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Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to provide new technical support for the variable temperature drying process and realize the adaptive control of drying temperature based on the change of moisture content, the study designed a temperature adaptive control system with the function of online detection of material moisture content. A moisture content online detection model with weight detection value, air velocity, the temperature of load sensor elastic substrate, airflow impingement distance as inputs, and the real material weight as outputs was established by using a convolutional neural network. A validation test of the moisture content online detection model was carried out. The results showed that the model meets the accuracy requirements of online moisture content detection in the variable temperature drying process, and the coefficient of determination R² and root mean square error (RMSE) of the five groups of model validation tests were 0.993 4 and 1.20% in that order. In this reasearch, an improved neural network-PID (INN-PID) controller was designed to realize temperature control in the variable temperature drying process. The dynamic performance of PID, neural network-PID (NN-PID), and INN-PID controllers was simulated in MATLAB software with unit step signal as input. The three controllers were tested for drying temperature control at 50-55 ℃. The results showed that the control stability and regulation time of the INN-PID controller were significantly better than the other two controllers in the simulation test, the drying temperature control results had approximately the same law with the simulation results, and the peak time of the INN-PID controller was 208.00 s, the regulation time was 120.59 s, and the maximum overshooting was 4.87%, which meets the requirements of temperature control in the variable-temperature drying process. In this paper, a temperature adaptive control system was built in the air-impingement dryer, and the temperature adaptive control test based on the moisture content change was carried out. The results showed that the system could quickly and effectively regulate the drying temperature in the variable temperature drying process based on the change in moisture content. This research is of great significance for improving the automation level of drying equipment, developing new variable-temperature drying processes, and providing reference for multi-information fusion detection and control strategy research in other fields. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The adoption of blockchain technology can guarantee the safe and reliable storage of IoT data. In the agricultural products traceability system based on blockchain + Internet of Things, the storage method used in most existing schemes is to save the original data in the off-chain database system, but the real data cannot be agreed on the blockchain. However, if all the data in the production Internet of things are stored directly on the blockchain, it will cause great storage pressure. In order to balance the reliability and storage pressure of the IoT data stored on blockchain in the agricultural industry chain, a high-value density blockchain compression storage scheme for agricultural IoT data is proposed. This paper connects all production links of the agricultural product chain based on consortium blockchain and collects field data based on the Internet of Things composed of sensors. Firstly, a blockchain storage framework for agricultural Internet of Things data is proposed. The collected Internet of Things data is summarized through gateways or edge server devices before being stored in the blockchain. The value density of on-chain data is increased by compression method. An adaptive lossy compression method with outliers is designed for the data compression process. The agricultural IoT data is divided into normal values and outliers based on the outlier separation method. According to the time correlation between sensor data and the sparse of abnormal data, an adaptive compression algorithm for normal data and outlier data compression algorithm is designed to compress normal data and outlier data respectively. Compressed data are stored in the blockchain instead of original data, reducing storage space occupation; The application service platform can obtain the data on the blockchain and reconstruct the data that meets the accuracy need. The results of experiments show that when the proposed scheme is used for data compression, k values can be adaptively selected for different data sets, and good compression effects can be obtained, on-chain storage space can be reduced, and the value density of data can be improved, satisfying the reconstruction accuracy of users. This method has a good compression effect for data with low change frequency, such as temperature and humidity data, but fails to achieve a high compression effect for data with high change frequency such as wind speed data. In the scheme, storing data on the blockchain can solve the problem of traceability data caused by off-chain storage. In view of the storage redundancy caused by storing all the data on the blockchain, lossy compression method is adopted to reduce the data volume and improve the value density of on-chain data within the acceptable error range of the Internet of Things data provider. Experiments show that suppose the compression ratio of normal data is 10:1, this method saves about 85% of on-chain storage space and increases the corresponding data value density by about 85%. The scheme only stores data with a compression factor through the blockchain network, reducing the storage and management overhead of on-chain data. At the same time, the scheme has the characteristics of availability, data traceability and non-repudiation. Apart from being a mere technical solution, this research endeavor emerges as a robust response to the imperatives of secure and reliable IoT data storage within the agricultural product traceability landscape. Looking ahead to the agricultural product traceability scenario based on blockchain, this innovative solution calls for the possibility of harmonious integration with technologies such as sidechain and data offloading. This integration will further mitigate blockchain storage redundancy while ensuring data consensus on the blockchain. The ultimate goal is to ensure the transparency and traceability of the entire agricultural product data traceability process. With the development of the industry and the continuous progress of the technology field, it provides technical support for the realization of distributed agricultural Internet of Things data compression storage. