HighlightsSeed roll density is dynamic and affected by the seed finger partition angle.At low and medium pressures, the system improved energy consumption, gin turn-out, and fiber quality.At low and medium pressures, the system improved energy consumption, gin turn-out, and fiberAbstract. Previously, we reported a prototype system whereby the position of the seed fingers in a saw gin could be adjusted continuously to affect the amount of residual lint on the ginned seed and provide more fiber (increased gin turn-out). The system combines partitioned seed fingers pivoted on a shaft that are controlled by electric actuators able to adjust the angular position of each seed finger partition according to the load exerted by the seed roll. That previous work noted that as the seed finger angle and load on the seed roll were increased, more residual lint was removed. Initial tests showed differences of up to 1.4% less residual lint with no impact on seed damage after the seed finger angle of the partitions was increased (in unison) to the maximum value. Following those findings, a dynamic feedback mechanism for automatically adjusting the seed finger partitions according to a relationship between the load applied by the seed roll and the seed finger angle was developed. In this article, we describe preliminary tests of the automatic mode (auto mode), i.e., the application of auto-modulating low (6°), medium (12°), and high (18°) loads to the seed roll in a commercial saw gin during seasonal production. The resulting effects on residual lint (turn-out), seed damage, and fiber quality in each mode were measured. The best results in terms of energy savings, reduced residual fiber on the ginned seed, seed damage, fiber length, and color grade were found when low (6°) to medium (12°) loads were applied across the seed roll. Keywords: Automation, Cotton, Ginning, Load sensor, Roll box, Seed finger, Seed roll.
{"title":"Field Trials of a Self-Adjusting Seed Finger System to Improve Gin Turn-Out and Fiber Properties","authors":"A. Krajewski, S. Gordon, David Fox","doi":"10.13031/trans.14489","DOIUrl":"https://doi.org/10.13031/trans.14489","url":null,"abstract":"HighlightsSeed roll density is dynamic and affected by the seed finger partition angle.At low and medium pressures, the system improved energy consumption, gin turn-out, and fiber quality.At low and medium pressures, the system improved energy consumption, gin turn-out, and fiberAbstract. Previously, we reported a prototype system whereby the position of the seed fingers in a saw gin could be adjusted continuously to affect the amount of residual lint on the ginned seed and provide more fiber (increased gin turn-out). The system combines partitioned seed fingers pivoted on a shaft that are controlled by electric actuators able to adjust the angular position of each seed finger partition according to the load exerted by the seed roll. That previous work noted that as the seed finger angle and load on the seed roll were increased, more residual lint was removed. Initial tests showed differences of up to 1.4% less residual lint with no impact on seed damage after the seed finger angle of the partitions was increased (in unison) to the maximum value. Following those findings, a dynamic feedback mechanism for automatically adjusting the seed finger partitions according to a relationship between the load applied by the seed roll and the seed finger angle was developed. In this article, we describe preliminary tests of the automatic mode (auto mode), i.e., the application of auto-modulating low (6°), medium (12°), and high (18°) loads to the seed roll in a commercial saw gin during seasonal production. The resulting effects on residual lint (turn-out), seed damage, and fiber quality in each mode were measured. The best results in terms of energy savings, reduced residual fiber on the ginned seed, seed damage, fiber length, and color grade were found when low (6°) to medium (12°) loads were applied across the seed roll. Keywords: Automation, Cotton, Ginning, Load sensor, Roll box, Seed finger, Seed roll.","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"32 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90822906","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}
HighlightsA non-destructive, in situ, and low-cost root phenotyping system was developed.The system can collect color images and 3D cloud points of corn roots in soil.When tested in a greenhouse, the scanning process did not cause significant disturbance of corn plants.The results showed significant differences in root growth for different watering treatments and growth stages.Abstract. Plant root phenotyping technologies play an important role in breeding, plant protection, and other plant science research projects. Root phenotyping researchers urgently need technologies that are low-cost, in situ, non-destructive to roots, and suitable for the natural soil environment. Many recently developed root phenotyping methods, such as minirhizotron, X-CT, and MRI scanners, have unique advantages in observing plant roots, but they also have disadvantages and cannot meet all the critical requirements simultaneously. This study focused on the development of a new plant root phenotyping robot, called MISIRoot, that is minimally invasive and works in situ in natural soil. The MISIRoot system mainly consists of an industrial-level robotic arm, a miniature camera with lighting, a plant pot holding platform, and image processing software for root recognition and feature extraction. MISIRoot can acquire high-resolution color images of roots in soil with minimal disturbance to the roots and measure the roots’ three-dimensional (3D) structure with an accuracy of 0.1 mm. In tests, well-watered and drought-stressed groups of corn plants were measured with MISIRoot at the V3, V4, and V5 growth stages. The system successfully acquired RGB color images of the roots and 3D point cloud data containing the locations of the detected roots. The plants measured with MISIRoot and the plants not measured (control) were carefully compared with the results from a hyperspectral imaging facility (reference). No significant differences were found between the two groups of plants at different growth stages. Keywords: 3D point cloud, Low-cost phenotyping, Minimally invasive root measurement, Plant root phenotyping, Robotic arm application, Root imaging.
