Pub Date : 2024-03-27DOI: 10.3390/agriculture14040527
Noémie Gonzalez, M. Fournier, Rose Buitenhuis, Eric Lucas
Syrphine hoverflies (Diptera: Syrphinae) are important predators of aphids in agricultural crops. While the use of flowering plants to enhance their efficacy is well established, recent research has developed an artificial diet for adult hoverflies consisting of a sugar solution and pollen in a dispenser. To ensure that the artificial diet is suitable to support hoverfly reproduction, a comparative analysis was conducted between a natural diet of flowering buckwheat plants versus an artificial diet consisting of artificial flowers (including honey solution and pollen), complemented by a sugar solution disperser. The study evaluated the fecundity, fertility, oviposition period, egg hatchability, and overall lifespan of the American hoverfly, Eupeodes americanus (Wiedemann 1830). The results indicate that the artificial diet does not negatively impact the reproductive parameters of E. americanus when compared to the buckwheat-based diet. Consequently, artificial diets emerge as a promising and more convenient alternative to flowering plants to support hoverflies in biological control strategies and for their mass rearing in research facilities and commercial insectaries.
{"title":"Artificial Adult Diet as a New Tool for Improving a Biocontrol Program with Predatory Hoverflies","authors":"Noémie Gonzalez, M. Fournier, Rose Buitenhuis, Eric Lucas","doi":"10.3390/agriculture14040527","DOIUrl":"https://doi.org/10.3390/agriculture14040527","url":null,"abstract":"Syrphine hoverflies (Diptera: Syrphinae) are important predators of aphids in agricultural crops. While the use of flowering plants to enhance their efficacy is well established, recent research has developed an artificial diet for adult hoverflies consisting of a sugar solution and pollen in a dispenser. To ensure that the artificial diet is suitable to support hoverfly reproduction, a comparative analysis was conducted between a natural diet of flowering buckwheat plants versus an artificial diet consisting of artificial flowers (including honey solution and pollen), complemented by a sugar solution disperser. The study evaluated the fecundity, fertility, oviposition period, egg hatchability, and overall lifespan of the American hoverfly, Eupeodes americanus (Wiedemann 1830). The results indicate that the artificial diet does not negatively impact the reproductive parameters of E. americanus when compared to the buckwheat-based diet. Consequently, artificial diets emerge as a promising and more convenient alternative to flowering plants to support hoverflies in biological control strategies and for their mass rearing in research facilities and commercial insectaries.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"17 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140374539","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}
Pub Date : 2024-03-27DOI: 10.3390/agriculture14040531
Qimin Gao, Lei Cheng, Renbing Wang, Mingjiang Chen, Wei-jun Zhao, Jingjing Fu, Zhenwei Wang
The mechanical properties of tomato stalk, relevant to the harvesting and crushing of tomato vines, significantly impact its harvesting quality and efficiency. Establishing a simulation model, which accurately mirrors these properties, is foundational for designing related mechanical components. The discrete element method models tomato stalk harvesting and is optimized through mechanical tests and simulations. A blend of Plackett–Burman, steepest ascent, and central composite design modeling identified three contact model parameters influencing the maximum stalk shear force. The optimal values of these three parameters were a normal stiffness of 1.04 × 1010 N m−3, tangential stiffness of 7.59 × 109 N m−3, and bond radius of 1.06 mm. The relative error in the simulated versus measured shear force was <1%, affirming the model’s accuracy in characterizing cutting properties. These findings lay the theoretical groundwork for numerical simulations of tomato-stalk-related equipment.