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purple soil is widely distributed in southwestern China and is one of the important natural resources. Because of the loose parent rock and low degree of differentiation, purple soil is characterized by a loose structure that is easily eroded and high soil fertility. Soil erosion is very serious in the purple soil region, which is one of the main sources of sediment in the upper reaches of the Yangtze River, and has a certain impact on the agricultural production and engineering development in the purple soil region. After erosion, purple soil shows the characteristics of reduced dry density of soil and serious loss of fine particles, which affects its water-holding characteristics. In order to explore the changes of soil water-holding properties of purple soil after rainfall erosion, this study was carried out to analyze the effect of missing grain groups on the water-holding properties of sandy clayey purple soil under rainfall conditions by selecting three test methods, namely, axial translation technique, filter paper method, and saturated salt saturated saline solution vapor equilibrium technique for the three grain groups which are the most susceptible to changes in the rainfall conditions, and carrying out the Soil-Water Characteristic Curve (SWCC) test with the absence of grain groups within the full suction range to analyze the effect of the missing grain groups on the water-holding properties of sandy clayey purple soil. The results show that: 1) the missing grain group reduces the water-holding characteristics of sandy clayey purple soil, which is most obvious in the boundary effect zone and transition zone, and has less effect on the residual zone. The mass of the missing grain group is inversely proportional to the air intake value and the residual water content. 2) Using the grain size parameters (Constrained diameter、Average diameter、Median diameter、Effective diameter) to characterize the soil grading condition, the relationship between the soil grading curves and the characteristic values of SWCC was established. It was found that except for effective diameter, the other parameters were linearly inversely related to the air intake value and residual water content; 3) The data obtained from different methods were fitted using the Fredlund-Xing model, and it was found that the results of the data obtained from a single test method fitted better, but the SWCC significantly deviated from the test data points in the boundary effect zone and the transition zone. Root mean square error (RMSE)、 percent bias (PB) and mean absolute percent relative error (MAPRE) were introduced as evaluation indexes, and it was found that the suction range was the main factor affecting the fitting effect of SWCC, and within a certain suction range, the larger the range of data points involved, the better the model fitting effect was, and after a certain suction value was reached, the suction range had very little effect on the model fitting effect. It is proposed that to obtain the accurate SWCC of purple soil quickly, only the maximum suction value needs to be determined, and the number of test points with high suction is reduced, which can effectively shorten the SWCC test period. The results lay a foundation for the subsequent study of the role of soil erosion and water-holding characteristics of purple soil, and also provide reliable ideas for the prevention of soil erosion and the application of soil-water characteristic curves in the Three Gorges Reservoir area. [ABSTRACT FROM AUTHOR]

In order to keep up the research dynamics in the field of nitrogen monitoring in wheat, this paper explores the current status and content evolution through visual analysis. Using bibliometric methods, we mined the trend of publications, subject areas, countries, institutions, journals and highly cited papers, research hotspots, and theme evolution between 1990 and 2022, and analyzed the intersection of disciplines and the concentration of literature. The research found that the global publication volume is generally on the rise, and China is the fastest growing country in recent years, but it can be further improved in terms of the number of local citations and the total number of citations. The field of wheat nitrogen monitoring has changed from one single discipline to multidisciplinary, the hotspots have evolved from the analysis of a single physiological process to the monitoring of remote sensing, crop modeling, growth simulation, and other directions. The research hotspots have evolved from the early stage of single physiological process analysis to the direction of digital agriculture, forming two major research nodes in the world represented by China and the United States. Six of the top ten authors are from China, and China occupies six seats in the top ten organizations, and China ranks in the top in all four indicators of highly cited papers. As time goes on, the tendency of teamwork and international cooperation has become evident, and the proportion of collaborative publications between China and the top ten countries is 31.48%. Agronomy journals are the main publications, with Field Crops Research being the most representative. The results show that the cross-disciplinary trend has become more and more obvious, the development trend of research hotspots and fields has become clearer and clearer, and in the future, the in-depth cooperation among different countries, disciplines, and teams will bring greater and more far-reaching opportunities. