travelling on longitudinal slopes of 24°, climbed over a 450 mm straight wall and crossed over a 1200 mm trench, which were similar to the simulation results, indicating that the simulation results were accurate and feasible, and met the design requirements for the travelling passage of the crawler potato harvester. This study provides an in-depth understanding of the tracked chassis of the potato combine harvester in hilly mountainous areas, with a view to providing reference for the design of tracked harvesters for other crops in hilly mountainous areas. [ABSTRACT FROM AUTHOR]

In order to solve the problems of high impurity rate and large loss rate in the whole fresh peanut harvesting and production process in hilly areas of China, the method of computational fluid dynamics (CFD) and discrete element (DEM) coupling is used to examine the gas–solid two-phase simulation of the cleaning device of the crawler fresh-peanut-picking combine harvester. In addition, the Box–Behnken test method is used to analyze the influence of different parameters on the impurity content and loss rate of materials in the cleaning process by taking the fan speed, feed amount, and air inlet angle as the test factors, and the optimal combination of working parameters is sought. The simulation results show that when the fan speed is 2905.07 r/min, the feed rate is 0.80 kg/s, the air inlet angle is 43.14°, the impurity content is 7.32%, and the loss rate is 4.78%. Compared with the simulation test results, the impurity content is increased by 0.68%, and the loss rate is increased by 1.24%, which verifies the reliability of the simulation model, and the research results provide some technical support for the improvement of the cleaning device in the later stages. [ABSTRACT FROM AUTHOR]

The mechanized harvesting level of potatoes in the arid areas of Northwest China is low and mainly relies on simple machinery to dig the soil surface, and then people manually pick up and bag the potatoes. This harvesting method has the problems of a high labor intensity, low operation efficiency, and high labor cost. Based on this, a wheeled-chassis potato combine harvester with integrated bagging and ton bag-lifting systems was developed, which could complete potato digging, potato–soil separation, potato–film separation, automatic bagging, and field ton bag lifting in one go. Firstly, based on the agronomic requirements and unique terrain characteristics of potato planting in this area, the structural design of the whole machine was completed with SOLIDORKS 2019 3D software. Secondly, the dynamic model was established for a numerical analysis, and the core parameters of key components were determined. The field experiments showed that the potato loss rate was 2.1%, the potato damage rate was 1.7%, the skin breaking rate was 2.5%, the impurity content was 1.9%, and the productivity was 0.15~0.23 hm2/h. The above field test indexes met the requirements of national and industrial standards. [ABSTRACT FROM AUTHOR]

Two-stage harvesting is the main method used for the mechanized harvesting of peanuts in China, in which the pickup device is a core part of the combine harvester. In order to solve the problem of pod loss caused by "stack" and "loss picking" from peanut plants when using a traditional spring-finger cylinder pickup device, an optimal spring-finger cylinder peanut pickup mechanism was designed and its picking properties were tested. Based on the picking characteristics and picking force analysis when considering a peanut plant windrow, the ideal picking attitude and swing rule of the spring-finger were determined, and the cam slide, as the core element of the spring-finger cylinder peanut pickup device, was optimized. A mathematical model of the cam cylinder center line was established according to the swing law of the four picking stations utilizing the spring-finger. MATLAB and ADAMS were used to establish a simulation of the pickup mechanism, and kinematics and dynamics simulation analyses of the pickup mechanism were carried out. According to the design results, a prototype was constructed and a running pickup test was carried out. The peanut plant picking experiments indicated that the phenomenon of peanut plant stacking had significantly disappeared. Furthermore, through response surface analysis, the optimal working parameters of the picking device were obtained as follows: the forward speed Vm was 48.0 m/min, the rotational speed N was 50 r/min, and the ground height H was −16.8 mm. The picking rate of peanut plants was 99.21% and the pod loss rate was 1.79% under two harvesting conditions, with a peanut plant moisture content of 15% to 17%. This study provides technical support for the future design of picking devices for two-stage peanut pickup harvesters. [ABSTRACT FROM AUTHOR]

The threshing mixture of Cyperus esculentus (Tiger nut) planted in sandy areas is complex during harvesting, and there are problems of high impurity rate and high cleaning loss rate of the seeds. In this paper, the threshing mixture of Cyperus esculentus is taken as the research object, and the suspension speed of each component is measured to design an “airflow + vibration” sieving device. Use the vector polygon method to explore the law of motion of the vibrating sieve, establish the force model of the seeds on the sieve surface, and analyze the conditions for the seeds to penetrate the sieve. According to the principle of seeds penetrating the sieve and long stalks not penetrating the sieve, the geometric model of sieve blades opening degree adjustment mechanism is constructed. Study of the conditions under which long stalks can be thrown out of the machine. The experiment bench of the cleaning device was built, and the evaluation indexes were the rate of seed impurity and the rate of cleaning loss of the device, and the crank speed, sieve blades opening degree and fan speed were used as the experiment factors to study the influence law of each influencing factor on the evaluation index through single-factor experiment. Using response surface methodology to find the optimal combination of working parameters of the cleaning device. To verify the device’s application on the combine harvester to improve the effectiveness of the cleaning operation of the Cyperus esculentus combine harvester. [ABSTRACT FROM AUTHOR]

