G. Feyereisen, E. Ghane, T. W. Schumacher, B. Dalzell, M. Williams
Highlights Novel three-bed, cascading-inlet bioreactor treated agricultural drainage from a 249-ha catchment. Nitrate removal rates and load reduction efficiencies were similar to those of traditional single-field bioreactors. Sedimentation problems reduced bed life; a sediment sensing and exclusion system solved them. This scale provides opportunities for centralized management and nutrient reduction verification. Abstract. Denitrifying bioreactors, a structural practice deployed at the field scale to meet water quality goals, have been underutilized and require additional evaluation at the small catchment scale. The objective of this study was to quantify the performance of a large, multi-bed denitrifying bioreactor system sized to treat agricultural drainage runoff (combined drainage discharge and surface runoff) from a 249-ha catchment. Three woodchip bioreactor beds, 7.6 m wide by 41 m long by 1.5 m deep, with cascading inlets, were constructed in 2016 in southern Minnesota, U.S. The beds received runoff for one water year from a catchment area that is 91% tile-drained row crops, primarily maize and soybeans. Initial woodchip quality differed among the three beds, affecting flow and nitrate removal rates. Bioreactor flow was unimpeded by sediment for twelve events from September 2016 to July 2017, during which time 55% of the discharge from the catchment was treated in the bioreactor beds. Average daily nitrate removal rates ranged from 2.5 to 6.5 g-N m-3 d-1 for the three bioreactor beds, with nitrate-N load removal of flow through the beds between 19% and 27%. When accounting for untreated by-pass flow, the overall nitrate-N removal of the multi-bed system was 12.5% (713 kg N). During high-flow events, incoming sediment clogged the reactor beds, decreasing their performance. There was 4,520 kg of sediment trapped in one bed, and evidence suggests the other two trapped a similar load. To solve this problem and prolong the bioreactor’s lifespan, we installed a shutoff gate that activated when inflow turbidity exceeded a threshold value. Finally, the findings indicate that catchment-scale denitrifying bioreactors can successfully remove nitrate load from agricultural runoff, but sediment-prevention measures may be required to extend the bioreactor's lifespan. Keywords: Bioreactor, Denitrification, Nitrate removal, Sedimentation, Subsurface drainage.
新型三床，梯级进水生物反应器处理249公顷集水区的农业污水。硝酸盐的去除率和负荷降低效率与传统的单场生物反应器相似。沉降问题降低了床层寿命;沉积物传感和排除系统解决了这些问题。该量表为集中管理和营养减少验证提供了机会。摘要反硝化生物反应器是在实地规模上为达到水质目标而部署的一种结构性做法，但尚未得到充分利用，需要在小集水区规模上进行额外评价。本研究的目的是量化大型多床反硝化生物反应器系统的性能，该系统用于处理249公顷集水区的农业排水径流(综合排水排放和地表径流)。2016年，美国明尼苏达州南部建造了三个木屑生物反应器床，宽7.6米，长41米，深1.5米，具有层叠式入口。这些床从集水区接收了一个水年的径流，该集水区91%是瓦片排水的行作物，主要是玉米和大豆。不同床层的初始木屑质量不同，影响了流速和硝酸盐去除率。在2016年9月至2017年7月的12个事件中，生物反应器的流动不受沉积物的阻碍，在此期间，55%的集水区排放在生物反应器床中进行处理。三个生物反应器床的平均每日硝酸盐去除率为2.5至6.5 g-N m-3 d-1，通过床的硝酸盐- n负荷去除率为19%至27%。考虑到未经处理的旁通流，多床系统的总体硝酸盐N去除率为12.5% (713 kg N)。在高流量事件期间，传入的沉积物堵塞了反应器床，降低了它们的性能。有4520公斤的沉积物被困在一个床上，证据表明其他两个床也有类似的负荷。为了解决这个问题并延长生物反应器的使用寿命，我们安装了一个关闭阀，当进水浊度超过阈值时就会启动。最后，研究结果表明，集水区规模的反硝化生物反应器可以成功地去除农业径流中的硝酸盐负荷，但可能需要采取防止沉积的措施来延长生物反应器的使用寿命。关键词:生物反应器，反硝化，硝酸盐去除，沉降，地下排水
{"title":"Can Woodchip Bioreactors Be Used at a Catchment Scale? Nitrate Performance and Sediment Considerations","authors":"G. Feyereisen, E. Ghane, T. W. Schumacher, B. Dalzell, M. Williams","doi":"10.13031/ja.15496","DOIUrl":"https://doi.org/10.13031/ja.15496","url":null,"abstract":"Highlights Novel three-bed, cascading-inlet bioreactor treated agricultural drainage from a 249-ha catchment. Nitrate removal rates and load reduction efficiencies were similar to those of traditional single-field bioreactors. Sedimentation problems reduced bed life; a sediment sensing and exclusion system solved them. This scale provides opportunities for centralized management and nutrient reduction verification. Abstract. Denitrifying bioreactors, a structural practice deployed at the field scale to meet water quality goals, have been underutilized and require additional evaluation at the small catchment scale. The objective of this study was to quantify the performance of a large, multi-bed denitrifying bioreactor system sized to treat agricultural drainage runoff (combined drainage discharge and surface runoff) from a 249-ha catchment. Three woodchip bioreactor beds, 7.6 m wide by 41 m long by 1.5 m deep, with cascading inlets, were constructed in 2016 in southern Minnesota, U.S. The beds received runoff for one water year from a catchment area that is 91% tile-drained row crops, primarily maize and soybeans. Initial woodchip quality differed among the three beds, affecting flow and nitrate removal rates. Bioreactor flow was unimpeded by sediment for twelve events from September 2016 to July 2017, during which time 55% of the discharge from the catchment was treated in the bioreactor beds. Average daily nitrate removal rates ranged from 2.5 to 6.5 g-N m-3 d-1 for the three bioreactor beds, with nitrate-N load removal of flow through the beds between 19% and 27%. When accounting for untreated by-pass flow, the overall nitrate-N removal of the multi-bed system was 12.5% (713 kg N). During high-flow events, incoming sediment clogged the reactor beds, decreasing their performance. There was 4,520 kg of sediment trapped in one bed, and evidence suggests the other two trapped a similar load. To solve this problem and prolong the bioreactor’s lifespan, we installed a shutoff gate that activated when inflow turbidity exceeded a threshold value. Finally, the findings indicate that catchment-scale denitrifying bioreactors can successfully remove nitrate load from agricultural runoff, but sediment-prevention measures may be required to extend the bioreactor's lifespan. Keywords: Bioreactor, Denitrification, Nitrate removal, Sedimentation, Subsurface drainage.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86312244","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 The frictional pressure drop correlation of agricultural residue-water slurry flows in vertical pipes is developed. Multiple linear regression with the backward elimination method was used in RStudio to obtain the optimal model. Some regression coefficients differ for different types of biomass feedstocks. The predicted pressure drops agree well with the experimental data within a 95% CI. Empirical models for the onset velocity of drag reduction of different particle sizes of biomass are proposed. Abstract. Large-scale biofuel production at levels equivalent to conventional oil refineries using long-distance pipeline hydro-transport of biomass can be a cleaner alternative to fossil fuels when it comes to economics and traffic congestion associated with the overland transportation of biomass. The transport of aqueous slurries of several saturated mass concentrations (5%-40%) and four particle sizes (from <3.2-19.2 mm) of two types of agricultural residue biomass (ARB) feedstock (corn stover and wheat