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aimed to establish, calibrate and verify a discrete element method (DEM) particle model of rototilled soil particles for investigating the particle migration and machine soil interaction mechanism when forming micro-ridge seed beds by the rapeseed direct seeding machine. The soil type was rototilled yellow-brown soil, which is widely distributed in the mid)lower Yangtze River. The study consisted of two parts: parameter calibration and application verification. The parameter calibration followed these steps: (1) testing the soil plastic limit and selecting the contact model accordingly; (2) measuring the basic parameters, such as the soil particle size distribution and repose angle after rototilling; (3) using the EDEM particle filling and particle factory function to reproduce the particle bed based on the particle size distribution; (4) solving the optimal contact parameter combination by using factorial design, steepest ascent method, and quadratic orthogonal rotation regression method. The application verification test used two sets of structural parameters of a rotary-cutting micro-ridge seedbed preparation device (RMSD, which is the key device of rapeseed direct seeding machine to forming micro-ridge seed beds) to conduct DEM simulation and field tests, and compared the particles migration patterns and the landform after operation. A soil plastic limit tester was used to determine the plastic limit of the soil. The plastic limit of the sampled soil was 24.79%, which is close to the upper limit of the moisture content for rototiller operation. Hence, the Hertze-Mindlin (no slip) contact model was selected. The particle size range and mass ratio of the rototilled soil particles from the rapeseed direct seeding machine were sieved and counted. The rototilled soil particles of each particle size range were scanned and modelled using the EinScan-Pro 3D scanner. Based on the 3D models of the soil particles, the EDEM particle filling function was used to reconstruct the particles with different particle sizes and mass ratios. The soil particles bed was re-generated in EDEM according to the particles` mass ratio. The contact parameter calibration test includes a two-level factorization test, steepest ascent test, and quadratic orthogonal regression test, respectively, to perform a preliminary analysis of test factors and eliminate non-significant tone system, narrow down the range of factors, and solve the combination of contact parameters. The contact parameter calibration test uses the repose angle as an indicator. The two-level factorization test showed that the impact restitution coefficient had no significant effect on the repose angle; the rolling friction coefficient, static friction coefficient, and the interaction term of the two significantly affected the repose angle. The steepest ascent test was designed based on the model regression equation from a two-level factorization test. The steepest ascent test reduced the range of factors tested 0.20-0.60 (static friction coefficient) and 0.05-0.40 (rolling friction coefficient) to 0.32-0.51 and 0.11-0.27, a reduction of greater than 50%, providing effective support for obtaining accurate regression models. Since the restitution coefficient had an insignificant effect on the repose angle, the impact recovery coefficient was set to an intermediate level of 0.350 for the quadratic orthogonal regression test. The calibrations resulted in restitution, static friction and rolling friction coefficients of 0.350, 0.351 and 0.257, respectively. The verification consists of simulations and field tests conducted on the RMSD with two structural parameters. The field verification test used the PIVlab tool and the Trimble TX8 3D laser scanner to obtain the soil particles` velocity and the land-form. The simulation of 2 structural parameters was consistent with field experiments. The error of micro-ridge distance is 8.25%, which increases with the number of vanes of RMSD. The calibration parameters are accurate. This paper provides fundamentals for the DEM simulation and structural improvement for rapeseed micro-ridge seedbed preparation device. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The water hammer simulation for pump station water supply systems with free-surface flow commonly employs the method of characteristics (MOC), often neglecting the influence of unsteady friction and the interaction between pressure and free-surface flow. In complex pipeline network systems, MOC often requires interpolation calculations or adjustments to wave speeds for computation. However, this can lead to issues such as numerical instability and reduced accuracy. This study establishes a second-order finite volume method model that considers unsteady friction for real-time joint calculations of pressure and free-surface flow. The second-order Godunov scheme is utilized to discretize the flow control equations independently for the pressure and free-surface flow. Riemann solvers are employed to compute the discretized fluxes. Simultaneously, the unsteady friction effect is taken into account to accurately simulate energy dissipation during hydraulic transient processes. The model is validated using experimental data. And a variable time-step approach is adopted at the interface between the pressure and free-surface flow. Furthermore, sensitivity analyses are conducted on the dimensions and locations of the throttled surge chamber in practical engineering scenarios. The results indicate that when unsteady friction effects are not considered, the model only matches experimental values at the first peak. However, when unsteady friction effects are taken into account, the model's simulation results are in good agreement with experimental results in terms of pressure peak, decay, and periodicity, and the maximum value of the water hammer pressure error at the valve is only 4.58%. Compared to the characteristics method, the second-order Godunov scheme exhibits higher stability and produces simulation results that are essentially the same when the Courant number is less than 1 as when the Courant number is set to 1.0. The real)time joint calculation method established in this paper can adequately consider the impact of water level fluctuations of the pressure flow outlet pool and the backflow of the free-surface flow. The water hammer pressure and the water levels of the throttled surge chamber obtained from the joint calculation of pressure and free-surface flow exhibit a faster decay compared to the results obtained from pure pressure flow calculations. For power outage conditions of pumps, the engineering scenarios studied in this paper would result in significant water hammer pressures and negative pressures if surge chambers were not installed. Optimization studies on the throttled surge chamber show that as the diameter of the connection tube