{"title":"MISIRoot: A Robotic, Minimally Invasive, in Situ Imaging System for Plant Root Phenotyping","authors":"W. Qiu, Jian Jin","doi":"10.13031/trans.14306","DOIUrl":"https://doi.org/10.13031/trans.14306","url":null,"abstract":"HighlightsA non-destructive, in situ, and low-cost root phenotyping system was developed.The system can collect color images and 3D cloud points of corn roots in soil.When tested in a greenhouse, the scanning process did not cause significant disturbance of corn plants.The results showed significant differences in root growth for different watering treatments and growth stages.Abstract. Plant root phenotyping technologies play an important role in breeding, plant protection, and other plant science research projects. Root phenotyping researchers urgently need technologies that are low-cost, in situ, non-destructive to roots, and suitable for the natural soil environment. Many recently developed root phenotyping methods, such as minirhizotron, X-CT, and MRI scanners, have unique advantages in observing plant roots, but they also have disadvantages and cannot meet all the critical requirements simultaneously. This study focused on the development of a new plant root phenotyping robot, called MISIRoot, that is minimally invasive and works in situ in natural soil. The MISIRoot system mainly consists of an industrial-level robotic arm, a miniature camera with lighting, a plant pot holding platform, and image processing software for root recognition and feature extraction. MISIRoot can acquire high-resolution color images of roots in soil with minimal disturbance to the roots and measure the roots’ three-dimensional (3D) structure with an accuracy of 0.1 mm. In tests, well-watered and drought-stressed groups of corn plants were measured with MISIRoot at the V3, V4, and V5 growth stages. The system successfully acquired RGB color images of the roots and 3D point cloud data containing the locations of the detected roots. The plants measured with MISIRoot and the plants not measured (control) were carefully compared with the results from a hyperspectral imaging facility (reference). No significant differences were found between the two groups of plants at different growth stages. Keywords: 3D point cloud, Low-cost phenotyping, Minimally invasive root measurement, Plant root phenotyping, Robotic arm application, Root imaging.","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"11 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73166862","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}
HighlightsA prototype pneumatic machine used to control the Colorado potato beetle (CPB) had no effect on potato plant growth.Yields in pneumatic treatment plots were comparable to those of control plots treated with a biological insecticide.Pneumatic control of the CPB could be an alternative to reduce reliance on chemical insecticides in potato fields.Abstract. The Colorado potato beetle (CPB), Leptinotarsa decemlineata (Say), is the major insect pest of potato plants. Currently, the most effective method for controlling the CPB is to apply chemical insecticides throughout its lifecycle. However, the CPB has the ability to resist most chemical insecticides. Control of this insect pest has therefore become extremely difficult, prompting researchers to explore effective alternatives. The use of pneumatic methods to control the CPB is a promising alternative to chemical means. The objective of this study was to develop an effective pneumatic control method for the CPB to reduce the reliance on chemical insecticides in potato fields. In this context, a prototype pneumatic machine was designed and built. The prototype uses positive air pressure to dislodge CPBs from potato foliage, deposit them on the ground between the rows, and crush them. The effects of three airflow velocities (45, 50, and 55 m s-1) and two tractor travel speeds (5 and 6 km h-1) on CPB control, plant growth, and tuber yield were investigated in potato plots. Overall, the results showed no significant differences in yield between treatments (p = 0.3268), indicating that the yield of potato plants treated with the prototype was comparable to that of plants treated with a biological insecticide (Entrust). In addition, the prototype did not have any negative effects on plant growth. This suggests that the prototype could be safely and efficiently used in potato fields to control the CPB. The success of this innovative control method could greatly contribute to reducing the use of chemical insecticides to control the CPB. Keywords: Airflow velocity, Leptinotarsa decemlineata (Say), Pneumatic control, Potato, Travel speed.
一种用于控制科罗拉多马铃薯甲虫(CPB)的气动原型机对马铃薯植株生长没有影响。气动处理地块的产量与用生物杀虫剂处理的对照地块相当。气动控制的CPB可能是减少马铃薯田对化学杀虫剂依赖的一种替代方法。科罗拉多马铃薯甲虫(CPB)， Leptinotarsa decemlineata (Say)，是马铃薯植物的主要害虫。目前，控制CPB最有效的方法是在其整个生命周期内施用化学杀虫剂。然而，CPB具有抵抗大多数化学杀虫剂的能力。因此，控制这种害虫变得极其困难，促使研究人员探索有效的替代方法。使用气动方法来控制CPB是一种有前途的替代化学手段。本研究的目的是开发一种有效的气动控制方法，以减少马铃薯田对化学杀虫剂的依赖。在此背景下，设计并制造了一台原型气动机。该原型机利用正气压将cpb从马铃薯叶片中移除，将它们放置在一排排之间的地面上，然后将它们粉碎。研究了3种风速(45、50和55 m s-1)和2种拖拉机行驶速度(5和6 km h-1)对马铃薯地CPB防治、植株生长和块茎产量的影响。综上所述，不同处理间产量差异不显著(p = 0.3268)，说明该样品处理的马铃薯产量与生物杀虫剂(委托)处理的马铃薯产量相当。此外，该原型对植物生长没有任何负面影响。这表明该原型可以安全有效地用于马铃薯田控制CPB。这种创新控制方法的成功将大大有助于减少化学杀虫剂的使用来控制CPB。关键词:气流速度，细麻，气动控制，马铃薯，行进速度
{"title":"Effects of a Prototype Pneumatic Machine to Control the Colorado Potato Beetle on Potato Plant Growth and Tuber Yield","authors":"Saad Almady, M. Khelifi","doi":"10.13031/trans.14734","DOIUrl":"https://doi.org/10.13031/trans.14734","url":null,"abstract":"HighlightsA prototype pneumatic machine used to control the Colorado potato beetle (CPB) had no effect on potato plant growth.Yields in pneumatic treatment plots were comparable to those of control plots treated with a biological insecticide.Pneumatic control of the CPB could be an alternative to reduce reliance on chemical insecticides in potato fields.Abstract. The Colorado potato beetle (CPB), Leptinotarsa decemlineata (Say), is the major insect pest of potato plants. Currently, the most effective method for controlling the CPB is to apply chemical insecticides throughout its lifecycle. However, the CPB has the ability to resist most chemical insecticides. Control of this insect pest has therefore become extremely difficult, prompting researchers to explore effective alternatives. The use of pneumatic methods to control the CPB is a promising alternative to chemical means. The objective of this study was to develop an effective pneumatic control method for the CPB to reduce the reliance on chemical insecticides in potato fields. In this context, a prototype pneumatic machine was designed and built. The prototype uses positive air pressure to dislodge CPBs from potato foliage, deposit them on the ground between the rows, and crush them. The effects of three airflow velocities (45, 50, and 55 m s-1) and two tractor travel speeds (5 and 6 km h-1) on CPB control, plant growth, and tuber yield were investigated in potato plots. Overall, the results showed no significant differences in yield between treatments (p = 0.3268), indicating that the yield of potato plants treated with the prototype was comparable to that of plants treated with a biological insecticide (Entrust). In addition, the prototype did not have any negative effects on plant growth. This suggests that the prototype could be safely and efficiently used in potato fields to control the CPB. The success of this innovative control method could greatly contribute to reducing the use of chemical insecticides to control the CPB. Keywords: Airflow velocity, Leptinotarsa decemlineata (Say), Pneumatic control, Potato, Travel speed.","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"47 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77244240","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. Rotz, S. Asem-Hiablie, E. Cortus, M. Spiehs, S. Rahman, A. Stoner