番茄茎秆的机械特性与番茄藤的收获和压碎有关，对其收获质量和效率有重大影响。建立一个能准确反映这些特性的模拟模型是设计相关机械部件的基础。离散元件法对番茄茎秆的收割进行建模，并通过机械测试和模拟进行优化。通过混合使用 Plackett-Burman、陡坡上升和中心复合设计模型，确定了影响最大茎秆剪切力的三个接触模型参数。这三个参数的最佳值分别为：法向刚度 1.04 × 1010 N m-3、切向刚度 7.59 × 109 N m-3、结合半径 1.06 mm。模拟剪切力与测量剪切力的相对误差小于 1%，这证明了该模型在表征切削性能方面的准确性。这些发现为番茄茎相关设备的数值模拟奠定了理论基础。
{"title":"Discrete Element Model Building and Optimization of Tomato Stalks at Harvest","authors":"Qimin Gao, Lei Cheng, Renbing Wang, Mingjiang Chen, Wei-jun Zhao, Jingjing Fu, Zhenwei Wang","doi":"10.3390/agriculture14040531","DOIUrl":"https://doi.org/10.3390/agriculture14040531","url":null,"abstract":"The mechanical properties of tomato stalk, relevant to the harvesting and crushing of tomato vines, significantly impact its harvesting quality and efficiency. Establishing a simulation model, which accurately mirrors these properties, is foundational for designing related mechanical components. The discrete element method models tomato stalk harvesting and is optimized through mechanical tests and simulations. A blend of Plackett–Burman, steepest ascent, and central composite design modeling identified three contact model parameters influencing the maximum stalk shear force. The optimal values of these three parameters were a normal stiffness of 1.04 × 1010 N m−3, tangential stiffness of 7.59 × 109 N m−3, and bond radius of 1.06 mm. The relative error in the simulated versus measured shear force was <1%, affirming the model’s accuracy in characterizing cutting properties. These findings lay the theoretical groundwork for numerical simulations of tomato-stalk-related equipment.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"50 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140376878","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}
Pub Date : 2024-03-27DOI: 10.3390/agriculture14040530
Fang Wang, Xueliang Fu, Weijun Duan, Buyu Wang, Honghui Li
The utilization of ear tags for identifying breeding pigs is a widely used technique in the field of animal production. Ear tag dropout can lead to the loss of pig identity information, resulting in missing data and ambiguity in production management and genetic breeding data. Therefore, the identification of ear tag dropout is crucial for intelligent breeding in pig farms. In the production environment, promptly detecting breeding pigs with missing ear tags is challenging due to clustering overlap, small tag targets, and uneven sample distributions. This study proposes a method for detecting the dropout of breeding pigs’ ear tags in a complex environment by integrating an attention mechanism. Firstly, the approach involves designing a lightweight feature extraction module called IRDSC using depthwise separable convolution and an inverted residual structure; secondly, the SENet channel attention mechanism is integrated for enhancing deep semantic features; and finally, the IRDSC and SENet modules are incorporated into the backbone network of Cascade Mask R-CNN and the loss function is optimized with Focal Loss. The proposed algorithm, Cascade-TagLossDetector, achieves an accuracy of 90.02% in detecting ear tag dropout in breeding pigs, with a detection speed of 25.33 frames per second (fps), representing a 2.95% improvement in accuracy, and a 3.69 fps increase in speed compared to the previous method. The model size is reduced to 443.03 MB, a decrease of 72.90 MB, which enables real-time and accurate dropout detection while minimizing the storage requirements and providing technical support for the intelligent breeding of pigs.
