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A rotary tiller is a common tillage tool for straw incorporation in an intensive tillage system. However, rotary tillage for seedbed preparation in dense-straw mulching conditions experiences high torque and poor performance of straw incorporation. Nowadays, a great deal of studies have been focused on mimicking the morphological features of low-resistance animals to improve the performance of soil-engaging tools. Accordingly, the present study investigated the performance of three C-type rotary blades (i.e., conventional, serrated, and biomimetic) under three straw lengths (50, 100, and 150 mm) for incorporation of straw into the field using an in situ field tillage testing bench. Compared to the conventional and serrated blades, the biomimetic blade had lower straw displacement (decreased by an average of 50 mm and 7 mm, respectively), higher straw burying rate (increased by an average of 5.2% and 7.8%, respectively), better straw distribution (decreased by an average of 9.1% and 10.4% on the coefficient of variation, respectively), as well as lower torque and power (decreased by an average of 3.3 N·m and 4.4 N·m, respectively) under all straw lengths. The improved performance of the biomimetic blade could be attributed to the fact that its typical teeth configuration was designed by mimicking the smooth arc of the mole-rat’s claw. These results demonstrated that the biomimetic-designed blade could be a better option for incorporating dense straw into the field conditions.

As brown mushrooms are both delicious and beneficial to health, the global production and consumption of brown mushrooms have increased significantly in recent years. Currently, to ensure the quality of brown mushrooms, selective manual picking is required, and the delicate surface of the mushrooms must not be damaged during the picking process. The labor cost of picking accounts for 50–80% of the total labor cost in the entire production process, and the high-humidity, low-temperature plant environment poses a risk of rheumatism for the laborers. In this paper, we propose a novel underactuated gripper based on a lead screw and linear bearings, capable of operating with flexible force control while simultaneously measuring the diameter of the mushrooms. The gripper features three degrees of freedom: lifting, grasping, and rotation, and enabling it to approach, grasp, and detach the mushroom. A thin-film force sensor is installed on the inner side of the fingers to achieve accurate grip force measurement. The use of a PID algorithm ensures precise grip force control, thereby protecting the brown mushrooms from damage. Experimental results demonstrate that the proposed gripper has a static grasping force error of 0.195 N and an average detachment force overshoot of 1.31 N during the entire picking process. The in situ measurement of the mushroom diameter achieves 97.3% accuracy, with a success rate of 98.3%. These results indicate that the gripper achieves a high success rate in harvesting, a low damage rate, and accurate diameter measurement.

In order to measure wheat yield and wheat spike phenotypes, the grain number of wheat spikes is counted manually at present, but acquiring the grain number of wheat spikes is laborious and time-consuming. Counting the grain number of wheat spikes with an image processing method is promising, yet the application of this method is flawed due to its low accuracy. In this work, images of wheat spikes were collected and processed with technical procedures, including image cropping, image graying, histogram equalization, image binarization, eroding operation, removing small objects, filling image holes, revolving vertical spikes, cutting off stems, and removing stems. Wheat stems in binary images were eliminated by the sum pixels method, and the morphological characteristic parameters of the image areas of wheat spikes and lengths of wheat spike axes were calculated. Mathematical models relating the image areas of wheat spikes and lengths of the wheat spike axes to the grain number were established, and the mathematical models were verified. The results showed that the characteristic parameters of the image areas of wheat spikes and the lengths of the wheat spike axes for the spike images were linear relative to the grain number, and the maximum determination coefficients R2 were 0.9336 and 0.9012, respectively. The maximum determination coefficients R2 for the practical and predicted grain numbers were 0.9552 and 0.9369, respectively, and the minimum average absolute error was 2.3, while the average relative error for the mathematical models was 5.65%. The mathematical models relating the image areas of wheat spikes and the lengths of the wheat spike axes to the grain number were practical and accurate, and the mathematical model comparing the image area of wheat spikes and the grain number was superior to that comparing the length of the wheat spike axis and the grain number. The grain number of wheat spikes could be acquired accurately and quickly by the image processing method extracting the characteristic parameters of wheat spikes.

The advancement of agricultural mechanization necessitates precise and standardized classification based on technical characteristics to enhance green, efficient, and high-quality development. The current lack of scientific and standardized definitions and classifications for various types of agricultural machinery has become a bottleneck, complicating the machine selection and affecting the compatibility of the machinery with optimized field operations. To address this complexity, we propose a comprehensive classification method that integrates principal component analysis (PCA), cluster analysis, and the qualitative analysis of the functional components for defining and scientifically classifying harvesters. The key functional and technical properties of harvesters were analyzed, and eight primary parameters (machine weight, cutting width, feed rate, rated power, overall machine length, width, height, and working efficiency) were selected, supplemented by nine key functional components (walking mechanism, cutting device, threshing device, separating device, cleaning device, grain collecting device, grain unloading device, cabin, and track size). In the first step, principal component analysis was performed to reduce the dimensionality of the parameters, yielding three principal components with contribution rates of 41.610%, 28.579%, and 15.134%, respectively. One primary parameter from each component was selected for further analysis. In the second stage, Q-type cluster analysis classified the harvesters based on the squared Euclidean distance between the operational parameters, resulting in three classes of harvesters. Finally, functional component analysis provided detailed insights, further refining the classification into four major categories: mini, small, medium, and large harvesters. The results of this work provide a scientific basis for the definition and classification of the harvester products available on the market. This method offers a robust framework for the rational selection and planning of agricultural machinery, promoting sustainable mechanization with a focus on technical parameters and functional attributes.

