Abstract in English:

ABSTRACT The plastic film materials are a widely used agricultural means of production. Recently, two types of new agricultural film mulches are developed and are used popularly. They are ethylene-vinyl acetate copolymer (EVA) and polyolefin (PO) film mulches. The transmittances of film mulches are related to thermal reservation and plant photosynthesis. We experimentally measure transmittances of several EVA and PO film mulches under different wavelengths. We also find that the transmittances of mulches vary with light intensity change at one wavelength. The variable transmittances for these mulches are also measured in experiments. These data measured can provides help for agricultural production and accurate numerical simulation for the establishment microclimate of plastic greenhouse, even the degradation of plastic films.

Abstract in English:

ABSTRACT The seed deterioration process during storage is inevitable, but it can be slowed down using packaging that reduces the influence of the external environment on stored corn seeds. Therefore, this study aimed to evaluate the physiological quality of corn seeds stored in different packages and subjected to storage conditions in the central region of Brazil. Thirty-seven corn genotypes were analyzed in three storage environments: multiwall paper, 10 °C temperature, and 40% relative air humidity; multiwall paper under uncontrolled conditions; and hermetic packaging under uncontrolled conditions. The results of germination, water content, electrical conductivity, accelerated aging, soilless cold test, and field emergence test were used. Physiological quality assessments indicated that storage under conditions of 10 °C temperature and 40% relative air humidity is more efficient in preserving corn seeds' physiological quality than packaging in an uncontrolled environment.

Abstract in English:

ABSTRACT Safflower stands out among oilseeds due to its oil quality and crop resilience in dry and cold regions. However, there have been limited studies on its water requirements. This study aimed to assess water stress indices and determine phenological stages with the highest water demands during safflower cultivation. The experiment was conducted in two phases: one in a greenhouse and another in the field. Treatments involved different irrigation timings during the stages of crop development. The variables analyzed included plant height, stem diameter, fresh and dry aboveground biomass, number of capitula, and number and weight of seeds. The results showed that safflower cultivation benefited from irrigation during its vegetative stage, in conjunction with irrigation during the reproductive and/or grain formation stage. It exhibited susceptibility to water deficit when irrigated only during the vegetative stage. Safflower can be cultivated in various climatic regions of Brazil and become an economically important species due to its adaptability, production, and potential.

Abstract in English:

ABSTRACT Maize yields are important for human food security, and the issue of how to quickly and accurately segment areas of maize disease is an important one in the field of smart agriculture. To address the problem of irregular and multi-area clustering of regions of maize leaf lesions, which can lead to inaccurate segmentation, this paper proposes an improved Swin-Unet model called squeeze-and-excitation Swin-Unet (SE-Swin Unet). Our model applies Swin Transformer modules and skip connection structures for global and local learning. At each skip connection, a SENet module is incorporated to focus on global target features through channel-wise attention, with the aims of highlighting significant regions of disease on maize leaves and suppressing irrelevant background areas. The improved loss function in SE-Swin Unet is based on a combination of the binary cross entropy and Dice loss functions, which form the semantic segmentation model. Compared to other traditional convolutional neural networks on the same dataset, SE-Swin Unet achieves higher mean results for the intersection over union, accuracy, and F1-score, with values of 84.61%, 92.98%, and 89.91%, respectively. The SE-Swin Unet model proposed in this paper is therefore better able to extract information on maize leaf disease, and can provide a reference for the realisation of the complex task of corn leaf disease segmentation.

Abstract in English:

ABSTRACT During high-speed seeding operations, collisions between seeds and seed guide tubes are very significant, resulting in poor seed spacing uniformity. To solve this problem, a high-speed seed guide device with conical spiral airflow was designed, which can use high-speed positive pressure airflow to move seeds smoothly. To improve the uniformity of the airflow field in the device, a single-factor test was carried out to determine the reasonable range of each factor. Then, the four-factor and five-level central composite test was carried out. The four main factors were screw pitch, cone angle, width of gap, and angle of air-tube, and the evaluation index was the mean variance of airflow velocity. The test results showed that the optimal parameters of the high-speed seed guide device with conical spiral airflow were a screw pitch of 24.98 mm, cone angle of 7.47/55, width of gap of 5.31 mm, and angle of air-tube of 25.09º. The verification test showed that the relative error between the verification test value and the predicted value was less than 5%, indicating that the model had high reliability. This research can provide references for the research of high-speed seed guide technology and the innovative design of seed guide devices.

Abstract in English:

ABSTRACT Current corn sowing equipment shows relatively low levels of automation and intelligent response. Issues such as wheel slipping and chain jumping occur in seeders driven by wheels and chains, leading to a decrease in the seeding qualification rate. To solve the problems of wheel slipping and low control strategy accuracy, an electric control sowing system has been designed. This system uses radar to collect the locomotive speed and automatically adjusts the motor speed. To improve the control accuracy of the electric control system, a dual closed-loop control method is employed, and the proportional-integral-derivative (PID) controller parameters are optimized by combining the particle swarm optimization (PSO) algorithm and the fuzzy algorithm. Control accuracy tests and field tests are conducted for both the traditional PID control system and the fuzzy PID control system based on the PSO algorithm. The average error of this system is 0.622%, which is 1.6% lower than that for the traditional method. Field tests show that in operation, the sowing system achieves the average seeding qualification index of 93.99%, which is 3.19% higher than that for the traditional PID control method. The fuzzy PID control system shows improved sowing effectiveness compared to the traditional PID control method.

Abstract in English:

ABSTRACT To address the poor fitness and low accuracy of multiobjective parameter optimization, the BP neural network-based constrained multiobjective optimization method was applied to optimize a seed-metering device. Taking the 2BQ-15 type Panax notoginseng seed-metering device as the research object, the picking hole column diameter, forward velocity, and dropping seed point-to-picking hole roll distance were selected as the experimental factors, and the quality index, missing index and multiple index were selected as the performance indicators. The experimental scheme was designed by the quadratic orthogonal rotation combination, and the BP neural network of the precision seed-metering device was built from the experimental data. The seed-metering device was optimized by the proposed method, and the optimal parameter combinations were obtained as follows: the picking hole column diameter was 27 mm, the forward velocity was 0.50 m/s, and the dropping seed point-to-picking hole roll distance was 330 mm. Under such parameter combinations, the quality index is 93.4%, the missing index is 3.15%, and the multiple index is 3.35%. Finally, a verification test was carried out on the basis of the optimization results, the errors were within the allowable range, and the test results and optimized results were consistent.

