Highlights The research field of supply chain energy management (SCEM) is introduced and applied to the German dairy sector. Changes in farm revenues are quantified, considering electricity sales and remuneration for energy data sharing. Results show that SCEM could become the most relevant driver for increasing energy-related revenues at dairy farms. Abstract. The dairy sector of the German food industry is vital not only for providing nutrition to people but also for promoting environmental responsibility. However, sustainability efforts in the sector must be balanced with profitability goals, and farmers face the challenge of operating profitably while also seeking new, sustainable sources of income. Energy management is one such lever that can help establish sustainable revenue streams for farms. Currently, energy management at dairy farms is mostly limited to the barn's boundaries, and there has been no comprehensive study yet around profit-oriented collaboration on energy management along German dairy supply chains. This lack of collaboration not only hinders revenue growth for dairy farms but also complicates the achievement of sustainability targets, which can negatively impact the sector's public perception. To address this issue, we have applied supply chain energy management (SCEM) as a research field that examines energy-related interdependencies along the dairy supply chain. Our scenario analysis assessing the future revenue change for German dairy farmers through the application of SCEM indicates that it has the potential to become the most relevant driver for increasing energy-related revenues at farms. For example, our studies on a sample farm with 56,950 kWh photovoltaic systems show that it can increase its energy-related revenues by 170% simply by adapting its energy (data) distribution mode in the context of SCEM. Based on these findings, we recommend conducting further studies within the research field of SCEM, which is the aim of the new initiative DairyChainEnergy. Keywords: DairyChainEnergy, Electricity sales, Energy data sharing, Food industry, Income, Profitability, SCEM, Sustainability.
{"title":"Scenario Analysis Indicates Revenue Increase for German Dairy Farmers Through Supply Chain Energy Management","authors":"Theresa Theunissen, H. Bernhardt","doi":"10.13031/ja.15379","DOIUrl":"https://doi.org/10.13031/ja.15379","url":null,"abstract":"Highlights The research field of supply chain energy management (SCEM) is introduced and applied to the German dairy sector. Changes in farm revenues are quantified, considering electricity sales and remuneration for energy data sharing. Results show that SCEM could become the most relevant driver for increasing energy-related revenues at dairy farms. Abstract. The dairy sector of the German food industry is vital not only for providing nutrition to people but also for promoting environmental responsibility. However, sustainability efforts in the sector must be balanced with profitability goals, and farmers face the challenge of operating profitably while also seeking new, sustainable sources of income. Energy management is one such lever that can help establish sustainable revenue streams for farms. Currently, energy management at dairy farms is mostly limited to the barn's boundaries, and there has been no comprehensive study yet around profit-oriented collaboration on energy management along German dairy supply chains. This lack of collaboration not only hinders revenue growth for dairy farms but also complicates the achievement of sustainability targets, which can negatively impact the sector's public perception. To address this issue, we have applied supply chain energy management (SCEM) as a research field that examines energy-related interdependencies along the dairy supply chain. Our scenario analysis assessing the future revenue change for German dairy farmers through the application of SCEM indicates that it has the potential to become the most relevant driver for increasing energy-related revenues at farms. For example, our studies on a sample farm with 56,950 kWh photovoltaic systems show that it can increase its energy-related revenues by 170% simply by adapting its energy (data) distribution mode in the context of SCEM. Based on these findings, we recommend conducting further studies within the research field of SCEM, which is the aim of the new initiative DairyChainEnergy. Keywords: DairyChainEnergy, Electricity sales, Energy data sharing, Food industry, Income, Profitability, SCEM, Sustainability.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"84834938","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 Convective heat transfer in an apple orchard was simulated by Ansys Fluent. The various heating patterns and convective heat transfer coefficients under different heating schemes were obtained. The heating effects of heater output intensity, output velocity, and heating angle were simulated. The heating duration and heat dissipation time were critical for mobile heating. Abstract. Frost events cause high economic losses in agriculture. Frost protection methods, particularly heating, have been implemented in cold-sensitive crops for millennia. Although often effective, traditional heating strategies can be insufficient or wasteful due to a lack of spatial temperature information, resulting in inadequate protection or uneven heating problems. Computational fluid dynamics (CFD) modeling has been widely used to simulate fluid flow, heat, and mass transfer by predicting various processes such as spatial flow velocity, pressure, and temperature distribution within a simulated environment. A three-dimensional CFD model for simulating airflow and heat transfer in an apple orchard was developed and validated, with the effects of heater output intensity and output velocity, heating angle, and heating duration analyzed. The validated model effectively predicted the spatial temperature changes over time inside the canopy for three representative heating schemes (heaters angled 0°, 45°, and 90° toward a tree row) with an average root mean square error (RMSE) of 2.6 °C. The simulated results show that the heating scheme of heaters angled 45° was the most effective, resulting in the largest average percentage of the protected canopy (72.3%), compared with heaters angled 0° (33.1%) and 90° (56.5%). The average percentage of the protected canopy increased by 108.2% when the heater output intensity increased to 477,000 KJ·h-1 and 46.0% when the heater output velocity increased to 15 m·s-1. However, the percentage of the protected canopy showed diminishing returns as the heater output intensity and velocity increased. The simulated heat dissipation time was linearly related to the heating duration, which can be utilized to determine the reheating time for mobile heating. The outcome of the study can be beneficial for making effective frost protection decisions in apple orchards. Keywords: Canopy, Computational fluid dynamics, Frost protection, Heat transfer, Porous media modeling.