increases, the maximum pressure head, the highest surge level of the throttled surge chamber, and the maximum reverse rotation speed of the pump increase, and the lowest surge level of the throttled surge chamber decreases. As the diameter of the throttled surge chamber increases, the highest surge level decreases, the lowest surge level increases and the maximum pressure decreases all the time when the connection tube diameter is relatively small, and will decrease first and then increase when the connection tube diameter is relatively large; when the connection tube diameter 3.5 m, throttled surge chamber diameter 15 m can meet the requirements of the system control parameters and also reduce the amount of engineering work. The closer the throttled surge chamber is to the pump station, the larger the maximum pressure, reverse rotation speed, and highest surge level, and the smaller the lowest surge level. When the throttled surge chamber is arranged 1.0 km behind the pump, the maximum surge level will reach 172.35 m, which does not meet the requirements of the control standards. In summary, the established model exhibits high accuracy, stability, and applicability, providing valuable insights for water hammer simulations in pump station water supply systems with free-surface flow. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Hyperspectral technology has been widely used in many fields due to its excellent performance characteristics such as high sensitivity, fine resolution, multi-channel data acquisition and processing capabilities, and non-destructive testing. However, despite its outstanding performance in data acquisition and information extraction, it also faces the challenges of high requirements and costs of hardware equipment. Hardware equipment such as high-precision optics, high-quality detectors, and complex data acquisition devices required for hyperspectral imaging have become one of the key factors limiting its popularity and application. To overcome this dilemma, researchers have begun to explore the reconstruction of RGB images into hyperspectral images by extracting information from traditional RGB images through spectral reconstruction techniques at relatively low cost. This innovative approach significantly reduces the complexity and cost of spectral data acquisition and provides a brand new way for wider application of hyperspectral technology. In the study of this paper, we use surimi adulteration detection as an example to explore the performance of different spectral reconstruction algorithms in depth. By mixing the dorsal muscle of silver carp with commercially available starch in different ratios and simulating the real state of surimi when it is sold, we successfully acquired RGB images and corresponding spectral data of a series of samples. In order to ensure the scientific validity and reliability of the experiment, we adopted the spectral-physical-chemical value covariance distance method (SPXY) for the sample set and divided the data set into calibration and validation sets according to the ratio of 5:3. In the process of spectral reconstruction, we explored two mainstream methods, the multivariate polynomial least squares regression algorithm (PMLR) and the deep learning hierarchical regression network (HRNet). Comparative experimental results show that the HRNet-based reconstruction technique has relative and root-mean-square errors of 0.010 4 between the spectra and the actual spectra, respectively, while the PMLR-based algorithm corresponds to relative and root-mean-square errors of 0.012 6. These results indicate that both methods are within acceptable error ranges, which provides a subsequent experimental results provide a solid foundation. In order to verify the reliability of the reconstructed spectra in practical applications, we established models of extreme learning machine regression (ELMR), support vector machine regression (SVR), and partial least squares regression (PLSR) based on the reconstructed spectra, and combined S-G convolutional smoothing (SG), mean centering (MC), standard normal variable transformation (SNV), derivative smoothing (DE), and normalization (NOR) methods were used to preprocess the spectra with a view to improving the model performance. By using corrected correlation coefficient (RC) corrected root mean square error (RMSEC) predicted correlation coefficient (RP) and root mean square error of prediction (RMSEP ) as evaluation metrics, we successfully detected the adulteration ratio of adulterated surimi. The experimental results show that the support vector machine regression model with standard normal transform (SNV) preprocessing achieves the best results with a prediction correlation coefficient (RP) of 0.983 0 and a root mean square error of prediction (RMSEP ) of 3.954 4% in the model based on the reconstruction of spectra by the PMLR algorithm. In the model based on the reconstructed spectrum of deep learning HRNet network, the support vector machine regression model, also using SNV preprocessing, achieved the best performance, with a prediction correlation coefficient of 0.998 7 and a prediction root-mean-square error of 4.080 8%. Therefore, the PMLR algorithm and HRNet network reconstruction technique based on RGB images not only realized efficient spectral reconstruction, but also provided a reliable solution for surimi adulteration detection. This research result provides new ideas and methods for quality and safety detection of food and agricultural products using low-cost hardware devices. [ABSTRACT FROM AUTHOR]