{"title":"The Detection of Ear Tag Dropout in Breeding Pigs Using a Fused Attention Mechanism in a Complex Environment","authors":"Fang Wang, Xueliang Fu, Weijun Duan, Buyu Wang, Honghui Li","doi":"10.3390/agriculture14040530","DOIUrl":"https://doi.org/10.3390/agriculture14040530","url":null,"abstract":"The utilization of ear tags for identifying breeding pigs is a widely used technique in the field of animal production. Ear tag dropout can lead to the loss of pig identity information, resulting in missing data and ambiguity in production management and genetic breeding data. Therefore, the identification of ear tag dropout is crucial for intelligent breeding in pig farms. In the production environment, promptly detecting breeding pigs with missing ear tags is challenging due to clustering overlap, small tag targets, and uneven sample distributions. This study proposes a method for detecting the dropout of breeding pigs’ ear tags in a complex environment by integrating an attention mechanism. Firstly, the approach involves designing a lightweight feature extraction module called IRDSC using depthwise separable convolution and an inverted residual structure; secondly, the SENet channel attention mechanism is integrated for enhancing deep semantic features; and finally, the IRDSC and SENet modules are incorporated into the backbone network of Cascade Mask R-CNN and the loss function is optimized with Focal Loss. The proposed algorithm, Cascade-TagLossDetector, achieves an accuracy of 90.02% in detecting ear tag dropout in breeding pigs, with a detection speed of 25.33 frames per second (fps), representing a 2.95% improvement in accuracy, and a 3.69 fps increase in speed compared to the previous method. The model size is reduced to 443.03 MB, a decrease of 72.90 MB, which enables real-time and accurate dropout detection while minimizing the storage requirements and providing technical support for the intelligent breeding of pigs.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"10 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140374832","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}
To address the issue of reduced yield in the second season caused by damaged stubbles resulting from being compressed during the harvesting process of the first season’s ratoon rice, a device for rectifying the compressed stubbles was designed. Utilizing the DEM-MBD coupling simulation method, a simulation analysis was conducted to determine the range of key parameters and verify the feasibility of the solution. Using rotational speed, forward speed, and stubble entry angle as experimental factors and stubble rectification rate and second-season yield as evaluation metrics, a three-factor, three-level Box–Behnken response surface field trial was conducted. The theoretically optimal working parameter combination was found to be a forward speed of 1.4 m/s, device rotational speed of 75 rpm, and stubble entry angle of 39°. Under these conditions, three parallel experiments were performed, resulting in a rectification rate of 90.35% in the mechanically harvested and compressed area and a second-season yield of 2202.64 ± 35 kg/hm². The deviation from the numerical simulation results of parameter optimization was less than 5%. These findings suggest that the designed stubble rectification device for ratoon rice can meet the requirements of stubble rectification during the first-season harvest of ratoon rice. Furthermore, it provides valuable insights for reducing harvest losses in the first season and further improving the level of mechanized harvesting for ratoon rice.
{"title":"Design and Parametric Optimization Study of an Eccentric Parallelogram-Type Uprighting Device for Ratoon Rice Stubbles","authors":"Shuaifeng Xing, Yang Yu, Guangqiao Cao, Jinpeng Hu, Linjun Zhu, Junyu Liu, Qinhao Wu, Qibin Li, Lizhang Xu","doi":"10.3390/agriculture14040534","DOIUrl":"https://doi.org/10.3390/agriculture14040534","url":null,"abstract":"To address the issue of reduced yield in the second season caused by damaged stubbles resulting from being compressed during the harvesting process of the first season’s ratoon rice, a device for rectifying the compressed stubbles was designed. Utilizing the DEM-MBD coupling simulation method, a simulation analysis was conducted to determine the range of key parameters and verify the feasibility of the solution. Using rotational speed, forward speed, and stubble entry angle as experimental factors and stubble rectification rate and second-season yield as evaluation metrics, a three-factor, three-level Box–Behnken response surface field trial was conducted. The theoretically optimal working parameter combination was found to be a forward speed of 1.4 m/s, device rotational speed of 75 rpm, and stubble entry angle of 39°. Under these conditions, three parallel experiments were performed, resulting in a rectification rate of 90.35% in the mechanically harvested and compressed area and a second-season yield of 2202.64 ± 35 kg/hm². The deviation from the numerical simulation results of parameter optimization was less than 5%. These findings suggest that the designed stubble rectification device for ratoon rice can meet the requirements of stubble rectification during the first-season harvest of ratoon rice. Furthermore, it provides valuable insights for reducing harvest losses in the first season and further improving the level of mechanized harvesting for ratoon rice.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"1 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140375898","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}
Nitrogen plays a crucial role in cotton growth, making the precise diagnosis of its nutrition levels vital for the scientific and rational application of fertilizers. Addressing this need, our study introduced an EMRDFC-based diagnosis model specifically for cotton nitrogen nutrition levels. In our field experiments, cotton was subjected to five different nitrogen application rates. To enhance the diagnostic capabilities of our model, we employed ResNet101, MobileNetV2, and DenseNet121 as base models and integrated the CBAM (Convolutional Block Attention Module) into each to improve their ability to differentiate among various nitrogen levels. Additionally, the Focal loss function was introduced to address issues of data imbalance. The model’s effectiveness was further augmented by employing integration strategies such as relative majority voting, simple averaging, and weighted averaging. Our experimental results indicated significant accuracy improvements in the enhanced ResNet101, MobileNetV2, and DenseNet121 models by 2.3%, 2.91%, and 2.93%, respectively. Notably, the integration of these models consistently improved accuracy, with gains of 0.87% and 1.73% compared to the highest-performing single model, DenseNet121FC. The optimal ensemble model, which utilized the weighted average method, demonstrated superior learning and generalization capabilities. The proposed EMRDFC model shows great promise in precisely identifying cotton nitrogen status, offering critical insights into the diagnosis of crop nutrient status. This research contributes significantly to the field of agricultural technology by providing a reliable tool for nitrogen-level assessment in cotton cultivation.