straw) was studied through a vertical test section of a 29 m long, 50 mm diameter closed circuit pipeline facility, and frictional pressure drops were recorded at different flow rates (0.5-4.3 m s-1). A framework was developed in RStudio (4.0.5) to analyze the experimentally obtained frictional pressure drops of biomass slurries through a multiple linear regression approach using a backward elimination method and Akaike information criterion. An empirical model was proposed to predict slurry frictional pressure drop in terms of slurry velocity, slurry solid mass concentration, particle aspect ratio, and feedstock type. The model satisfactorily predicted the frictional pressure drops of both feedstocks of biomass-water slurry flows through pipes within a 95% confidence interval. The correlations introduced for onset velocities of drag reduction in terms of slurry solid mass concentrations seemed helpful to interpret the transition points of the corresponding slurries in vertical upward flows through pipes. The empirical correlation developed in this research could help select biomass slurry pumps and pipe dimensions when designing a typical long distance pipeline network for biofuel production at the commercial level. Keywords: Agricultural biomass wastes, Frictional loss prediction, Numerical model, Onset velocity correlation, Regression coefficients, Upward pipe flow.
{"title":"The Development of Empirical Correlations to Understand the Frictional Behavior of Aqueous Biomass Slurry Flows in Vertical Pipes","authors":"Kashif Javed, Vinoj Kurian, Ajay Kumar","doi":"10.13031/ja.15498","DOIUrl":"https://doi.org/10.13031/ja.15498","url":null,"abstract":"Highlights The frictional pressure drop correlation of agricultural residue-water slurry flows in vertical pipes is developed. Multiple linear regression with the backward elimination method was used in RStudio to obtain the optimal model. Some regression coefficients differ for different types of biomass feedstocks. The predicted pressure drops agree well with the experimental data within a 95% CI. Empirical models for the onset velocity of drag reduction of different particle sizes of biomass are proposed. Abstract. Large-scale biofuel production at levels equivalent to conventional oil refineries using long-distance pipeline hydro-transport of biomass can be a cleaner alternative to fossil fuels when it comes to economics and traffic congestion associated with the overland transportation of biomass. The transport of aqueous slurries of several saturated mass concentrations (5%-40%) and four particle sizes (from <3.2-19.2 mm) of two types of agricultural residue biomass (ARB) feedstock (corn stover and wheat straw) was studied through a vertical test section of a 29 m long, 50 mm diameter closed circuit pipeline facility, and frictional pressure drops were recorded at different flow rates (0.5-4.3 m s-1). A framework was developed in RStudio (4.0.5) to analyze the experimentally obtained frictional pressure drops of biomass slurries through a multiple linear regression approach using a backward elimination method and Akaike information criterion. An empirical model was proposed to predict slurry frictional pressure drop in terms of slurry velocity, slurry solid mass concentration, particle aspect ratio, and feedstock type. The model satisfactorily predicted the frictional pressure drops of both feedstocks of biomass-water slurry flows through pipes within a 95% confidence interval. The correlations introduced for onset velocities of drag reduction in terms of slurry solid mass concentrations seemed helpful to interpret the transition points of the corresponding slurries in vertical upward flows through pipes. The empirical correlation developed in this research could help select biomass slurry pumps and pipe dimensions when designing a typical long distance pipeline network for biofuel production at the commercial level. Keywords: Agricultural biomass wastes, Frictional loss prediction, Numerical model, Onset velocity correlation, Regression coefficients, Upward pipe flow.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81341929","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}
Toby A. Adjuik, S. Nokes, M. Montross, O. Wendroth, R. Walton
Highlights A lignin-based hydrogel was synthesized and shown to possess a swelling ratio of 2013%. The hydrogel contained important hydrophilic hydroxyl groups and macropores for water retention. The hydrogel improved soil water retention in silt loam soil at high matric potentials and in the dry soil range. Increasing hydrogel concentration increased water retention in a loamy fine sand soil at high and low matric potentials. Abstract. Superabsorbent polymers (hydrogels) have been proposed as soil amendments to increase the amount of plant-available water in the soil. Synthetic hydrogels have been widely investigated for use in agriculture. Due to increasing environmental concerns related to synthetic hydrogels, naturally sourced hydrogels are of interest because of their potential for increased biodegradability and biocompatibility. A lignin-based hydrogel was synthesized for this study, and its swelling properties and water absorption capacity were determined. The hydrogel was characterized using scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and gas pycnometry. A hanging water column, pressure plate apparatus, and dew point potentiometer were used to measure the soil water retention curve from saturation to oven-dryness for silt loam and loamy fine sand soils after amendment with the lignin-based hydrogel. Results showed a maximum swelling ratio in deionized water of 2013% of the hydrogel’s original mass, 1092% in tap water, and 825% in a 0.9% NaCl solution. The FTIR spectra of the hydrogel showed the presence of O-H bonds from the lignin structure, which renders the hydrogel reactive to a crosslinker and forms insoluble bonds, thereby allowing the hydrogel to swell when exposed to water. SEM images of the lignin hydrogels indicate large macropores, which allowed for water absorption. Applying hydrogels significantly increased the soil's water-holding capacity at 0.3% (w/w) treatment. Hydrogel treatment significantly increased water retention at saturation or near saturation by 0.12 cm3 cm-3 and at field capacity by 0.08 cm3 cm-3 for silt loam soil at 1% (w/w) treatment compared to the control treatment with no added lignin hydrogel. Hydrogel application increased water retention over the range of the soil water retention curve from -3 to -15,000 cm for the loamy fine sand soil at 1% (w/w) treatment. However, the application of lignin-based hydrogel did not affect plant available water capacity (PAWC) in either soil tested. These results serve as preliminary evidence upon which further lignin-based hydrogel amendment studies could be built by testing higher concentrations of hydrogel in the soil. Keywords: Lignin, Soil water retention curve, Super absorbent polymers, Swelling capacity, Water retention.