Abstract in English:

ABSTRACT Rapeseed cutting and sunning are important processes associated with rapeseed harvesting in China. However, existing rapeseed windrowers have problems such as a tendency to entangle rapeseed plants, low laying quality, low operational efficiency, and high cutting power consumption for tall rapeseed plants. Hence, a new type of rapeseed windrower was designed. A new cutter with a planetary gear driving double moving cutting bars was designed, a motion model of the planetary gear mechanism was established, and the motion and structural parameters of the cutter were analysed. A theoretical analysis of this new cutting system showed that it not only had low cutting impact, minimal disturbance to rapeseed stalks, and high cutting continuity, but also low power consumption and stable operating performance. A reel based on a double-crank planar five-link mechanism was designed, and kinematics modelling and analysis of the new reel were carried out. The structure and motion parameters for the new reel were obtained. Finally, field experiments were conducted on both the newly designed rapeseed windrower and the original one. The results indicated that the newly designed windrower was suitable for high-quality, efficient cutting and sunning operations for tall rapeseed plants.

Abstract in English:

ABSTRACT Accurate crop classification, crucial for a macro-level understanding of food production, formulating relevant agricultural policies, and predicting comprehensive agricultural productivity, enables precise crop distribution. In remote sensing image classification, feature selection and representation play a pivotal role in accuracy. An augmented U-Net algorithm, named ASPP-SAM-UNet, integrating spatial attention mechanisms and multi-scale features is proposed for the enhancement of typical crop classification accuracy in remote sensing. The ASPP-SAM-UNet design integrates features over multiple scales, boosts the representational capacity of shallow features, and expands the neural network’s receptive field by incorporating Atrous Spatial Pyramid Pooling (ASPP) into the convolutional components of the standard U-Net encoder via residual connections. The integration of the residual module allows for a profound fusion of deep and shallow features, thereby enhancing their utility. The spatial attention mechanism amalgamates spatial and semantic information, empowering the decoder to reclaim more spatial information. This study focused on Bayan County, Harbin City, Heilongjiang Province, China, employing GF-6 WFV remote sensing images for crop classification. Empirical outcomes showed a significant improvement in classification accuracy with the advanced algorithm, boosting the overall accuracy (OA) from 89.49 to 92.80%. Specifically, the segmentation accuracy for maize, rice, and soybean increased from 89.90, 89.96, and 87.37% to 93.47, 94.82, and 89.35%, respectively. The suggested algorithm offers a pioneering performance standard for crop classification leveraging GF-6 WFV remote sensing imagery.

Abstract in English:

ABSTRACT This study aimed to obtain the sorption isotherms of grain sorghum flour, fit mathematical models to experimental data, and recommend safe water levels for preserving the material at different temperatures. Sorghum grains with an initial moisture content of 34% dry basis (db) were subjected to drying at a temperature of 60 °C, reaching moisture contents ranging from 32.20 to 9.8% db. Water activity was obtained using Hygropalm Aw1 equipment placed inside a BOD chamber at temperatures of 10, 20, 30, and 40 °C. The experimental data were fitted to mathematical models frequently used to predict the isotherms of plant products. The modified Oswin model presented the best fit to estimate the sorption isotherms of sorghum flour. Safe moisture content limits for storing sorghum flour are 18.45, 17.3, 16.08, and 15.2% db for temperatures of 10, 20, 30, and 40 °C, respectively. The isosteric heat for the range of equilibrium moisture contents from 9.80 to 32.20% db varied from 2779.49 to 2498.46 kJ kg−1.

Abstract in English:

ABSTRACT To meet environmental standards and sustainability policies, diesel-biodiesel-ethanol blends have been investigated as partial replacements for diesel. This study aimed to evaluate the emissions and performance of a diesel engine using a blend of biodiesel and ethanol. Four blends of biodiesel (7, 10, 15, and 20%) and four blends of ethanol (0, 1, 3, and 5%) were used. The power remained stable with the addition of biodiesel but decreased with the addition of ethanol for all blends. The power was reduced from 76 to 74 kW when the ethanol content increased from 0 to 5%. The addition of 1% ethanol increased the maximum torque linearly from 372 to 378 kW. A slight increase in the specific consumption was observed with the use of biodiesel and ethanol in the blend. An increase in the ethanol fraction from 0 to 5% reduced nitrogen oxide emissions, especially at high loads. Ethanol caused a decrease of up to 42% in nitrogen oxide. At high loads, a reduction in carbon monoxide emissions was observed with an increase in the blends of ethanol and biodiesel. Blends of biodiesel and ethanol with concentrations of 20% biodiesel and 5% ethanol are alternatives to diesel in agricultural tractor engines.

Abstract in English:

ABSTRACT Considering the spectral differences between broadleaf weeds and narrow-leaf crops and the influence of terrain and soil variables on weed infestations, integrating such information into a machine-learning algorithm can lead to accurate weed maps. Therefore, we aim to evaluate the effectiveness of these variables in classifying the occurrence of broadleaf weeds in narrow-leaf crops. Weed data was collected at georeferenced points across two areas covering 200 ha (pasture) and 106 ha (sorghum), creating classes 0 (absence) and 1 (presence). For each sample point, we obtained 11 variables: soil clay content, cation exchange capacity, soil organic matter, terrain elevation, slope, NDVI, EVI, CIgreen, BGND (derived from PlanetScope images), and spatial information (X and Y coordinates). These variables were used as predictors of broadleaf weed presence and absence in the Random Forest classification algorithm. The presence and absence of broadleaf weeds were correctly classified in 84% and 74% of all predictions in the test sample sets for pasture and sorghum areas, respectively. This strategy represents an efficient way to map and manage the occurrence of broadleaf weeds in narrow-leaf crops.