The combine harvester equipped with attitude-adjustment functionality significantly enhances its adaptability to complex terrain but often struggles to maintain the reliability of its mechanisms. Therefore, investigating the dynamic load characteristics of the attitude-adjustment mechanism becomes imperative. This article employed the DEM–FMBD (Discrete Element Method–Flexible Multibody Dynamics) bidirectional coupling simulation method to establish a multibody dynamic model of a tracked combine harvester. The study delved into the interaction mechanism and dynamic stress response characteristics between the tracked chassis and the complex terrain under various height adjustments, lateral adjustment angles, longitudinal adjustment angles, and different field-ridge crossing methods. Finally, the accuracy of the coupled simulation model was validated through a constructed stress detection system. The research findings revealed that the displacement and tilt angle deviation of the hydraulic cylinders utilized to execute the chassis adjustment actions in the constructed coupled simulation model was less than 5%, and the deviation between the simulation results and the actual maximum dynamic stress under multiple working conditions ranged from 7% to 15%. This verification confirmed the effectiveness of the DEM–FMBD coupled simulation method. Under different adjustment conditions, the maximum stress position was consistently distributed in the same area of the left-front and left-rear rotating arms. The primary and secondary effects of the various parts of the adjustment mechanism on the overall reliability of the chassis were as follows: left front > right front > left rear > right rear. By implementing the middle height with the adjustment strategy, the dynamic stress extreme value of the adjustment mechanism can be effectively reduced by 21.98%, thereby enhancing the structural stability of the chassis. [ABSTRACT FROM AUTHOR]

Sensors are very import parts of the IoT (Internet of Things). To detect the cleaning loss of combine harvesters during operation, a new detection method based on acoustic signal was proposed. The simulation models of the impact among grain, stem and plate were established by using the ALE algorithm, and the vibration excitation characteristics of the grain and stem were investigated; the results showed that both grain and stem signal were generated by surface vibration's excitation of the air, and the highest amplitudes of grain and stem signal were 15 kHz and 7 kHz respectively, which made it possible to distinguish grain and stem impact acoustic signals. Therefore, this paper proposed a novel method to separate the grain and stem signals by identifying the characteristic frequency area and subsequently an improved EMD denoising method based on an autocorrelation function was proposed. The critical stratum of EMD was identified based on the autocorrelation value of the eigenmode function, and the improved de-noising method was able to effectively remove the noise and the stem signal. To verify the feasibility of the improved denoising method, a field wheat harvesting experiment was conducted to acquire the actual acoustic signal of the cleaning operation. Data processing results showed that the average error of the comparison between the detected loss amount and the actual loss amount was 6.1%. This paper presents a novel approach for researching combine harvester cleaning loss detection and denoising methods. [ABSTRACT FROM AUTHOR]

The threshing cylinder will wear and deform during the threshing process, causing dynamic balance problems. The combine harvester has multiple vibration excitation sources and a complex vibration environment, making it challenging to extract weak unbalanced signals from strong background noise. A novel three-step filtering framework is proposed in this paper. A zero phase filter was used as the pre-processing layer to filter out the high frequency components in the original signal and reduce the number of parameter-adaptive variational mode decompositions (PAVMD) needed. The PAVMD was used to decompose the non-stationary vibration signal before Adaptive Neuron Linear (Adaline) function was used to fit sinusoidal signal parameters. A measurement index, termed the correlation amplitude (CA) index, is constructed. The parameterisation of PAVMD was guided by the CA index, and the modal component of the unbalanced fault features were located. The simulation and real cylinder signals proved that the proposed method could effectively extract unbalanced signals under noise interference, and the unbalance was identified accurately by the influence coefficient method. Experiments on a threshing cylinder showed that the amplitude identification error was <24 g in single-sided unbalance identification, and the amplitude identification error was <27 g in double-sided unbalance identification. The proposed method had high robustness and small identification error, especially under short-time working conditions, compared with other similar approaches. • Unbalance signal extraction method based on parameter-adaptive VMD was proposed. • It uses a novel three-step filtering framework for signal extraction. • Experiments on threshing cylinder demonstrated the effectiveness and advantages. [ABSTRACT FROM AUTHOR]