{"title":"CFD Simulation of Porous Canopy Heat Transfer in Apple Orchard-Based Frost Protection","authors":"Weiyun Hua, P. Heinemann, Long He, Wenan Yuan","doi":"10.13031/ja.15550","DOIUrl":"https://doi.org/10.13031/ja.15550","url":null,"abstract":"Highlights Convective heat transfer in an apple orchard was simulated by Ansys Fluent. The various heating patterns and convective heat transfer coefficients under different heating schemes were obtained. The heating effects of heater output intensity, output velocity, and heating angle were simulated. The heating duration and heat dissipation time were critical for mobile heating. Abstract. Frost events cause high economic losses in agriculture. Frost protection methods, particularly heating, have been implemented in cold-sensitive crops for millennia. Although often effective, traditional heating strategies can be insufficient or wasteful due to a lack of spatial temperature information, resulting in inadequate protection or uneven heating problems. Computational fluid dynamics (CFD) modeling has been widely used to simulate fluid flow, heat, and mass transfer by predicting various processes such as spatial flow velocity, pressure, and temperature distribution within a simulated environment. A three-dimensional CFD model for simulating airflow and heat transfer in an apple orchard was developed and validated, with the effects of heater output intensity and output velocity, heating angle, and heating duration analyzed. The validated model effectively predicted the spatial temperature changes over time inside the canopy for three representative heating schemes (heaters angled 0°, 45°, and 90° toward a tree row) with an average root mean square error (RMSE) of 2.6 °C. The simulated results show that the heating scheme of heaters angled 45° was the most effective, resulting in the largest average percentage of the protected canopy (72.3%), compared with heaters angled 0° (33.1%) and 90° (56.5%). The average percentage of the protected canopy increased by 108.2% when the heater output intensity increased to 477,000 KJ·h-1 and 46.0% when the heater output velocity increased to 15 m·s-1. However, the percentage of the protected canopy showed diminishing returns as the heater output intensity and velocity increased. The simulated heat dissipation time was linearly related to the heating duration, which can be utilized to determine the reheating time for mobile heating. The outcome of the study can be beneficial for making effective frost protection decisions in apple orchards. Keywords: Canopy, Computational fluid dynamics, Frost protection, Heat transfer, Porous media modeling.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"83977706","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}
Nahndi Tirrell Kirk-Bradley, Tomilayo Grace Salau, Keyan Zhu Salzman, J. Moore
Highlights The exposure of C. maculatus to reactive gas species (RGS) from atmospheric cold plasma treatment (ACP) resulted in significant mortality at all life stages tested. Three-minute ACP treatments at voltages of 70 kV have the best insecticidal effect. The greatest impact of treatment was during the egg and young larval stages of C. maculatus. Abstract. The insecticidal capability and mechanism of high-voltage atmospheric cold plasma were studied using a dielectric barrier discharge reactor against Callosobruchus maculatus, a significant insect pest in stored grain degradation. The mortality rate of > 90.0% for egg and larval stages can be achieved with a longer treatment time of 3 minutes and a higher voltage of 70 kV. However, this treatment condition, paired with a post-treatment retention time of 4 days, is required to kill 95% of adult insects. The use of atmospheric cold plasma has a considerable impact on the mortality of a range of insect life stages. Sufficient toxicity can be achieved by plasma process management using modified atmospheric pressure with a working gas of 65% oxygen, 30% carbon dioxide, and 5% nitrogen to address the insect lifecycle phases that are vectors for pathogens, which can increase mycotoxin contamination and degrade grain quality. Introducing atmospheric cold plasma treatment as an alternative to chemical fumigation may provide a safer alternative for integrated pest management. Keywords: Atmospheric cold plasma (ACP), Cowpea weevil, Dielectric barrier, Insecticidal effect, Integrated pest management (IPM), Pesticide, Reactive gas species (RGS).