Abstract in English:

ABSTRACT A sunken solar greenhouse is a unique structure used in China that has good thermal performance and a low cost. To explore the thermal environment and the marginal effect area under the trellis membrane in a sunken solar greenhouse, daytime heat absorption and nighttime exothermic models of the greenhouse were established based on existing theories and hypotheses. An experimental study of the three-dimensional thermal environment of a solar greenhouse was also conducted in the Jinzhong Basin of Shanxi Province. The daytime heat absorption model described how the internal thermal environment of the greenhouse changes in three dimensions, while the nighttime model calculated the amount of heat released at night. The results showed that the rate of change in the maximum temperature difference along the height direction in the greenhouse was 13 times that along the vertical direction, and three times that along the horizontal direction. We also observed that the marginal effect area under the membrane varied over time and by month. The minimum value of the marginal effect area occurred at the middle cross-section, spanning the middle position of the greenhouse, and the maximum height was 2.7 m. The results of this study can provide theoretical guidance and experimental data for the thermal environment of greenhouses of the same type in the Jinzhong Basin of Shanxi Province, thus providing a basis for environmental regulation and low-temperature margins in greenhouses.

Abstract in English:

ABSTRACT This study aims to investigate the influence of moisture contents and grouser heights on traction force exerted on different surfaces in the track-soil interaction system. A sandy loam was employed for acquiring the soil parameters, such as kc, kφ, n, C, Ca, δ, φ, and γ. These parameters were obtained through the mean of the bevameter technique. Moisture contents of the sandy loam were changed from low to high levels, which could be listed as 1.4%, 8.0%, 14.7%, and 22.2% at last. The direct shear and penetration tests were performed for each soil condition of the moisture content, respectively. The model of the single-grouser-shoe (track model) had a length of 9 cm, a width of 15 cm, and varied grouser heights from 0 to 15 cm with a 0.5 cm interval. Based on the calculation result, in general, the shearing force produced by the bottom surface always performs better than either the shear force on the grouser-tip surface or two lateral surfaces. Simultaneously, prediction results also show that the shearing forces were significantly influenced by the level of moisture content in the soil.

Abstract in English:

ABSTRACT During the harvesting of waste straw in the field, a self-propelled baler undergoes significant oscillations in the longitudinal direction around its centre of gravity, which greatly affect the stability of operation and the comfort of the driver. In order to analyse the vibration characteristics of the main frame under multi-source excitation, the complete frame is divided into a chassis frame and a baling frame. A nine-degree-of-freedom vibration system model of the whole machine is established based on the relationship between the internal motion devices, and simulations are carried out using MATLAB/Simulink. In addition, a multi-body dynamics simulation of the compression device is carried out, and the law governing the variation in force at different unit points of the mechanism is analysed. Finally, the vibration response of the main frame under different working conditions is explored. The results show that the main frequency component of the frame in the no-load state is 80 Hz, and the main response frequency of the frame is about 1.6 Hz, a finding that is consistent with the operating frequency of the compression mechanism. In particular, the displacement amplitude of the simulated signal at the centroid position is consistent with that measured in experiments, which verifies the validity of the dynamic model. Our results can provide guidance for future work aiming to further reduce the body vibration amplitude and optimise the design of the frame.

Abstract in English:

ABSTRACT As the application scenarios of embedded devices become increasingly extensive, the use of high-performance convolutional neural networks can solve the problem of low accuracy of multiple defects detection in apples. However, owing to the overly large parameters and network structure of the convolutional neural network, perfectly integrating it with the embedded devices is difficult. Therefore, this study proposes a lightweight and improved algorithm based on Yolov5s. First, the structure of the optimized MobileNetV3 is introduced in the backbone layer to reduce the computational and parametric quantities of the model. Wise-IoU is used as the loss function of the localization regression of the bounding box to reduce the harm of low-quality samples on anchor box regression. The efficient multiscale attention mechanism is embedded in each downsampling layer of the backbone, and small target detection is added to the neck layer to improve the attention of the convolutional layer on important features. The experimental results showed that the Yolov5s-Super model parametric count decreased by 78%, and accuracy P, mAP@50, and mAP@50:95 improved by 10.3%, 3.2%, and 4.2%, respectively, compared to the original model. Theoretical support is provided for the migration of this network model to embedded devices.

Abstract in English:

ABSTRACT As weeds cannot be eradicated in corn fields, a crab claw toe was used as the research object and combined with the agronomic requirements of corn fields to design a bionic weed claw suitable for corn fields. The contour curve of the crab claw toe was extracted and fitted through the Matlab image processing technology and fitting tool to establish a bionic claw finger 3D model using Solid works. According to the mechanical soil dynamics theory of dynamics analysis, the root–soil aggregates are easily broken, loosened, and drained under the action of the bionic claw fingers. Based on single image inverse reconstruction technology, the weed root system–soil aggregates discrete meta-model was established. Recur Dyn was used in the bionic weed claw kinematics simulation to verify the reliability of the movement of the mechanism and to realise the expected action of the weeding operation. We analysed the movement speed, displacement, and trajectory of soil particles in different depth layers through the joint simulation and comparison test. Using the mechanism of weeding and resistance reduction of the bionic weeding claw, under the same working conditions, the average resistance reduction rate of the bionic claw finger compared with the flat claw finger in the grasping process was 16.4%. The resistance of grass roots was reduced 23.3%, making it easier to pull out the more intact grass roots.

Abstract in English:

ABSTRACT In complex environments, beet harvesters vibrate strongly under the influence of multiple sources of excitation. The modal constraints of the harvester's frame were obtained using modal simulation, and the accuracy of the finite element model was verified through SIMO modal testing. Additionally, field experiments were conducted to collect the vibration signals of the harvester under various conditions. Time-domain analysis revealed that the RMS value of the frame's Z-axis acceleration was highest in sugar beet fields and lowest on unpaved roads. There is a correlation between the operation of working components and changes in amplitude. Frequency domain analysis determined that the main vibration frequency of the frame was in the range of 0–75 Hz, and the operating frequency of the engine (35 Hz) and the power input shaft (12.7 Hz) excites the constrained modal of the frame, which may lead to resonance. Integrating the results of the modal response and vibration testing provides a more comprehensive approach to studying the vibration characteristics of agricultural machinery.