{"title":"Diagnosis of Cotton Nitrogen Nutrient Levels Using Ensemble MobileNetV2FC, ResNet101FC, and DenseNet121FC","authors":"Peipei Chen, Jianguo Dai, Guoshun Zhang, Wenqing Hou, Zhengyang Mu, Yujuan Cao","doi":"10.3390/agriculture14040525","DOIUrl":"https://doi.org/10.3390/agriculture14040525","url":null,"abstract":"Nitrogen plays a crucial role in cotton growth, making the precise diagnosis of its nutrition levels vital for the scientific and rational application of fertilizers. Addressing this need, our study introduced an EMRDFC-based diagnosis model specifically for cotton nitrogen nutrition levels. In our field experiments, cotton was subjected to five different nitrogen application rates. To enhance the diagnostic capabilities of our model, we employed ResNet101, MobileNetV2, and DenseNet121 as base models and integrated the CBAM (Convolutional Block Attention Module) into each to improve their ability to differentiate among various nitrogen levels. Additionally, the Focal loss function was introduced to address issues of data imbalance. The model’s effectiveness was further augmented by employing integration strategies such as relative majority voting, simple averaging, and weighted averaging. Our experimental results indicated significant accuracy improvements in the enhanced ResNet101, MobileNetV2, and DenseNet121 models by 2.3%, 2.91%, and 2.93%, respectively. Notably, the integration of these models consistently improved accuracy, with gains of 0.87% and 1.73% compared to the highest-performing single model, DenseNet121FC. The optimal ensemble model, which utilized the weighted average method, demonstrated superior learning and generalization capabilities. The proposed EMRDFC model shows great promise in precisely identifying cotton nitrogen status, offering critical insights into the diagnosis of crop nutrient status. This research contributes significantly to the field of agricultural technology by providing a reliable tool for nitrogen-level assessment in cotton cultivation.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"14 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140378759","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}
Pub Date : 2024-03-26DOI: 10.3390/agriculture14040526
Yuan Tian, Xiuyi Shi
In order to cope with global climate warming, measurement of the low-carbon utilization efficiency (LCUE) of cultivated land, considering carbon sink and carbon emission effects, is proposed. To address this, based on the data of 30 provinces in China, this study conducts a LCUE evaluation system by the MinDS-U-M productivity index model in order to analyze the spatiotemporal patterns and driving factors of LCUE with the geographic detector model and GTWR model. The results show the following: (1) Over the past 20 years, the average LCUE value exhibits a slow increasing trend from 2001 to 2021, which ranges from 0.9864 to 1.0272. Provinces with mid-level LCUE ranging from 1.0000 to 1.0990 account for the highest proportion in each period. (2) The annual growth rate of LCUE in the central region is the highest, where the promotion of green technology and farmland protection policies have played important roles. (3) According to the Geodetector analysis, urbanization rate (UR), irrigation index (IR), grain output value (GOV), precipitation (PR), arable land area (ALA), and environmental pollution control (EPC) are important drivers of the spatial difference of LCUE. (4) The GTWR model shows that the positive effects of ALA and SRT have always been concentrated in the main grain-producing areas over time. UR and PR have strong explanatory power for the space/time differentiation of LCUE, especially in eastern coastal regions. IR has an increasing effect on LCUE in the Western region, and the positive effect of EPC on the LCUE is concentrated in the central region. In order to coordinate regional LCUE contradictions, it is suggested to be wary of land resource damage caused by economic development, warn about the impacts of climate change, and strengthen the supervision of land remediation projects in order to achieve sustainable land management.