{"title":"Atmospheric Cold Plasma (ACP) Treatment for Efficient Disinfestation of the Cowpea Weevil, Callosobruchus maculatus","authors":"Nahndi Tirrell Kirk-Bradley, Tomilayo Grace Salau, Keyan Zhu Salzman, J. Moore","doi":"10.13031/ja.15449","DOIUrl":"https://doi.org/10.13031/ja.15449","url":null,"abstract":"Highlights The exposure of C. maculatus to reactive gas species (RGS) from atmospheric cold plasma treatment (ACP) resulted in significant mortality at all life stages tested. Three-minute ACP treatments at voltages of 70 kV have the best insecticidal effect. The greatest impact of treatment was during the egg and young larval stages of C. maculatus. Abstract. The insecticidal capability and mechanism of high-voltage atmospheric cold plasma were studied using a dielectric barrier discharge reactor against Callosobruchus maculatus, a significant insect pest in stored grain degradation. The mortality rate of > 90.0% for egg and larval stages can be achieved with a longer treatment time of 3 minutes and a higher voltage of 70 kV. However, this treatment condition, paired with a post-treatment retention time of 4 days, is required to kill 95% of adult insects. The use of atmospheric cold plasma has a considerable impact on the mortality of a range of insect life stages. Sufficient toxicity can be achieved by plasma process management using modified atmospheric pressure with a working gas of 65% oxygen, 30% carbon dioxide, and 5% nitrogen to address the insect lifecycle phases that are vectors for pathogens, which can increase mycotoxin contamination and degrade grain quality. Introducing atmospheric cold plasma treatment as an alternative to chemical fumigation may provide a safer alternative for integrated pest management. Keywords: Atmospheric cold plasma (ACP), Cowpea weevil, Dielectric barrier, Insecticidal effect, Integrated pest management (IPM), Pesticide, Reactive gas species (RGS).","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"81737926","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}
Laxmi R. Prasad, Anita M. Thompson, Francisco J. Arriaga, Lydia Koropeckyj-Cox, Yongping Yuan
Highlights No-till and no-till residue systems were effective in reducing runoff particulate and total nutrients but increased dissolved nutrients. Maintaining >30% residue cover reduced most runoff constituents, irrespective of no-till or tillage. No-till-residue prevented runoff nutrient losses and benefitted farm revenue by avoiding tillage. Abstract. Reduced tillage management conservation practices (No-till and Reduced-till) are widely adopted in agriculture; however, understanding their overall effectiveness for water quality protection is challenging. A meta-analysis was conducted to understand and quantify the effectiveness of residue and tillage management on runoff, sediment, and nutrient losses from agricultural fields. Annual runoff and the associated sediment, and nutrient (nitrogen and phosphorus) loads were compiled from 60 peer reviewed research articles published across the United States and Canada. A total of 1575 site-years of data were categorized into tillage (<30% surface cover), no-tillage (<30% surface cover), tillage with residue (>30% surface cover), no-tillage with residue (>30% surface cover), and pasture management. No-tillage, no-tillage-residue, and tillage-residue managements were evaluated for their effectiveness in reducing runoff, nutrients, and sediment loads compared to tillage. Synthesized and surveyed corn yield data were used to evaluate the economic cost effectiveness of no-tillage-residue management with respect to tillage. Across the site years (1968-2019) studied, median runoff depth for no-tillage and no-tillage-residue were 84% and 70% greater than tillage and tillage-residue management, respectively. No-tillage-residue management had up to 86% less sediment losses than tillage systems, on average, for both >30% and <30% surface cover. No-tillage-residue management was most effective, with a positive performance effectiveness of 65% to 90% in controlling sediments, particulate, and total nutrient losses in runoff compared to tillage. Cost effectiveness analysis revealed the benefits of no-tillage-residue management in reducing nutrient loads and increasing net-farm revenue by avoiding tillage operational costs. Except for dissolved phosphorus, no-tillage-residue management cost effectiveness for sediments and nutrient loads ranged from negative $6 to negative $102 per every Mg or kg of load reduction, indicating it had both economic and environmental benefits compared to tillage management. Overall, these results indicate that over the long-term, no-tillage and tillage, combined with greater than 30% residue cover, can effectively reduce sediment and nutrient losses. This work highlights the importance of crop residues on the soil surface to reduce runoff losses, even in no-tillage systems. Keywords: Conservation tillage, No-tillage, Residue cover, Tillage, Water quality.
{"title":"Effectiveness of Residue and Tillage Management on Runoff Pollutant Reduction from Agricultural Areas","authors":"Laxmi R. Prasad, Anita M. Thompson, Francisco J. Arriaga, Lydia Koropeckyj-Cox, Yongping Yuan","doi":"10.13031/ja.15518","DOIUrl":"https://doi.org/10.13031/ja.15518","url":null,"abstract":"Highlights No-till and no-till residue systems were effective in reducing runoff particulate and total nutrients but increased dissolved nutrients. Maintaining &gt;30% residue cover reduced most runoff constituents, irrespective of no-till or tillage. No-till-residue prevented runoff nutrient losses and benefitted farm revenue by avoiding tillage. Abstract. Reduced tillage management conservation practices (No-till and Reduced-till) are widely adopted in agriculture; however, understanding their overall effectiveness for water quality protection is challenging. A meta-analysis was conducted to understand and quantify the effectiveness of residue and tillage management on runoff, sediment, and nutrient losses from agricultural fields. Annual runoff and the associated sediment, and nutrient (nitrogen and phosphorus) loads were compiled from 60 peer reviewed research articles published across the United States and Canada. A total of 1575 site-years of data were categorized into tillage (&lt;30% surface cover), no-tillage (&lt;30% surface cover), tillage with residue (&gt;30% surface cover), no-tillage with residue (&gt;30% surface cover), and pasture management. No-tillage, no-tillage-residue, and tillage-residue managements were evaluated for their effectiveness in reducing runoff, nutrients, and sediment loads compared to tillage. Synthesized and surveyed corn yield data were used to evaluate the economic cost effectiveness of no-tillage-residue management with respect to tillage. Across the site years (1968-2019) studied, median runoff depth for no-tillage and