Highlights The Integrated Farm System Model appropriately represented average emission rates measured in corn production. Compared to the use of feedlot manure, application of bedded pack manure generally increased N and P losses. Compared to inorganic fertilizer use, cattle manure increased soluble P loss while reducing GHG emission. Production and environmental differences among production systems were similar under recent and future climate. Nitrogen (N), phosphorus (P) and carbon (C) emissions from livestock systems have become important regional, national, and international concerns. Our objective was to use process-level simulation to explore differences among manure and inorganic fertilizer treatments in a corn production system used to feed finishing cattle in the Northern Plains region of the United States. Our analysis included model assessment, simulation to compare treatments under recent climate and comparisons using projected mid-century climate. The Integrated Farm System Model was evaluated in representing the performance and nutrient losses of corn production using cattle manure without bedding, manure with bedding, urea, and no fertilization treatments. Two-year field experiments conducted near Clay Center, NE; Brookings, SD; and Fargo, ND provided observed emission data following these treatments. Means of simulated emission rates of methane, ammonia, and nitrous oxide were generally similar to those observed from field-applied manure or urea fertilizer. Simulation of corn production systems over 25 years of recent climate showed greater soluble P runoff with use of feedlot and bedded manure compared to use of inorganic fertilizers, but life-cycle fossil energy use and greenhouse gas emission were decreased. Compared to feedlot manure, application of bedded pack manure generally increased N and P losses in corn production by retaining more N in manure removed from a bedded housing facility and through increased runoff because a large portion of the stover was removed from the cornfield for use as bedding material. Simulation of these treatments using projected mid-century climate indicated a trend toward a small increase in simulated grain production in the Dakotas with a small decrease for irrigated corn in Nebraska. Climate differences affected the three production systems similarly, so production and environmental impact differences among the fertilization systems under future climate were similar to those obtained under recent climate.
{"title":"An Environmental Assessment of Cattle Manure and Urea Fertilizer Treatments for Corn Production in the Northern Great Plains","authors":"C. Rotz, S. Asem-Hiablie, E. Cortus, M. Spiehs, S. Rahman, A. Stoner","doi":"10.13031/TRANS.14275","DOIUrl":"https://doi.org/10.13031/TRANS.14275","url":null,"abstract":"Highlights The Integrated Farm System Model appropriately represented average emission rates measured in corn production. Compared to the use of feedlot manure, application of bedded pack manure generally increased N and P losses. Compared to inorganic fertilizer use, cattle manure increased soluble P loss while reducing GHG emission. Production and environmental differences among production systems were similar under recent and future climate. Nitrogen (N), phosphorus (P) and carbon (C) emissions from livestock systems have become important regional, national, and international concerns. Our objective was to use process-level simulation to explore differences among manure and inorganic fertilizer treatments in a corn production system used to feed finishing cattle in the Northern Plains region of the United States. Our analysis included model assessment, simulation to compare treatments under recent climate and comparisons using projected mid-century climate. The Integrated Farm System Model was evaluated in representing the performance and nutrient losses of corn production using cattle manure without bedding, manure with bedding, urea, and no fertilization treatments. Two-year field experiments conducted near Clay Center, NE; Brookings, SD; and Fargo, ND provided observed emission data following these treatments. Means of simulated emission rates of methane, ammonia, and nitrous oxide were generally similar to those observed from field-applied manure or urea fertilizer. Simulation of corn production systems over 25 years of recent climate showed greater soluble P runoff with use of feedlot and bedded manure compared to use of inorganic fertilizers, but life-cycle fossil energy use and greenhouse gas emission were decreased. Compared to feedlot manure, application of bedded pack manure generally increased N and P losses in corn production by retaining more N in manure removed from a bedded housing facility and through increased runoff because a large portion of the stover was removed from the cornfield for use as bedding material. Simulation of these treatments using projected mid-century climate indicated a trend toward a small increase in simulated grain production in the Dakotas with a small decrease for irrigated corn in Nebraska. Climate differences affected the three production systems similarly, so production and environmental impact differences among the fertilization systems under future climate were similar to those obtained under recent climate.","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"27 1","pages":"0"},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89379463","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}
Jiayao Chen, Ying Wang, Dongtai Liang, Wenhao Xu, Yang Chen
HighlightsA spring buffering system was added to a longitudinal vibration picking mechanism for berry shrub fruits.Vibration models of the picking part and side branch were established to obtain the vibration relationship.Blueberry picking experiments were conducted to verify the performance of the picking mechanism.Abstract. Current berry shrub picking mechanisms are generally rigid structures, which can easily cause the mechanism to jam and produce rigid impacts, damaging the berry shrub branches. In view of this situation, a longitudinal vibratory picking mechanism for berry shrub fruits is proposed in this study with a spring system added to provide a buffering effect. Vibration models were established for the picking part and for the berry shrub side branch, and analysis was performed to obtain the vibration relationships. Using blueberry as an example, suitable parameters were determined through calculation and then used in blueberry picking experiments with a prototype of the picking mechanism. The experiments verified that the vibration frequency calculated with the vibration relationships can meet the requirements for picking, and the performance of the longitudinal vibratory picking mechanism for berry shrub fruits was verified. Keywords: Berry shrub picking, Buffer, Longitudinal vibration, Vibration analysis.
