Lake Erie is threatened by eutrophication and harmful algal blooms due to excess nutrient loading from agricultural sources. To reduce nutrient loading to Lake Erie, widespread adoption of agricultural conservation practices (ACPs) has been proposed. However, identifying appropriate and effective locations for ACP placement has been challenging. Another challenge is understanding how effective the ACPs are in reducing nutrient loading and achieving water quality goals. Therefore, identifying the most effective ACPs, as well as spatially optimal placement of ACPs to achieve the maximum environmental benefit, is of paramount importance. The main objective of this study was to integrate the Agricultural Conservation Planning Framework (ACPF) with the Soil and Water Assessment Tool (SWAT) to assess the potential effectiveness of ACPs developed by ACPF in reducing phosphorous losses from an agriculturally dominated small watershed within the Western Lake Erie Basin. ACPF was used to develop a series of ACP opportunity plans, which were then integrated into a calibrated SWAT model. SWAT simulation of ACPF developed ACP opportunity plans for grassed waterways (GWs), contour buffer strips (CBSs), water and sediment control basins (WASCOBs), nutrient removal wetlands (NRWs), and farm ponds (FPs) revealed various reductions in sediment, soluble reactive phosphorus (SRP), and total phosphorus (TP) at the watershed-scale. The simulation of individual ACP opportunity plans revealed that GW resulted in the greatest annual average SRP and TP reductions (19% and 30%, respectively), followed by CBS (16% and 22%), and WASCOB (13% and 16%); NRWs were the most effective at reducing sediment (56%) but increased SRP (27%). Combined GW, CBS, and WASCOB opportunity plans resulted in the greatest reduction of SRP (34%), while the combination of all ACP opportunity plans resulted in the greatest reduction of TP (49%) and sediment (78%).
{"title":"Integrating ACPF and SWAT to Assess Potential Phosphorus Loading Reductions to Lake Erie: A Case Study.","authors":"Yongping Yuan, Samantha Whisenant","doi":"10.13031/aea.15644","DOIUrl":"https://doi.org/10.13031/aea.15644","url":null,"abstract":"<p><p>Lake Erie is threatened by eutrophication and harmful algal blooms due to excess nutrient loading from agricultural sources. To reduce nutrient loading to Lake Erie, widespread adoption of agricultural conservation practices (ACPs) has been proposed. However, identifying appropriate and effective locations for ACP placement has been challenging. Another challenge is understanding how effective the ACPs are in reducing nutrient loading and achieving water quality goals. Therefore, identifying the most effective ACPs, as well as spatially optimal placement of ACPs to achieve the maximum environmental benefit, is of paramount importance. The main objective of this study was to integrate the Agricultural Conservation Planning Framework (ACPF) with the Soil and Water Assessment Tool (SWAT) to assess the potential effectiveness of ACPs developed by ACPF in reducing phosphorous losses from an agriculturally dominated small watershed within the Western Lake Erie Basin. ACPF was used to develop a series of ACP opportunity plans, which were then integrated into a calibrated SWAT model. SWAT simulation of ACPF developed ACP opportunity plans for grassed waterways (GWs), contour buffer strips (CBSs), water and sediment control basins (WASCOBs), nutrient removal wetlands (NRWs), and farm ponds (FPs) revealed various reductions in sediment, soluble reactive phosphorus (SRP), and total phosphorus (TP) at the watershed-scale. The simulation of individual ACP opportunity plans revealed that GW resulted in the greatest annual average SRP and TP reductions (19% and 30%, respectively), followed by CBS (16% and 22%), and WASCOB (13% and 16%); NRWs were the most effective at reducing sediment (56%) but increased SRP (27%). Combined GW, CBS, and WASCOB opportunity plans resulted in the greatest reduction of SRP (34%), while the combination of all ACP opportunity plans resulted in the greatest reduction of TP (49%) and sediment (78%).</p>","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095117/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140960976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Highlights A rice-leaf-disease detection and classification algorithm for multiple rice-leaf-diseases in a complicated rice leaf image is proposed in this article. To increase rice-leaf-disease classification accuracy, an algorithm for coarse-to-fine determination is proposed. Since features of rice-leaf-disease types such as color, shape, and so on are similar and difficult to classify even with the human eye, tolerances among those features are small. The algorithm considers enlarging the tolerances using two-step classification of coarse-to-fine. Severity level of rice leaf disease is also estimated in our proposed method. Abstract. Farmers may decide to select an appropriate insecticide for rice-leaf disease treatment in a paddy rice field based on disease class and severity level. To classify the class of rice leaf disease and estimate the severity level in a paddy rice field, several parts of the rice leaf are included in a captured image, and sometimes there exists more than one disease boundary in a part of rice leaf. This article proposes a method of rice-leaf disease classification and severity level estimation for multiple diseases on a multiple rice-leaf image. This method first finds rice-leaf candidate boundaries and identifies the rice leaf based on its feature of color, shape, and area ratio. To enlarge classification tolerance based on the coarse-to-fine concept, disease candidate boundaries are categorized into two major groups in the coarse level, and then both groups are classified into rice leaf classes in the fine level. To evaluate the performance of the proposed method, experiments were performed with 8,303 images of three rice leaf diseases including brown spot, rice blast, rice hispa and healthy rice leaf, and our proposed method achieved 99.27% which outperformed the deep learning approach by 0.43%. Keywords: Coarse to fine, Multiple rice-leaf diseases, Rice-leaf disease recognition, Severity level.