{"title":"Alkali Lignin-Based Hydrogel: Synthesis, Characterization, and Impact on Soil Water Retention From Near Saturation to Dryness","authors":"Toby A. Adjuik, S. Nokes, M. Montross, O. Wendroth, R. Walton","doi":"10.13031/ja.15207","DOIUrl":"https://doi.org/10.13031/ja.15207","url":null,"abstract":"Highlights A lignin-based hydrogel was synthesized and shown to possess a swelling ratio of 2013%. The hydrogel contained important hydrophilic hydroxyl groups and macropores for water retention. The hydrogel improved soil water retention in silt loam soil at high matric potentials and in the dry soil range. Increasing hydrogel concentration increased water retention in a loamy fine sand soil at high and low matric potentials. Abstract. Superabsorbent polymers (hydrogels) have been proposed as soil amendments to increase the amount of plant-available water in the soil. Synthetic hydrogels have been widely investigated for use in agriculture. Due to increasing environmental concerns related to synthetic hydrogels, naturally sourced hydrogels are of interest because of their potential for increased biodegradability and biocompatibility. A lignin-based hydrogel was synthesized for this study, and its swelling properties and water absorption capacity were determined. The hydrogel was characterized using scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and gas pycnometry. A hanging water column, pressure plate apparatus, and dew point potentiometer were used to measure the soil water retention curve from saturation to oven-dryness for silt loam and loamy fine sand soils after amendment with the lignin-based hydrogel. Results showed a maximum swelling ratio in deionized water of 2013% of the hydrogel’s original mass, 1092% in tap water, and 825% in a 0.9% NaCl solution. The FTIR spectra of the hydrogel showed the presence of O-H bonds from the lignin structure, which renders the hydrogel reactive to a crosslinker and forms insoluble bonds, thereby allowing the hydrogel to swell when exposed to water. SEM images of the lignin hydrogels indicate large macropores, which allowed for water absorption. Applying hydrogels significantly increased the soil's water-holding capacity at 0.3% (w/w) treatment. Hydrogel treatment significantly increased water retention at saturation or near saturation by 0.12 cm3 cm-3 and at field capacity by 0.08 cm3 cm-3 for silt loam soil at 1% (w/w) treatment compared to the control treatment with no added lignin hydrogel. Hydrogel application increased water retention over the range of the soil water retention curve from -3 to -15,000 cm for the loamy fine sand soil at 1% (w/w) treatment. However, the application of lignin-based hydrogel did not affect plant available water capacity (PAWC) in either soil tested. These results serve as preliminary evidence upon which further lignin-based hydrogel amendment studies could be built by testing higher concentrations of hydrogel in the soil. Keywords: Lignin, Soil water retention curve, Super absorbent polymers, Swelling capacity, Water retention.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87426483","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}
Mukesh Mehata, S. Datta, S. Taghvaeian, T. Ochsner, A. Mirchi, D. Moriasi
Highlights Among six manufacturer calibrations, the default calibration resulted in the largest errors. Sensor performance was negatively affected by higher clay content and salinity. Sensor-based approaches to estimating field capacity were inconsistent and spatially variable. Abstract. Maintaining the economic and environmental sustainability of crop production requires optimizing irrigation management using advanced technologies such as soil water sensors. In this study, the performance of a commercially available multi-sensor capacitance probe was evaluated under irrigated field conditions across western Oklahoma. The effects of clay content and salinity on sensor performance were investigated too. In addition, the field capacity (FC) of soil cores collected at study sites was determined in the laboratory. These laboratory FC values were used to assess the performance of two sensor-based approaches for estimating FC: the days to reach laboratory FC after major watering events and the percentile of collected sensor readings that represented laboratory FC. The results showed that among the six calibrations provided by the manufacturer, the default and silty clay loam calibrations produced the largest and smallest soil water content errors, respectively. Errors generally increased with clay and salinity, except for the heavy clay calibration, which showed improved performance with increasing clay content. The default and sand calibrations were more sensitive to increases in clay and salinity compared to other calibrations. In the case of sensor-based FC, on average, one to three days were required to reach laboratory FC, with a large range of one to nine days. The percentiles representing laboratory FC had an average of 56% and a range of 3%-97%. Overall, the sensor-based approaches produced inconsistent and highly variable estimates of FC. Keywords: Calibrations, Clay content, Irrigation scheduling, Salinity, Sensor accuracy, Soil water threshold.