{"title":"Design of a Buffered Longitudinal Vibratory Picking Mechanism for Berry Shrub Fruits","authors":"Jiayao Chen, Ying Wang, Dongtai Liang, Wenhao Xu, Yang Chen","doi":"10.13031/trans.14119","DOIUrl":"https://doi.org/10.13031/trans.14119","url":null,"abstract":"HighlightsA spring buffering system was added to a longitudinal vibration picking mechanism for berry shrub fruits.Vibration models of the picking part and side branch were established to obtain the vibration relationship.Blueberry picking experiments were conducted to verify the performance of the picking mechanism.Abstract. Current berry shrub picking mechanisms are generally rigid structures, which can easily cause the mechanism to jam and produce rigid impacts, damaging the berry shrub branches. In view of this situation, a longitudinal vibratory picking mechanism for berry shrub fruits is proposed in this study with a spring system added to provide a buffering effect. Vibration models were established for the picking part and for the berry shrub side branch, and analysis was performed to obtain the vibration relationships. Using blueberry as an example, suitable parameters were determined through calculation and then used in blueberry picking experiments with a prototype of the picking mechanism. The experiments verified that the vibration frequency calculated with the vibration relationships can meet the requirements for picking, and the performance of the longitudinal vibratory picking mechanism for berry shrub fruits was verified. Keywords: Berry shrub picking, Buffer, Longitudinal vibration, Vibration analysis.","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"14 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82562257","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}
HighlightsParticulate matter (PM) data were analyzed to identify PM emission characteristics among different animal types.The PM concentrations were higher in broiler chicken and swine farrowing houses and were higher in winter.The PM emissions were also higher in broiler chicken houses and swine farrowing rooms.The PM in the layer chicken house in Indiana had narrower distributions with a greater percentage of smaller particles.Abstract. Understanding the characteristics of particulate matter (PM) emissions from animal feeding operations (AFOs) is essential to address the associated health and environmental impacts and to develop control strategies to mitigate such impacts. This article reports a study of PM concentrations and emission characteristics from 26 poultry and swine production houses to investigate the similarities and differences in PM emission characteristics, e.g., concentrations, emission rates, and particle size distribution (PSD), among different animal and housing types. Concentration and emission data for PM2.5, PM10, and total suspended particulates (TSP) collected by the National Air Emission Monitoring Study (NAEMS) were used to compare the differences among different production practices and animal types. The PSDs of the PM were examined based on the PM2.5/PM10 and PM10/TSP emission rate ratios. It was discovered that the concentrations of PM varied among animal types. For poultry, the concentrations of PM were higher in broiler houses than in other poultry houses. For swine, the average concentrations of PM were higher in farrowing rooms than in swine barns. Moreover, the PM concentrations in poultry and swine houses exhibited significant seasonal trends, with higher concentrations in winter and lower concentrations in summer, which were in a reverse relationship with ventilation rates. The PM emissions also varied among animal types. For poultry, the PM emissions were significantly higher for poultry production houses in California. For swine, the PM emissions were significantly higher for farrowing rooms than other swine houses. The PSD of PM varied among animal types, with mass median diameters (MMD) in the ranges of 6.51 to 13.62 µm for poultry houses and 7.94 to 17.19 µm for swine houses. The geometric standard deviations (GSD) were in the ranges of 1.66 to 2.71 and 1.65 to 2.9 for poultry and swine PM, respectively. The PM in the layer house in Indiana had a narrower distribution (smaller GSD) with a greater percentage of smaller particles than the other poultry houses, while the PM in the broiler house in California had a broader distribution (larger GSD) than the other poultry houses. For swine, the PM in the sow barn in North Carolina had a narrower distribution (smaller GSD) than the other swine houses, while the PM in the farrowing houses in Oklahoma had a broader distribution (larger GSD) than the other swine houses. The knowledge gained from this research may provide insights for addressing the PM emissions f
{"title":"Characteristics of Particulate Matter Emissions from Swine and Poultry Production Houses in the United States","authors":"Fei Hu, Bin Cheng, Lingjuan Wang-Li","doi":"10.13031/trans.14622","DOIUrl":"https://doi.org/10.13031/trans.14622","url":null,"abstract":"HighlightsParticulate matter (PM) data were analyzed to identify PM emission characteristics among different animal types.The PM concentrations were higher in broiler chicken and swine farrowing houses and were higher in winter.The PM emissions were also higher in broiler chicken houses and swine farrowing rooms.The PM in the layer chicken house in Indiana had narrower distributions with a greater percentage of smaller particles.Abstract. Understanding the characteristics of particulate matter (PM) emissions from animal feeding operations (AFOs) is essential to address the associated health and environmental impacts and to develop control strategies to mitigate such impacts. This article reports a study of PM concentrations and emission characteristics from 26 poultry and swine production houses to investigate the similarities and differences in PM emission characteristics, e.g., concentrations, emission