Abstract in English:

ABSTRACT This study aimed to evaluate the duplicity and synergism of slow drying and storage processes at low temperatures, using a refrigerated room under suitable conditions for coffee fruit just after harvest. A cold room was prepared to receive and store coffee fruit in bulk directly from the field, perform slow drying, and maintain water content at approximately 12% during three months of storage. The room operated at temperatures between 7 and 14 ºC and relative humidity between 37 and 41%. The coffee variety used was the Conilon Yellow 62. The initial water content reduction period from 54% (wb) to 12% (wb) was two months. For comparison, coffee harvested from the same batch was dried on a covered suspended bed. Results showed that the coffee dried and stored in the cold room received a sensory score of 86.41, while that dried on a suspended bed obtained a sensory score of 84.16. Moreover, the coffee dried and stored in the cold room had a higher energy content. Colorimetric analysis showed that the dried grains stored in the cold room had a reduction in the "a" coordinate, indicating an approximation to the green color. The cold room also allowed for extended storage of the coffee grains.

Abstract in English:

ABSTRACT There are significant differences in the quantities of Camellia oleifera fruits growing within and outside the canopy distribution, meaning that a single mode of picking has drawbacks. To improve the harvesting efficiency for the inner and outer layers, this article proposes a synergistic mode of harvesting based on a vibration comb brush, and presents a design for a harvesting device based on this principle. The overall structure and working principle of the proposed device are explained, and the operational processes of the vibration and comb parts of the device are analyzed. ADAMS software is used to construct a rigid-flexible coupling model of the device and the fruiting branch, and simulation results are presented to show that the fruit drop and flower loss rates for Camellia oleifera are related to the vibration frequency, the amplitude, and the spacing between the teeth and comb plates. Finally, a three factor and three level field orthogonal experiment was conducted, and the results showed that under the conditions of vibration frequency 5.85Hz, amplitude 60.43mm, and comb spacing 45mm, the flower loss rate was the lowest and it had good picking performance. Under these conditions, the fruit drop rate is 87.32% and the flower loss rate is 8.06%, values that meet the requirements for mechanized picking of Camellia oleifera fruits.

Abstract in English:

ABSTRACT Fertilization at the large bell stage of maize is the key to increasing maize yield and improving fertilizer use efficiency. To achieve fast and accurate recognition of maize stems by intelligent agricultural equipment in complex field environments, an improved YOLO v4 maize stem recognition model with an increased CBAM, which can achieve real-time identification and positioning of maize stems, is proposed. In this paper, first, we collected images of maize stems under different conditions in the field, expanded the maize stem images and produced a maize stem image dataset by adding Gaussian noise, changing the brightness and performing other data enhancement methods, and manually annotated the maize stem via LabelImg software. Second, a convolutional block attention module (CBAM) and SIoU loss function were added to the original YOLO v4 target detection network to obtain the CB-YOLO v4 target detection network. Last, this network was compared with the original YOLO v4, Faster-RCNN, SSD and YOLO v3 target detection networks, and it achieved 93.1%, 92.4% and 92.6% precision, recall and mAP (mean average precision), respectively, for maize root recognition, which is significantly better than the other algorithms and is suitable for practical maize interrow operation systems.

Abstract in English:

ABSTRACT In order to realise automatic row alignment for sugar beet harvesting, and to improve the efficiency of sugar beet combine harvesters, it is essential to be able to detect the positions of sugar beet rows. In this paper, we consider beet harvesting as a scenario, and an extraction algorithm for beet crop rows is proposed based on videos of beets collected with a monocular camera. We focus on the characteristics of the root and stem features, which are relatively difficult to distinguish from the surrounding environment after cutting the tops and beating the leaves of sugar beet, and a crop row extraction algorithm is designed in which threshold segmentation is carried out based on histogram equalisation and MM-Filter (median filtering and minimum area filtering) is applied to remove noise. The proposed algorithm retains more complete feature information and has better denoising effect than the traditional algorithm, and the processing time is only 11.751 ms, a value 6.9% lower than for the alternative approach. Our algorithm is feasible in terms of recognition and extraction, and can provide a theoretical basis for the construction of an automatic row-to-row control system for a sugar beet combine harvester. It can also provide technical support for the design of an automatic sugar beet combine harvester.

Abstract in English:

ABSTRACT Mechanised watercress harvesting involves clamping and cutting its stalks, which can result in their incomplete breaking and crushing. The harvest quality is directly affected by the force used to clamp and cut the watercress stalks. Therefore, studying the physical and mechanical properties of the stalks is important to accurately calculate the force that needs to be applied. Herein, the microstructure of watercress stalk sections with and without nodes was observed using scanning electron microscopy. Moreover, the basic physical properties, such as the total length, internode outer diameter, internode inner diameter and water content, of watercress stalks were measured. Additionally, the mechanical properties of watercress stalks at different positions were measured using four modes: tension, compression, shear and bending. Results revealed that watercress stalks with nodes exhibited a more pronounced medullary cavity and a greater number of internal vascular bundles. The lower section of the watercress stalks was considerably more resistant to mechanical stress than the rest of the stalk. Further, in terms of resisting load, the stalks with nodes were stronger than those without nodes. This study provides useful information for efficient watercress harvesting.

Abstract in English:

ABSTRACT We focus here on the problem of poor real-time performance and low accuracy of seed box allowance detection during wheat sowing operations, and present a real-time weighing system for a seed box allowance. The proposed weighing system obtains the seed box allowance using an ultrasonic sensor and load cell, and displays it in real time via a computer. Based on the proposed weighing system, the weighing structure is also designed for the seed box. At the software level, three filtering methods are proposed to condition the signal, namely mean filtering, median filtering, and the acceleration method, and models of these three filtering algorithms are implemented in MATLAB/Simulink. Experiments to assess the accuracy of the system and filtering algorithm were carried out on the test bench; the results show that the system error is initially in the range −16.3 g to 63.8 g, and is reduced to the range −13.4 g to 15.1 g after correction. No significant difference between the three filtering algorithms is found, but since the acceleration method can improve the response speed of the system, this is selected as the final filtering method.