Agricultural machinery has been widely used in large-scale operation and wide distribution in recent years. However, the returning duration of refueling and queuing has seriously limited the operational efficiency of agricultural machinery, particularly in tens of acres or even hundreds of acres of land. Apparently, the return refueling cannot fully meet the requirements for the continuous operation of agricultural machinery in the context of large-scale production. It is very necessary to guarantee the fuel rationing and supply of agricultural machinery with less time and high yield in the field. Fuel rationing in the field for agricultural machinery refers to the fuel supply point distributing the required amount of fuel to the farmland, where the agricultural machinery is located within the required time and completing fuel refueling. Fuel rationing in actual agricultural production includes fuel delivery into the field via filling buckets, and mobile refueling service by mobile refueling trucks. The rationing relies mainly on unsafe, untimely, and manual decision-making with a low level of digitization. It is still lacking in the systematic decision-making on rationing, in order to improve the efficiency of fuel rationing and distribution cost-saving. In this study, a fuel rationing in-field strategy was proposed using an intelligent management platform. The fuel demand of agricultural machinery was combined to utilize the agricultural Internet of Things (IoT), taking the synergistic advancement of "demand analysis-order allocation-route planning" as the core. Firstly, a two-stage mathematical model of fuel rationing in agricultural machinery was established using real-time data and the theory of trustworthiness in the intelligent management platform. In the first stage of pre-optimization, a multi-objective vehicle route planning model was established with the fuzzy demand and fuzzy time window using the platform data. In the second stage, the distribution route planning was re-routed to update the relevant information for undelivered orders using the dynamic events in agricultural production. Secondly, the solution was designed after the two stages. Taking the lowest total distribution cost and the highest total satisfaction as the objectives, a multi-objective cooperative co-evolutionary genetic method was applied to realize the distribution route planning using an order analysis. The dynamic optimization was realized to obtain the dynamically optimal scheme of fuel rationing. Finally, an empirical study was conducted with the Nenjiang Farm. An intelligent management platform was selected to implement the scheduling of agricultural machinery. According to the Beidou navigation satellite system terminal carried by the agricultural machinery, the operation data was acquired in the field, such as the location, the amount of operation, and the status information. The production data of the farm was also adopted to conduct simulation experiments. A comparison was then made between the distribution cost and current indicators to verify the feasibility and practicality. The function of fuel rationing was realized in field planning. The results show that high satisfaction and distribution cost-saving were achieved in the fuel rationing in the field for the agricultural machinery, according to the real-time data from the intelligent platform. The final scheme of dynamic optimization was reduced to 14 distribution routes, compared with the current one. The total distribution cost was reduced by about 15 times. The satisfaction rate of 72.85% was slightly lower than the actual one. The relevant functions were promoted in the intelligent platform for agricultural machinery. The finding can provide a scientific basis for the intelligent management of fuel rationing in the field of agricultural machinery. [ABSTRACT FROM AUTHOR]

Strong impacts and vibrations exist in various structures of rice combine harvesters in harvesting, so the bolt connection structure on the harvesters is prone to loosening and failure, which would further affect the service life and working efficiency of the working device and structure. In this paper, based on the vibration signal acquisition experiment on the bolt and connection structure of the vibrating screen on the harvester, failure feature identification is studied. According to the sensitivity analysis results and the primary extraction of the time-frequency feature, most features have limitations on the identification of failure features of vibrating screen bolts. Therefore, based on the establishment of a high-dimensional feature matrix and multivariate fusion feature matrix, the validity of the feature set was verified based on the whale optimization algorithm. And then, based on the SVM method and high-dimensional mapping of the kernel functions, the high-dimensional feature matrix is trained by the LIBSVM classification decision model. The identify success rates of time domain feature matrix A, frequency domain feature matrix B, WOA-VMD energy entropy matrix C, and normalized multivariate fusion feature matrix G are 64.44%, 74.44%, 81.11%, and more than 90%, respectively, which can reflect the applicability of the failure state identification of the normalized multivariate fusion feature matrix. This paper provided a theoretical basis for the identification of a harvester bolt failure feature. [ABSTRACT FROM AUTHOR]

In view of the problem that peanut harvesting in hilly areas mainly involves fresh food, and that the peanut-picking purity rate is low and there is high breakage in the peanut-harvesting process, key components such as the picking system of a fresh-peanut-picking crawler combine harvester, the picking tooth, and the concave screen were designed, and ANSYS Workbench 2020 software was used to check the reliability of the picking roller under working conditions in hilly areas. In the process of equipment operation, the picking purity rate and breakage rate were the main evaluation indexes, and the Box–Behnken test method was used to study the speed of the peanut-picking roller, the feeding amount, and the picking gap as the test factors. The results showed that the picking purity rate is 98.95%, with an error margin of 0.98%, compared to the predicted value under the conditions of 342 r/min speed, 0.75 kg/s feeding amount, and 32 mm picking gap. The breakage rate is 4.23% and the error is 0.4% compared with the predicted value, indicating that the optimized model is reliable and predictive. This study provides a theoretical basis for the optimal design of the peanut-picking system of peanut-picking combine harvesters in hilly areas. [ABSTRACT FROM AUTHOR]

During the operation of combine harvesters, the cutting platform height is typically controlled using manual valve hydraulic systems, which can result in issues such as delays in adjustment and high labor intensity, affecting both the quality and efficiency of the operation. There is an urgent need to enhance the automation level. Conventional methods frequently employ single-point measurements and lack extensive area coverage, which means their results do not fully represent the terrain's variations in the area and are prone to local anomalies. Given the inherently undulating terrain of farmland during harvesting, a control strategy that does not adjust for minor undulations but only for significant ones proves to be more rational. To this end, a sine wave superposition model was established to simulate three-dimensional ground elevation changes, and an area array LiDAR was used to collect 8 × 8 data for the header height. The effects of mounds and stubble on the measurement results were analyzed, and a dynamic process simulation model for the solenoid valve core was developed to analyze the on/off delay characteristics of a three-position four-way electromagnetic directional valve. Moreover, a physical model of the hydraulic system was constructed based on the Simscape module in Simulink, and the Bang Bang switch predictive control system based on position threshold was introduced to achieve early switching of the electromagnetic directional valve circuit. In addition, an automatic control system for cutting platform height was designed based on an STM32 microcontroller. The control system was tested on the hydraulic automatic control test rig developed by Shanxi Agricultural University. The simulation and experimental results demonstrated that the control system and strategy were robust to output disturbances, effectively enhancing the intelligence and environmental adaptability of agricultural machinery operations. [ABSTRACT FROM AUTHOR]