no-tillage-residue were 84% and 70% greater than tillage and tillage-residue management, respectively. No-tillage-residue management had up to 86% less sediment losses than tillage systems, on average, for both &gt;30% and &lt;30% surface cover. No-tillage-residue management was most effective, with a positive performance effectiveness of 65% to 90% in controlling sediments, particulate, and total nutrient losses in runoff compared to tillage. Cost effectiveness analysis revealed the benefits of no-tillage-residue management in reducing nutrient loads and increasing net-farm revenue by avoiding tillage operational costs. Except for dissolved phosphorus, no-tillage-residue management cost effectiveness for sediments and nutrient loads ranged from negative $6 to negative $102 per every Mg or kg of load reduction, indicating it had both economic and environmental benefits compared to tillage management. Overall, these results indicate that over the long-term, no-tillage and tillage, combined with greater than 30% residue cover, can effectively reduce sediment and nutrient losses. This work highlights the importance of crop residues on the soil surface to reduce runoff losses, even in no-tillage systems. Keywords: Conservation tillage, No-tillage, Residue cover, Tillage, Water quality.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"135319905","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}
Xinyang Mu, Magni Hussain, Long He, Paul Heinemann, James Schupp, Manoj Karkee, Minghui Zhu
Highlights A cartesian robotic spraying system was developed for precision apple blossom thinning. Flower clusters were detected and localized with deep learning model for target spraying. A communication algorithm was developed for positioning the spray end-effector to the target flowers. The cartesian robotic system greatly reduced chemical usage while maintaining thinning effectiveness in the final green fruit set. Abstract . Crop thinning, including blossom thinning, is one of the critical management strategies that determines the annual profitability of apple orchards. Challenges still remain for applying appropriate amounts of chemical thinner; if thinning is inadequate and too many fruits remain on the tree, fruit size will be small, fruit quality will be poor, and flower bud initiation for the following year’s crop may be either reduced or eliminated. Over-thinning also carries economic perils since yield and crop value in the year of application will be reduced. In addition, chemical thinning with excessive spray volume may cause leaf damage and fruit russeting. Thus, a robotic apple blossom thinning system was proposed, aiming to reduce the usage of chemical thinner while maintaining good thinning performance. The robotic system consisted of three major components: (1) a machine vision system that can identify and localize the apple flower clusters in tree canopies, (2) a cartesian robotic system with the guidance of a machine vision system to reach target flower clusters, and (3) a flat-shaped spraying nozzle connected with a solenoid valve as a spraying end-effector to deposit chemical thinner to the targeted flower clusters. A set of field tests was conducted to evaluate the performance of the robotic thinning system by comparing it to conventional air-blast and boom-type sprayers. In the test, the flower cluster detection reached a precision of 93.82%. The integrated robotic system used 2.3 L of chemical thinner to finish the chemical thinning for 18 apple trees, followed by the boom sprayer and air blast sprayer with 4.2 and 6.8 L usage, respectively. The robotic system also obtained an average fruit set of 2.4 per cluster after thinning, which was comparable to that of the air blast sprayer. The results showed that the robotic thinning system saved 66.7% and 45.5% of chemicals compared to the air-blast sprayer and boom-typed sprayers, respectively, while achieving a similar fruit set per cluster. The outcomes of the study provided guidance for developing a full-scale robotic chemical thinning system for modern apple orchards. Keywords: Apple orchard, Blossom thinning, Cartesian robot, Chemical thinning, Machine vision.
{"title":"An Advanced Robotic System for Precision Chemical Thinning of Apple Blossoms","authors":"Xinyang Mu, Magni Hussain, Long He, Paul Heinemann, James Schupp, Manoj Karkee, Minghui Zhu","doi":"10.13031/ja.15678","DOIUrl":"https://doi.org/10.13031/ja.15678","url":null,"abstract":"Highlights A cartesian robotic spraying system was developed for precision apple blossom thinning. Flower clusters were detected and localized with deep learning model for target spraying. A communication algorithm was developed for positioning the spray end-effector to the target flowers. The cartesian robotic system greatly reduced chemical usage while maintaining thinning effectiveness in the final green fruit set. Abstract . Crop thinning, including blossom thinning, is one of the critical management strategies that determines the annual profitability of apple orchards. Challenges still remain for applying appropriate amounts of chemical thinner; if thinning is inadequate and too many fruits remain on the tree, fruit size will be small, fruit quality will be poor, and flower bud initiation for the following year’s crop may be either reduced or eliminated. Over-thinning also carries economic perils since yield and crop value in the year of application will be reduced. In addition, chemical thinning with excessive spray volume may cause leaf damage and fruit russeting. Thus, a robotic apple blossom thinning system was proposed, aiming to reduce the usage of chemical thinner while maintaining good thinning performance. The robotic system consisted of three major components: (1) a machine vision system that can identify and localize the apple flower clusters in tree canopies, (2) a cartesian robotic system with the guidance of a machine vision system to reach target flower clusters, and (3) a flat-shaped spraying nozzle connected with a solenoid valve as a spraying end-effector to deposit chemical thinner to the targeted flower clusters. A set of field tests was conducted to evaluate the performance of the robotic thinning system by comparing it to conventional air-blast and boom-type sprayers. In the test, the flower cluster detection reached a precision of 93.82%. The integrated robotic system used 2.3 L of chemical thinner to finish the chemical thinning for 18 apple trees, followed by the boom sprayer and air blast sprayer with 4.2 and 6.8 L usage, respectively. The robotic system also obtained an average fruit set of 2.4 per cluster after thinning, which was comparable to that of the air blast sprayer. The results showed that the robotic thinning system saved 66.7% and 45.5% of chemicals compared to the air-blast sprayer and boom-typed sprayers, respectively, while achieving a similar fruit set per cluster. The outcomes of the study provided guidance for developing a full-scale robotic chemical thinning system for modern apple orchards. Keywords: Apple orchard, Blossom thinning, Cartesian robot, Chemical thinning, Machine vision.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"135600979","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}