Abstract in English:

ABSTRACT Banana stalk production for fiber is an important crop activity in southern China. The fiber extraction technology used has a great impact on the effectiveness and quality of the fiber from banana stalks. A mechanical model of the process for banana stalk fiber extraction was developed through theoretical analysis. The existing problems of machines for banana stalk fiber extraction include high rates of fiber impurity and damaged fibers. A 3-factor 3-horizon orthogonal rotation combination test was established. The rates of fiber impurity and damaged fibers were the evaluation indices. The significant order of the factors determining the rate of fiber impurity, from largest to smallest, was the gap between the scraper and the holding plate, the number of scrapers, and the rotational speed of the scraping knives roller. The significant order of factors for the rate of damaged fiber was the gap between the scraper, the rotational speed of the scraping knives roller, and the number of scrapers. The optimized banana straw fiber extraction machine was tested in the field. The results show that the development of this model can provide valuable experience and references for understanding and improving other similar agricultural machinery and equipment.

Abstract in English:

ABSTRACT The use of irrigation enhances productivity, reduces vulnerability to drought and climate variation, and boosts agricultural production. This study aimed to verify the economic viability of implementing center pivot irrigation for corn, cowpea, and soybean crops. A 50-hectare area irrigated by a center pivot system was considered, simulating rotational cultivation in the region of Paraíso das Águas, MS. The historical average ET0 of 8 mm day-1 for the region was used for project design and irrigation management. Financial indicators were calculated based on regional technical cultivation coefficients. Overall, 62.1% of the total production costs for the corn, cowpea, and soybean agricultural system were allocated to preparation, planting, cultural practices, and harvesting, while 34.8% were allocated to irrigation (investment in hydraulic equipment and infrastructure, energy, depreciation, and maintenance). The net present value (NPV) for corn, cowpea, and soybean crops were $72.07, $359.68, and $410.59 per hectare, respectively, averaging $842.34 per hectare per year. This profitability provides gains for producers, generating employment and regional development. The implementation of a 50-hectare center pivot irrigation system is economically feasible for cultivating corn, cowpea, and soybeans, considering a 4-year and 9-month return on capital investment under the study conditions.

Abstract in English:

ABSTRACT This study aimed to evaluate, on a real production scale, the management of batches of harvested soybean grains in storage units, which are submitted for different technological processes of drying. The study regions were divided into micro-regions based on structure and static storage capacity. For each micro-region (West, East, North, South, Central), soybeans were dried using a continuous dryer-CD1, a continuous dryer + silo-dryer-CDSD2, and a continuous dryer + aerator-silo-CDAS3. Grain quality losses due to drying management ranged from 0.23 to 3.26% in crude protein, and from 0.15 to 3.05% in crude oil. In regions with large-scale soybean production, adopting storage unit structures at the farm level, ranging from 11 to 19 km, with high drying technology in partial continuous grain flow and final stationary drying in a silo-dryer or silo-aerator is the best alternative for a productive-sustainable system. Managing CDSD2 and CDAS3 soybean drying system is an alternative that ensures low losses and high grain quality, improving protein and crude oil content. In conclusion, the CDSD2 and CDAS3 drying systems reduced crude protein and oil content losses by 94% and 95%, respectively, providing a much better sustainable postharvest system.

Abstract in English:

ABSTRACT Wheel slipping and fuel consumption are variables influenced by tire pressure, speed, ballasting, and soil surface. Once the tractor is present in all agricultural operations, knowledge of these variables is essential to achieving the most operational efficiency. This study aimed to develop an embedded system to collect data and show tractor slipping and fuel consumption in real-time via smartphone. The system was developed using prototyping platforms and validated through randomized field tests under four speeds and two terrain conditions. Three methods for determining slippage under different conditions were compared. The developed embedded system determined an agricultural tractor's slipping and fuel consumption conditions. The slip and fuel consumption rates varied depending on the type of rolling surface (ground preparations) and the tractor's operating speeds. Conventional tillage surface increased fuel demand by 6% and slippage by 17% compared to no-till rates. The proposed embedded system found similar results and could present the slipping values in the developed Android to real-time operation compared to a conventional method. This application shows both slipping and fuel consumption values over time on graphs, which can be very useful during machine operation, helping to define better configuration and reduce environmental impacts.

Abstract in English:

ABSTRACT The aim of this study was to improve the accuracy of pig behavior identification and classification using a feature extraction method. Pig activity was measured with a triaxial accelerometer, capturing acceleration data in the X, Y, and Z directions. Statistical features, including the mean, median, maximum, minimum, first quartile, and third quartile for each axis, were extracted to form a 21-dimensional dataset. ReliefF and random forest algorithms were used to analyze and rank the significance of each feature for behavior identification and classification. Features with minimal impact were removed, reducing the dataset from 21 to 9 dimensions. The results showed that when using the ReliefF-reduced dataset, the major mean accuracy for identifying and classifying behaviors of Pigs A, B, and C was 80.9%, 81.7%, and 82.0%, respectively. Similarly, when using the random forest-reduced dataset, the major mean accuracy was 86.4%, 85.3%, and 87.2%, respectively. Thus, the random forest algorithm demonstrated superior performance in feature extraction and dimensionality reduction for classifying pig behavior in this study.

Abstract in English:

ABSTRACT Discrete element method is widely used to study grain particles; however, there is a lack of research on the mathematical model parameters of rice straw particles in the crushing simulation process. To determine suitable parameter settings for crushing of rice straw particles in the simulation process, a twin-screw rice straw crushing test device was built using rice straw particles as the research object. Through actual tests, the parameters of the Ab-T10 crushing models of rice straw particles with five different moisture contents were calibrated, and the crushing characteristics of the rice straw particles were analyzed. The Ab-T10 crushing models with calibrated parameters were verified by comparing the probability of the particle-size distribution (t10) between the simulation and actual tests. The results show that the crushing probability and t10 of rice straw increase with the increase in accumulated contact specific energy and decrease with the increase in rice straw moisture content. The minimum value of the fitting parameter between the simulated and measured values is 0.9654, which indicates that the calibrated Ab-T10 crushing model can accurately simulate the rice straw particle-crushing process. This study provides a reference for the analysis of crushing in subsequent rice straw pulping.