In complex field environments, wheat grows densely with overlapping organs and different plant weights. It is difficult to accurately predict feed quantity for wheat combine harvester using the existing YOLOv5s and uniform weight of a single wheat plant in a whole field. This paper proposes a feed quantity prediction method based on the improved YOLOv5s and weight of a single wheat plant without stubble. The improved YOLOv5s optimizes Backbone with compact bases to enhance wheat spike detection and reduce computational redundancy. The Neck incorporates a hierarchical residual module to enhance YOLOv5s' representation of multi-scale features. The Head enhances the detection accuracy of small, dense wheat spikes in a large field of view. In addition, the height of a single wheat plant without stubble is estimated by the depth distribution of the wheat spike region and stubble height. The relationship model between the height and weight of a single wheat plant without stubble is fitted by experiments. Then, feed quantity can be predicted using the weight of a single wheat plant without stubble estimated by the relationship model and the number of wheat plants detected by the improved YOLOv5s. The proposed method was verified through experiments with the 4LZ-6A combine harvester. Compared with the existing YOLOv5s, YOLOv7, SSD, Faster R-CNN, and other enhancements in this paper, the mAP50 of wheat spikes detection by the improved YOLOv5s increased by over 6.8%. It achieved an average relative error of 4.19% with a prediction time of 1.34 s. The proposed method can accurately and rapidly predict feed quantity for wheat combine harvesters and further realize closed-loop control of intelligent harvesting operations. [ABSTRACT FROM AUTHOR]

Background: The present investigation is an attempt to study the effect of different harvesting and threshing methods on germination and seedling vigour of dhaincha. The use of a combine harvester to harvest dhaincha will be an effective alternative method that has not been widely tried. However, work on different methods of harvesting and threshing of dhaincha is limited. Hence, a study was conducted to evaluate the impact of various harvesting and threshing methods on germination and seedling vigour of dhaincha. Methods: This study was conducted at Anbil Dharmalingam Agricultural College and Research Institute, TNAU, Tiruchirappalli, Tamil Nadu. The dhaincha crop was harvested and threshed using four different methods viz., manual harvesting and manual threshing, manual harvesting and threshing by tractor treading, manual harvesting and mechanical threshing and harvesting and threshing by combine harvester. The resultant seeds were tested for mechanical damage and germination potential. The experiment was laid in completely randomized block design. Germination was tested by roll towel method using 100 seeds in four replications. Germination percentage, root and shoot length were measured in seven days after sowing from ten randomly selected seedlings in each replication. For the estimation of dry matter production, ten seedlings were selected at random and kept in a hot air oven maintained at 85°C for 24 hours after measuring their root and shoot length and vigour index was calculated. Mechanical damage to seeds was observed by ferric chloride test. Seed recovery per cent was calculated based on the 100 kgs of dhaincha seeds were cleaned and graded treatment wise using cleaner cum grader and the seeds retained on the bottom sieve were weighed and expressed as per cent of total quantity of seed. Result: The results revealed that the significant difference was found among the different harvesting and threshing methods. The seeds harvested and threshed by manual method recorded 85 per cent germination followed by seeds harvested manually and threshed by mechanical threshing (84 per cent) and seeds harvested manually and threshed by tractor treading (80.5 per cent). The lowest germination of 80.0 per cent was recorded by combine harvesting. From this study, it could be inferred that combine harvester is a modern method for harvesting of dhaincha that saves time and labour when compared to all other methods [ABSTRACT FROM AUTHOR]

Soybean plants cultivated using mulched drip irrigation planting technology have the following characteristics during the harvest period: green stems and leaves, and a high straw/grain ratio. Moreover, the threshing device of a soybean combine harvester is difficult to adapt to, resulting in an increase in the accumulation and unevenness of the threshed mixture. This leads to an increase in impurity content and the loss rate. We conducted a single-factor experiment on a self-developed longitudinal/axial-flow soybean threshing and separation test bench, employing drum speed, feeding rate, and threshing clearance as experimental factors. The influence of the soybean threshing and separation device's working parameters on the distribution and uniformity of the threshed mixture in the axial and radial directions of the drum was explored through experiments. The results showed that the mass of the threshed mixture and soybean seeds showed a trend of first rapidly increasing and then slowly decreasing in the axial direction of the drum. Additionally, the mass showed a distribution feature of large values on both sides and small values in the middle in the radial direction. A lower drum speed, greater threshing clearance, and a smaller feeding rate make the radial distribution of a threshed mixture more uniform. Based on the combination of the crushing rate and unthreshed rate, the optimal working parameter combination was determined to be as follows: a drum speed of 500 r/min, a feeding rate of 6 kg/s, and a threshing clearance of 25 mm. The findings of this research offer valuable insights for the structural optimization and design enhancement of threshing and cleaning mechanisms within soybean combine harvesters. [ABSTRACT FROM AUTHOR]