{"title":"Analysis of Dynamic Evolution and Driving Factors of Low-Carbon Utilization Efficiency of Cultivated Land in China","authors":"Yuan Tian, Xiuyi Shi","doi":"10.3390/agriculture14040526","DOIUrl":"https://doi.org/10.3390/agriculture14040526","url":null,"abstract":"In order to cope with global climate warming, measurement of the low-carbon utilization efficiency (LCUE) of cultivated land, considering carbon sink and carbon emission effects, is proposed. To address this, based on the data of 30 provinces in China, this study conducts a LCUE evaluation system by the MinDS-U-M productivity index model in order to analyze the spatiotemporal patterns and driving factors of LCUE with the geographic detector model and GTWR model. The results show the following: (1) Over the past 20 years, the average LCUE value exhibits a slow increasing trend from 2001 to 2021, which ranges from 0.9864 to 1.0272. Provinces with mid-level LCUE ranging from 1.0000 to 1.0990 account for the highest proportion in each period. (2) The annual growth rate of LCUE in the central region is the highest, where the promotion of green technology and farmland protection policies have played important roles. (3) According to the Geodetector analysis, urbanization rate (UR), irrigation index (IR), grain output value (GOV), precipitation (PR), arable land area (ALA), and environmental pollution control (EPC) are important drivers of the spatial difference of LCUE. (4) The GTWR model shows that the positive effects of ALA and SRT have always been concentrated in the main grain-producing areas over time. UR and PR have strong explanatory power for the space/time differentiation of LCUE, especially in eastern coastal regions. IR has an increasing effect on LCUE in the Western region, and the positive effect of EPC on the LCUE is concentrated in the central region. In order to coordinate regional LCUE contradictions, it is suggested to be wary of land resource damage caused by economic development, warn about the impacts of climate change, and strengthen the supervision of land remediation projects in order to achieve sustainable land management.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"105 26","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140380482","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}
Pub Date : 2024-03-26DOI: 10.3390/agriculture14040524
Xuejun Zhang, Lei Guo, Jinshan Yan, Zenglu Shi, Mengchen Kang, Jieting Yao
The extended duration of mulching in Xinjiang cotton fields leads to a significant decline in the tensile strength of plastic film. When recycling is in operation, the soil and the spring teeth of the machinery used can easily cause secondary damage and fracture the residual film. Establishing appropriate working parameters for recycling is essential to enhance the overall quality of collection efforts. By analyzing the motion process of a chain-tooth residual film pickup device, we identified key working parameters that significantly impact the efficiency of recycling. Employing the finite element method (FEM) and a coupled algorithm incorporating smooth particle hydrodynamics (SPH), we developed a coupled finite element model representing the interaction among spring teeth, soil, and residual film. Through simulation and analysis of the process of inserting the spring teeth into the soil to collect film, we derived the governing rules for residual film stress and deformation changes. Utilizing forward speed, rotational angular velocity, and angle of entry into the soil of the spring teeth as test factors and selecting the residual film stress and the residual film deformation as test indices, we conducted a multi-factor simulation test. We established a mathematical model correlating test factors with test indices, and the influence of each factor on the test index was analyzed. Subsequently, we optimized the working parameters of the spring teeth. The results indicated that the optimal working parameters are forward speed of 1111.11 mm/s, rotational angular velocity of 25 rad/s, and angle of entry into the soil of 30°. At these values, the average peak stress of residual film was 4.51 MPa and the height of residual film pickup was 84.48 mm. To validate the optimized the spring teeth impact on performance, field experiments were conducted with recovery rate and winding rate as test indices. The results demonstrated a 92.1% recovery rate and a 1.1% winding rate under the optimal combination of working parameters. The finite element model presented in this paper serves as a reference for designing and analyzing key components of residual film recycling machines.