{"title":"Performance of a Multi-Sensor Capacitance Probe in Estimating Soil Water Content and Field Capacity","authors":"Mukesh Mehata, S. Datta, S. Taghvaeian, T. Ochsner, A. Mirchi, D. Moriasi","doi":"10.13031/ja.15416","DOIUrl":"https://doi.org/10.13031/ja.15416","url":null,"abstract":"Highlights Among six manufacturer calibrations, the default calibration resulted in the largest errors. Sensor performance was negatively affected by higher clay content and salinity. Sensor-based approaches to estimating field capacity were inconsistent and spatially variable. Abstract. Maintaining the economic and environmental sustainability of crop production requires optimizing irrigation management using advanced technologies such as soil water sensors. In this study, the performance of a commercially available multi-sensor capacitance probe was evaluated under irrigated field conditions across western Oklahoma. The effects of clay content and salinity on sensor performance were investigated too. In addition, the field capacity (FC) of soil cores collected at study sites was determined in the laboratory. These laboratory FC values were used to assess the performance of two sensor-based approaches for estimating FC: the days to reach laboratory FC after major watering events and the percentile of collected sensor readings that represented laboratory FC. The results showed that among the six calibrations provided by the manufacturer, the default and silty clay loam calibrations produced the largest and smallest soil water content errors, respectively. Errors generally increased with clay and salinity, except for the heavy clay calibration, which showed improved performance with increasing clay content. The default and sand calibrations were more sensitive to increases in clay and salinity compared to other calibrations. In the case of sensor-based FC, on average, one to three days were required to reach laboratory FC, with a large range of one to nine days. The percentiles representing laboratory FC had an average of 56% and a range of 3%-97%. Overall, the sensor-based approaches produced inconsistent and highly variable estimates of FC. Keywords: Calibrations, Clay content, Irrigation scheduling, Salinity, Sensor accuracy, Soil water threshold.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77932961","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 An empirical equation was embedded in a user-friendly tool to estimate the site-specific design drainage rate. The site-specific design drainage rate was based on the local soil, weather, and economics of the area of interest. The tool uses the site-specific design drainage rate to estimate the optimum drain spacing. The optimum drain spacing maximizes the economic return on investment. Abstract. Properly estimating the subsurface drain spacing is critical to optimizing crop production. The Hooghoudt equation can be used in humid climates to approximate the drain spacing. However, the application of this equation has been limited due to site-specific data requirements and because it is a complicated process that is not usually practical for practitioners. Traditionally, drainage contractors have chosen a drain spacing without using the Hooghoudt equation. The objective of this article is to develop a user-friendly decision-support tool that estimates the site-specific optimum drain spacing for maximum economic return on investment. We developed the Drain Spacing Tool for the Midwest USA based on the Hooghoudt equation and site-specific inputs. The tool automatically acquires the site-specific equivalent saturated hydraulic conductivity of the soil profile and depth to the restrictive layer from the gSSURGO database, and the user manually enters the desired drain depth. The site-specific input of design drainage rate (DDR), that is required in the Hooghoudt equation, is estimated from an empirical equation that was developed from a DRAINMOD modeling study. The site-specific inputs for the empirical equation include site-specific 30-year average growing-season rainfall, drain depth, equivalent saturated hydraulic conductivity, and depth to the restrictive layer, all of which are automatically acquired from gSSURGO, except for the rainfall data, which was acquired from the PRISM Climate Group. The site-specific DDR value from the empirical equation was then used in the Hooghoudt equation to estimate the optimum drain spacing that maximizes economic return on investment. In conclusion, the tool estimates the site-specific optimum drain spacing based on the local soil, weather, and economics of the area of interest. Keywords: Decision-support tool, Design drainage rate, DRAINMOD, Farm profitability, Tile drainage.
{"title":"A Drain Spacing Tool That Estimates the Optimum Subsurface Drain Spacing for Maximum Profit","authors":"E. Ghane, A. Nejadhashemi, Ian Kropp","doi":"10.13031/ja.15406","DOIUrl":"https://doi.org/10.13031/ja.15406","url":null,"abstract":"Highlights An empirical equation was embedded in a user-friendly tool to estimate the site-specific design drainage rate. The site-specific design drainage rate was based on the local soil, weather, and economics of the area of interest. The tool uses the site-specific design drainage rate to estimate the optimum drain spacing. The optimum drain spacing maximizes the economic return on investment. Abstract. Properly estimating the subsurface drain spacing is critical to optimizing crop production. The Hooghoudt equation can be used in humid climates to approximate the drain spacing. However, the application of this equation has been limited due to site-specific data requirements and because it is a complicated process that is not usually practical for practitioners. Traditionally, drainage contractors have chosen a drain spacing without using the Hooghoudt equation. The objective of this article is to develop a user-friendly decision-support tool that estimates the site-specific optimum drain spacing for maximum economic return on investment. We developed the Drain Spacing Tool for the Midwest USA based on the Hooghoudt equation and site-specific inputs. The tool automatically acquires the site-specific equivalent saturated hydraulic conductivity of the soil profile and depth to the restrictive layer from the gSSURGO database, and the user manually enters the desired drain depth. The site-specific input of design drainage rate (DDR), that is required in the Hooghoudt equation, is estimated from an empirical equation that was developed from a DRAINMOD modeling study. The site-specific inputs for the empirical equation include site-specific 30-year average growing-season rainfall, drain depth, equivalent saturated hydraulic conductivity, and depth to the restrictive layer, all of which are automatically acquired from gSSURGO, except for the rainfall data, which was acquired from the PRISM Climate Group. The site-specific DDR value from the empirical equation was then used in the Hooghoudt equation to estimate the optimum drain spacing that maximizes economic return on investment. In conclusion, the tool estimates the site-specific optimum drain spacing based on the local soil, weather, and economics of the area of interest. Keywords: Decision-support tool, Design drainage rate, DRAINMOD, Farm profitability, Tile drainage.