Ankit Kumar Singh, Boris Bravo-Ureta, Richard McAvoy, Xiusheng Yang
Highlights Increasing population, demand, and urbanization have increased food security pressures. We compared GREENBOX with a greenhouse for urban crop production. GREENBOX and greenhouse provided the required environmental conditions and comparable biomass output year-round. GREENBOX performance is comparable to a greenhouse for urban crop production but with more advantages. Abstract . The Yang Laboratory at the University of Connecticut has developed the GREENBOX technology for growing fresh produce in urban areas to meet the increasing demand for sustainable and local food production. Previous studies have shown that GREENBOX units can provide the desired environmental conditions to sustain crop production in midlatitude urban warehouse environments. This study was conducted to compare the environmental conditions, productivity, and water consumption for growing lettuce between GREENBOX and a conventional greenhouse that has been widely applied for crop production. Two modular GREENBOX units, equipped with LED lighting, hydroponic growing platform, and climate controls, were located in a high ceiling headhouse of a greenhouse complex to mimic warehouse conditions. We used bays in a nearby greenhouse that was glass glazed, equipped with supplemental lighting, and fully controlled by an Argus Titan control system for comparison purposes. Forty-eight (48) heads of Butterhead Rex lettuce (Lactuca sativa) were grown over four 30-day cycles in spring, summer, fall, and winter in the GREENBOX units and the greenhouse bays, respectively, at the University of Connecticut, Storrs, Connecticut, United States. Environmental variables, including light, temperature, relative humidity, and carbon dioxide concentration, were measured at a frequency of every minute. Biomass data of wet weight, dry weight, total leaf area, and lettuce head area were collected using destructive and non-destructive methods every three days. The water consumption rate was logged using a lysimeter. We derived the Daily Light Integral (DLI), Leaf Area Index (LAI), Specific Leaf Area (SLA), productivity, and water consumed per lettuce head, per unit wet weight, and per unit dry weight from the measurements. Results were analyzed using descriptive statistics and ANOVA. The DLI values in the GREENBOX units were significantly higher than the recommended minimum DLI by over 20 mol/m2.d in the GREENBOX units and over 10 mol/m2.d in the greenhouse bays. The range of the daily temperature variation is only a few degrees in the GREENBOX units, while in the greenhouse bays was over 20°C. The average daily temperature in both growing locations fell within the optimal range of 17-29°C for lettuce. The relative humidity inside both growing locations fell primarily within the optimal range of 40%-60%. The mean CO2 concentrations inside both growing locations were slightly lower than the ambient concentration of 350 ppm. Measured parameters such as LAI, SLA, and productivity followed similar pat
{"title":"GREENBOX Technology II - Comparison of Environmental Conditions, Productivity, and Water Consumption With Greenhouse Operation","authors":"Ankit Kumar Singh, Boris Bravo-Ureta, Richard McAvoy, Xiusheng Yang","doi":"10.13031/ja.15344","DOIUrl":"https://doi.org/10.13031/ja.15344","url":null,"abstract":"Highlights Increasing population, demand, and urbanization have increased food security pressures. We compared GREENBOX with a greenhouse for urban crop production. GREENBOX and greenhouse provided the required environmental conditions and comparable biomass output year-round. GREENBOX performance is comparable to a greenhouse for urban crop production but with more advantages. Abstract . The Yang Laboratory at the University of Connecticut has developed the GREENBOX technology for growing fresh produce in urban areas to meet the increasing demand for sustainable and local food production. Previous studies have shown that GREENBOX units can provide the desired environmental conditions to sustain crop production in midlatitude urban warehouse environments. This study was conducted to compare the environmental conditions, productivity, and water consumption for growing lettuce between GREENBOX and a conventional greenhouse that has been widely applied for crop production. Two modular GREENBOX units, equipped with LED lighting, hydroponic growing platform, and climate controls, were located in a high ceiling headhouse of a greenhouse complex to mimic warehouse conditions. We used bays in a nearby greenhouse that was glass glazed, equipped with supplemental lighting, and fully controlled by an Argus Titan control system for comparison purposes. Forty-eight (48) heads of Butterhead Rex lettuce (Lactuca sativa) were grown over four 30-day cycles in spring, summer, fall, and winter in the GREENBOX units and the greenhouse bays, respectively, at the University of Connecticut, Storrs, Connecticut, United States. Environmental variables, including light, temperature, relative humidity, and carbon dioxide concentration, were measured at a frequency of every minute. Biomass data of wet weight, dry weight, total leaf area, and lettuce head area were collected using destructive and non-destructive methods every three days. The water consumption rate was logged using a lysimeter. We derived the Daily Light Integral (DLI), Leaf Area Index (LAI), Specific Leaf Area (SLA), productivity, and water consumed per lettuce head, per unit wet weight, and per unit dry weight from the measurements. Results were analyzed using descriptive statistics and ANOVA. The DLI values in the GREENBOX units were significantly higher than the recommended minimum DLI by over 20 mol/m2.d in the GREENBOX units and over 10 mol/m2.d in the greenhouse bays. The range of the daily temperature variation is only a few degrees in the GREENBOX units, while in the greenhouse bays was over 20°C. The average daily temperature in both growing locations fell within the optimal range of 17-29°C for lettuce. The relative humidity inside both growing locations fell primarily within the optimal range of 40%-60%. The mean CO2 concentrations inside both growing locations were slightly lower than the ambient concentration of 350 ppm. Measured parameters such as LAI, SLA, and productivity followed similar pat","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"135601268","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}