This study aimed to enhance the efficiency of tiger nut combine harvesters by reducing impurity and loss rates during processing. Scholars focused on analyzing the composition and suspension speed of the bean mixture, leading to the development of a wind-screen impurity-removal method. The wind-screen-type bean-separation device was designed with a cross-flow fan, louver screen, frame, and driving mechanism. Theoretical analysis was employed to discuss the motion characteristics and behavior of the sieve body and material, thereby revealing the screening dynamics of tiger nuts and impurities. Factors such as crank radius, crank speed, and fan speed were identified as crucial for optimizing separation performance. Initial single-factor tests helped narrow down the range of influencing factors. Subsequently, a three-factor, three-level Box–Behnken test was conducted with crank radius, crank speed, and fan speed as variables and impurity rate and loss rate as evaluation indexes. This led to the establishment of a multiple regression equation linking these factors to the evaluation indexes. Through response surface analysis and multi-objective optimization using the regression model, the optimal operational parameters for the device were determined: crank radius of 45 mm, crank speed of 497 r/min, and the fan speed of 1100 r/min. Theoretical calculations predicted an impurity rate of 2.42% and a loss rate of 0.51%. Verification tests confirmed these findings, showing an average impurity rate of 2.53% and a loss rate of 0.56%, which met the mechanized harvesting standards for tiger nuts. Overall, this study introduces a novel method and technical framework for effectively separating tiger nuts from impurities, thereby advancing the mechanization of tiger nut harvesting processes. [ABSTRACT FROM AUTHOR]

Inadequate parameter design of the cleaning device in soybean combine harvesters leads to elevated levels of machine harvesting losses and impurity rates. To provide fundamental data for the optimization of structural parameters of soybean cleaning sieves, it is of great significance to study the collision and bouncing characteristics of soybeans on the cleaning sieve surface and the impact of parameters on the coefficient of restitution (COR). The current study designed a collision platform, using soybeans at the harvest stage as the research subject. The experimental factors included drop height, wall inclination angle, wall movement speed, and wall material. Through single-factor experiments and orthogonal experiments, the effects of different collision parameters on the rebound trajectory and COR of soybeans were investigated. This study focuses on soybeans at the harvest stage as the test subjects. Experiments were conducted on a collision platform and recorded with a high-speed camera to capture the three-dimensional motion trajectories of the soybeans using the principle of specular reflection. Through single-factor experiments, the jumping characteristics of the soybeans on sieve surfaces with different motion characteristics were analyzed. The impact of drop height (400–650 mm), wall inclination angle (8–13°), wall movement speed (0.6–1.1 m/s), and wall material (stainless steel plates and polyurethane plates) on the coefficient of restitution (COR) was calculated and clarified. Multi-factor orthogonal experiments were conducted to determine the significance order of the different factors affecting the COR. Three-dimensional models of the soybeans and the collision platform were constructed using SolidWorks software, and the collision between the soybeans and the cleaning wall was simulated using EDEM software. The micro-forces and energy transfer during the soybean collision were analyzed. The results indicated that the COR of soybeans decreases as the drop height increases, but increases with wall inclination angle and wall movement speed. Additionally, the COR is higher when the soybeans collide with stainless steel plates compared to polyurethane plates. The order of influence of the four factors on the COR were: wall material > wall inclination angle > wall speed > drop height. This study provides important reference value for the efficient and low-loss design of cleaning devices. [ABSTRACT FROM AUTHOR]

The bolts and connections of each working part of a rice combine harvester can suffer from severe instantaneous impacts and alternating loads, and these strong impacts and loads cause instantaneous fracture and fatigue failure of the bolt face and even the loosening, detachment, and fracture of the bolt. The main vibration directions and the most complex vibration parts of the bolts and connections in the main working parts of a combine harvester under time-variable multiload excitation were obtained through the analysis of response signals in terms of time-domain and frequency–domain characteristics via a vibration response experiment. This study revealed that the random peak value of the vibrating screen is 12.5622, which is the severe impact and collision standard. For the vibrating screen, the local peak in the 4-Y direction was the main load of the destroying bolt connection (the impact reached 60.57 m/s2, 96.91 m/s2) and the vibration energy intensity in the 4-Z direction was mainly concentrated at 12.42 m/s2, which is the maximum vibration energy value in the three directions (the peak vibration value reached 109~115.68 m/s2), so the bolted connections of the vibrating screen are the most vulnerable to destruction. Therefore, a kinetic model and a microscopic response model of a vibrating screen were established via the centralized mass method to explore the kinetic response characteristics of bolted structures subjected to multiple excitation loads, thus providing a mathematical model for identifying the features of bolted connections based on static characteristics. [ABSTRACT FROM AUTHOR]

In the rainy season, which often has uncertain rainfall, crawler combine harvesters have difficulty traversing wet and soft rice fields. A large amount of clay is often accumulated on the track surfaces, resulting in frequent slipping and sinking, which greatly affects the operational performance and harvesting efficiency of crawler combine harvesters. To address this issue, this paper proposes a high-traction track grouser based on the structure of an ostrich's foot sole. First, a traction force mathematical model is constructed to analyze the interaction between a track grouser and wet and soft rice fields, and parameter optimization is conducted. Then, the bionic information of a dung beetle's non-smooth body surface is extracted, and the surface of the track is designed with biomimetic convex hull patterns based on the geometric similarity principle and adhesive experiments. Finally, the analysis results indicate that the optimized track grouser significantly improved the traction of the track in wet and soft rice fields. For the track plate with a bionic desorption convex hull pattern, a convex hull diameter of 6 mm, convex hull spacing of 8.25 mm, and convex hull height of 3 mm led to good adhesion reduction and desorption effects in wet and soft soil. [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]