{"title":"Boundary-Based Rice-Leaf-Disease Classification and Severity Level Estimation for Automatic Insecticide Injection","authors":"Sayan Tepdang, K. Chamnongthai","doi":"10.13031/aea.15257","DOIUrl":"https://doi.org/10.13031/aea.15257","url":null,"abstract":"Highlights A rice-leaf-disease detection and classification algorithm for multiple rice-leaf-diseases in a complicated rice leaf image is proposed in this article. To increase rice-leaf-disease classification accuracy, an algorithm for coarse-to-fine determination is proposed. Since features of rice-leaf-disease types such as color, shape, and so on are similar and difficult to classify even with the human eye, tolerances among those features are small. The algorithm considers enlarging the tolerances using two-step classification of coarse-to-fine. Severity level of rice leaf disease is also estimated in our proposed method. Abstract. Farmers may decide to select an appropriate insecticide for rice-leaf disease treatment in a paddy rice field based on disease class and severity level. To classify the class of rice leaf disease and estimate the severity level in a paddy rice field, several parts of the rice leaf are included in a captured image, and sometimes there exists more than one disease boundary in a part of rice leaf. This article proposes a method of rice-leaf disease classification and severity level estimation for multiple diseases on a multiple rice-leaf image. This method first finds rice-leaf candidate boundaries and identifies the rice leaf based on its feature of color, shape, and area ratio. To enlarge classification tolerance based on the coarse-to-fine concept, disease candidate boundaries are categorized into two major groups in the coarse level, and then both groups are classified into rice leaf classes in the fine level. To evaluate the performance of the proposed method, experiments were performed with 8,303 images of three rice leaf diseases including brown spot, rice blast, rice hispa and healthy rice leaf, and our proposed method achieved 99.27% which outperformed the deep learning approach by 0.43%. Keywords: Coarse to fine, Multiple rice-leaf diseases, Rice-leaf disease recognition, Severity level.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67051872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Highlights Drift data collected from herbicide applications for corn, soybean, and cotton, including three commercial producers. Drift volumes and drift distances were estimated and correlated to wind speed, boom length, spray height, tractor speed, and droplet size (DV50). Boom length and spray height appear to be the dominant parameters affecting drift volume and drift distance, respectively. The results show a three- to fourfold reduction in drift using a hooded sprayer or spraying in calm weather. Abstract. Although several best practices are available, there are still opportunities to mitigate off-target pesticide drift, protect nearby sensitive crops, and address health concerns for humans/animals. The purpose of the study is to identify opportunities to mitigate drift from ground-based preemergent herbicide applications. Seven herbicide applications were tested for corn, soybean and cotton, including three regional commercial producers. Drift data were collected using water sensitive cards. ImageJ was used to analyze the droplet spectrum. Drift volumes and drift distances were estimated for each experiment. Data collected on wind speed, boom length, spray height, tractor speed, droplet size (DV50), and chemical application rate were used as explanatory variables of drift volume and drift distance. Individual and multiple linear regressions (MLRs) were carried out between drift volume, drift distance, and the explanatory variables. Our results show a three- to fourfold reduction in drift using a hooded sprayer or spraying in calm weather. Boom length and spray height appear to be the dominant parameters affecting drift volume and drift distance, respectively. The MLR results suggest that we can estimate drift (a) volume reasonably using a combination of boom length, DV50, and tractor speed and (b) distance reliably using a combination of spray height, boom length, and DV50. Keywords: Drift distance, Droplet spectrum, Fence board, Herbicide drift, Hooded sprayer, Preemergent herbicide, Water sensitive card.