Abstract in English:

ABSTRACT For the classification and zoning study of crops at Jianshan Farm, data were acquired by integrating Sentinel-2 optical satellite imagery with Sentinel-1 radar satellite imagery. Different crop spectral features were extracted, and four vegetation indices (NDVI, SAVI, EVI, and NDWI) were computed to analyze the spectral differences among soybean, corn, potato, and sorghum. The UNet algorithm was employed to conduct crop zoning on the remote sensing images of Jianshan Farm from September 2020 to September 2023 for four consecutive years. An improved UNet model incorporating a channelwise attention and spatial attention module (CBAM) achieved a prediction accuracy of 100% for the 2023 image data. This represents a 12.5% improvement over the baseline UNet model. These results provide data support for research on crop classification methods.

Abstract in English:

ABSTRACT Agriculture consumes the largest amount of water resources in the world; for this reason, developing technologies aimed at efficiently using these resources for food production is necessary. In the present work, red-green-blue (RGB) and infrared (IR) images of plots with corn (Zea mays L.) were used to estimate the changes in soil moisture. These images were obtained by cameras installed in an unmanned aerial vehicle (drone), which flew over the plots on different dates. The results showed that both RGB and IR images of corn plants can be used to estimate soil moisture with minimum and acceptable levels of root mean square error (with RMSEs of 1.02 and 1.58 for RGB and IR images, respectively); however, the optical response of plants can be altered by different factors in addition to changes in soil moisture; thus, the training of mathematical models to estimate this variable should preferably be performed with validation data at the plot level.

Abstract in English:

ABSTRACT The traditional wheat plot seed-metering device is hampered by poor seed dispersion uniformity and a long seed falling time. To improve upon these characteristics, in this paper, we designed a double-cone combined seed-metering device. Motion analysis was conducted of wheat seeds sliding down the device, and it was concluded that the motion of wheat seed grains is affected by the cone diameter (D), cone angle (θ), and cone compartment tray rotational speed (n). The D, θ, and n were listed as test factors, and the variation coefficient of seed dispersion uniformity (VCU) and the speed of seed entry into the compartment tray (SC) were used as test indexes to conduct a test with discrete element simulation software. The results of the simulation test showed that the best performance of the seed-metering device, a VCU of 8.75% and an SC of 1.03 m s-1, was obtained when the D was 173.23 mm, θ was 45.78°, and n was 4.43r min-1, and the bench verification test was carried out under the optimal parameters, a VCU of 9.10% and an SC of 1.05 m s-1. It was shown that the simulation test was consistent with the bench test. The results of this paper provide a reference for optimizing the design of the seed-metering device and improving the seed dispersion uniformity of the wheat plot seeder.

Abstract in English:

ABSTRACT In the satisfactory development of soybeans an ally is quality seeding and soil preparation. The aim was to evaluate the quality of soybean seeding under different speeds and cover crops. The experiment was conducted in a commercial soybean crop, using a high-performance pneumatic seeder. The design experimental was randomized blocks, in 2x2 strip arrangement and nine repetitions. The factors consisted of two seeding speeds (7.0 km h-1 and 8.5 km h-1) and two cover crops (Urochloa brizantha cv. Marandu and Urochloa ruziziensis). The operational quality was analyzed by statistical quality control, statistical process control and boxplot. It was found that U. ruziziensis provided more uniformity of coverage and soil humidity than U. brizantha cv. Marandu, but with lower straw produced. It is recommended speeds of 7.0 and 8.5 km h-1 for no-till soybean in U. ruziziensis straw, and 7.0 km h-1 in U. brizantha cv. Marandu straw.

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ABSTRACT Fatigue vibration is a primary cause of fruit damage during transportation. Drawing on the Palmgren–Miner fatigue accumulation damage theory and the correlation between fruit vibration damage characteristics and external vibration excitation, this paper proposes a fruit vibration fatigue accumulation damage model and its method for parameter determination. Using pears as the research objects, we conducted fatigue damage vibration and critical fatigue damage vibration tests under various conditions to determine the vibration fatigue constant of the pears. By utilizing the critical value of the damage area specified in the pear grading standard for premium grade, we derived the threshold acceleration value for pear damage. These findings serve as a technical foundation for advancing our understanding of fruit vibration fatigue damage mechanisms and guiding the development of cushioning packaging to protect fruit from vibrations.

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ABSTRACT Chickpea has recently gained prominence in agriculture, being an excellent option for crop rotation in areas cultivated with soybean or corn. Seeds must have good physiological quality, mainly during storage, to ensure crop success. Seeds undergo metabolic reactions that impair their performance when stored improperly. In this context, a study was carried out to evaluate the physiological variables of the chickpea cultivar BRS Aleppo in different types of packaging and storage environments. The analyses were performed with seeds evaluating water content, germination, first count, and accelerated aging, according to established standards. Therefore, the physiological quality of chickpea seeds can be preserved through controlled storage in hermetic packaging, thus ensuring their viability and vigor over time.

Abstract in English:

ABSTRACT The use of reduced-scale physical models is highly valuable, as it is based on the theory of similarity. These models have become an important factor in evaluating different roofing materials for intensive animal farming. In light of this, this study aims to evaluate the thermal performance of different types of roofing, with various roof modification techniques (ceiling and roof shading). Fifteen reduced-scale models of broiler houses (1:10) were employed to evaluate the following treatments: roofing materials (ceramic, fiber-cement, and metal) and adaptations (control, thermal shading net 70% coverage on the roof, black shading net 70% coverage on the roof, ceiling with thermal shading net 70%, and ceiling with black shading net 70%). The results indicate that the utilization of ceilings, especially ceilings with black shading net 70%, is the most effective treatment in reducing all thermal comfort indices. However, none of the treatments were efficient enough to reduce the indices to a level that would provide a comfortable environment for broiler chickens.