The shovel type seedbed preparation machine is suitable for the preparation of rapeseed seedbeds in the rice-oil rotation area in the mid-lower Yangtze River. It can complete the functions of soil plowing, soil leveling, straw burying, and furrow opening in one operation. However, the unit had large vibration and noise during idling and field operations, which can easily cause wear and tear of key components, reduce work reliability and trouble-free working time, and affect the health and comfort of the driver. In order to solve the problem of large vibration during unit operation, this paper analyzed the theoretical excitation frequency of the main vibration source during the operation of the tractor coupling unit through theoretical calculation, and the vibration acceleration of the unit under idle speed and field operation conditions was tested by using Coco80 dynamic signal Test and analysis system. By using time-domain analysis and frequency-domain analysis, the vibration acceleration at different measuring points under two working conditions was determined, and the main excitation source of the unit was the movement of the shovel type tillage and soil preparation device. Based on the results of the vibration test, a scheme to reduce the vibration of the shovel type seed bed preparation machine was proposed by optimizing the arrangement of the crank phase angle to reduce the combined inertial force and inertia moment of the machine. According to the mass substitution method and kinematics analysis, the inertial force variation trend of a single group of shovel tillage and land preparation devices was obtained. Base on the calculation results, it was further clarified that the inertial force on the whole machine can be reduced by rationally designing the crank phase angle arrangement of the ten groups of mechanisms of the unit. Based on the calculated inertia force on a single group of mechanisms and combined with the crank phase angle of the existing machine tools arrangement, the inertial force and inertial moment force models of ten sets of crank-rocker mechanisms of the whole machine were established, and the arrangement of the crank phase angle that minimizes the total inertial force and inertial moment of the whole machine was obtained by using MATLAB software. Under this crank phase angle arrangement, the total inertial force of the whole machine was basically balanced, and the average absolute value of the total inertia moment in the x and y axes were reduced by 37.40% and 30.09% respectively. In order to verify the vibration reduction effect of changing the crank arrangement on the unit, the acceleration time domain signal was collected from the improved unit at the place where the vibration was relatively large. Compared with the unit before improvement, the total vibration of the measuring points after the improvement was respectively reduced by 36.42% and 31.97% under the conditions of idle speed and field operation. This research can provide reference for the inertia force balance design of planar linkage mechanisms and the research on vibration reduction of agricultural machinery based on planar linkage mechanism groups. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rice shrimp co-cultivation, as a circular agriculture model that integrates ecological, economic, and social benefits, has been widely applied in China. Accurately obtaining information on the planting area, spatial distribution, and changes of rice shrimp co-cultivation is of great significance for ensuring safe production, social supply of rice and shrimp, and formulating corresponding management and planning policies by government departments. Most of the existing methods for extracting rice shrimp farming fields used medium-resolution temporal images as data sources to analyze the characteristics of water or vegetation changes within a year to construct models. The accuracy of the extraction depended on the results of water or vegetation analysis, the boundaries were unclear and there was a lot of noise. To solve the problems of complex temporal analysis, low accuracy of extraction results, and incomplete boundaries in existing extraction methods, this paper used high-resolution images of a single temporal phase as the data source, without analyzing the temporal features of rice shrimp farming fields. Only the spatial features of rice shrimp farming fields on high-resolution images were used for high-precision extraction. We proposed a deep learning semantic segmentation model named EASNet (edge assisted segmentation network), which was mainly composed of three modules: feature extraction module (FE Module), edge assist module (EA Module), and information fusion Module (IF Module). The FE Module was used to extract multi-level and fused contextual semantic information features of the target object. The EA module used the unique edge "shrimp groove" of rice and shrimp farming fields as an auxiliary information for separate segmentation in the designed EA Module. The IF Module integrated the outputs of the FE Module and the EA Module, enabling the main task to not only enhanced the boundary structure information of rice shrimp farming fields but also learned the unique spatial and semantic information of rice shrimp farming fields. The experimental results showed that with the enhancement of the EA Module, the segmentation results of rice shrimp farming fields were more complete and the boundaries were clearer. The IoU (Intersection over Union) of semantic accuracy and the F1-Score of boundary accuracy were improved by 1.5% and 5.8%, respectively. The recall, IoU, and F1-Score of overall semantic accuracy reached 0.970, 0.964, and 0.930, respectively. The Recall and F1-Score of boundary accuracy reached 0.864 and 0.859, while the Recall and F1-Score of relaxed boundary accuracy reached 0.876 and 0.913. The trained EASNet model was applied to the whole area of Xuyi County, and the spatial distribution map of rice shrimp farming fields in Xuyi County in 2020 was obtained. In comparison with the results of rice shrimp breeding fields extracted by the traditional Water Seasonal Difference method and the Random Forest method, our method obtained the optimal results with an OA(overall accuracy) of 96.71% and a Kappa coefficient of 0.934. The method used in this paper has higher accuracy, lower missing rate, more regular boundaries, and fewer instances of similar integration in extracting results. It can provide a basis for natural resource surveys, and government departments to formulate corresponding rice shrimp breeding management and planning policies. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