{"title":"Opportunities to Mitigate Particle Drift from Ground-Based Preemergent Herbicide Applications","authors":"N. Kannan, Christina Huggins","doi":"10.13031/aea.15307","DOIUrl":"https://doi.org/10.13031/aea.15307","url":null,"abstract":"Highlights Drift data collected from herbicide applications for corn, soybean, and cotton, including three commercial producers. Drift volumes and drift distances were estimated and correlated to wind speed, boom length, spray height, tractor speed, and droplet size (DV50). Boom length and spray height appear to be the dominant parameters affecting drift volume and drift distance, respectively. The results show a three- to fourfold reduction in drift using a hooded sprayer or spraying in calm weather. Abstract. Although several best practices are available, there are still opportunities to mitigate off-target pesticide drift, protect nearby sensitive crops, and address health concerns for humans/animals. The purpose of the study is to identify opportunities to mitigate drift from ground-based preemergent herbicide applications. Seven herbicide applications were tested for corn, soybean and cotton, including three regional commercial producers. Drift data were collected using water sensitive cards. ImageJ was used to analyze the droplet spectrum. Drift volumes and drift distances were estimated for each experiment. Data collected on wind speed, boom length, spray height, tractor speed, droplet size (DV50), and chemical application rate were used as explanatory variables of drift volume and drift distance. Individual and multiple linear regressions (MLRs) were carried out between drift volume, drift distance, and the explanatory variables. Our results show a three- to fourfold reduction in drift using a hooded sprayer or spraying in calm weather. Boom length and spray height appear to be the dominant parameters affecting drift volume and drift distance, respectively. The MLR results suggest that we can estimate drift (a) volume reasonably using a combination of boom length, DV50, and tractor speed and (b) distance reliably using a combination of spray height, boom length, and DV50. Keywords: Drift distance, Droplet spectrum, Fence board, Herbicide drift, Hooded sprayer, Preemergent herbicide, Water sensitive card.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67052238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Priyanka Gupta, Charles R. Hurburgh, Erin Bowers, Gretchen A Mosher
Highlights Most simulated scenarios showed low probabilities of meeting with 0.9% and 1.5% tolerance limits. 3.0% and 5.0% tolerance limits were achievable at some supply chain stages under specific conditions. Feasible tolerance limits at individual supply chain stages ranged from 2.25% to 6.25%. Seed purity and cross-pollination were key factors affecting the probability of meeting AP tolerance limits. Abstract . Tolerance limits for the adventitious presence (AP) of GM material in non-GM grain, food, and feed vary worldwide from 0.9% to 5.0%. This research analyzed the likelihood of meeting four common trade tolerance limits for AP (0.9%, 1.5%, 3.0%, and 5.0%) in the U.S. commodity corn supply chain. A model was developed to evaluate existing practices and patterns for bulk corn production, handling, and processing in an open-market supply chain that concurrently handles GM and non-GM products. Monte Carlo simulation was used to test 50,000 iterations of supply chain scenarios to determine the likelihood of successfully meeting specified tolerance limits. The model revealed that the supply chain, as it exists today, does not effectively facilitate the concurrent handling of GM and non-GM streams at 0.9% and 1.5% tolerance limits in most cases. At individual supply chain stages, some tolerance limits were reasonably achievable, such as 3.0% and 5.0% at the farm stage. The probabilities of complying with 0.9% and 1.5% tolerance limits at the farm stage were just over 10% and 67%, respectively, while the probabilities of complying with 3.0% and 5.0% tolerance limits were more than 90%. The grain elevator and grain processor could achieve 3.0% and 5.0% tolerance limits with reasonable likelihood. At the feed mill, a 5.0% tolerance limit was achievable but only when bypassing some supply chain stages. The 99% feasible tolerance limits at individual supply chain stages ranged from 2.25% to 6.25%. Significant factors influencing the ability to meet AP tolerances were identified using sensitivity analysis. These factors included seed impurity, cross-pollination, and transportation vehicles. Keywords: Adventitious presence, Corn, Feed, Genetically modified grain, Monte Carlo simulation, Segregation, Supply chain.