rates, and particle size distribution (PSD), among different animal and housing types. Concentration and emission data for PM2.5, PM10, and total suspended particulates (TSP) collected by the National Air Emission Monitoring Study (NAEMS) were used to compare the differences among different production practices and animal types. The PSDs of the PM were examined based on the PM2.5/PM10 and PM10/TSP emission rate ratios. It was discovered that the concentrations of PM varied among animal types. For poultry, the concentrations of PM were higher in broiler houses than in other poultry houses. For swine, the average concentrations of PM were higher in farrowing rooms than in swine barns. Moreover, the PM concentrations in poultry and swine houses exhibited significant seasonal trends, with higher concentrations in winter and lower concentrations in summer, which were in a reverse relationship with ventilation rates. The PM emissions also varied among animal types. For poultry, the PM emissions were significantly higher for poultry production houses in California. For swine, the PM emissions were significantly higher for farrowing rooms than other swine houses. The PSD of PM varied among animal types, with mass median diameters (MMD) in the ranges of 6.51 to 13.62 µm for poultry houses and 7.94 to 17.19 µm for swine houses. The geometric standard deviations (GSD) were in the ranges of 1.66 to 2.71 and 1.65 to 2.9 for poultry and swine PM, respectively. The PM in the layer house in Indiana had a narrower distribution (smaller GSD) with a greater percentage of smaller particles than the other poultry houses, while the PM in the broiler house in California had a broader distribution (larger GSD) than the other poultry houses. For swine, the PM in the sow barn in North Carolina had a narrower distribution (smaller GSD) than the other swine houses, while the PM in the farrowing houses in Oklahoma had a broader distribution (larger GSD) than the other swine houses. The knowledge gained from this research may provide insights for addressing the PM emissions f","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"2016 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86589065","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}
HighlightsWhile freshness is a critical value of food quality, its assessment requires complex methods, which are costly and time-consuming.In this work, it is demonstrated that spectral responses obtained from a portable VIS/NIR imaging spectrometer can be used to predict food freshness using a CNN-based machine learning algorithm.In the food industry, the method can assess real-time food freshness nondestructively and cost-effectively.Abstract. There has been strong demand for the development of accurate but simple methods to assess the freshness of foods. In this study, a system is proposed to determine the freshness of fish by analyzing the spectral response with a portable visible/near-infrared (VIS/NIR) imaging spectrometer and a convolution neural network (CNN) machine learning algorithm. Spectral response data from salmon and tuna, which were incubated at 25°C, were obtained every minute for 30 h and were categorized into three stages (fresh, likely spoiled, or spoiled) based on the time and pH. Using the obtained spectral data, a CNN-based machine learning algorithm was built to evaluate the freshness of the experimental samples. The accuracy of the spectral data in predicting the freshness was ~84% for salmon and ~88% for tuna. Keywords: CNN, Fish, Freshness, pH, Spectral data, VIS/NIR.
{"title":"Non-Destructive Evaluation of Salmon and Tuna Freshness in a Room-Temperature Incubation Environment Using a Portable Visible/Near-Infrared Imaging Spectrometer","authors":"Jinshi Cui, C. Cui","doi":"10.13031/TRANS.13858","DOIUrl":"https://doi.org/10.13031/TRANS.13858","url":null,"abstract":"HighlightsWhile freshness is a critical value of food quality, its assessment requires complex methods, which are costly and time-consuming.In this work, it is demonstrated that spectral responses obtained from a portable VIS/NIR imaging spectrometer can be used to predict food freshness using a CNN-based machine learning algorithm.In the food industry, the method can assess real-time food freshness nondestructively and cost-effectively.Abstract. There has been strong demand for the development of accurate but simple methods to assess the freshness of foods. In this study, a system is proposed to determine the freshness of fish by analyzing the spectral response with a portable visible/near-infrared (VIS/NIR) imaging spectrometer and a convolution neural network (CNN) machine learning algorithm. Spectral response data from salmon and tuna, which were incubated at 25°C, were obtained every minute for 30 h and were categorized into three stages (fresh, likely spoiled, or spoiled) based on the time and pH. Using the obtained spectral data, a CNN-based machine learning algorithm was built to evaluate the freshness of the experimental samples. The accuracy of the spectral data in predicting the freshness was ~84% for salmon and ~88% for tuna. Keywords: CNN, Fish, Freshness, pH, Spectral data, VIS/NIR.","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"34 1","pages":"521-527"},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85422110","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}
Taylor C. Pinkerton, A. Assi, V. Pappa, E. Kan, R. Mohtar