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82153930","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 We proposed to use GREENBOX technology for urban crop production in warehouse settings. We assessed the profitability of the application of GREENBOX technology using Benefit Cost Analysis (BCA) to evaluate the Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP). We conducted sensitivity analyses on NPV, IRR, and PP over different scenarios. GREENBOX was found financially feasible for all the hypothetical scenarios in major cities in the USA. Abstract . Food security pressure, especially in urban areas, continues to rise due to surging demand for food resulting from a growing population and declining resources. It has been critical to improve crop production and make food readily available to consumers without traveling long distances in an economically sustainable manner. The novel GREENBOX technology uses Controlled Environment Agriculture (CEA) principles for leafy green crop production in urban structures. A GREENBOX is an individual thermally insulated chamber with an artificial lighting source and a soilless cultivation system (hydroponics) in an environment that is controlled at the grower's discretion. This study performed a financial feasibility study of GREENBOX technology for urban crop production in various scenarios to evaluate the system's profitability from an individual business's perspective and used market prices of the goods and services paid for or received by a project. The representative GREENBOX unit in the base case scenario had dimensions of a standard shipping pallet (1.0 x 1.2 x 0.9 m, or 40 x 48 x 36 in) and included thermally insulated walls, an LED artificial lighting source, a camera for monitoring growth, a Nutrient Film Technique (NFT) hydroponic growth platform, and an environmental monitoring and control system. A warehouse can host numerous GREENBOX units for mass production. We carried out a benefit-cost analysis by assessing the Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP). These parameters were evaluated for a base case scenario from data collected or estimated for a representative GREENBOX unit. We also applied the base case scenario to investigate the financial performance of the GREENBOX setup in selected urban areas in the United States; New York City (New York), Miami (Florida), Los Angeles (California), Dallas (Texas), Atlanta (Georgia), Chicago (Illinois), Boston (Massachusetts), and Philadelphia (Pennsylvania). We then carried out a sensitivity analysis on NPV, IRR, and PP by keeping all the parameters in the base case scenario invariant except for one at a time. We obtained a summary equation to understand the variation of the financial parameters with changing lettuce sale price, electricity cost, rental cost, labor cost, and the number of GREENBOX units. A GREENBOX unit would require an initial investment of $398 to assemble and an annual outflow of $157 to cover operating expenses. GREENBOX cultivation was financially viable
我们建议将GREENBOX技术用于城市农作物的仓库生产。我们使用效益成本分析(BCA)来评估净现值(NPV)、内部收益率(IRR)和投资回收期(PP)，以评估应用GREENBOX技术的盈利能力。我们对不同情景下的NPV、IRR和PP进行了敏感性分析。GREENBOX在美国主要城市的所有假设场景中都是经济可行的。摘要由于人口增长和资源减少导致粮食需求激增，粮食安全压力，特别是城市地区的粮食安全压力继续上升。以经济上可持续的方式，在不长途跋涉的情况下，提高作物产量，使消费者随时可以获得食物，这一点至关重要。新型的GREENBOX技术采用了控制环境农业(CEA)原则，用于城市结构中的绿叶作物生产。GREENBOX是一个独立的隔热室，有人工光源和无土栽培系统(水培)，环境由种植者自行控制。本研究对GREENBOX技术在不同情况下用于城市作物生产的财务可行性进行了研究，从个体企业的角度评估该系统的盈利能力，并使用了项目支付或收到的商品和服务的市场价格。在基本情况下，典型的GREENBOX单元具有标准运输托盘的尺寸(1.0 x 1.2 x 0.9 m，或40 x 48 x 36英寸)，包括隔热墙，LED人工照明光源，用于监测生长的摄像机，营养膜技术(NFT)水培生长平台以及环境监测和控制系统。一个仓库可以容纳大量的GREENBOX单元进行大规模生产。我们通过评估净现值(NPV)、内部收益率(IRR)和投资回收期(PP)进行了收益-成本分析。这些参数是根据收集到的数据或为具有代表性的GREENBOX单元估计的基本情况进行评估的。我们还应用基本情景来调查GREENBOX设置在美国选定城市地区的财务绩效;纽约市(纽约州)、迈阿密(佛罗里达州)、洛杉矶(加利福尼亚州)、达拉斯(德克萨斯州)、亚特兰大(佐治亚州)、芝加哥(伊利诺伊州)、波士顿(马萨诸塞州)和费城(宾夕法尼亚州)。然后，我们对NPV、IRR和PP进行了敏感性分析，方法是保持基本情景中的所有参数不变，每次只保留一个参数。我们得到一个总结方程来理解财务参数随生菜销售价格、电费成本、租金成本、人工成本和GREENBOX单位数量的变化。一个GREENBOX单元需要初始投资398美元来组装，每年流出157美元来支付运营费用。在基本情景和所有研究的城市中，GREENBOX种植在财务上是可行的，具有不同程度的财务绩效。敏感性分析显示，除了熟练劳动力成本超过19美元/小时外，GREENBOX培养在所有情况下都是经济可行的，并且GREENBOX单位少于300个。推导出具有统计学意义的回归方程，其中租金成本、人工成本和电价的上升对NPV产生负向影响，而生菜销售价格和GREENBOX单位数量的上升对NPV产生正向影响。GREENBOX农业可以作为当地新鲜作物的来源，为城市消费者提供各种好处，包括改善食品安全，提高食品的新鲜度和营养，通过创造就业机会和销售收入为当地经济做出贡献，以及通过推广食品营养和生产计划提供教育机会。关键词:农业经营，环境控制，GREENBOX，生菜，都市农业
{"title":"GREENBOX Technology III - Financial Feasibility for Crop Production in Urban Settings","authors":"Ankit Kumar Singh, Boris Bravo-Ureta, Richard McAvoy, Xiusheng Yang","doi":"10.13031/ja.15345","DOIUrl":"https://doi.org/10.13031/ja.15345","url":null,"abstract":"Highlights We proposed to use GREENBOX technology for urban crop production in warehouse settings. We assessed the profitability of the application of GREENBOX technology using Benefit Cost Analysis (BCA) to evaluate the Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP). We conducted sensitivity analyses on NPV, IRR, and PP over different scenarios. GREENBOX was found financially feasible for all the hypothetical scenarios in major cities in the USA. Abstract . Food security pressure, especially in urban areas, continues to rise due to surging demand for food resulting from a growing population and declining resources. It has been critical to improve crop production and make food readily available to consumers without traveling long distances in an economically sustainable manner. The novel GREENBOX technology uses Controlled Environment Agriculture (CEA) principles for leafy green crop production in urban structures. A GREENBOX is an individual thermally insulated chamber with an artificial