{"title":"Assessing the Feasibility of Meeting Tolerance Limits for GM Adventitious Presence in Corn Supply Chain Using Probabilistic Modeling","authors":"Priyanka Gupta, Charles R. Hurburgh, Erin Bowers, Gretchen A Mosher","doi":"10.13031/aea.15570","DOIUrl":"https://doi.org/10.13031/aea.15570","url":null,"abstract":"Highlights Most simulated scenarios showed low probabilities of meeting with 0.9% and 1.5% tolerance limits. 3.0% and 5.0% tolerance limits were achievable at some supply chain stages under specific conditions. Feasible tolerance limits at individual supply chain stages ranged from 2.25% to 6.25%. Seed purity and cross-pollination were key factors affecting the probability of meeting AP tolerance limits. Abstract . Tolerance limits for the adventitious presence (AP) of GM material in non-GM grain, food, and feed vary worldwide from 0.9% to 5.0%. This research analyzed the likelihood of meeting four common trade tolerance limits for AP (0.9%, 1.5%, 3.0%, and 5.0%) in the U.S. commodity corn supply chain. A model was developed to evaluate existing practices and patterns for bulk corn production, handling, and processing in an open-market supply chain that concurrently handles GM and non-GM products. Monte Carlo simulation was used to test 50,000 iterations of supply chain scenarios to determine the likelihood of successfully meeting specified tolerance limits. The model revealed that the supply chain, as it exists today, does not effectively facilitate the concurrent handling of GM and non-GM streams at 0.9% and 1.5% tolerance limits in most cases. At individual supply chain stages, some tolerance limits were reasonably achievable, such as 3.0% and 5.0% at the farm stage. The probabilities of complying with 0.9% and 1.5% tolerance limits at the farm stage were just over 10% and 67%, respectively, while the probabilities of complying with 3.0% and 5.0% tolerance limits were more than 90%. The grain elevator and grain processor could achieve 3.0% and 5.0% tolerance limits with reasonable likelihood. At the feed mill, a 5.0% tolerance limit was achievable but only when bypassing some supply chain stages. The 99% feasible tolerance limits at individual supply chain stages ranged from 2.25% to 6.25%. Significant factors influencing the ability to meet AP tolerances were identified using sensitivity analysis. These factors included seed impurity, cross-pollination, and transportation vehicles. Keywords: Adventitious presence, Corn, Feed, Genetically modified grain, Monte Carlo simulation, Segregation, Supply chain.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135559703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Highlights Proposed application of 3D CNNS for recognition of farming behavior. Transfer learning was used to speed up training and improve model accuracy. A farming behavior dataset was constructed, expanded and compared with previous studies. An object detection network was used for data preprocessing rather than using traditional methods. Abstract. The quality and quantity of crop yields in agriculture primarily depend on the timing and precision of various implemented farming behaviors. Basins and hills dominate southwest China. Due to topographical constraints, the rate of agricultural mechanization in the region remains low, and agriculture remains primarily non-mechanized. The acquisition and recognition of information on farming behaviors play an important role in crop production. In this article, transfer learning was used in a current state-of-the-art 3DCNN-based behavior recognition model for farming behavior recognition and classification tasks. The focus was on fine-tuning and evaluating state-of-the-art 3D convolutional neural networks for farming behavior recognition. The evaluated architectures included Res3D, MC3, and R2+1D. The six common farming behaviors recognized include weeding, planting, harvesting, transplanting, fertilizing, and spraying. The accuracy of all models pretrained on Kinetics-400 after fine-tuning exceeded 90%, where MC3 had the best performance, with an accuracy of 0.9628, precision of 0.9647, sensitivity of 0.963, and specificity of 0.9925, which was slightly greater than the other two. MC3 was also the most lightweight of all models; its parameters were only 32.6% of Res3D and 36.7% of R2+1D. The experimental results demonstrated that the fine-tuned MC3 model offers high classification accuracy and effective recognition and classification of farming behaviors, which lays a good foundation for improved crop production. Keywords: Deep learning, Farming behavior recognition, Farm management, Fine-tuning, Precision agriculture, 3D convolutional neural networks, Transfer learning.
{"title":"A Comparative Study of Recognition Models Based on Fine-Tuning 3D CNNs for Farming Behaviors","authors":"Shibin Su, Xiaonan Hu, Xiang Li","doi":"10.13031/aea.15242","DOIUrl":"https://doi.org/10.13031/aea.15242","url":null,"abstract":"Highlights Proposed application of 3D CNNS for recognition of farming behavior. Transfer learning was used to speed up training and improve model accuracy. A farming behavior dataset was constructed, expanded and compared with previous studies. An object detection network was used for data preprocessing rather than using traditional methods. Abstract. The quality and quantity of crop yields in agriculture primarily depend on the timing and precision of various implemented farming behaviors. Basins and hills dominate southwest China. Due to topographical constraints, the rate of agricultural