Cleaning control based on changes in cleaning loss rate and impurity rate has emerged as a hot topic in the research on intelligent control for rice and wheat combined harvesters. However, numerous operation parameters can lead to deviations beyond the normal range of cleaning loss rate and impurity rate. The impact of cleaning control parameters in rice and wheat combined harvesters on cleaning loss rate and impurity rate often tends to be contradictory. How to combine different contradictory cleaning control strategies to get a more widely used and better cleaning control strategy is a hot issue in the current cleaning control research. In this paper, the granularity of quotient space is introduced into the cleaning control based on operation parameters, and a cleaning control model based on granularity synthesis theory is proposed. This method first constructs a knowledge base for intelligent control of cleaning tailored to the cleaning loss rate and impurity rate using production rule representation, and considers that these control strategies constitute different quotient spaces, and then organizes these quotient spaces according to granularity synthesis theory to get the cleaning control strategy. The experimental results verify that the validity of the cleaning control based on granular computing is better than fuzzy control. [ABSTRACT FROM AUTHOR]

Maize cobs are valuable plant residues that can be used for many different purposes, including as a renewable energy source. Despite their value, maize cobs are still underutilized, mainly because people are not aware of their potential and harvesting techniques for their collection are still being developed. Therefore, this research focused on finding the most suitable energy- and time-efficient method for mechanical collection of maize cobs. Upgrading the combine harvester with an additional hopper proved to be the most promising solution, as it allows harvesting and storage of maize grain and maize cobs in one pass, while the harvesting time remains almost the same and the maize cobs are of good quality, as they do not fall on the field. A prototype with enlarged openings in the straw walkers, an additional grab container for maize cobs, a transport auger, a transport cleaning fan with built-in knives, a transport tube and some other assemblies was fabricated and used in practice. The first test results are very encouraging (94.4%-96.0% purity of maize cobs) and the system has been patented as a promising solution, especially in times when the environmental sustainability of the planet and energy independence are becoming increasingly important. [ABSTRACT FROM AUTHOR]

During the operation of the longitudinal axis flow threshing device of a combine harvester, the threshed materials form accumulations and blockages on both sides of the screen surface, severely affecting the harvesting process. To evenly distribute the materials on the screen and solve the blockage issue, a multi-wing curved combination centrifugal fan is designed to match the mass distribution of the threshed materials. The movement mechanism of rice threshed materials in the cleaning shoe of a longitudinal axis flow combine harvester is investigated using the coupled CFD-DEM simulation method. The cleaning efficiency and performance of the traditional straight-blade fan screen device and the newly designed cleaning device are compared and analyzed, and field tests are conducted. The results show that the trajectory of the threshed materials cleaned by the device equipped with the multi-wing curved combination centrifugal fan is consistent with the mass distribution of the materials separated by the longitudinal axis flow threshing device. The absolute value of the centroid velocity of the material group in the X/Y direction is greater than that of the traditional fan, indicating that the movement speed of the particle group in the optimized fan is greater than that of the traditional fan. Therefore, in the actual cleaning process, the optimized fan's air flow distribution more effectively accelerates the movement speed of the threshed materials, increasing the amount of materials cleaned per unit time, thereby improving the cleaning efficiency. Field comparative tests show that the designed cleaning device reduced the cleaning loss rate by up to 25.00% and the impurity content rate by 32.20%, achieving efficient and low-damage cleaning of the combine harvester. The study demonstrates the effectiveness of the proposed method for evenly distributing the materials and provides important reference for the study of other piled particle distribution systems. [ABSTRACT FROM AUTHOR]

There are many excitation sources and complex vibration environments in combine harvesters. The coupling and superposition of different vibration signals on the plate and shell seriously affect the working parts of the body. This also reduces the reliability of the whole machine. At present, domestic and foreign research on existing harvesters mainly focuses on harvesting performance, with less research on vibration characteristics. Therefore, in this paper, the vibration response of the metal plate–shell under the two connection modes of bolt connection and welding is studied, in order to optimize the design and structure of the plate–shell structure of the combine harvester and improve the overall performance. First, the welded and bolted plates are numerically modeled using Hypermesh pre-processing functions. Then, the boundary conditions are simulated by continuous variable stiffness elastic constraint experiments. Finally, the intrinsic vibration dynamic model of the four-sided simply supported plate and four-sided solidly supported plate is established using the modal superposition method. By analyzing the modal frequencies and vibration patterns, the following results are obtained. The connection method between the plate and the frame has a significant impact on the inherent vibration characteristics of the plate. The bolt connection will make the plate's intrinsic vibration frequency higher than that of the welding method, but the effect on the plate's intrinsic vibration pattern is more minor. At the same time, in order to verify the accuracy of the model, the actual modal vibration patterns and frequencies of the same proportion of plates in the modal test are compared with the results of modal vibration patterns and frequencies obtained by Ansys. The errors of the two dynamic model analytical methods are within 1% and 3%, respectively. This result verifies the accuracy of the dynamic model of the metal plate and shell structure under different connection methods. [ABSTRACT FROM AUTHOR]