Abstract in English:

ABSTRACT The use of unmanned aerial vehicles (UAVs) to apply pesticides has grown significantly, but technical data to support improvements in application efficiency are lacking, especially for perennial crops. This study aimed to determine the best operational parameters for the application of pesticides to coffee plants using UAVs. The experiment consisted of 8 treatments and 4 replicates in a 2x2x2 factorial design: two spray mixture compositions (solutions with spreading adjuvant and mineral oil), two spray nozzles (XR flat-fan nozzle and Airmix flat-fan nozzle with air induction) and two spray volumes (10 and 20 L ha-1). Spray solution deposition was evaluated by spectrophotometric detection of a tracer in leaves from the upper and lower parts of the coffee canopy, and spray coverage, droplet density and droplet size were evaluated using water-sensitive paper. The surface tension, pH and electrical conductivity of the solutions were also evaluated. The air induction nozzle was more suitable than the standard nozzle for UAV application, as the former yielded greater deposition of spray solution. Mineral oil improved the spray deposition on the coffee leaves, although the spreader reduced the surface tension to a greater extent. The higher spray volume increased the droplet density, as well as the coverage, which is very relevant, especially whit contact pesticides.

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ABSTRACT Pleurotus ostreatus is considered a functional food with benefits for human health. However, its shelf life is very short even when refrigerated. This study compared the effects of five drying treatments on the water activity, color, microstructure, hardness, rehydration index, total polyphenol (TP) content and volatile compounds of P. ostreatus. The drying treatments included lyophilization (T1), forced air oven drying (T2) and refractive window (RW) drying at 60 °C (T3), 70 °C (T4) and 80 °C (T5). Bromatological analysis showed that the samples contained high concentrations of proteins and carbohydrates, with values of 29.28 g/100 g and 47.80 g/100 g, respectively. Microstructural analysis revealed less cell shrinkage and damage under T1 than under the other treatments. This finding was corroborated by the texture analysis results, which indicated a lower hardness value for T1 (5.07 N) than for T2 (8.94 N). The TP content varied between 4.62 and 6.82 mg GAE/g. Some parameter values of samples treated by RW at 80 °C were similar to those of lyophilized samples, showing that RW, which presents advantages over lyophilization, such as a lower cost and processing time, is very suitable for dehydrating P. ostreatus.

Abstract in English:

ABSTRACT To solve the problem of slow seed filling of soybean seeds under their own gravity, this study presents the design of a push-type precision metering device. Through a theoretical analysis, the key components and working principle of the push-type precision metering device were determined. The operational process was divided into two stages: dropping of seeds, and pushing of seeds. The discrete element method and a regression analysis were used to optimize the working parameters during the seed dropping stage. The optimal combination was found by the response surface optimization method, and both the seed dropping module and the whole machine were tested on a test bench with this parameter combination. The results showed that the optimal solution was obtained with a seed stirring disk speed of 17.57 r min-1, 8.8 seed stirring rods (rounded to nine), and a central arc length proportion of 3.5% in the seed entry port. The predicted number of seeds dropped into the seed discharged cylinder (Y1) under this parameter combination was 678.96, with a coefficient of variation of seed dropping uniformity (Y2) of 6.33%. The experimental results gave values for Y1 of 691.37 seeds and Y2 of 6.93%, which were close to the predicted results.

Abstract in English:

ABSTRACT The influence of other working parts on the cab of a combine harvester will lead to increased vibration. The traditional time-frequency domain method for vibration signal analysis will result in a mixture of high and low frequencies, and it is impossible to remove irrelevant signals, resulting in unclear characteristic frequency characterization. In this paper, the vibration signal of a harvester under four working conditions is analysed by using the traditional analysis method and a low-pass filter-EEMD combination method. The analysis results show that after low-pass filtering and EEMD signal processing, the vibration signal is decomposed and reconstructed, and irrelevant signal components are eliminated to avoid mode aliasing. After processing, the peak vibration acceleration of the signal is 0.104 m/s2, 0.113 m/s2, 0.089 m/s2 and 0.112m/s2, respectively. This is closer to the simulated acceleration value of the harmonic response mode in the X direction of the cab. In addition, it can effectively extract the external excitation characteristic frequencies (6.4 Hz, 61.44 Hz, 40.96 Hz) of the shaker, grass crusher and engine that cause the increase in cab vibration, helping to quickly find the vibration source in the vibration and noise reduction project of the harvester. It can improve the reliability of the combine, reduce the vibration and failure rate, enhance the driver's comfort and promote the development of agricultural engineering.

Abstract in English:

ABSTRACT This study aimed to evaluate the impact of wear on different models of hydraulic ceramic spray nozzles focusing on changes in flow rate and the droplet size distribution in applications by medium-scale farmers in the agricultural region of Mato Grosso do Sul. Additionally, the study assessed the adequacy of nozzle replacement practices in accordance with recommended guidelines. Seven hydraulic ceramic nozzle models —JA3, AD/D 11002, BD 11002, JCI 80025, AXI 11003, CVI 110025, and AVI 11002—were tested. Nominal flow rates for each nozzle model were measured following ISO 10625 standardization criteria. The evaluated parameters included nominal flow rate, volumetric median diameter (VMD), relative span, and the percentage of the volume composed of droplets smaller than 100 µm (P<100). Prolonged use of hydraulic spray nozzles resulted in increased flow rates and modifications to droplet population characteristics, especially in the variation of the volume percentage of droplets smaller than 100 µm, which are more susceptible to drift. Although wear affected the volumetric median diameter, the change was not substantial enough to alter the droplet size classification.

Abstract in English:

ABSTRACT The MATOPIBA, encompassing parts of the states of Maranhão, Piauí, and Bahia, as well as the entire state of Tocantins, is an expanding agricultural region characterized by water resource management challenges. The availability of water in the hydrographic basins of this region plays a fundamental role in sustaining agricultural activities and preserving local ecosystems. Remote sensing information was used to estimate the flow in 32 hydrographic basins sited in the MATOPIBA region. For this purpose, precipitation and evapotranspiration variables obtained from TerraClimate using the Google Earth Engine (GEE) platform, were considered to calculate monthly, annual, and long-term simplified water balances. To verify the performance of the remotely sensed flow data, the results were compared with those of the Agência Nacional de Águas e Saneamento Básico (ANA), using statistical performance parameters. The results showed that the estimates of long-term and annual mean flows were better than monthly ones. These findings reveal that the simplified water balance done long-term using remote sensing satisfactorily determines mean streamflow in the hydrographic basins of the study area.