HighlightsQuantitative evaluation was performed of dairy waste on soil water-holding capacity.Considering the soil variability on a farm is significant for management practices.Soil aggregate structure plays a pivotal role in studying the impact of waste reuse.Abstract. The livestock sector contributes about 40% of global agricultural output and uses over 30% of total feed-crop land. The sector’s continuing growth has led to increased technology and larger-scale, commercialized agriculture, and it correlates to growth in by-products and waste, which can compromise the environment and human health. Although organic manure is an excellent soil fertilizer whose nutrient content increases crop yield, untreated and/or overapplied manure pollutes local water resources and can alter soil aggregate structure, potentially affecting soil health and available water. Proper livestock waste management is essential for sustainable food production. Waste reuse strategies exist, with goals such as minimizing freshwater consumption, improving food production, and contributing to energy production, However, each strategy has tradeoffs in environmental, energy, or monetary costs. This study provides a quantitative approach to evaluating waste impact on soil health and helps to better manage irrigation practices and water supply gaps in arid and semi-arid areas by better understanding how management practices affect physical soil health. The TypoSoil apparatus was used to measure and analyze the hydrostructural parameters (water-holding capacity and soil structure) of fine sandy loam (A horizon) and sandy clay (B horizon). Soils from the Texas A&M AgriLife Research Dairy (Stephenville, Texas) were collected and compared with control (untouched) soils. Waste (manure, bedding materials, wash water) was separated into liquid (passed through a natural lagoon treatment process) and solid components (applied as fertilizer). Approximately half the wastewater was reused as wash water, the remainder for irrigation. Although the soil varied substantially between sample locations, a statistically significant difference existed between the control and manure/wastewater applications in both the A and B horizons. Both applications improved plant-available water (AW) in the A horizon (40% and 30%, respectively) but deteriorated AW in the B horizon (25% and 30%). Thus, dairy farm waste is a viable source for agricultural use. Keywords: Available water capacity, Pedostructure, Soil health, Soil shrinkage curve, Soil water characteristic curve.
{"title":"Impact of Dairy Wastewater Irrigation and Manure Application on Soil Structural and Water-Holding Properties","authors":"Taylor C. Pinkerton, A. Assi, V. Pappa, E. Kan, R. Mohtar","doi":"10.13031/TRANS.14351","DOIUrl":"https://doi.org/10.13031/TRANS.14351","url":null,"abstract":"HighlightsQuantitative evaluation was performed of dairy waste on soil water-holding capacity.Considering the soil variability on a farm is significant for management practices.Soil aggregate structure plays a pivotal role in studying the impact of waste reuse.Abstract. The livestock sector contributes about 40% of global agricultural output and uses over 30% of total feed-crop land. The sector’s continuing growth has led to increased technology and larger-scale, commercialized agriculture, and it correlates to growth in by-products and waste, which can compromise the environment and human health. Although organic manure is an excellent soil fertilizer whose nutrient content increases crop yield, untreated and/or overapplied manure pollutes local water resources and can alter soil aggregate structure, potentially affecting soil health and available water. Proper livestock waste management is essential for sustainable food production. Waste reuse strategies exist, with goals such as minimizing freshwater consumption, improving food production, and contributing to energy production, However, each strategy has tradeoffs in environmental, energy, or monetary costs. This study provides a quantitative approach to evaluating waste impact on soil health and helps to better manage irrigation practices and water supply gaps in arid and semi-arid areas by better understanding how management practices affect physical soil health. The TypoSoil apparatus was used to measure and analyze the hydrostructural parameters (water-holding capacity and soil structure) of fine sandy loam (A horizon) and sandy clay (B horizon). Soils from the Texas A&M AgriLife Research Dairy (Stephenville, Texas) were collected and compared with control (untouched) soils. Waste (manure, bedding materials, wash water) was separated into liquid (passed through a natural lagoon treatment process) and solid components (applied as fertilizer). Approximately half the wastewater was reused as wash water, the remainder for irrigation. Although the soil varied substantially between sample locations, a statistically significant difference existed between the control and manure/wastewater applications in both the A and B horizons. Both applications improved plant-available water (AW) in the A horizon (40% and 30%, respectively) but deteriorated AW in the B horizon (25% and 30%). Thus, dairy farm waste is a viable source for agricultural use. Keywords: Available water capacity, Pedostructure, Soil health, Soil shrinkage curve, Soil water characteristic curve.","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85756997","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}
R. Baumhardt, L. Haag, P. Gowda, R. Schwartz, G. Marek, F. Lamm