The complex mechanical system of a rice combine harvester not only has various excitation sources, but also, the vibration transmission path between each working device and the vibration contribution characteristics to the frame are not clear, so it is difficult to perform a reduction vibration design for the sharp vibration of the rice combine harvester frame. Therefore, based on the comparison and improvement of multiple classical transfer path analysis methods, this paper analyzed the vibration transfer characteristics and transfer characteristics of each harvester by the discrete time matrix method and operating path method. In the Experimental section, through the vibration characteristic experiment firstly, this paper obtained the power spectrum variation and the most needed optimized path in the transmission path of each device under each operating condition. Secondly, through frame simulation analysis under the exciting force, we obtained the vibration damping areas that needs to be optimized. Finally, the damping optimization experiment connected with the vibration characteristic experiment, and the excitation force simulation analysis was performed. The results of the damping optimization experiment displayed that the maximum change value of the vibration acceleration of the cutting table decreased from 7.862 m·s−2 to 3.522 m·s−2, decreasing by 55.2%, and the peak amplitude of the multipoint test in the cab was 5.4, 5.3, 1.7 and 2.0 μm, respectively, which was significantly reduced, so the optimization effect was significant. This study provides theoretical support for the vibration reduction optimization of a rice combine harvester frame. [ABSTRACT FROM AUTHOR]

Intelligent control has become an important research direction of a combine harvester. However, the impact of cleaning control parameters in rice–wheat combine harvesters on cleaning loss rate and impurity rate often tends to be contradictory. In this paper, an intelligent controlling model based on multi-objective optimization particle swarm (MOPSO) was constructed to solve this problem. The control model can real-time monitor the cleaning performance such as the cleaning loss rate and impurity rate and regulate the cleaning operation conditions such as the angle of the air distributor plate, the opening of the upper sieve and the fan speed. The field operation experiment of 10 kg feeding rice–wheat combine harvester proves that the control model based on MOPSO is more effective than the model based on fuzzy control. [ABSTRACT FROM AUTHOR]

With the rapid advancement of agricultural mechanization, intelligent header technology has emerged as a pivotal element in optimizing the efficiency and quality of grain combine harvesters. This paper offers a comprehensive analysis of the current state of intelligent header technology, with a particular emphasis on the structure, working principles, contour-following mechanisms, and height control technologies. By integrating cutting-edge sensor technologies, advanced control algorithms, and optimized mechanical designs, intelligent headers can achieve precise control over height and posture, thereby significantly reducing crop losses and enhancing both harvesting efficiency and quality. Despite substantial progress, challenges remain in areas such as response speed, real-time performance, height measurement accuracy, and control algorithm effectiveness. Future research will likely concentrate on improving control system performance, refining component and system designs, and incorporating emerging technologies to better accommodate diverse crops and complex terrains. This paper also provides a critical evaluation of current limitations in intelligent header research and projects future trends, offering valuable theoretical and practical insights for optimizing header structures, minimizing losses, and enhancing intelligent functionalities. The ultimate aim is to drive continuous innovation and advancement in header technology for grain combine harvesters. [ABSTRACT FROM AUTHOR]

In order to address the high impurity and loss rates in the cleaning process of existing peanut combine harvesters, the design basis of the cleaning sieve was explored. Tests were conducted to determine the composition of the peanut picking fruit and the characteristics of the material suspension mixture. Additionally, the mechanical relationship between the fruit and miscellaneous mixtures and the cleaning sieve was investigated. The wind speed ranged from 8 m/s to 10 m/s, the vibration frequency ranged from 6 Hz to 8 Hz, and the inclination angle of the sieve ranged from 5° to 9°. The scavenger sieve platform was constructed and tested using Box-Behnken's central combination test method. The optimal combination of fan wind speed (9 m/s), sieve surface inclination angle (8°), and sieve vibration frequency (7 Hz) resulted in a pod impurity rate of 1.16% and a loss rate of 1.4%. The device significantly reduces impurity content and loss rate during peanut harvesting. The study's results can serve as a reference for improving the design of the peanut combine harvester cleaning mechanism and optimizing operating parameters. [ABSTRACT FROM AUTHOR]

Basic breeding efforts initiated at the USDA‐ARS in Houma, LA, in the late 1950s allowed Louisiana sugarcane breeders, once again, to cross with the wild germplasm of cultivated sugarcane, Sacharum spontaneum. 'LCP 85‐384' was the first success story from this effort and was quickly adopted by growers. It became clear that the cultivar would prove to be substantially impactful to the Louisiana sugar industry. Performing at unprecedented yields in ratoon crops, LCP 85‐384 changed how Louisiana growers would manage their crops. The variety proved to possess traits that fared well in the subtropical production zones of the state. Substantial stalk populations seemed to play a vital role in the necessary ratoon ability and consequent cold tolerance necessary for production in Louisiana. After significant disease pressure, the variety quickly declined in production acreage, but not in impact. It continued to provide sustained progress as a parent for years, contributing to most modern commercial cultivars in Louisiana. Today, LCP 85‐384 and its progeny are used in breeding and genetic research to usher in the next era of progress in the Louisiana sugar industry. Meanwhile, through cooperative efforts of breeding programs around the world, it is making its mark on the sugarcane industries of Argentina in much the same way as it did in Louisiana. In the future, it is expected that the progress made in the breeding program will continue by building upon the gains achieved from LCP 85‐384 and its progeny for the sustained success of the Louisiana sugarcane industry. Core Ideas: LCP 85‐384 has shaped the Louisiana sugar industry in ways that are unprecedented.Combined increases in cane yield, harvesting efficiency, and stand longevity boosted sugar yield by about 22%.Its release coincided with the widespread adoption of mechanical combine harvesters which improved harvesting efficiency.Crossing with LCP 85‐384 has led to the release of 13 cultivars in Louisiana.In Argentina, it received wide adoption as a cultivar and is the parent of a newly released cultivar. [ABSTRACT FROM AUTHOR]