{"title":"Simulation Analysis and Parameter Optimization of Residual Film Pickup Process Based on Finite Element Method","authors":"Xuejun Zhang, Lei Guo, Jinshan Yan, Zenglu Shi, Mengchen Kang, Jieting Yao","doi":"10.3390/agriculture14040524","DOIUrl":"https://doi.org/10.3390/agriculture14040524","url":null,"abstract":"The extended duration of mulching in Xinjiang cotton fields leads to a significant decline in the tensile strength of plastic film. When recycling is in operation, the soil and the spring teeth of the machinery used can easily cause secondary damage and fracture the residual film. Establishing appropriate working parameters for recycling is essential to enhance the overall quality of collection efforts. By analyzing the motion process of a chain-tooth residual film pickup device, we identified key working parameters that significantly impact the efficiency of recycling. Employing the finite element method (FEM) and a coupled algorithm incorporating smooth particle hydrodynamics (SPH), we developed a coupled finite element model representing the interaction among spring teeth, soil, and residual film. Through simulation and analysis of the process of inserting the spring teeth into the soil to collect film, we derived the governing rules for residual film stress and deformation changes. Utilizing forward speed, rotational angular velocity, and angle of entry into the soil of the spring teeth as test factors and selecting the residual film stress and the residual film deformation as test indices, we conducted a multi-factor simulation test. We established a mathematical model correlating test factors with test indices, and the influence of each factor on the test index was analyzed. Subsequently, we optimized the working parameters of the spring teeth. The results indicated that the optimal working parameters are forward speed of 1111.11 mm/s, rotational angular velocity of 25 rad/s, and angle of entry into the soil of 30°. At these values, the average peak stress of residual film was 4.51 MPa and the height of residual film pickup was 84.48 mm. To validate the optimized the spring teeth impact on performance, field experiments were conducted with recovery rate and winding rate as test indices. The results demonstrated a 92.1% recovery rate and a 1.1% winding rate under the optimal combination of working parameters. The finite element model presented in this paper serves as a reference for designing and analyzing key components of residual film recycling machines.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"119 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140381210","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}
This study investigates the relationship between nitrogen fertilization and pepper fruit color by employing five different nitrogen treatments (N1: 750 kg/hm2, N2: 562.5 kg/hm2, N3: 375 kg/hm2, N4: 187.5, and N0: 0 kg/hm2). Fruits were harvested at 30 (S1: green ripening stage), 45 (S2: color transition stage), and 60 days (S3: red ripening stage) after flowering. Subsequently, pigment content, carotenoid component content, carotenoid enzyme activity, and transcriptome sequence were analyzed, and CA12g04950 function was validated through virus-induced gene silencing (VIGS). The results indicate that a reduction in nitrogen application led to an earlier onset of fruit color breakdown, and increased the contents of total carotenoid, capsanthin, phytoene and PSY (phytoene synthase) activity, LCYB (lycopene β-cyclase) activity and CCS (capsanthin/capsorubin synthase) activity. The analysis of different expression genes indicated that the most differently expressed genes were enriched in the N1 vs. N4 comparison, with 18 genes involved in carotenoid metabolism and 16 genes involved in nitrogen metabolism. Most DE genes were enriched in the pathways of photosynthesis, porphyrin, carotenoid biosynthesis, seleno-compounds, and nitrogen metabolism. There were numerous differential transcription factor families, including ERF, bHLH, MYB, C2H2, and NAC. Pearson correlation analysis revealed a significant positive correlation between CA12g04950 expression and 11 carotenoid genes in the N4 treatment. Subsequent silencing of CA12g04950 using VIGS resulted in delayed color ripening while a significant decrease in total carotenoid content and the expression levels of carotenoid genes. In conclusion, nitrogen reduction led to an increase in carotenoid content in pigment pepper fruits. Furthermore, under nitrogen reduction, CA12g04950 positively influenced the redness of the fruits.