mechanization in the region remains low, and agriculture remains primarily non-mechanized. The acquisition and recognition of information on farming behaviors play an important role in crop production. In this article, transfer learning was used in a current state-of-the-art 3DCNN-based behavior recognition model for farming behavior recognition and classification tasks. The focus was on fine-tuning and evaluating state-of-the-art 3D convolutional neural networks for farming behavior recognition. The evaluated architectures included Res3D, MC3, and R2+1D. The six common farming behaviors recognized include weeding, planting, harvesting, transplanting, fertilizing, and spraying. The accuracy of all models pretrained on Kinetics-400 after fine-tuning exceeded 90%, where MC3 had the best performance, with an accuracy of 0.9628, precision of 0.9647, sensitivity of 0.963, and specificity of 0.9925, which was slightly greater than the other two. MC3 was also the most lightweight of all models; its parameters were only 32.6% of Res3D and 36.7% of R2+1D. The experimental results demonstrated that the fine-tuned MC3 model offers high classification accuracy and effective recognition and classification of farming behaviors, which lays a good foundation for improved crop production. Keywords: Deep learning, Farming behavior recognition, Farm management, Fine-tuning, Precision agriculture, 3D convolutional neural networks, Transfer learning.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67051921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Church, A. Hristov, P. Kleinman, Sarah K. Fishel, Michael R. Reiner, R. Bryant
Highlights The MAPHEX System removes and concentrates most of the P and other nutrients from liquid dairy manures. Most of the N and K are left in the liquid fraction for the beneficial use of the farmer. Design and expected performance of a simplified but much larger System is discussed. Abstract. The relatively recent concept of the manureshed highlights the problem of the broken nutrient cycle in modern animal agriculture and the low nitrogen:phosphorus ratio in manure relative to crop requirement that results in P accumulation in soils near source areas. One solution to avoid P accumulation is to transport the manure to soils with a deficit of P, but liquid manure’s bulkiness and low nutrient density present challenges for transport over great distances. While the full MAnure PHosphorus EXtraction (MAPHEX) System has shown to be capable of removing greater than 90% of the P from liquid manures while leaving much of the N in the liquid fraction for use on the farm, other nutrients present in manures in lesser amounts than N and P have not been reported on. This study indicates that both the full MAPHEX System and a newly designed MAPHEX Lite System, that not only conserves more N but is more efficient and less costly, are highly efficient at extracting and concentrating most nutrients in solid form while leaving most of the N and K in the liquid phase for beneficial use by the farmer near the manure source. Therefore, it seems clear that both Systems, and the components they include have the potential to play a significant role in manureshed management. Keywords: Chemical treatment, Liquid-solid separation, Manure, Nitrogen, Phosphorus, Potassium, Treatment systems.
{"title":"Nutrient Fate in the Full MAnure PHosphorus EXtraction (MAPHEX) System, and Design of a Simplified System (MAPHEX Lite)","authors":"C. Church, A. Hristov, P. Kleinman, Sarah K. Fishel, Michael R. Reiner, R. Bryant","doi":"10.13031/aea.15365","DOIUrl":"https://doi.org/10.13031/aea.15365","url":null,"abstract":"Highlights The MAPHEX System removes and concentrates most of the P and other nutrients from liquid dairy manures. Most of the N and K are left in the liquid fraction for the beneficial use of the farmer. Design and expected performance of a simplified but much larger System is discussed. Abstract. The relatively recent concept of the manureshed highlights the problem of the broken nutrient cycle in modern animal agriculture and the low nitrogen:phosphorus ratio in manure relative to crop requirement that results in P accumulation in soils near source areas. One solution to avoid P accumulation is to transport the manure to soils with a deficit of P, but liquid manure’s bulkiness and low nutrient density present challenges for transport over great distances. While the full MAnure PHosphorus EXtraction (MAPHEX) System has shown to be capable of removing greater than 90% of the P from liquid manures while leaving much of the N in the liquid fraction for use on the farm, other nutrients present in manures in lesser amounts than N and P have not been reported on. This study indicates that both the full MAPHEX System and a newly designed MAPHEX Lite System, that not only conserves more N but is more efficient and less costly, are highly efficient at extracting and concentrating most nutrients in solid form while leaving most of the N and K in the liquid phase for beneficial use by the farmer near the manure source. Therefore, it seems clear that both Systems, and the components they include have the potential to play a significant role in manureshed management. Keywords: Chemical treatment, Liquid-solid separation, Manure, Nitrogen, Phosphorus, Potassium, Treatment systems.