It is widely recognized that the value of rice in the market is highly depends on its variety, with some varieties commanding significantly higher prices than others. Unfortunately, this has led to a situation where unscrupulous vendors may attempt to pass off inferior or lower-value rice varieties as more valuable ones. This urgently requires a reliable and efficient methods for accurately detecting and identifying different rice varieties. The use of near-infrared spectroscopy and deep learning for rice variety detection is an important research direction in this field. The establishment of an accurate detection model depends on a large-scale sample data, however, the process of collecting and preprocessing samples is very timeconsuming, which limits the improvement of accuracy. To address the aforementioned needs and limitations, this paper proposes a rice variety detection method based on near-infrared spectroscopy combined with an improved deep convolutional generative adversarial network (DCGAN) for data augmentation. Based on the classical deep convolution generative adversarial neural network, the network increases the number of convolution layers and adjusts the network structure. Subsequent experiments showed that the network has better generation ability. In this study, we selected four rice varieties, namely Wuchang, Xiangshui, Yinshui, and Yueguang, and collected 80 samples for each variety, amounting to a total of 320 rice powder samples as experimental samples. Firstly, we collected near-infrared spectra of the samples and preprocessed the raw spectral data by applying detrend correction (DC) and uninformative variable elimination (UVE) algorithms to eliminate irrelevant spectral features. Then, we established an improved DCGAN model to augment the preprocessed spectral data. Three traditional data enhancement methods, random left and right translation, superimposed Gaussian noise and translation noise, were used for comparison. Comparative experiments demonstrated that the spectral data generated by the improved DCGAN showed significant superiority in terms of structural similarity compared to traditional data augmentation methods. Finally, we investigated different data augmentation methods combined with different classification methods to establish a rice variety classification model. We employed five classifiers, namely partial least squares discriminant analysis (PLS-DA), k-nearest neighbors (KNN), random forest (RF), decision tree (DT), and one-dimensional convolutional neural network (1D-CNN), and combined them with four data augmentation methods to build the rice variety classification model. The results showed that the model built using DCGAN-augmented data achieved the highest accuracy on the test set, the accuracy rate was 98.21%. Through quantitative analysis of the models built using DCGAN combined with the five classifiers, it was found that the variety detection model established by DCGAN-1D-CNN method performed the best on the test set, with a coefficient of determination R 2 of 0.992 2, mean absolute error (MAE) of 0.008 9, and root mean square error (RMSE) of 0.050 5, indicating its optimal performance. Based on the comprehensive experimental results, the model established by combining the improved DCGAN data augmentation with the 1D-CNN classification algorithm exhibited the best performance in terms of accuracy on the test set, providing a new approach for convenient and accurate rice variety detection applications. By utilizing near-infrared spectroscopy and deep learning methods, combined with the improved DCGAN for data augmentation, we can enhance the accuracy and reliability of rice variety detection, thus meeting the market demand and consumer expectations. [ABSTRACT FROM AUTHOR]

Recirculating aquaculture is an important aquaculture model with the advantages of high density, low environmental pollution and high economic benefit. However, recirculating aquaculture needs to add a large amount of feed to the system. Due to the problems of solid feed particles and fish feces deposition in the process of water circulation, the accumulation time is too long, which can easily lead to the decomposition of such sediments, and produce harmful substances to pollute the water body, while further consuming dissolved oxygen in the water body, and ultimately lead to the sub-health and death of fish. Therefore, how to quickly and efficiently discharge the residual bait and feces in the aquaculture tank and reduce its impact on water quality is the primary problem facing the recirculating aquaculture model, which needs to be solved urgently. In this paper, physical experiments were conducted to study the effects of fish culture density on the hydrodynamic characteristics of circular recirculating aquaculture tank and the accumulation of dirt movement, and to reveal the response relationship between culture density and self-cleaning capacity of aquaculture tank driven by different flow rates. Based on different breeding density (ρ=0, 2.65, 4.41, 6.2 kg/m³ ) and influent flow rate (Q=5.2, 6.54, 9.81 L/min), 12 groups of test conditions were designed for the single tube wall inlet mode of circular aquaculture tank. The Acoustic Doppler Velocimeter (ADV) was used to measure the flow velocity of the water body in the aquaculture tank, and the de-extremization operation was carried out to remove 5% of the maximum and minimum values, and then the average treatment was carried out, which approximately represented the flow velocity of the ADV measuring point. The weighted average flow rate, water resistance coefficient, turbulence intensity and other parameters of the whole breeding pond were calculated by the formula. The self-cleaning capacity of the aquaculture tank was analyzed by using these flow field parameters and combining the data of collecting time under different working conditions obtained from the pollution collection test. The results show that the low water flow rate in the circulation process is easy to lead to the deposition of part of the sewage and aggregation, and it is difficult to discharge the sewage. Increasing the density of fish culture could reduce the average flow velocity (vavg) of the overall flow field in the pond, the attenuation amplitude was within 0.05 m/s (less than 25%), and the resistance coefficient Ct in the water was increased. Turbulence caused by fish swimming can cause the sewage in the pool to re-suspension, which helps the dirt to be discharged; The sewage collection time was affected by the breeding density and flow rate at the same time, and the sewage collection time was within 5 min under the influent flow rate of 9.8 L/min. When the influent flow rate was 6.54 L/min, the breeding density increased from 0 to 6.2 kg/m³, the turbulence intensity increased by 2.4 times, and the sewage collection time was reduced by more than 40 min. The research results can provide reference for the design and daily management of circular aquaculture ponds. [ABSTRACT FROM AUTHOR]