Abstract in English:

ABSTRACT Vegetation indices are a quick and practical alternative for monitoring crops due to the availability of satellite images on various platforms for free, allowing a quick analysis of the vegetative state of the crop and interventions in the field in case of signs of diseases and pests. In this context, this study aimed to evaluate the vegetative state of the coffee crop using vegetation indices (NDVI, SAVI, ARVI, EVI, and VDVI) in an agricultural year. The study was carried out on a commercial farm using satellite images from the Planet platform, during an agricultural coffee growing season (2021/2022). The indices selected for the study were the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Atmospherically Resistant Vegetation Index (ARVI), Enhanced Vegetation Index (EVI), and Visible Difference Vegetation Index (VDVI). The index data were analyzed using descriptive statistics, Pearson correlation, classification/interpretation proposal, and the Kappa index. NDVI and SAVI are efficient in monitoring coffee cultivation in an agricultural year, as the Kappa index was higher than 90%. ARVI and EVI had Kappa index values close to 90% and can be used to monitor the crop. VDVI was inefficient, with a low Kappa index value when compared to the others. The proposed classification for vegetation indices based on NDVI classes and values consisted of an important tool for classifying and interpreting the values of these indices, assisting monitoring and management of coffee cultivation.

Abstract in English:

ABSTRACT The geometric characteristics, physical parameters and contact parameters of coated cotton seeds were obtained through theoretical analysis and experimental measurements. A discrete element model reflecting the intrinsic parameters of cotton seeds was established, the contact parameters of coated cotton seeds were calibrated using Discrete Element Method (DEM), and the significant factors affecting the stacking angle were screened using the Plackett-Burman method. The optimal ranges of the parameters were determined by the steepest ascent method, and a second-order regression model of the stacking angle and significant parameters was established by a central composite design. The following optimal values were obtained for cotton seeds: collision recovery (0.38), static friction (0.57) and rolling friction (0.19) coefficients. The average value of the stacking angle obtained by simulations with the best combination of parameters was 30.52°, the result of the simulation test was 30.91°, and the relative error was 1.278%. It is shown that the discrete element particle model and calibration parameters of cotton seed are closer to the actual situation, which can provide theoretical reference for analyzing the precise seeding of cotton seed and optimizing the structural parameters of seed disperser.

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ABSTRACT Cocoa production significantly contributes to Brazil's economy, as the country is the seventh largest cocoa producer in the world. A substantial portion of Brazil's cocoa production comes from family farming, where cocoa bean processing relies on artisanal methods and manual labor. Therefore, there is a need to enhance technology in cocoa bean production, seeking even incremental innovations to increase productivity. This article presents a technical and economic feasibility study for implementing a new management system in the cocoa bean fermentation process on a farm in Novo Repartimento, Pará State (Brazil). The study aims to increase bean production for further processing, suggesting that these changes will improve productivity, reduce costs, and ultimately achieve greater profitability.

Abstract in English:

ABSTRACT Determining hydrographs for hydraulic works projects such as dams and reservoirs requires the definition of the design rainfall hyetograph. The Chicago method stands out as one of the most used methods, with the advantage of being easy to apply. However, the dependence on traditional and updated IDF equations can be pointed out as a limitation of the method. This study aimed to adapt and apply the Chicago hyetograph method with the intense rainfall equations of the alternative model, which stands out for its ease of obtaining and updating. The equations for estimating rainfall intensities for the duration before and after the peak of the hyetograph were presented. The equations were also adapted to obtain the accumulated depths or volumes of rainfall before and after the peak of the hyetograph. This information allows us to easily obtain the rainfall blocks for each interval of the hyetograph. The method was applied to determine the hyetograph based on the maximum daily rainfall, demonstrating each calculation step. The equations presented here can be implemented in electronic spreadsheets or programming routines, allowing Engineering professionals to apply methods that are more appropriate to local data.

Abstract in English:

ABSTRACT The hydrogen sulfide (H2S) present in biogas needs to be removed due to concerns about corrosion during transportation, storage, health and safety. One of the existing removal processes is biological, using a biotrickling filter (BTF). In this study, the performance of full-scale BTF for H2S removal under different operating conditions was evaluated. The BTF system was operated for 300 days, during which two spraying regimes (constant and intermittent) and two sources of nitrate (NO3-) as nutrient solution were evaluated (residual effluent from pig farming and synthetic solution prepared with commercial NaNO3). The performance was monitored by the following parameters: removal efficiency (RE), elimination capacity (EC), pH, dissolved oxygen (DO), empty bed residence time (EBRT) and nitrate concentration (NO3-). The results showed an REH2S = 36.3% with an EC= 1.95 gH2S m-3 d-1 for constant spraying, RE= 99.59% and EC= 4.2 gH2S m-3 d-1 for intermittent spraying with residual effluent from pig farming and RE=99.26% and EC= 4.13 gH2S m-3 d-1 with synthetic solution prepared with commercial NaNO3 solution. The results indicate that intermittent spraying provides better efficiency in the removal of H2S from biogas regardless of the nitrate source (effluent or synthetic medium).

Abstract in English:

ABSTRACT Under the conservation tillage model, corn stubble with a complex structure has become the main obstacle for the operation of tillage tools. To better design relevant tillage tools as a reference, this study established a discrete element model of corn stubble. The intrinsic parameters and partial contact parameters of corn single root (CSR) were obtained through physical experiments, and the maximum shear force (Fmax) of CSR was tested. Fmax was used as the response value, Plackett-Burman test, steepest climbing test, and Box-Behnken test were used to determine the optimal parameters of the discrete element model. The results showed that the coefficient of friction of CSR-CSR, the coefficient of friction of CSR-steel, and the bonded disk radius all had significant effects on Fmax (P<0.01). The optimal solution is when they are 0.81, 0.76, and 0.93 mm respectively. Under this condition, the relative error of Fmax between the simulation and the fitting equation was 2.85%. In addition, shear validation tests were conducted on CSR with different diameters. Finally, based on the actual size of the corn stubble, a discrete element model of the entire corn stubble was established, which can provide a reference for studying the crushing of corn stubble.