lighting source and a soilless cultivation system (hydroponics) in an environment that is controlled at the grower's discretion. This study performed a financial feasibility study of GREENBOX technology for urban crop production in various scenarios to evaluate the system's profitability from an individual business's perspective and used market prices of the goods and services paid for or received by a project. The representative GREENBOX unit in the base case scenario had dimensions of a standard shipping pallet (1.0 x 1.2 x 0.9 m, or 40 x 48 x 36 in) and included thermally insulated walls, an LED artificial lighting source, a camera for monitoring growth, a Nutrient Film Technique (NFT) hydroponic growth platform, and an environmental monitoring and control system. A warehouse can host numerous GREENBOX units for mass production. We carried out a benefit-cost analysis by assessing the Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP). These parameters were evaluated for a base case scenario from data collected or estimated for a representative GREENBOX unit. We also applied the base case scenario to investigate the financial performance of the GREENBOX setup in selected urban areas in the United States; New York City (New York), Miami (Florida), Los Angeles (California), Dallas (Texas), Atlanta (Georgia), Chicago (Illinois), Boston (Massachusetts), and Philadelphia (Pennsylvania). We then carried out a sensitivity analysis on NPV, IRR, and PP by keeping all the parameters in the base case scenario invariant except for one at a time. We obtained a summary equation to understand the variation of the financial parameters with changing lettuce sale price, electricity cost, rental cost, labor cost, and the number of GREENBOX units. A GREENBOX unit would require an initial investment of $398 to assemble and an annual outflow of $157 to cover operating expenses. GREENBOX cultivation was financially viable","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135318290","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, Richard McAvoy, Boris Bravo-Ureta, Xiusheng Yang
Highlights There are pressures on food security due to increasing population, demand, and urbanization. GREENBOX uses controlled environment agriculture for urban crop production in warehouse settings. GREENBOX provided the required environmental conditions and comparable biomass output year-round. GREENBOX is technically feasible for urban crop production. Abstract. The surging worldwide population and urbanization have increased food security and safety pressures. Therefore, there is a need to increase food production capacity in urban areas to feed this growing population. We have developed the GREENBOX technology to grow vegetables in individual climate-controlled boxes in urban warehouse environments. A GREENBOX is a thermally insulated modular structure of standard size with an artificial lighting source, a hydroponic nutrient supply system, and environmental controls. GREENBOX units can be used together in various numbers to form different configurations and production capacities. This study was conducted to evaluate the technical feasibility and performance of the GREENBOX technology for urban crop production in warehouse settings commonly found in urban areas. Two model GREENBOX units, constructed with commercially available parts, were located in a high-ceiling headhouse of a laboratory greenhouse complex at Storrs, Connecticut, USA, for the study. Forty-eight (48) heads of Butterhead Rex lettuce (Lactuca sativa) were grown in the model GREENBOX units (24 in each) over a 30-day growing cycle for four seasons. Environmental data, including light, temperature, relative humidity, and carbon dioxide, were collected using iPonic sensors at a frequency of every minute and processed to 15-minute averages. Crop growth was quantified with biomass data, which were wet weight, dry weight, total leaf area, and lettuce head area, using destructive and non-destructive methods every three days. A lysimeter was used to determine the water consumption rate by plants every fifteen minutes. 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. Descriptive statistics were used to describe and analyze the results. The DLI in the GREENBOX ranged between 32.48-37.23 mol/m2.d at the lettuce heads' height, higher than the recommended minimum DLI of 6.5-9.7 mol/m2.d. GREENBOX does not rely on external light but solely on the artificial lighting source, regulated at the grower's discretion. The mean temperatures inside were 24.5-26.9°C, falling within the optimal range of 17-29°C for lettuce. The artificial lighting source was a heat source to sustain cultivation. All year, the average relative humidity was 35.53%-58.54%, mostly within the ideal range of 40%-60%. The CO2 concentration inside the boxes fell slightly below the ambient concentration of 350 ppm, between 301.39 and 311.34 ppm over different seasons. Measured growth par
{"title":"GREENBOX Technology I - Technical Feasibility and Performance in Warehouse Environment","authors":"Ankit Kumar Singh, Richard McAvoy, Boris Bravo-Ureta, Xiusheng Yang","doi":"10.13031/ja.15343","DOIUrl":"https://doi.org/10.13031/ja.15343","url":null,"abstract":"Highlights There are pressures on food security due to increasing population, demand, and urbanization. GREENBOX uses controlled environment agriculture for urban crop production in warehouse settings. GREENBOX provided the required environmental conditions and comparable biomass output year-round. GREENBOX is technically feasible for urban crop production. Abstract. The surging worldwide population and urbanization have increased food security and safety pressures. Therefore, there is a need to increase food production capacity in urban areas to feed this growing population. We have developed the GREENBOX technology to grow vegetables in individual climate-controlled boxes in urban warehouse environments. A GREENBOX is a thermally insulated modular structure of standard size with an artificial lighting source, a hydroponic nutrient supply system, and environmental controls. GREENBOX units can be used together in various numbers to form different configurations and production capacities. This study was conducted to evaluate the technical feasibility and performance of the GREENBOX technology for urban crop production in warehouse settings commonly found in urban areas. Two model GREENBOX units, constructed with commercially available parts, were located in a high-ceiling headhouse of a laboratory greenhouse complex at Storrs, Connecticut, USA, for the study. Forty-eight (48) heads of Butterhead Rex lettuce (Lactuca sativa) were grown in the model GREENBOX units (24 in each) over a 30-day growing cycle for four seasons. Environmental data, including light, temperature, relative humidity, and carbon dioxide, were collected using iPonic sensors at a frequency of every minute and processed to 15-minute averages. Crop growth was quantified with biomass data, which were wet weight, dry weight, total leaf area, and lettuce head area, using destructive and non-destructive methods every three days. A lysimeter was used to determine the water consumption rate by plants every fifteen minutes. 