The number of trees is essential information for modern forestry management, which affects managers' formulation of development strategies. At present, tree inventory mainly relies on manual counting, which is costly, time-consuming and labor-intensive. Using unmanned aerial vehicle (UAV) to count targets has become increasingly popular in agriculture and forestry due to its low cost, ease of operation, and flexibility of use. This study focused on using UAV images to count spruce numbers. A total of 603 images with an average canopy density of 81% and an average plant density of 6 667 plants/hm² were selected for the dataset, each containing an average of 354 spruce trees. Among these, 205 images had interference factors such as weeds. The images were divided into a training set and a test set at a ratio of 7:3. The training set was expanded by randomly flipping the images to improve the robustness to different flight attitudes of UAV. After data augmentation, 844 training images and 181 test images were obtained. Aiming at the problem of dense spruces in natural environments including severe adhesion and background interference such as weeds with similar characteristics to spruces, we selected IntegrateNet, a model known for its strong performance in dense target counting tasks as baseline model for spruces. This study then worked to improve the IntegrateNet model to achieve a more accurate counting of dense spruce that is closer to real-world conditions. First of all, this paper used the self-calibrated convolutions (SCConv) to replace the ordinary convolutional layers at 1/8, 1/16 feature maps and density maps in the baseline model to expand the convolution receptive field. Secondly, in order to deal with background interference problems such as weeds and the serious adhesion of the target, this paper added the criss-cross attention mechanism (CCA) to the feature fusion of the IntegrateNet model. It can consider the horizontal and vertical context information of each pixel to generate richer semantic features to improve the contextual information extraction ability of the model. The mean counting accuracy(MCA), mean absolute error(MAE), root mean square error(RMSE), and the coefficient of determination R² are used as evaluation indicators. The ablation experiments and comparative experiments are designed to verify the performance of the proposed model. The ablation experiments show that the improved methods proposed in this paper can effectively improve the counting accuracy of the model. The comparative experiments show that the improved IntegrateNet model proposed in this study has MCA, MAE and RMSE reached 98.32%, 8.99 plants and 13.79 plants respectively, and the R² was 0.99.Compared with TasselNetv3_lite, TasselNetv3_seg, and IntegrateNet models, the MCA of the improved IntegrateNet model increased by 16.44, 10.55, and 9.26 percentage points, the MAE of the improved IntegrateNet model decreased by 25.62, 10.45, and 6.99 plants, and the RMSE of the improved IntegrateNet model decreased by 48.25, 13.84, and 12.52 plants. In summary, the improved IntegrateNet model proposed in this study demonstrated a significant increase in accuracy for counting dense spruce in natural environments. Moreover, our research is not limited to spruce, as the methodology can be applied to other tree species as well. It can providing technical support for subsequent forestry intelligent statistics. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Vigorously promoting photovoltaic power generation meets the requirements of energy structure transition, which contributes to environmental protection. Abundant land resources in rural areas provide inherently convenient conditions for photovoltaic power generation. Rural photovoltaic projects provide a sustainable, clean, and low-carbon power supply for production and life, which increases positive ecological values, such as reducing carbon emissions by helping farmers wean off traditional fossil fuels, creating employment opportunities, etc. However, there are also some negative ecological values, such as the construction of photovoltaic power stations causing soil-water losses and construction occupations, which not only reduce the planting incomes of farmers, but also damage rural ecosystems. Therefore, ecological compensation for participators in the photovoltaic project, i.e., photovoltaic power station construction enterprises, farmers, and village collectives, is required to balance the participants' benefits and losses. However traditional compensation methods cannot decide the accurate compensation standards for participators. Hence, referring to the ecosystem service values in the Millennium Ecosystem Assessment, an ecosystem service assessment index system (ESAIS) that includes economic, social, and environmental aspects is proposed in this paper. Based on the proposed ESAIS, the calculation modes for economic values (e.g., electric energy, construction incomes, etc.), social security values, and environment values (e.g., energy conservation and emission reduction, soil-water losses, etc.) are proposed based on market valuation methods, shadow project approaches, opportunity cost methods, etc., can be employed to quantitatively analyze the ecological values of participators. On this basis, the relationship between benefits and expenditures among the participators is established. Then an optimal decision-making model for ecological compensation is introduced to minimize the proportion of low-income farmers with the constraints of the balance of payments, which contributes to achieving win-win cooperation among the participators and sustainable energy development. Based on actual data from rural photovoltaic projects in China, case studies are carried out to verify the proposed ecological compensation model. Under the premise of ensuring reasonable profitability for all participators, the proposed model maximizes the contributions of beneficiaries in the ecological compensation schemes, which contributes to preventing farmers from returning to low income. Compared to traditional compensation methods that compensate farmers based on production inputs, direct losses, or waste disposal fees, the proposed method not only guarantees all participators have positive ecological values and environmental values after compensation, but also increases all farmers’ income levels by maximizing their incomes. Hence, the proposed model contributes to the realization of rural revitalization strategy and sustainable development, which has directive significance for economic advancement in underdeveloped regions worldwide. [ABSTRACT FROM AUTHOR]