HighlightsLater planting and greater site elevation or latitude decreased seasonal growing degree days and cotton yield in Kansas.Higher irrigation capacity (rate) usually increased lint yield, which was probably due to increased early boll load.Strategies for splitting land allocations between high irrigation rates and dryland did not increase production.Cotton may reduce irrigation withdrawals from the Ogallala aquifer, but the Kansas growing season limits production.Abstract. Precipitation in the western Great Plains averages about 450 mm, varying little with latitude and providing 40% to 80% of potential crop evapotranspiration (ETc). Supplemental irrigation is required to fully meet crop water demand, but the Ogallala or High Plains aquifer is essentially non-recharging south of Nebraska. Pumping water from this aquifer draws down water tables, leading to reduced water availability and deficit irrigation to produce an alternate crop such as cotton (Gossypium hirsutum L.) with a lower peak water demand than corn (Zea mays L.). Our objective was to compare simulated cotton yield response to emergence date, irrigation capacity, and application period at three western Kansas locations (Colby, Tribune, and Garden City) with varying seasonal energy or cumulative growing degree days (CGDD) and compare split center pivot deficit irrigation strategies with a fixed water supply (i.e., where portions of the center pivot land area are managed with different irrigation strategies). We used actual 1961-2000 location weather records with the GOSSYM simulation model to estimate yields of cotton planted into soil at 50% plant-available water for three emergence dates (DOY 145, 152, and 159) and all combinations of irrigation period (0, 4, 6, 8, and 10 weeks beginning at first square) and capacity (2.5, 3.75, and 5.0 mm d-1). Simulated lint yield and its ratio to ETc, or water use efficiency (WUE), consistently decreased with delayed planting (emergence) as location elevation or latitude increased due to effects on growing season CGDD. Depending on location, simulated cotton lint consistently increased (p = 0.05) for scenarios with increasing irrigation capacity, which promoted greater early season boll load, but not for durations exceeding 4 to 6 weeks, probably because later irrigation and fruiting did not complete maturation during the short growing season. Cotton WUE generally increased, with greater yields resulting from earlier emergence and early high-capacity irrigation. We calculated lower WUE where irrigation promoted vigorous growth with added fruiting forms that delayed maturation and reduced the fraction of open bolls. The irrigation strategy of focusing water at higher capacities on a portion of the center pivot in combination with the dryland balance did not increase net yields significantly at any location because the available seasonal energy limited potential crop growth and yield response to irrigation. However, the overall net lint yield w
在堪萨斯州，较晚的种植和较高的地点海拔或纬度减少了季节性生长日数和棉花产量。较高的灌水量(灌水量)通常能提高皮棉产量，这可能是由于早铃负荷增加所致。在高灌溉率和旱地之间分配土地的策略并没有增加产量。棉花可以减少奥加拉拉含水层的灌溉用水量，但堪萨斯州的生长季节限制了棉花的产量。大平原西部的平均降水量约为450毫米，随纬度变化不大，提供了40%至80%的潜在作物蒸散(ETc)。补充灌溉需要完全满足作物的用水需求，但奥加拉拉或高平原的含水层基本上不补给内布拉斯加州南部。从这一含水层抽水降低了地下水位，导致可用水量减少和灌溉不足，以生产替代作物，如棉花(棉)，其峰值需水量低于玉米(玉米)。我们的目标是比较在堪萨斯州西部的三个地点(Colby、Tribune和Garden City)，模拟棉花产量对出苗期、灌溉能力和施用期的响应，这些地点具有不同的季节能量或累积生长日数(CGDD)，并比较固定供水的分裂中心支点亏缺灌溉策略(即，部分中心支点土地面积采用不同的灌溉策略)。我们使用GOSSYM模拟模型使用1961-2000年的实际地点天气记录来估计在三个出苗期(DOY 145,152和159)和所有灌溉周期(从第一个方形开始的0,4,6,8和10周)和容量(2.5,3.75和5.0 mm d-1)的土壤中种植50%植物有效水分的棉花的产量。由于生长季节CGDD的影响，模拟皮棉产量及其与ETc的比值(WUE)随着种植(出苗期)的推迟而持续下降。在不同的地点，随着灌溉能力的增加，模拟棉绒持续增加(p = 0.05)，这促进了更大的季前铃负荷，但持续时间不超过4 ~ 6周，可能是因为后期灌溉和结果在短生长季节没有完成成熟。棉花水分利用效率普遍提高，出苗期较早，高容量灌溉期较早，产量较高。我们计算了较低的水分利用效率，灌溉促进了旺盛的生长，增加了果实形式，延迟了成熟，减少了开铃的比例。将较高容量的水集中在中心支点部分的灌溉策略与旱地平衡相结合，并没有显著增加任何地点的净产量，因为可用的季节性能源限制了潜在的作物生长和对灌溉的产量响应。然而，在堪萨斯州西南部地区(花园城市)，集中灌溉策略的总体净皮棉产量在数值上较大。基于均匀或分裂中心枢轴亏缺灌溉条件下的棉棉产量模拟，我们得出结论，由于CGDD的生长季节有限，棉花不适合作为堪萨斯州中西部和西北部的替代作物。关键词:棉花，作物模拟，亏缺灌溉，蒸散，灌水量，分流中心灌溉，水分利用效率，产量限制因素
{"title":"Modeling Cotton Growth and Yield Response to Irrigation Practices for Thermally Limited Growing Seasons in Kansas","authors":"R. Baumhardt, L. Haag, P. Gowda, R. Schwartz, G. Marek, F. Lamm","doi":"10.13031/trans.13877","DOIUrl":"https://doi.org/10.13031/trans.13877","url":null,"abstract":"HighlightsLater planting and greater site elevation or latitude decreased seasonal growing degree days and cotton yield in Kansas.Higher irrigation capacity (rate) usually increased lint yield, which was probably due to increased early boll load.Strategies for splitting land allocations between high irrigation rates and dryland did not increase production.Cotton may reduce irrigation withdrawals from the Ogallala aquifer, but the Kansas growing season limits production.Abstract. Precipitation in the western Great Plains averages about 450 mm, varying little with latitude and providing 40% to 80% of potential crop evapotranspiration (ETc). Supplemental irrigation is required to fully meet crop water demand, but the Ogallala or High Plains aquifer is essentially non-recharging south of Nebraska. Pumping water from this aquifer draws down water tables, leading to reduced water availability and deficit irrigation to produce an alternate crop such as cotton (Gossypium hirsutum L.) with a lower peak water demand than corn (Zea mays L.). Our objective was to compare simulated cotton yield response to emergence date, irrigation capacity, and application period at three western Kansas locations (Colby, Tribune, and Garden City) with varying seasonal energy or cumulative growing degree days (CGDD) and compare split center pivot deficit irrigation strategies with a fixed water supply (i.e., where portions of the center pivot land area are managed with different irrigation strategies). We used actual 1961-2000 location weather records with the GOSSYM simulation model to estimate yields of cotton planted into soil at 50% plant-available water for three emergence dates (DOY 145, 152, and 159) and all combinations of irrigation period (0, 4, 6, 8, and 10 weeks beginning at first square) and capacity (2.5, 3.75, and 5.0 mm d-1). Simulated lint yield and its ratio to ETc, or water use efficiency (WUE), consistently decreased with delayed planting (emergence) as location elevation or latitude increased due to effects on growing season CGDD. Depending on location, simulated cotton lint consistently increased (p = 0.05) for scenarios with increasing irrigation capacity, which promoted greater early season boll load, but not for durations exceeding 4 to 6 weeks, probably because later irrigation and fruiting did not complete maturation during the short growing season. Cotton WUE generally increased, with greater yields resulting from earlier emergence and early high-capacity irrigation. We calculated lower WUE where irrigation promoted vigorous growth with added fruiting forms that delayed maturation and reduced the fraction of open bolls. The irrigation strategy of focusing water at higher capacities on a portion of the center pivot in combination with the dryland balance did not increase net yields significantly at any location because the available seasonal energy limited potential crop growth and yield response to irrigation. However, the overall net lint yield w","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"74 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82470028","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}