{"title":"Transcript Analysis Reveals Positive Regulation of CA12g04950 on Carotenoids of Pigment Pepper Fruit under Nitrogen Reduction","authors":"Lingfeng Shen, Chenfei Zhang, Yahui Xia, Shasha Yang, Tian Chang, Saleem Ullah, Xuehua Ji","doi":"10.3390/agriculture14040521","DOIUrl":"https://doi.org/10.3390/agriculture14040521","url":null,"abstract":"This study investigates the relationship between nitrogen fertilization and pepper fruit color by employing five different nitrogen treatments (N1: 750 kg/hm2, N2: 562.5 kg/hm2, N3: 375 kg/hm2, N4: 187.5, and N0: 0 kg/hm2). Fruits were harvested at 30 (S1: green ripening stage), 45 (S2: color transition stage), and 60 days (S3: red ripening stage) after flowering. Subsequently, pigment content, carotenoid component content, carotenoid enzyme activity, and transcriptome sequence were analyzed, and CA12g04950 function was validated through virus-induced gene silencing (VIGS). The results indicate that a reduction in nitrogen application led to an earlier onset of fruit color breakdown, and increased the contents of total carotenoid, capsanthin, phytoene and PSY (phytoene synthase) activity, LCYB (lycopene β-cyclase) activity and CCS (capsanthin/capsorubin synthase) activity. The analysis of different expression genes indicated that the most differently expressed genes were enriched in the N1 vs. N4 comparison, with 18 genes involved in carotenoid metabolism and 16 genes involved in nitrogen metabolism. Most DE genes were enriched in the pathways of photosynthesis, porphyrin, carotenoid biosynthesis, seleno-compounds, and nitrogen metabolism. There were numerous differential transcription factor families, including ERF, bHLH, MYB, C2H2, and NAC. Pearson correlation analysis revealed a significant positive correlation between CA12g04950 expression and 11 carotenoid genes in the N4 treatment. Subsequent silencing of CA12g04950 using VIGS resulted in delayed color ripening while a significant decrease in total carotenoid content and the expression levels of carotenoid genes. In conclusion, nitrogen reduction led to an increase in carotenoid content in pigment pepper fruits. Furthermore, under nitrogen reduction, CA12g04950 positively influenced the redness of the fruits.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":" 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140384501","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}
Pub Date : 2024-03-25DOI: 10.3390/agriculture14040523
Huinan Huang, Yan Zhang, D. Wang, Zijiang Fu, Hui Tian, Junjuan Shang, Mahmoud Helal, Zhijun Lv
The hopper is an important piece of basic equipment used for storing and transporting materials in the agricultural, grain, chemical engineering, coal mine and pharmaceutical industries. The discharging performance of hoppers is mainly affected by material properties and hopper structure. In this work, the flow capacity of cylindrical pellets in the hopper with the unloading paddle is studied. A series of numerical simulation analyses with the aid of the discrete element method (DEM) platform are carried out. Then, the discharging process is illustrated, and the flow capacity of pellets in the hopper is analyzed by the mass flow index (MFI), the dynamic discharging angle (DDA) formed in the discharging process and porosity among pellets. Furthermore, the effect of parameters such as hopper half angle, rotation speed of the unloading paddle and outlet diameter of the hopper is investigated. The results show that MFI increases with an increase in hopper half angle or outlet diameter and a decrease in rotation speed. Meanwhile, DDA and porosity decrease with the increase in the hopper half angle or outlet diameter and the decrease in the rotation speed. Finally, the MFI ~0.24 is identified as the criterion to distinguish the mass flow from the funnel flow for the hopper with an unloading paddle, and the optimization results are decided as follows: hopper half angle greater than 60°, outlet diameter greater than 60 mm and rotation speed between 45 rpm and 60 rpm. These results should be useful for providing a theoretical reference for the optimization design of feeding devices for swine feeders.