Alvin Ray Womac, Erdal Ozkan, Heping Zhu, John Kochendorfer, Hongyoung Jeon, Nataraj Eswarachandra
Highlights Wind tunnels were extensively used to study precision applications of agricultural sprays. Use of wind tunnels significantly contributed to the broad-reaching impact of precision applications. Wind tunnels provide controlled conditions to study a plethora of wide ranging spray variables. Abstract. The objective of this study was to review publications that were representative of wind tunnels and their uses to study variables affecting precision applications of agricultural sprays. Precision application involved the deliberate engineering of sprayers for accurate formation and dispersal of droplets and sprays to enhance spray deposits on targeted crop, foliage, or pest for increased agricultural production with reduced adverse effects to neighboring ecology and the environment. Categorical themes of wind tunnel uses were (1) spray atomization, (2) adjuvant effects, (3) spray drift, (4) spray, air movement, crop foliage interactions, (5) UAV applications, (6) airflow around sprayer, and (7) spray test methods and collections. A discovery was that nozzle design had more impact on droplet size than spray formulation, which emphasized the importance of spray nozzle selection for atomization, and that air induction (AI) venturi nozzles consistently provided reduced spray drift potential. On occasion, some adjuvants marketed as drift reduction agents acted in an opposite manner and decreased droplet size. Wind tunnel use for spray drift had the broadest range of variables studied among conceptual applications and included various nozzles, boom height, product active ingredients, adjuvants, and other variables. Deposits decreased in foliage from upper, middle, to lower foliage heights and decreased with increased wind speed. Low wind turbulence in the canopy did not contribute to deposition. Foliage deposition depended more on droplet size and local ambient winds. Canopy porosity limited the droplet size to less than 100 µm for contribution to deposits internal to the foliage. Wind tunnel use for UAV applications was mostly focused on spray drift for UAV variables such as rotor configurations and payload for mounted or tethered UAV. An ultimate recommendation was to use AI nozzles, reduce application speed, and to use a suitable adjuvant – which was similar to other applications. Contrasting results for the impact of airflow around sprays were reported for vortices around fan spray discharge of a nozzle versus a 4-nozzle boom study that found no differences in velocity and turbulence fields due to the presence or no presence of spray discharge. Spray test methods and collections determined in wind tunnels primarily focused on collection efficiencies for a wide range of spray collectors. Collection efficiencies varied with collector and droplet size. Keywords: Keywords.,Boom sprayer,Droplet size,Droplet trajectory,Nozzle classification,Spray deposit,Spray drift,Spray nozzles.
{"title":"Wind Tunnels and Their Uses to Study Variables Affecting Precision Applications of Agricultural Sprays","authors":"Alvin Ray Womac, Erdal Ozkan, Heping Zhu, John Kochendorfer, Hongyoung Jeon, Nataraj Eswarachandra","doi":"10.13031/ja.15622","DOIUrl":"https://doi.org/10.13031/ja.15622","url":null,"abstract":"Highlights Wind tunnels were extensively used to study precision applications of agricultural sprays. Use of wind tunnels significantly contributed to the broad-reaching impact of precision applications. Wind tunnels provide controlled conditions to study a plethora of wide ranging spray variables. Abstract. The objective of this study was to review publications that were representative of wind tunnels and their uses to study variables affecting precision applications of agricultural sprays. Precision application involved the deliberate engineering of sprayers for accurate formation and dispersal of droplets and sprays to enhance spray deposits on targeted crop, foliage, or pest for increased agricultural production with reduced adverse effects to neighboring ecology and the environment. Categorical themes of wind tunnel uses were (1) spray atomization, (2) adjuvant effects, (3) spray drift, (4) spray, air movement, crop foliage interactions, (5) UAV applications, (6) airflow around sprayer, and (7) spray test methods and collections. A discovery was that nozzle design had more impact on droplet size than spray formulation, which emphasized the importance of spray nozzle selection for atomization, and that air induction (AI) venturi nozzles consistently provided reduced spray drift potential. On occasion, some adjuvants marketed as drift reduction agents acted in an opposite manner and decreased droplet size. Wind tunnel use for spray drift had the broadest range of variables studied among conceptual applications and included various nozzles, boom height, product active ingredients, adjuvants, and other variables. Deposits decreased in foliage from upper, middle, to lower foliage heights and decreased with increased wind speed. Low wind turbulence in the canopy did not contribute to deposition. Foliage deposition depended more on droplet size and local ambient winds. Canopy porosity limited the droplet size to less than 100 µm for contribution to deposits internal to the foliage. Wind tunnel use for UAV applications was mostly focused on spray drift for UAV variables such as rotor configurations and payload for mounted or tethered UAV. An ultimate recommendation was to use AI nozzles, reduce application speed, and to use a suitable adjuvant – which was similar to other applications. Contrasting results for the impact of airflow around sprays were reported for vortices around fan spray discharge of a nozzle versus a 4-nozzle boom study that found no differences in velocity and turbulence fields due to the presence or no presence of spray discharge. Spray test methods and collections determined in wind tunnels primarily focused on collection efficiencies for a wide range of spray collectors. Collection efficiencies varied with collector and droplet size. Keywords: Keywords.,Boom sprayer,Droplet size,Droplet trajectory,Nozzle classification,Spray deposit,Spray drift,Spray nozzles.