The wind sieve cleaner is widely used in the screening system of combine harvesters due to its compact structure and efficient screening capability. In order to study more deeply the feeding load distribution of the combine harvester and the influence of the airflow field on the clearing effect, a mechanical analysis method was adopted to analyze the dynamics of the material in the inclined airflow, and a kinetic model was established. At the same time, the motion state of the material in the airflow field was explored, and combined with the actual orthogonal test, the response surface model of factors and indicators was established. Experimental validation was carried out. It provides an important research foundation and theoretical basis for optimizing the structural parameters of the screening system and improving its operational performance. [ABSTRACT FROM AUTHOR]

As a result of the uneven growth of rice, unbalanced vibration of threshing drum caused by stalk entanglement in combine harvester is more and more severe. In order to reveal the influence of unbalanced excitation on the roller axis locus during rice threshing, the stability of threshing drum was studied. The dynamic signal test and analysis system are used to test the axial trajectory of threshing drum. At the same time, the influence of the unbalanced excitation caused by the axis winding on the axis trajectory is analyzed by the experimental results. Axis locus rules under no-load and threshing conditions are obtained. In order to simulate the axial and radial distribution of unbalanced excitation along the threshing drum, the counterweight was distributed on the threshing drum instead of the entangled stalk. Then, the definite effect of unbalanced excitation on the rotating stability of threshing drum is analyzed. Results show that the amplitude of stem winding along the grain drum is larger in the vertical direction and smaller in the horizontal direction when compared with the unloaded state under 200 g weight. It was found that the amplitude in both horizontal and vertical directions decreased after 400 g and 600 g counterweights were added, respectively, to simulate the radial distribution of stalk winding along the grain barrel. Finally, it can be seen that with the increase in the weight of the counterweight, the characteristics of the trajectory misalignment of the threshing cylinder axis become more and more obvious. This study can provide reference for reducing the unbalanced excitation signal of threshing drum and improving driving comfort. [ABSTRACT FROM AUTHOR]

Aiming at the problems of uneven distribution of dislodged material on the screen surface of longitudinal axial flow grain combine harvester, a large difference in material clearing time, and large clearing loss, a dislodged material homogenizing device that can realize dislodged material return and homogenization at the rear of longitudinal axial flow was developed. (1) The structure and motion parameters of the reflux plate were determined, and simulation tests were carried out to verify them; (2) A test bench was set up, and the Box-Behnken test method was adopted to determine the influence law of each factor on the operating effect and the optimal parameter combination, and the results showed that the tilt angle of the return plate, motor speed, and amplitude had a significant influence on the distribution uniformity of the material on the screen surface; it was determined that the optimal combination of the angle of the return plate configuration was 28.7°, the speed of the motor was 247 r/min, the amplitude of the return plate was 18.3 mm, and the seed contamination rate was 0.48%. The optimum combination was determined to be 28.7°, 247 r/min, 18.3 mm, and 0.48% impurity rate; (3) under the conditions of the field test validation, the validation error is less than 5%, proving that it can effectively improve the performance of the clearing and reduce the rate of impurity content. [ABSTRACT FROM AUTHOR]

As the world's first large grain crop, wheat in its mechanized harvesting process faces a serious problem, namely, when the combine harvester operating parameters are not set reasonably, it leads to increased losses of wheat kernels to an extent exceeding the prescribed standard, of which the loss of scavenging accounts for a large proportion. Excessive grain harvest loss will not only reduce the quality of the wheat harvest but also adversely affect its yield. Real-time monitoring of losses in the harvesting process is key to the dynamic adjustment of operating parameters to decrease machine harvesting losses. This article proposes a grain cleaning loss monitoring device for combine harvesters suitable for wheat crops. It aims to measure the loss of grain cleaning in the process of wheat harvesting in real time and adjust the operating parameters of the harvester timeously by feeding back the data to the driver in real time, so as to decrease the loss of wheat grains in the process of harvesting and achieve the purpose of reducing the loss of harvest. When the device was tested in the field, the wheat variety was Bainong 4199, the yield per mu was 625.83 kg (one mu is 1/15 of a hectare, or approximately 666.67 m2), the mass of grain was 43.21 g, and the water content was 14.2%. After the test, the monitoring error of the loss monitoring device was within 8%, and the average error rate was 6.69%. The test proves that the monitoring device achieves the expected design effect and meets design requirements. The results of this paper are of significance to the intelligent control system of wheat combine harvesters and provide a reference for research into grain cleaning loss monitoring devices for wheat combine harvesters. [ABSTRACT FROM AUTHOR]

The cleaning loss rate is a crucial performance metric for rice-wheat combine harvesters. Most studies on the relationship between the cleaning operation parameters of the combined harvester and the cleaning loss rate lack research on the dynamic correlation between harvest losses and operational parameters, specifically focusing on the dynamic correlation between harvest losses and multiple operational parameters such as the cleaning loss rate. In this paper, we formulate a dynamic deductive model for the scenario of harvesting loss regulation involving multiple operational parameters, delving into the dynamic associations between cleaning loss and the regulation of multiple operational parameters and constructing dynamic Bayesian network prediction model. Through experimental analysis of the dynamic Bayesian network prediction model for cleaning loss rates, the comparison of results among the other three algorithms demonstrated that it was efficient for our DBN to predict the cleaning loss rate. [ABSTRACT FROM AUTHOR]