{"title":"Study the Flow Capacity of Cylindrical Pellets in Hopper with Unloading Paddle Using DEM","authors":"Huinan Huang, Yan Zhang, D. Wang, Zijiang Fu, Hui Tian, Junjuan Shang, Mahmoud Helal, Zhijun Lv","doi":"10.3390/agriculture14040523","DOIUrl":"https://doi.org/10.3390/agriculture14040523","url":null,"abstract":"The hopper is an important piece of basic equipment used for storing and transporting materials in the agricultural, grain, chemical engineering, coal mine and pharmaceutical industries. The discharging performance of hoppers is mainly affected by material properties and hopper structure. In this work, the flow capacity of cylindrical pellets in the hopper with the unloading paddle is studied. A series of numerical simulation analyses with the aid of the discrete element method (DEM) platform are carried out. Then, the discharging process is illustrated, and the flow capacity of pellets in the hopper is analyzed by the mass flow index (MFI), the dynamic discharging angle (DDA) formed in the discharging process and porosity among pellets. Furthermore, the effect of parameters such as hopper half angle, rotation speed of the unloading paddle and outlet diameter of the hopper is investigated. The results show that MFI increases with an increase in hopper half angle or outlet diameter and a decrease in rotation speed. Meanwhile, DDA and porosity decrease with the increase in the hopper half angle or outlet diameter and the decrease in the rotation speed. Finally, the MFI ~0.24 is identified as the criterion to distinguish the mass flow from the funnel flow for the hopper with an unloading paddle, and the optimization results are decided as follows: hopper half angle greater than 60°, outlet diameter greater than 60 mm and rotation speed between 45 rpm and 60 rpm. These results should be useful for providing a theoretical reference for the optimization design of feeding devices for swine feeders.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":"111 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140381679","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}
Pub Date : 2024-03-25DOI: 10.3390/agriculture14040519
C. Bocean
Amidst the rapid evolution of digital technologies and their prospective implications for agricultural productivity, farmers are increasingly turning to Agriculture 4.0. As digitization permeates every facet of agriculture, the potential for boosting productivity while ensuring sustainability and resilience becomes increasingly tangible. The objective of this study is to understand how the adoption of digital technologies influences agricultural productivity within the diverse socioeconomic and agricultural landscapes of EU nations. The research of this study aims to address questions concerning the impact of digital technology use on agricultural productivity across EU countries. This study employs a robust analytical framework combining equation modeling (SEM), artificial neural networks, and cluster analysis. SEM analysis reveals significant associations and influences between digital technology use and productivity related to the total labor force across EU countries. Moreover, cluster analysis outlines distinct clusters of EU member states distinguished by varying degrees of digital technology incorporation and corresponding agricultural productivity, emphasizing the diverse socioeconomic contexts that influence these associations. These findings underscore the significance of embracing digital technology as a catalyst for enhancing agricultural productivity across EU nations. Future research could focus on devising strategies to promote the widespread adoption of digital technologies in agriculture across EU member states, and longitudinal analyses could offer insights into the dynamic relationship between digital technology use and agricultural output, informing policy interventions.
{"title":"A Cross-Sectional Analysis of the Relationship between Digital Technology Use and Agricultural Productivity in EU Countries","authors":"C. Bocean","doi":"10.3390/agriculture14040519","DOIUrl":"https://doi.org/10.3390/agriculture14040519","url":null,"abstract":"Amidst the rapid evolution of digital technologies and their prospective implications for agricultural productivity, farmers are increasingly turning to Agriculture 4.0. As digitization permeates every facet of agriculture, the potential for boosting productivity while ensuring sustainability and resilience becomes increasingly tangible. The objective of this study is to understand how the adoption of digital technologies influences agricultural productivity within the diverse socioeconomic and agricultural landscapes of EU nations. The research of this study aims to address questions concerning the impact of digital technology use on agricultural productivity across EU countries. This study employs a robust analytical framework combining equation modeling (SEM), artificial neural networks, and cluster analysis. SEM analysis reveals significant associations and influences between digital technology use and productivity related to the total labor force across EU countries. Moreover, cluster analysis outlines distinct clusters of EU member states distinguished by varying degrees of digital technology incorporation and corresponding agricultural productivity, emphasizing the diverse socioeconomic contexts that influence these associations. These findings underscore the significance of embracing digital technology as a catalyst for enhancing agricultural productivity across EU nations. Future research could focus on devising strategies to promote the widespread adoption of digital technologies in agriculture across EU member states, and longitudinal analyses could offer insights into the dynamic relationship between digital technology use and agricultural output, informing policy interventions.","PeriodicalId":503580,"journal":{"name":"Agriculture","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140382240","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}
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