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"136003529","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 Relative source contributions to stream bed sediment from construction sites and stream banks were quantified. Two machine-learning techniques were used to select composite fingerprinting properties. The MixSIR Bayesian model was employed for source apportionment. Statistical methods employed for fingerprinting properties selection have the potential to impact source apportionments. Management strategies to reduce sediment mobilization should be targeted depending on the dominant source of sediment in each sub-watershed. Abstract. Sediment fingerprinting is an extensively used approach for investigating sediment sources by linking in-stream sediment mixtures with watershed source materials. The overall goal of this research was to estimate the relative source contributions of stream banks and construction sites to the stream bed sediment in an urbanized watershed (Alabama, USA) using a fingerprinting technique established on composite fingerprints selected by two different machine learning techniques at a sub-watershed scale. The two statistical approaches employed to select the subset of fingerprinting properties were: (1) the Random Forest algorithm (RF) with Gini importance ranking of variables; and (2) logistic regression with the least absolute shrinkage and selection operator (LASSO). A Bayesian mixing model was then used to estimate the distribution of mixing proportions along with the associated uncertainty. The models were built based on the composite fingerprints selected using the two machine learning methods. Overall, using the subset of fingerprints selected by RF and LASSO, the relative contribution of stream banks ranged from 14±9% to 97±2% and from 24±18% to 94±5%, respectively, throughout the watershed. The stream bank contributions were compared with a previous study conducted in the watershed that utilized a two-step statistical procedure (which involved a Mann-Whitney U-test as the first step and discriminant function analysis (DFA) as the second step) to select the composite of fingerprinting properties and a frequentist mixing model to calculate the source apportionments. The relative contributions of stream banks to stream bed sediment in the previous study reported ranged from 9±8% to 100±1%. Therefore, the study demonstrated the dependence of source attributions on the statistical procedures used to select the optimum composite fingerprints for sediment fingerprinting applications. Furthermore, the results underscored the importance of using different mixing model structures to obtain reliable estimates of source contributions. Keywords: Least absolute shrinkage and selection operator (LASSO), MixSIR Bayesian model, Random Forest (RF), Statistical techniques.
{"title":"Application of Sediment Fingerprinting to Apportion Sediment Sources: Using Machine Learning Models","authors":"Kritika Malhotra, Jingyi Zheng, Ash Abebe, Jasmeet Lamba","doi":"10.13031/ja.14906","DOIUrl":"https://doi.org/10.13031/ja.14906","url":null,"abstract":"Highlights Relative source contributions to stream bed sediment from construction sites and stream banks were quantified. Two machine-learning techniques were used to select composite fingerprinting properties. The MixSIR Bayesian model was employed for source apportionment. Statistical methods employed for fingerprinting properties selection have the potential to impact source apportionments. Management strategies to reduce sediment mobilization should be targeted depending on the dominant source of sediment in each sub-watershed. Abstract. Sediment fingerprinting is an extensively used approach for investigating sediment sources by linking in-stream sediment mixtures with watershed source materials. The overall goal of this research was to estimate the relative source contributions of stream banks and construction sites to the stream bed sediment in an urbanized watershed (Alabama, USA) using a fingerprinting technique established on composite fingerprints selected by two different machine learning techniques at a sub-watershed scale. The two statistical approaches employed to select the subset of fingerprinting properties were: (1) the Random Forest algorithm (RF) with Gini importance ranking of variables; and (2) logistic regression with the least absolute shrinkage and selection operator (LASSO). A Bayesian mixing model was then used to estimate the distribution of mixing proportions along with the associated uncertainty. The models were built based on the composite fingerprints selected using the two machine learning methods. Overall, using the subset of fingerprints selected by RF and LASSO, the relative contribution of stream banks ranged from 14±9% to 97±2% and from 24±18% to 94±5%, respectively, throughout the watershed. The stream bank contributions were compared with a previous study conducted in the watershed that utilized a two-step statistical procedure (which involved a Mann-Whitney U-test as the first step and discriminant function analysis (DFA) as the second step) to select the composite of fingerprinting properties and a frequentist mixing model to calculate the source apportionments. The relative contributions of stream banks to stream bed sediment in the previous study reported ranged from 9±8% to 100±1%. Therefore, the study demonstrated the dependence of source attributions on the statistical procedures used to select the optimum composite fingerprints for sediment fingerprinting applications. Furthermore, the results underscored the importance of using different mixing model structures to obtain reliable estimates of source contributions. Keywords: Least absolute shrinkage and selection operator (LASSO), MixSIR Bayesian model, Random Forest (RF), Statistical techniques.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"136004021","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 Rice fissuring and breakage have a negative impact on milling quality and market value. Fissure formation during microwave drying may be a combination of different phenomena. The phenomena include the buildup of high internal temperatures and pressures in the kernel and stresses generated from a higher heat flux of liquid at high microwave intensities. Abstract. Rice fissuring and breakage have negative economic impacts on rice processing. Many advances in multi-pass conventional rice drying technologies have not been successful in completely preventing rice fissure formation. Thankfully, novel drying technologies such as the 915 MHz industrial microwave have been shown to have a great potential for rice drying and may reduce rice fissuring (or increase head rice yield) due to the volumetric heating property of microwaves. This review assessed the mechanism of fissure formation in conventionally and microwave-dried grains to provide recommendations for managing fissure formation during the drying of freshly harvested paddy rice. Literature search indicates that fissure formation during microwave drying may be mainly a combination of different phenomena, such as the buildup of high internal temperature and pressure in the kernel, stresses generated from a higher flux of liquid at high microwave intensities, and other mechanisms that are yet to be discovered. Fissure formation in rice during conventional drying of the rice kernels can be explained using the glass transition phenomenon. Keywords: 915 MHz microwave, Fissures, Glass transition Phenomenon, Rice, Volumetric heating.