Explaining the physiological and ecological effects of wheat population density can provide new research methods for field crop production. A three-year field trial under drill single-seed seeding was conducted, which used three different intra-row seed-seedling spacings to quantitatively analyze the density effect from three perspectives—population, individual plant, and single-stem panicle—at the winter wheat harvest. The results showed that year and density had significant effects on both the population and individual plant yield (p < 0.05), as well as on some yield components and biomass indicators. The interaction between planting density and annual climate was found only in the number of grains for both the entire population and individual plants. With the increase in planting density, the CI gradually increased, inhibiting the growth of individual plants and leading to a negative impact on monoculture wheat yield. The drill single-seed seeding method can provide a basic experiment condition for analyzing the density effect. The density effect of wheat populations originates from intraspecific competition, which mainly affects the growth of individual plants. Research based on the analysis of density effects from the perspectives of population, individual plants, and single-stem panicles can provide a methodological reference for precision agriculture.

Root fractal analysis is instrumental in comprehending the intricate structures of plant root systems, offering insights into root morphology, branching patterns, and resource acquisition efficiency. We conducted a field experiment on paddy–wheat root systems under varying nitrogen fertilizer strategies to address the need for quantitative standardization in root fractal analysis. The study evaluated the impact of nitrogen fertilizer heterogeneity on root length and number. We established functional relationships and correlations among root fractal characteristics and root length across different box dimension scales and various root placement angles at 2.5, 5, 10, 20, 40, and 80 box dimension scales. Results indicated that nitrogen fertilizer had a limited impact on paddy–wheat axile roots, with a coefficient of variation below 0.35 among samples. Box dimension scale influenced 3D fractal dimension (FD) and fractal abundance (FA), with strong correlations (>78%) among 3D fractal features and low sample errors (0.76 for FA and >0.5 for FD) and low sample errors (

In order to clarify the mechanism of tiller–soil interaction in the process of strip rotary tillage, this paper conducted a simulation and experimental research on four blade configurations composed of three rotary blades (bent C, straight and hoe) at three rotation speeds (280, 380 and 510 rpm). The study found that the soil throwing characteristics of the blades are the key factors affecting the quality of tillage. The increase in the rotation speed not only improved the soil breaking effect, but also enhanced the phenomenon of soil throwing and then led to a reduction in the soil backfill. In the BC configuration (combination of four bent C blades), the bent C blades showed the best soil throwing characteristics and created the best soil fragmentation. However, due to the obvious side throwing of the soil, the backfill effect of soil fragmentation was the worst. The backfill rate was only 8% when the rotation speed was 510 rpm and could not allow reaching the required seed–soil contact during sowing. The hoe blades in the HC configuration (combination of four hoe blades) could collect part of the soil fragments and throw them towards the direction of the machine during the cultivation process, which led to a good soil breaking effect and a low soil side throwing rate. When the rotation speed was 510 rpm, 36% of the soil was backfilled into the seedbed. In the SC configuration (combination of four straight blades), the straight blades could well control the scattering of the side-thrown soil fragments. At a super-high rotation speed (510 rpm), the side throwing rate was only 70%, and the backfill rate was as high as 60%. However, the soil fragments created by the blades were too large (average soil block diameter > 40 mm) and could not form a loose and finely broken seedbed environment. The MC configuration (combination of two straight blades and two hoe blades) benefited from the combination of straight blades and hoe blades, offering outstanding advantages for backfill and soil fragmentation. Therefore, under the condition of a centralized configuration of field surface straw, it is recommended to use the MC configuration of the wheat rotary strip–till planter for cohesive paddy soil.

