Agriculture最新文献

{"title":"Management of Rust in Wheat Using IPM Principles and Alternative Products","authors":"Lise Nistrup Jørgensen, N. Matzen, Rebekka Leitzke, Jane E. Thomas, Aoife O’Driscoll, Bettina Klocke, C. Maumené, Ida Lindell, Kerstin Wahlquist, Līga Zemeca, Marcos Barberena Apesteguia, Biango Randazzo, Svetlana Slikova, Sarah Holdgate","doi":"10.3390/agriculture14060821","DOIUrl":"https://doi.org/10.3390/agriculture14060821","url":null,"abstract":"Overall, there is a major wish that European farmers implement integrated pest management (IPM), particularly to reduce dependence on pesticides. In the European Rustwatch project, partners conducted nineteen trials across nine different countries during 2020 and 2021 to investigate different IPM strategies, focusing on controlling rust diseases in winter wheat. The trials included the use of varieties with contrasting levels of resistance, variety mixtures, reduced fungicide rates, thresholds, and Decision Support Systems (DSSs), and testing alternative products to fungicides. Sixteen trials developed yellow rust (Puccinia striiformis f. sp. tritici) infections, and six trials developed brown rust (Puccinia triticina) infections. Resistant varieties proved highly effective in keeping down yellow rust infection, and variety mixtures also effectively reduced infection levels and stabilized yields. Rust was fully controlled using 25% of standard fungicide rates, even under high disease pressure. Using DSSs provided sufficient control of rust diseases and resulted in competitive net economic returns due to fewer fungicide applications. The alternative products tested included two biological control agents and four alternative chemistries, which all gave inferior and insufficient control against rust compared with chemical fungicides. The trial work demonstrated that there are good and reliable options for including IPM into disease control in wheat.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"4 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141100818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"APEIOU Integration for Enhanced YOLOV7: Achieving Efficient Plant Disease Detection","authors":"Yun Zhao, Chengqiang Lin, Na Wu, Xing Xu","doi":"10.3390/agriculture14060820","DOIUrl":"https://doi.org/10.3390/agriculture14060820","url":null,"abstract":"Plant diseases can severely hamper plant growth and yield. Currently, these diseases often manifest diverse symptoms, characterized by small targets and high quantities. However, existing algorithms inadequately address these challenges. Therefore, this paper proposes improving plant disease detection by enhancing a YOLOV7-based model. Initially, we strengthen multi-scale feature fusion using the fourth prediction layer. Subsequently, we reduce model parameters and the computational load with the DW-ELAN structure, followed by optimizing the downsampling process using the improved SPD-MP module. Additionally, we enhance the Soft-SimAM attention mechanism to prioritize crucial feature components and suppress irrelevant information. To distinguish overlapping predicted and actual bounding box centroids, we propose the APEIOU loss function and refine the offset formula and grid matching strategy, significantly increasing positive samples. We train the improved model using transfer learning. The experimental results show significant enhancements: the mAP, F1 score, Recall, and Precision are 96.75%, 0.94, 89.69%, and 97.64%, respectively. Compared to the original YOLOV7, the improvements are 5.79%, 7.00%, 9.43%, and 3.30%. The enhanced model outperforms the original, enabling the more precise detection of plant diseases.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"77 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141101588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil Organic Carbon Dynamics in the Long-Term Field Experiments with Contrasting Crop Rotations","authors":"Tomáš Šimon, M. Madaras, M. Mayerová, E. Kunzová","doi":"10.3390/agriculture14060818","DOIUrl":"https://doi.org/10.3390/agriculture14060818","url":null,"abstract":"Trends in soil organic carbon (SOC) were analyzed in the soils from the oldest Czech long-term field experiment, the Prague-Ruzyně Long-Term Fertilizer Experiment, conducted on Haplic Luvisol since 1955. The aim of the work was to compare the long-term dynamics of SOC in contrasting crop rotations and different fertilization regimes. The trial design includes two crop rotations (CR): simple CR with two-year rotation of sugar beet and spring wheat, and multi-crop rotation (MCR) with nine crops. Four fertilization treatments were chosen for SOC analysis: unfertilized control, only mineral fertilization (NPK), farmyard manure application (FYM), as well as FYM and NPK application. SOC content was significantly affected by both fertilization and crop rotation practices. In the simple CR, both the unfertilized control and the NPK treatment exhibited a consistent decline in SOC content over the study period, with percentages decreasing from an initial 1.33% in 1955 to 1.15% and 1.14%, respectively. Although the FYM and FYM + NPK treatments showed an increase in SOC content in the 1990s, a gradual decline was recorded in the last two decades. This decrease was not observed in MCR: positive C balances were recorded in all treatments within MCR, with the largest increase in SOC stock occurring when NPK was combined with FYM. In contrast, over the last decade, C balances have decreased in simple CR for all treatments except FYM. This trend coincides with changes in the local climate, particularly rising temperatures. The results indicate that diversified crop rotations and FYM fertilization are effective in mitigating the negative impacts of changing environmental conditions on SOC stocks.