{"title":"Fissure Formation in Rice During Conventional and Microwave Drying","authors":"R. Bruce, G. Atungulu, R. C. Bautista","doi":"10.13031/ja.15228","DOIUrl":"https://doi.org/10.13031/ja.15228","url":null,"abstract":"Highlights Rice fissuring and breakage have a negative impact on milling quality and market value. Fissure formation during microwave drying may be a combination of different phenomena. The phenomena include the buildup of high internal temperatures and pressures in the kernel and stresses generated from a higher heat flux of liquid at high microwave intensities. Abstract. Rice fissuring and breakage have negative economic impacts on rice processing. Many advances in multi-pass conventional rice drying technologies have not been successful in completely preventing rice fissure formation. Thankfully, novel drying technologies such as the 915 MHz industrial microwave have been shown to have a great potential for rice drying and may reduce rice fissuring (or increase head rice yield) due to the volumetric heating property of microwaves. This review assessed the mechanism of fissure formation in conventionally and microwave-dried grains to provide recommendations for managing fissure formation during the drying of freshly harvested paddy rice. Literature search indicates that fissure formation during microwave drying may be mainly a combination of different phenomena, such as the buildup of high internal temperature and pressure in the kernel, stresses generated from a higher flux of liquid at high microwave intensities, and other mechanisms that are yet to be discovered. Fissure formation in rice during conventional drying of the rice kernels can be explained using the glass transition phenomenon. Keywords: 915 MHz microwave, Fissures, Glass transition Phenomenon, Rice, Volumetric heating.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"74818710","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}
Enrique Eduardo Pena Martinez, J. Ward, G. Collins, Natalie Nelson
Highlights Agreement in the mean difference between the traditional and the UAV-based method only occurred in poor stands. Effects of different sampling sizes between methods were evident in mediocre-to-good stand assessments. Abstract. When suboptimal cotton stands occur, growers face the decision to accept or reject the stand. The replanting decision is difficult because the tradeoffs associated with replanting expenditures and reduced yields are difficult to objectively assess. Traditional methods like visual assessments and manual counts of cotton stands are commonly used to support a replanting decision. Typically, manual counts of skip size and frequency will provide more accurate assessments of the stand than visual assessments, but they are cumbersome to conduct and may not provide clear evidence that a replant is needed. Still, manual counts are popular among cotton farmers and the scientific community. Skip counts generated with the help of unmanned aerial vehicles (UAV) are less popular among cotton growers but provide more coverage and a larger sampling size across a given field. Therefore, UAVs have the potential to overcome the limitations associated with traditional methods. The motivation behind this study is to inform readers if manual methods can still be used for accurate decision-making regarding the replanting decision. More specifically, we study the interchangeability, or agreement, between a manual and a UAV-based method using Bland-Altman plots. Each method quantified skips greater than or equal to 0.91 m at different sampling sizes. Treatment plots varied in their stand counts, skip size, and skip frequency. Agreement between both methods was only found in the lowest stand treatment, where skips of large sizes were predominant. Conversely, methods disagreed in the higher stand where skips greater than or equal to 0.91 m were scarce. Keywords: Agriculture, Altman, Bland, Drone, Gaps, Precision, Remote, Sensing, UAS.
{"title":"Testing the Agreement Between a Traditional and UAV-Based Method for Quantifying Skips in Suboptimal Cotton Stands","authors":"Enrique Eduardo Pena Martinez, J. Ward, G. Collins, Natalie Nelson","doi":"10.13031/ja.14760","DOIUrl":"https://doi.org/10.13031/ja.14760","url":null,"abstract":"Highlights Agreement in the mean difference between the traditional and the UAV-based method only occurred in poor stands. Effects of different sampling sizes between methods were evident in mediocre-to-good stand assessments. Abstract. When suboptimal cotton stands occur, growers face the decision to accept or reject the stand. The replanting decision is difficult because the tradeoffs associated with replanting expenditures and reduced yields are difficult to objectively assess. Traditional methods like visual assessments and manual counts of cotton stands are commonly used to support a replanting decision. Typically, manual counts of skip size and frequency will provide more accurate assessments of the stand than visual assessments, but they are cumbersome to conduct and may not provide clear evidence that a replant is needed. Still, manual counts are popular among cotton farmers and the scientific community. Skip counts generated with the help of unmanned aerial vehicles (UAV) are less popular among cotton growers but provide more coverage and a larger sampling size across a given field. Therefore, UAVs have the potential to overcome the limitations associated with traditional methods. The motivation behind this study is to inform readers if manual methods can still be used for accurate decision-making regarding the replanting decision. More specifically, we study the interchangeability, or agreement, between a manual and a UAV-based method using Bland-Altman plots. Each method quantified skips greater than or equal to 0.91 m at different sampling sizes. Treatment plots varied in their stand counts, skip size, and skip frequency. Agreement between both methods was only found in the lowest stand treatment, where skips of large sizes were predominant. Conversely, methods disagreed in the higher stand where skips greater than or equal to 0.91 m were scarce. Keywords: Agriculture, Altman, Bland, Drone, Gaps, Precision, Remote, Sensing, UAS.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","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":"80368299","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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