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67052260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Highlights After inoculation with the Salmonella spp. cocktail and E. faecium, timothy hay samples had an initial microbial load of 7.81 and 7.75 log CFU/g, respectively. After RF treatments of 165, 175, 185, and 195 s, Salmonella spp. loads were reduced to 5.80 (SD ± 0.24), 4.00 (SD ± 0.27), 1.42 (SD ± 2.01) log CFU/g with complete decontamination at 195 s. At 165 and 175 s of RF treatments, the E. faecium loads were reduced to 7.50 (SD ± 0.14) and 6.39 (SD ± 0.31) log CFU/g with complete decontamination at 185 and 195 s. There were no statistically significant changes in the iron, vitamin A, or amino acid responses; sodium levels increased, and potassium and calcium levels decreased due to increasing RF treatment duration. Abstract. The objectives of this research were: 1) to investigate the efficacy of RF heating on the decontamination of Salmonella enterica and Enterococcus faecium NRRL B-2354 in timothy hay; 2) to evaluate the suitability of E. faecium as a surrogate of Salmonella in timothy hay during RF treatment; 3) to assess the physicochemical changes after RF treatment on vitamins, amino acids, fatty acids, and trace minerals in the timothy hay. A pilot-scale parallel-plate RF heating system (6 kW, 27.12 MHz) was used to conduct this study. The electrode gap in the RF system was adjusted to 205 mm. Timothy hay was procured from a pet food manufacturing plant in Lincoln, Nebraska, at an initial moisture content (MC) of 7% to 9% (wet basis). Timothy hay samples (150 g) were inoculated with either a cocktail containing five serotypes of Salmonella enterica [Salmonella Agona (447967), Salmonella Mbandaka (698538), Salmonella Montevideo (488275), Salmonella Tennessee (K4643), and Salmonella Reading (Moff 180418)] or a broth of Enterococcus faecium then incubated at 37°C for 24 ± 2 h. Timothy hay samples were exposed to RF energy for 165, 175, 185, and 195 s. It was determined that after inoculation with the Salmonella cocktail and E. faecium, timothy hay samples had an initial microbial load of 7.81 and 7.75 log CFU/g, respectively. After RF treatments of 165, 175, 185, and 195 s, Salmonella loads (mean ± SD log CFU/g) were reduced to 5.80 ± 0.24, 4.00 ± 0.27, 1.42 ± 2.01 log CFU/g and below the level of detection, respectively. At 165 and 175 s of RF treatments, the E. faecium loads (mean ± SD log CFU/g) were reduced to 7.50 ± 0.14 and 6.39 ± 0.31 log CFU/g and below the detection level at 185 and 195 s. There was complete decontamination at 185 and 195 s. There were no statistically significant changes in the iron, vitamin A, or amino acid responses because of increasing RF treatment duration. The study demonstrated a non-chemical approach to decontaminating Salmonella and Enterococcus faecium from low-moisture foods such as pet foods. Keywords: Decontamination, Enterococcus faecium, Low moisture, Pet food, Radio-frequency, Salmonella, Timothy hay.
{"title":"Development of a Radio-Frequency Technology for the Decontamination of <i>Salmonella</i> from Timothy Hay","authors":"Deandrae Smith, Surabhi Wason, Rebecca Bruce, Griffiths Atungulu","doi":"10.13031/aea.15598","DOIUrl":"https://doi.org/10.13031/aea.15598","url":null,"abstract":"Highlights\u0000 \u0000 \u0000 \u0000 \u0000 After inoculation with the Salmonella spp. cocktail and E. faecium, timothy hay samples had an initial microbial load of 7.81 and 7.75 log CFU/g, respectively.\u0000 \u0000 \u0000 After RF treatments of 165, 175, 185, and 195 s, Salmonella spp. loads were reduced to 5.80 (SD ± 0.24), 4.00 (SD ± 0.27), 1.42 (SD ± 2.01) log CFU/g with complete decontamination at 195 s.\u0000 \u0000 \u0000 At 165 and 175 s of RF treatments, the E. faecium loads were reduced to 7.50 (SD ± 0.14) and 6.39 (SD ± 0.31) log CFU/g with complete decontamination at 185 and 195 s.\u0000 \u0000 \u0000 There were no statistically significant changes in the iron, vitamin A, or amino acid responses; sodium levels increased, and potassium and calcium levels decreased due to increasing RF treatment duration.\u0000 \u0000 \u0000 \u0000 \u0000 Abstract. The objectives of this research were: 1) to investigate the efficacy of RF heating on the decontamination of Salmonella enterica and Enterococcus faecium NRRL B-2354 in timothy hay; 2) to evaluate the suitability of E. faecium as a surrogate of Salmonella in timothy hay during RF treatment; 3) to assess the physicochemical changes after RF treatment on vitamins, amino acids, fatty acids, and trace minerals in the timothy hay. A pilot-scale parallel-plate RF heating system (6 kW, 27.12 MHz) was used to conduct this study. The electrode gap in the RF system was adjusted to 205 mm. Timothy hay was procured from a pet food manufacturing plant in Lincoln, Nebraska, at an initial moisture content (MC) of 7% to 9% (wet basis). Timothy hay samples (150 g) were inoculated with either a cocktail containing five serotypes of Salmonella enterica [Salmonella Agona (447967), Salmonella Mbandaka (698538), Salmonella Montevideo (488275), Salmonella Tennessee (K4643), and Salmonella Reading (Moff 180418)] or a broth of Enterococcus faecium then incubated at 37°C for 24 ± 2 h. Timothy hay samples were exposed to RF energy for 165, 175, 185, and 195 s. It was determined that after inoculation with the Salmonella cocktail and E. faecium, timothy hay samples had an initial microbial load of 7.81 and 7.75 log CFU/g, respectively. After RF treatments of 165, 175, 185, and 195 s, Salmonella loads (mean ± SD log CFU/g) were reduced to 5.80 ± 0.24, 4.00 ± 0.27, 1.42 ± 2.01 log CFU/g and below the level of detection, respectively. At 165 and 175 s of RF treatments, the E. faecium loads (mean ± SD log CFU/g) were reduced to 7.50 ± 0.14 and 6.39 ± 0.31 log CFU/g and below the detection level at 185 and 195 s. There was complete decontamination at 185 and 195 s. There were no statistically significant changes in the iron, vitamin A, or amino acid responses because of increasing RF treatment duration. The study demonstrated a non-chemical approach to decontaminating Salmonella and Enterococcus faecium from low-moisture foods such as pet foods. Keywords: Decontamination, Enterococcus faecium, Low moisture, Pet food, Radio-frequency, Salmonella, Timothy hay.