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"12 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141100526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model and Parameter Adaptive MPC Path Tracking Control Study of Rear-Wheel-Steering Agricultural Machinery","authors":"Meng Wang, Changhe Niu, Zifan Wang, Yongxin Jiang, Jianming Jian, Xiuying Tang","doi":"10.3390/agriculture14060823","DOIUrl":"https://doi.org/10.3390/agriculture14060823","url":null,"abstract":"To further enhance the precision and the adaptability of path tracking control, and considering that most of the research is focused on front-wheel steering, an adaptive parametric model predictive control (MPC) was proposed for rear-wheel-steering agricultural machinery. Firstly, the kinematic and dynamic models of rear-wheel-steering agricultural machinery were established. Secondly, the influence laws of curvature and velocity on the prediction horizon Np, control horizon Nc, and preview value Npre were obtained by simulating and analyzing the factors influencing the MPC tracking effect. The results revealed that raising Npre can improve curve tracking performance. Np was correlated negatively with the curvature change, whereas Nc and Npre were positively connected. Np, Nc, and Npre were correlated positively with the velocity change. Then, the parameters for self-adaptation of Np, Nc, and Npre were accomplished via fuzzy control (FC), and particle swarm optimization (PSO) was utilized to optimize the three parameters to determine the optimal parameter combination. Finally, simulation and comparative analysis were conducted to assess the tracking effects of the manual tuning MPC, the FC_MPC, and the PSO_MPC under U-shaped and complex curve paths. The results indicated that there was no significant difference and all three methods achieved better tracking effects under no disturbance, with the mean absolute value of lateral error ≤0.18 cm, standard deviation ≤0.37 cm, maximum deviation of U-shaped path <2.38 cm, and maximum deviation of complex curve path <3.15 cm. The mean absolute value of heading error was ≤0.0096 rad, the standard deviation was ≤0.0091 rad, and the maximum deviation was <0.0325 rad, indicating that manual tuning can find optimal parameters, but with high uncertainty and low efficiency. However, FC_MPC and PSO_MPC have better adaptability and tracking performance compared to the manual tuning MPC with fixed horizons under variable-speed disturbance and are more able to meet the actual needs of agricultural machinery operations.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"3 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141101025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vibration Response of Metal Plate and Shell Structure under Multi-Source Excitation with Welding and Bolt Connection","authors":"Zhexuan Ding, Zhong Tang, Ben Zhang, Zhao Ding","doi":"10.3390/agriculture14060816","DOIUrl":"https://doi.org/10.3390/agriculture14060816","url":null,"abstract":"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.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"5 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141098690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Heavy Metal Contamination and Associated Human Health Risk in Soils around a Battery Industrial Zone in Henan Province, Central China","authors":"Jingjing Zhang, Qiujuan Jiao, Yong Wu, Haitao Liu, Peiyi Yu, Deyuan Liu, Dangling Hua, Jia Song","doi":"10.3390/agriculture14060804","DOIUrl":"https://doi.org/10.3390/agriculture14060804","url":null,"abstract":"This research investigated the contamination characteristics, sources, and health risks of five metals in soils from two villages named DK and SXC, downstream from a battery industry hub in Xinxiang city, Henan Province, China. The average concentrations of Cd, Pb, Ni, Cu, and Zn in DK were 5.93, 41.31, 71.40, 62.20, and 115.83 mg/kg, respectively, and in SXC were 2.04, 30.41, 41.22, 36.18, and 96.04 mg/kg, respectively. The single factor pollution index (Pi) revealed a consistent descending order of Cd > Cu > Zn > Ni > Pb in DK and SXC. The geo-accumulation index (Igeo) indicated that the Cd pollution in DK was extreme, and in SXC was at a heavy to extreme level. The potential ecological risk index (PERI) indicated that Cd presented a significantly high ecological risk while it was low for other metals. Principal component analysis classified them into the anthropogenic origin of Cd and common mixed origin of others. The elevated levels and pollution load of heavy metals with closer proximity to the battery factory imply that the factory is a probable source of contamination. Overall, the health risks posed by heavy metals were more pronounced for local children compared to adults, with Cd being the primary contributor to both pollution and health risks. This investigation provides a crucial basis for the heavy metal pollution management and related risk prevention in areas affected by electronic waste irrigation.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"39 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141107725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on a Variable Universe Control Method and the Performance of Large Sprayer Active Suspension Based on an Artificial Fish Swarm Algorithm–Back Propagation Fuzzy Neural Network","authors":"Fan Yang, Lei Liu, Yanan Zhang, Yuefeng Du, Enrong Mao, Zhongxiang Zhu, Zhen Li","doi":"10.3390/agriculture14060811","DOIUrl":"https://doi.org/10.3390/agriculture14060811","url":null,"abstract":"In view of the typical requirements of large high-clearance sprayers, such as those operating in poor road conditions for farmland plant protection and at high operation speeds, reducing the vibration of sprayer suspension systems has become a research hotspot. In this study, the hydro-pneumatic suspension (HPS) of large high-clearance sprayers was taken as the object, and a variable universe T-S fuzzy controller with real vehicle vibration data as input was proposed to control suspension motion in real time. Different from traditional semi-active suspension, based on the characteristics of variable universe extension factors, a training method combining the artificial fish swarm algorithm and the back propagation algorithm was used to establish a fuzzy neural network controller with precise input to optimize the variable universe. Then, the time-domain and frequency-domain response characteristics of HPS were analyzed by simulating the special road conditions typical of farmland. Finally, the field performance of the sprayer equipped with the new controller was tested. The results show that the error rate of the AFSA-BP algorithm in training the FNN could be reduced to 3.9%, and compared with a passive suspension system, the T-S fuzzy controller improved the effects of spring mass acceleration, pitch angle acceleration, and roll angle acceleration by 18.3%, 23.3%, and 27.7%, respectively, verifying the effectiveness and engineering practicality of the active controller in this study.