In the process of wheat storage, rice weevil is a kind of extremely harmful moth-eaten pest, which belongs to the hidden pest that eats inside the grain, and in the growth and development process of rice weevil ( egg stage, larva stage, pupa stage, adult stage), there are different degrees of damage to wheat until the adult stage is drilled out. In severe cases, wheat grains can be eaten into empty shells, and the excrement is left inside the grains, which seriously damages the protein quality of wheat and affects the quality of flour. In order to explore the effects of rice weevil infection on wheat protein quality at different stages. In this paper, the crude protein, uric acid, protein components, wet gluten, gluten water absorption, lactic acid solvent retention capacity (SRC), sucrose SRC, sulfhydryl (-SH), disulfide bond (-S-S-), protein secondary structure, gluten protein microstructure of the wheat infected by rice weevil and the color and texture characteristics of the corresponding whole wheat noodles were measured and analyzed. The results showed that the growth and development of rice weevil in wheat and the damage of wheat would cause a series of changes in wheat protein, which was manifested in the deterioration of physical and chemical properties and morphological structure. With the growth and development of rice weevil inside the wheat kernels, the content of crude protein in wheat grains increased significantly, the content of wet gluten, gluten water absorption, lactic acid solvent retention SRC, sucrose SRC, -SH and-SS-decreased, The proportion of wheat protein components and secondary structures, which are very important for wheat, also changed significantly ( P<0.05 ), and the edible quality and nutritional value of wheat also decreased. The microstructure of gluten protein showed that with the growth and development of rice weevil in wheat grains, the surface roughness of gluten increased, and the fracture surface and burr increased. After reaching the adult stage, some gluten structures had been seriously broken and could not be identified. After making whole wheat noodles, the color of noodles deepened, L* value and cooking loss rate increased, a* value, b* value, hardness, adhesion, elasticity, cohesiveness, chewiness and resilience decreased. The experimental results further elucidated the deterioration mechanism of wheat damaged by rice weevil, and provided a theoretical basis for the quality improvement of wheat during storage and the insect infected wheat. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Food is the top priority for the people, and food safety has always been a key concern for the people's livelihood. Building a Knowledge graph for food safety and food events has attracted many scholars' attention in recent years. One of the key technologies to build a large structured knowledge graph is to extract triples from unstructured text. A triplet typically consists of a pair of entities and semantic relations between them. When extracting entities and relationships from Chinese food inspection announcements, many long sentences often appear in the text, which contain a large number of food names and food types. If we learn about their features by using the current deep learning models, the strong dependencies between words will be weakened by the long distance between words, this issue has received little attention in the extraction of entity and relationships in the food safety field. So to solve the problem of dependency relations between words in those sentences, this paper proposes a joint entity relation extraction model (TAG-JE) based on improved Chinese dependency syntax tree and multi feature fusion. TAG-JE improves the expression of Chinese dependency syntax tree that is adding a "CLS" tag before the natural sentence and establish dependency relations between the "CLS" tag and each word in the sentence. Then we use it to describe the syntactic structure of text, and converts the syntax tree into a character adjacency graph so as to match the syntax tree with the word processing mode of Chinese BERT encoding. Then we learn syntactic structure features from the encoded word adjacency graph through a graph neural network(GCN), and fuse them with the context features extracted by BERT. Context features and structural features can describe the linear and spatial representation of sentences. The weight of the fusion is automatically adjusted by a gate network. After the above steps, the fusion features of unstructured text will be obtained which can fully reflect the representation of the food inspection announcement. In the process of entity and relationship extraction, the joint extraction mode is adopted, because compared to separate extraction of entities and relationships, joint extraction reduces error accumulation and TAG-JE also adds a relation selector in relation analysis, relation selector is used to optimize the embedding features of relations, and the relation selector would be trained by reinforcement learning to improve the accuracy of relation extraction. To verify the effectiveness of TAG-JE, this paper compared its extraction performance with mainstream deep learning models such as BiLSTM+CRF, combined with IDCNN, BERT, and Attention to obtain three BiLSTM+CRF framework models. In addition to the classic models mentioned above, this paper also compares the TAG-JE model with mainstream models GraphRel and CasRel. The results showed that the accuracy, recall, and F1 values of TAG-JE reached 90.86%, 90.50%, and 90.68%, respectively, which showed a significant improvement compared to other models and demonstrated its knowledge mining ability in Chinese food inspection documents. TAG-JE provides technical support for the construction of food safety knowledge graph. In the experiments targeting Chinese public datasets, TAG-JE also achieved better results compared to GraphRel and CasRel, proving that TAG-JE also has good generalization performance. The research results provide reference for the construction of food safety knowledge graph. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)