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135559690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HighlightsMine water irrigation can promote the plant height growth of winter wheat, but inhibit the growth of leaf area.High salinity mine water irrigation will inhibit the growth and development of winter wheat and reduce the yield.Mixed irrigation of mine water and clean water (the ratio is 1:1) is beneficial to the growth of winter wheat.Short-term mine water irrigation will not cause soil salinization.Abstract. There is a serious shortage of irrigation water in the overlapped areas of crop and mineral production in North China. The key to solve the problem is to utilize mine water safely and efficiently. The effects of mine water irrigation (MI), mixed mine water and clean water irrigation (MIMC), rotational mine water and clean water irrigation, irrigated with mine water first, then clean water (RIMC) and clean water irrigation (CK) on winter wheat growth and soil salinity were studied through two years of field trials (2012 to 2014). The results showed that different models of mine water irrigation had no difference in plant height, but had obvious inhibitory effect on leaf area of wheat. Compared with CK, MI increased plant height by 1.0% to 3.4%, and leaf area was 69.5% to 81.9% of that of CK. Compared with CK, the yield of MIMC was increased by 2.6% to 6.67%, and the yield of RIMC and MI was decreased by 3.4% to 21.1% and 10.4% to 11.2%, respectively. The MI with high salinity could inhibit the growth and development of winter wheat, and reduce the yield and quality, while the yield of MIMC was higher than that of CK, and could improve the quality of winter wheat. Long-term irrigation of using mine water with high salinity will increase the risk of soil salinization, but MIMC can improve soil fertility. Keywords: Growth, Irrigation, Mine water, Soil salinity, Winter wheat.
{"title":"Effects of Mine Water Irrigation on Soil Salinity and Winter Wheat Growth","authors":"Zhixi Huang, Baoguo Ma, Jian Wang, Liang Liu, Ying Zhao, Z. Xi, Shuanwang Qi, Shihao Song, Ronghao Guan","doi":"10.13031/aea.14841","DOIUrl":"https://doi.org/10.13031/aea.14841","url":null,"abstract":"HighlightsMine water irrigation can promote the plant height growth of winter wheat, but inhibit the growth of leaf area.High salinity mine water irrigation will inhibit the growth and development of winter wheat and reduce the yield.Mixed irrigation of mine water and clean water (the ratio is 1:1) is beneficial to the growth of winter wheat.Short-term mine water irrigation will not cause soil salinization.Abstract. There is a serious shortage of irrigation water in the overlapped areas of crop and mineral production in North China. The key to solve the problem is to utilize mine water safely and efficiently. The effects of mine water irrigation (MI), mixed mine water and clean water irrigation (MIMC), rotational mine water and clean water irrigation, irrigated with mine water first, then clean water (RIMC) and clean water irrigation (CK) on winter wheat growth and soil salinity were studied through two years of field trials (2012 to 2014). The results showed that different models of mine water irrigation had no difference in plant height, but had obvious inhibitory effect on leaf area of wheat. Compared with CK, MI increased plant height by 1.0% to 3.4%, and leaf area was 69.5% to 81.9% of that of CK. Compared with CK, the yield of MIMC was increased by 2.6% to 6.67%, and the yield of RIMC and MI was decreased by 3.4% to 21.1% and 10.4% to 11.2%, respectively. The MI with high salinity could inhibit the growth and development of winter wheat, and reduce the yield and quality, while the yield of MIMC was higher than that of CK, and could improve the quality of winter wheat. Long-term irrigation of using mine water with high salinity will increase the risk of soil salinization, but MIMC can improve soil fertility. Keywords: Growth, Irrigation, Mine water, Soil salinity, Winter wheat.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67050304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhihong Zhang, Zhaoyang Chen, Qinghui Lai, H. Guler, Liangliang Zhao, Le Yang