Agricultural production can achieve sustainability by appropriately applying agricultural mechanization, especially in developing countries where smallholding farmers lack sufficient agricultural machinery for their farming operations. This paper aimed to study the extent to which small-, medium-, and large-scale farms in the Delta of Egypt use agricultural mechanization in their wheat crop farming operations. K-means clustering was used to aggregate and analyze the scenarios implemented by farmers for wheat cultivation so as to suggest guidelines for each cluster of farmers on how to mechanize their indoor wheat agricultural operations to maximize production. The study is divided into two parts: Firstly, data were collected regarding the percentage of small, medium, and large farms; the cultivated area of wheat crops in small-, medium-, and large-scale farms; and the size of tractors, as an indicator of the mechanization available in the governorates of Egypt’s Delta. Secondly, data were collected through a questionnaire survey of 2652 smallholding farmers, 328 medium-holding farmers, and 354 large-holding farmers from Egypt’s Delta governorates. Based on the surveyed data, 14, 14, and 12 scenarios (indexes) were established for small-, medium-, and large-scale farms, respectively, related to various agricultural operations involved in wheat crop production. These scenarios were analyzed based on the centroids using K-means clustering. The identified scenarios were divided into three clusters for the three levels of farms. The data obtained showed the need for smallholding farmers to implement mechanization, which could be achieved through renting services. These findings, if implemented, would have huge social and economic effects on farmers’ lives, in addition to increasing production, saving time and effort, and reducing dependence on labor.

Strip rotary tillage seeding technology has been widely used in rice–wheat rotation system, benefiting the economy greatly. The purpose of farming is to create a comfortable seedbed environment for crop growth. Therefore, it is necessary to consider the effects of tillage methods on wheat root configuration and growth trend in the research of strip tillage, instead of just focusing on optimizing the shape of tillage tools, sowing methods, and soil fragmentation. To clarify the effects of different tillage methods on crop root growth trends, a two-year wheat planting experiment was carried out. Strip tillage (ST1 and ST2) and full width tillage treatment (FT) were designed, 3D models of root structure and soil on the surface of the seedbed wall were established, and four quantitative indexes were proposed: soil surface roughness of seedbed wall (SR), difference coefficient of root soil space occupation (P), difference coefficient of root angle expansion trend (PA), and difference coefficient of root length expansion trend (PL). The results showed that the cultivation method directly affects the growth trend of wheat roots. The wheat roots tended to grow along the inter-specific direction under ST treatment on the 14th day, and the average P, PA, and PL were as high as 38, 43, and 55, respectively. The SR produced by ST1 treatment was 70% lower than that of ST2 treatment, suggesting ST1 treatment had more serious restrictions on root growth. P, PA, and PL in ST1 treatment were 38.5%, 14%, and 43% higher than those in ST2 treatment within 14 days, respectively. This paper briefly explains the effects of tillage methods on the growth trend of wheat roots, provides new methods and technologies for the rapid and effective acquisition of soil surface information, solved the problem of the trend of root expansion being difficult to quantify, and provided a new direction for the optimization of tillage methods.

High-yielding agriculture in an intensive rice–wheat rotation system leads to plenty of residues left in the field after harvest, which is detrimental to seeding operation, seed germination, and early plant growth. Some residue thus needs to be incorporated into the soil. Providing the relationship between tillage operations and residue incorporation and establishing a mathematical model play important roles in residue management and the design of tillage machinery. In order to obtain detailed data on the interaction between residue incorporation and tillage operations, a multifunctional field-testing bench with precise parameter control was developed to assess residue incorporation characteristics of rotary tillage, and we investigated the effects of straw length, stubble height and rotary speed on residue incorporation. Three experimental factors affecting residue incorporation performance were studied, i.e., six lengths of straw (30–150 mm), four heights of stubble (50–200 mm), and three rotary speeds (240–320 rpm). Chopped straw and stubble with certain sizes were prepared for the test, and we measured the burying rate and distribution uniformity of residue after rotary tillage. The results indicated that straw length, stubble height, and rotary speed all impact residue incorporation quality. The burying rate and distribution uniformity of residue decreased with the increase in straw length and stubble height; a lower rotary speed parameter buried less residue and distributed it with worse uniformity than a higher one. It is suggested that farmers determine the straw length and stubble height at the stage of harvest according to the required burying rate and distribution uniformity of residue.

Poor shelling quality degrades the performance and profit of the peanut industry. The Hertz theory and the wear resistance experimental method were applied to identify a highly wear-resistant material guaranteeing a low mechanical damage rate (MDR) of peanut kernels. The Box–Behnken design method was applied in the experiment to illustrate the influence of the material’s elastic modulus (X1), radius of curvature of the key parts (X2), rotating speed of the shelling drum (X3), and clearance between the shelling drum and concave screen (X4) on MDR and shelling efficiency (SE). Depending on the analysis of variance, the weights of the influential factors were observed as X1 > X3 > X4 > X2. The mathematical models of MDR and SE were derived from the least squares’ method, and four-dimensional slice diagrams of the three most significant factors were used to illustrate the trends of MDR and SE. A multi-objective analysis provided the optimal combination of parameters as: X1 = 10 MPa, X2 = 12.77 mm, X3 = 277.48 r/min, and X4 = 24.24 mm, yielding MDR = 4.89% and SE = 97.91%. The results were further verified by a production trial test, proving that the proposed solution with the selected material, machine design, and working parameters were effective in improving peanut shelling quality.