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. Descriptive statistics were used to describe and analyze the results. The DLI in the GREENBOX ranged between 32.48-37.23 mol/m2.d at the lettuce heads' height, higher than the recommended minimum DLI of 6.5-9.7 mol/m2.d. GREENBOX does not rely on external light but solely on the artificial lighting source, regulated at the grower's discretion. The mean temperatures inside were 24.5-26.9°C, falling within the optimal range of 17-29°C for lettuce. The artificial lighting source was a heat source to sustain cultivation. All year, the average relative humidity was 35.53%-58.54%, mostly within the ideal range of 40%-60%. The CO2 concentration inside the boxes fell slightly below the ambient concentration of 350 ppm, between 301.39 and 311.34 ppm over different seasons. Measured growth par","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135601265","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 A one-stage reactor PN/A process was developed and evaluated. The highest TN removal rate was 87.3% for the PN/A process to treat synthetic wastewater containing poultry litter at room temperature. Bacterial composition of mature sludge community of wastewater was investigated in this study. Adjusted parameters controlled the growth of AOB and NOB. Abstract. Anammox is an increasingly common process used for the treatment of municipally rejected water and even mainstream wastewater due to its low oxygen demand. However, anammox is not commonly utilized in the treatment of poultry litter because of its high organic content, which would inhibit the anammox process. One-stage partial nitrification and anammox (PN/A) process was developed and evaluated for removing total nitrogen (TN) content from synthetic digestate of poultry litter using a sequencing batch biofilm reactor (SBBR). Independent variables including carbon to nitrogen ratio (C/N) at 1, 2, and 3, dissolved oxygen level (DO, mg/L) at 0.2, 0.35, and 0.5, and hydraulic retention time (HRT, h) at 24, 48, and 72 were examined using Central Composite Design (CCD) coupled with Response Surface Methodology (RSM) to optimize the TN removal rate. Results showed that the one-stage PN/A process achieved an optimal TN removal rate of 87.3% and an optimal NH4+-N removal rate of 100% when C/N, DO, and HRT were 1, 0.5 mg/L, and 72 h, respectively. The quadratic regression model developed (p = 0.0018) perfectly fitted the nitrogen removal efficiency of the SBBR. The uncertainty analysis showed an error range of 0.12% to 0.96% for the model's accuracy within the DO, C/N ratio, and HRT ranges tested. The bacterial consortium analysis suggested that the control of the growth of ammonium oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) was achieved. Keywords: Anammox, Comammox, Nitrospira, Partial nitrification, Poultry litter wastewater.
{"title":"Evaluation of the Combined C/N ratio, DO Set Point, and HRT Influence on Nitrogen Removal Rate in One-Stage Reactor Through Partial Nitrification Anammox Process During Treatment of Synthetic Digestate of Poultry Litter Wastewater","authors":"Yiting Xiao, Yuanhang Zhan, Jun Zhu, M. Vanotti","doi":"10.13031/ja.15019","DOIUrl":"https://doi.org/10.13031/ja.15019","url":null,"abstract":"Highlights A one-stage reactor PN/A process was developed and evaluated. The highest TN removal rate was 87.3% for the PN/A process to treat synthetic wastewater containing poultry litter at room temperature. Bacterial composition of mature sludge community of wastewater was investigated in this study. Adjusted parameters controlled the growth of AOB and NOB. Abstract. Anammox is an increasingly common process used for the treatment of municipally rejected water and even mainstream wastewater due to its low oxygen demand. However, anammox is not commonly utilized in the treatment of poultry litter because of its high organic content, which would inhibit the anammox process. One-stage partial nitrification and anammox (PN/A) process was developed and evaluated for removing total nitrogen (TN) content from synthetic digestate of poultry litter using a sequencing batch biofilm reactor (SBBR). Independent variables including carbon to nitrogen ratio (C/N) at 1, 2, and 3, dissolved oxygen level (DO, mg/L) at 0.2, 0.35, and 0.5, and hydraulic retention time (HRT, h) at 24, 48, and 72 were examined using Central Composite Design (CCD) coupled with Response Surface Methodology (RSM) to optimize the TN removal rate. Results showed that the one-stage PN/A process achieved an optimal TN removal rate of 87.3% and an optimal NH4+-N removal rate of 100% when C/N, DO, and HRT were 1, 0.5 mg/L, and 72 h, respectively. The quadratic regression model developed (p = 0.0018) perfectly fitted the nitrogen removal efficiency of the SBBR. The uncertainty analysis showed an error range of 0.12% to 0.96% for the model's accuracy within the DO, C/N ratio, and HRT ranges tested. The bacterial consortium analysis suggested that the control of the growth of ammonium oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) was achieved. Keywords: Anammox, Comammox, Nitrospira, Partial nitrification, Poultry litter wastewater.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"150 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79029057","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}
S. S. Kachout, S. Youssef, S. Khnissi, K. Guenni, A. Zoghlami, A. Ennajah, N. Ghorbel, J. Anchang, N. Hanan