Highlights An alternative bioinspired perspective that focuses on analogous geometrical features of soil animals was proposed. Reverse-engineering technique was adopted to build the virtual prototype of mini-rotavator’s blades. EDEM investigation along with soil bin experiment were conducted to evaluate blades’ performance and reveal the soil-blades interaction mechanism. The tillage tools designed by convergent evolution-inspired approach could increase their availability in underdeveloped hilly and mountainous areas. Abstract. High resistance torque and energy consumption severely limit the applications of mini rotavators in underdeveloped hilly and mountainous areas. From the perspective of convergent evolution, this study proposes an alternative optimization approach that takes a broader perspective and focuses on analogous structures of soil animal claws that serve the functions of efficient soil burrowing. Experimental investigations were carried out to test the hypothesis that serrated structures with certain geometrical parameters could have the potential of reducing penetrating resistance and improving energy efficiency of rotary soil-engaging component. By taking mini rotavator’s blade as the research object, the convergent evolution inspired serrated structures were utilized for the design of the blade’s front, side and transition cutting edge. In this investigation, five types bioinspired mini rotavator’s blades were designed and prepared, then their performances were compared with the conventional blade. By taking the length of serrated unit, rotational speed and tilling depth as experimental factors, and the resistance torque as experimental index, quadratic regression rotation orthogonal combination test was conducted. Then, the optimal parameters for the design of bionic blade were determined. Further, the performance of mini rotavator assembled with bionic and conventional blades were evaluated by EDEM. The mechanism of bionic blades for reducing resistance and improving tillage efficiency was investigated. Soil bin experiments indicated that the optimal parameters combination was length of serrated unit of 30 mm, the speed of 165 r/min, and tilling depth of 90 mm. At this condition, the average torque for bionic and conventional blade was 2.97 and 3.82 N·m, respectively. The bioinspired serrated structure reduced resistance torque by 22.25%. To further investigate the interaction behavior between soil and different types of blades, the reverse-engineering technique was used to extract the geometric characteristics and build virtual prototypes of the bionic and conventional blades. Then, the virtual prototypes of blades was meshed with tetrahedral elements. Simulation model was established based on EDEM. The variation behavior of resistance torque and three-dimensional forces of the two types of blades were analyzed. As expected, the simulation results showed that the average torque of the bionic
{"title":"Preliminary Investigation of Convergent Evolution-Inspired Serrated Structure for Optimization of Mini Rotavator Blade’s Cutting-Edge","authors":"Zhihong Zhang, Zhaoyang Chen, Qinghui Lai, H. Guler, Liangliang Zhao, Le Yang","doi":"10.13031/aea.15151","DOIUrl":"https://doi.org/10.13031/aea.15151","url":null,"abstract":"Highlights An alternative bioinspired perspective that focuses on analogous geometrical features of soil animals was proposed. Reverse-engineering technique was adopted to build the virtual prototype of mini-rotavator’s blades. EDEM investigation along with soil bin experiment were conducted to evaluate blades’ performance and reveal the soil-blades interaction mechanism. The tillage tools designed by convergent evolution-inspired approach could increase their availability in underdeveloped hilly and mountainous areas. Abstract. High resistance torque and energy consumption severely limit the applications of mini rotavators in underdeveloped hilly and mountainous areas. From the perspective of convergent evolution, this study proposes an alternative optimization approach that takes a broader perspective and focuses on analogous structures of soil animal claws that serve the functions of efficient soil burrowing. Experimental investigations were carried out to test the hypothesis that serrated structures with certain geometrical parameters could have the potential of reducing penetrating resistance and improving energy efficiency of rotary soil-engaging component. By taking mini rotavator’s blade as the research object, the convergent evolution inspired serrated structures were utilized for the design of the blade’s front, side and transition cutting edge. In this investigation, five types bioinspired mini rotavator’s blades were designed and prepared, then their performances were compared with the conventional blade. By taking the length of serrated unit, rotational speed and tilling depth as experimental factors, and the resistance torque as experimental index, quadratic regression rotation orthogonal combination test was conducted. Then, the optimal parameters for the design of bionic blade were determined. Further, the performance of mini rotavator assembled with bionic and conventional blades were evaluated by EDEM. The mechanism of bionic blades for reducing resistance and improving tillage efficiency was investigated. Soil bin experiments indicated that the optimal parameters combination was length of serrated unit of 30 mm, the speed of 165 r/min, and tilling depth of 90 mm. At this condition, the average torque for bionic and conventional blade was 2.97 and 3.82 N·m, respectively. The bioinspired serrated structure reduced resistance torque by 22.25%. To further investigate the interaction behavior between soil and different types of blades, the reverse-engineering technique was used to extract the geometric characteristics and build virtual prototypes of the bionic and conventional blades. Then, the virtual prototypes of blades was meshed with tetrahedral elements. Simulation model was established based on EDEM. The variation behavior of resistance torque and three-dimensional forces of the two types of blades were analyzed. As expected, the simulation results showed that the average torque of the bionic ","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67051885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号