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"45 42","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141103633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on a Low-Cost High-Precision Positioning System for Orchard Mowers","authors":"Ke Fei, Chaodong Mai, Runpeng Jiang, Ye Zeng, Zhe Ma, Jiamin Cai, Jun Li","doi":"10.3390/agriculture14060813","DOIUrl":"https://doi.org/10.3390/agriculture14060813","url":null,"abstract":"To regulate the energy flow in orchard ecosystems and maintain the environment, weeding has become a necessary measure for fruit farmers, and the use of automated mowers can help reduce labor costs and improve the economic efficiency of orchards. However, due to the complexity of the geographic and spatial environment of the orchard, in particular, the loose and undulating road surface, the interference of satellite signals by large trees, etc., which decreases the positioning accuracy and stability of the positioning system of the mower, and the high cost of the sensor also affect the popularization of intelligent mowers for these applications. To address the above problems, this paper constructs a positioning system through a low-cost global navigation satellite system (GNSS), inertial measurement unit (IMU), and odometry, and utilizes the Kalman filter algorithm based on the error state for a combined GNSS/IMU positioning so that the inertial navigation system can maintain a more accurate positioning when the GNSS signals are poor. Considering the side-slip and error accumulation problems of the odometry of the traction mower, the combined GNSS/IMU positioning information is used to optimize the odometry model and improve the navigation and positioning accuracy. To reduce the measurement error of the IMU and the problem of error accumulation, this paper utilizes the nonholonomic constraint (NHC) of a lawn mower to suppress the dispersion of IMU measurement errors and constructs periodic and nonperiodic zero-velocity updating (ZUPT) strategies in combination with the travel paths of lawn mower navigation operations in the region to update the IMU data to improve the positioning accuracy and stability of the positioning system. The experiments show that the average error of the constructed positioning system is controlled within 0.15 m, the maximum error is maintained at approximately 0.3 m, and the positioning system constructed by using low-cost sensors can achieve a positioning accuracy similar to that of the differential global navigation satellite system (DGNSS), which is beneficial for the promotion and application of intelligent mowers in orchards.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"47 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141107321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Damping Optimization Method of Combine Harvester Frame Undergoing Multi-Source Excitation","authors":"Bangzhui Wang, Shuren Chen, Guoqiang Wang, Zhong Tang, Hantao Ding","doi":"10.3390/agriculture14060815","DOIUrl":"https://doi.org/10.3390/agriculture14060815","url":null,"abstract":"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.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"46 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141103470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Broiler Weight Estimation through Gaussian Kernel Density Estimation Modeling","authors":"Yumi Oh, Peng Lyu, Sunwoo Ko, Jeongik Min, Juwhan Song","doi":"10.3390/agriculture14060809","DOIUrl":"https://doi.org/10.3390/agriculture14060809","url":null,"abstract":"The management of individual weights in broiler farming is not only crucial for increasing farm income but also directly linked to the revenue growth of integrated broiler companies, necessitating prompt resolution. This paper proposes a model to estimate daily average broiler weights using time and weight data collected through scales. In the proposed model, a method of self-adjusting weights in the bandwidth calculation formula is employed, and the daily average weight representative value is estimated using KDE. The focus of this study is to contribute to the individual weight management of broilers by intensively researching daily fluctuations in average broiler weight. To address this, weight and time data are collected and preprocessed through scales. The Gaussian kernel density estimation model proposed in this paper aims to estimate the representative value of the daily average weight of a single broiler using statistical estimation methods, allowing for self-adjustment of bandwidth values. When applied to the dataset collected through scales, the proposed Gaussian kernel density estimation model with self-adjustable bandwidth values confirmed that the estimated daily weight did not deviate beyond the error range of ±50 g compared with the actual measured values. The next step of this study is to systematically understand the impact of the broiler environment on weight for sustainable management strategies for broiler demand, derive optimal rearing conditions for each farm by combining location and weight data, and develop a model for predicting daily average weight values. The ultimate goal is to develop an artificial intelligence model suitable for weight management systems by utilizing the estimated daily average weight of a single broiler even in the presence of error data collected from multiple weight measurements, enabling more efficient automatic measurement of broiler weight and supporting both farms and broiler demand.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"58 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}