HighlightsAn algorithm was developed to process laser sensor data to make more accurate measurements of canopy dimensions.The algorithm isolated individual canopies, removed distortion, and estimated the occluded portions of the dataset.The algorithm reduced measured error by 46% in terms of root mean square error (RMSE).The RMSE was higher for sensor heights below and above a calculated optimal sensor height.Abstract. Laser-guided intelligent spray technology for greenhouse applications requires sensors that can accurately measure plant dimensions. This study proposed a new method to overcome current limitations by introducing a processing algorithm that manipulates the noisy dataset and determines the optimal sensor height to produce better measurements of the canopy width. The processing algorithm involves a combination of registration, clustering, and mirroring. Registration aligns multiple scans of the same scene to improve resolution. Clustering isolates individual plant canopies from the dataset to enable further processing. Mirroring is used to resolve the problems of distortion and occlusion and predict missing information in the dataset. The performance of the processing algorithm was evaluated by calculating the root mean square error (RMSE) in the canopy width measurements. Its results were compared with the measurements reported in earlier research, where there was limited processing of the laser sensor data. The processing algorithm reduced RMSE values by 46% compared to the earlier research, and the largest improvements were seen for objects placed beyond 1.5 m from the sensor. The sensor height was observed to be inversely proportional to the RMSE values. The average RMSE of the processing algorithm was 25 mm, compared to 47 mm in the earlier research when the laser sensor was at a height of 1 m. Another experimental setup was used to test the limits of the relationship between sensor height and algorithm performance while using objects that were more representative of plant canopy shapes. The accuracy of the processing algorithm decreased when the sensor height was either above or below the optimal sensor height, which was derived from calculations made in earlier research. The processing algorithm has potential to improve spray efficiencies. Keywords: Automation, Clustering, LiDAR, Point cloud data processing, Variable-rate spray.
{"title":"Improved Canopy Characterization with Laser Scanning Sensor for Greenhouse Spray Applications","authors":"Uchit Nair, P. Ling, Heping Zhu","doi":"10.13031/TRANS.14290","DOIUrl":"https://doi.org/10.13031/TRANS.14290","url":null,"abstract":"HighlightsAn algorithm was developed to process laser sensor data to make more accurate measurements of canopy dimensions.The algorithm isolated individual canopies, removed distortion, and estimated the occluded portions of the dataset.The algorithm reduced measured error by 46% in terms of root mean square error (RMSE).The RMSE was higher for sensor heights below and above a calculated optimal sensor height.Abstract. Laser-guided intelligent spray technology for greenhouse applications requires sensors that can accurately measure plant dimensions. This study proposed a new method to overcome current limitations by introducing a processing algorithm that manipulates the noisy dataset and determines the optimal sensor height to produce better measurements of the canopy width. The processing algorithm involves a combination of registration, clustering, and mirroring. Registration aligns multiple scans of the same scene to improve resolution. Clustering isolates individual plant canopies from the dataset to enable further processing. Mirroring is used to resolve the problems of distortion and occlusion and predict missing information in the dataset. The performance of the processing algorithm was evaluated by calculating the root mean square error (RMSE) in the canopy width measurements. Its results were compared with the measurements reported in earlier research, where there was limited processing of the laser sensor data. The processing algorithm reduced RMSE values by 46% compared to the earlier research, and the largest improvements were seen for objects placed beyond 1.5 m from the sensor. The sensor height was observed to be inversely proportional to the RMSE values. The average RMSE of the processing algorithm was 25 mm, compared to 47 mm in the earlier research when the laser sensor was at a height of 1 m. Another experimental setup was used to test the limits of the relationship between sensor height and algorithm performance while using objects that were more representative of plant canopy shapes. The accuracy of the processing algorithm decreased when the sensor height was either above or below the optimal sensor height, which was derived from calculations made in earlier research. The processing algorithm has potential to improve spray efficiencies. Keywords: Automation, Clustering, LiDAR, Point cloud data processing, Variable-rate spray.","PeriodicalId":23120,"journal":{"name":"Transactions of the ASABE","volume":"47 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82587903","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}
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