Highlights Defoliation initiates physiological recovery and chemical defense mechanisms in Phalaris aquatica. Under infrequent defoliation treatment, P. aquatica has high DM production. Defoliation severity on herbage regrowth was associated with variation of secondary metabolite content and antioxidant activity. Phalaris may be suited to conservation pasture systems; the interval between cuts is about six weeks to maximize rates of regrowth. Results indicate that Phalaris may be used as fodder crop to sustained production and food security. Abstract. Perennial grasses are the key to the economic and environmental sustainability of pastures for livestock, and in arid and semi-arid environments, they can provide multiple ecosystem services more effectively than production systems based on annual crops. The objective of this study was to evaluate the effect of different defoliation frequencies on forage production and nutritive value of the Phalaris aquatica L. variety Soukra under field conditions in Tunis, Tunisia, over a period of 12 weeks. We tested four defoliation frequencies: (1) severe, (2) moderate, (3) infrequent, and (4) control. The growth responses measured were plant tiller number (NT), dry matter production (DM), and relative leaf regrowth rate (RLR). DM under the severe and moderate defoliation frequencies was 7% and 41% less than under control defoliation, respectively. However, DM production under infrequent defoliation was 91% and 43% higher than under severe and moderate defoliation. The relative leaf regrowth rate was affected by defoliation frequency; the highest regrowth rate was under severe treatment. However, tillering of P. aquatica was reduced under the severe and moderate frequencies of defoliation. Under increased defoliation frequencies, concentrations of secondary metabolites significantly decreased; total polyphenol content, flavonoid content, and tannin contents were higher in control and infrequent than in moderate and severe treatments. Antioxidant activity also decreased significantly with defoliation compared to the control treatment. There were no significant differences (P > 0.05) in ABTS (3-ethylbenzothiazoline-6-sulfonic acid) among the defoliation frequencies. Pearson's r correlation and PCA (Principal component analysis) data revealed that growth parameters, secondary metabolites, and antioxidant activity have positive and negative correlations in distinguishing the control and defoliation treatments. Results indicate that P. aquatica management should target moderate harvest rates in the adoption of perennial grass forage production systems in Tunisia. Use of perennial grasses for forage production can contribute to sustained production, food security, and rural livelihoods, and move farming systems towards providing multiple economic, environmental, and social benefits. Keywords: ABTS, Defoliation frequency, DPPH, Flavonoids, Growth responses, Matter production, Pe
{"title":"Growth Responses of the Perennial Grass, Phalaris Aquatica L., to Cutting Frequency and Influence on Secondary Metabolites and Antioxidant Activity","authors":"S. S. Kachout, S. Youssef, S. Khnissi, K. Guenni, A. Zoghlami, A. Ennajah, N. Ghorbel, J. Anchang, N. Hanan","doi":"10.13031/ja.15370","DOIUrl":"https://doi.org/10.13031/ja.15370","url":null,"abstract":"Highlights Defoliation initiates physiological recovery and chemical defense mechanisms in Phalaris aquatica. Under infrequent defoliation treatment, P. aquatica has high DM production. Defoliation severity on herbage regrowth was associated with variation of secondary metabolite content and antioxidant activity. Phalaris may be suited to conservation pasture systems; the interval between cuts is about six weeks to maximize rates of regrowth. Results indicate that Phalaris may be used as fodder crop to sustained production and food security. Abstract. Perennial grasses are the key to the economic and environmental sustainability of pastures for livestock, and in arid and semi-arid environments, they can provide multiple ecosystem services more effectively than production systems based on annual crops. The objective of this study was to evaluate the effect of different defoliation frequencies on forage production and nutritive value of the Phalaris aquatica L. variety Soukra under field conditions in Tunis, Tunisia, over a period of 12 weeks. We tested four defoliation frequencies: (1) severe, (2) moderate, (3) infrequent, and (4) control. The growth responses measured were plant tiller number (NT), dry matter production (DM), and relative leaf regrowth rate (RLR). DM under the severe and moderate defoliation frequencies was 7% and 41% less than under control defoliation, respectively. However, DM production under infrequent defoliation was 91% and 43% higher than under severe and moderate defoliation. The relative leaf regrowth rate was affected by defoliation frequency; the highest regrowth rate was under severe treatment. However, tillering of P. aquatica was reduced under the severe and moderate frequencies of defoliation. Under increased defoliation frequencies, concentrations of secondary metabolites significantly decreased; total polyphenol content, flavonoid content, and tannin contents were higher in control and infrequent than in moderate and severe treatments. Antioxidant activity also decreased significantly with defoliation compared to the control treatment. There were no significant differences (P > 0.05) in ABTS (3-ethylbenzothiazoline-6-sulfonic acid) among the defoliation frequencies. Pearson's r correlation and PCA (Principal component analysis) data revealed that growth parameters, secondary metabolites, and antioxidant activity have positive and negative correlations in distinguishing the control and defoliation treatments. Results indicate that P. aquatica management should target moderate harvest rates in the adoption of perennial grass forage production systems in Tunisia. Use of perennial grasses for forage production can contribute to sustained production, food security, and rural livelihoods, and move farming systems towards providing multiple economic, environmental, and social benefits. Keywords: ABTS, Defoliation frequency, DPPH, Flavonoids, Growth responses, Matter production, Pe","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"163 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77788761","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}
Nitin Rai, Xin Sun, C. Igathinathane, Kirk Howatt, Michael Ostlie
Highlights Lightweight deep learning models were trained on an edge device to identify weeds in aerial images. A customized configuration file was setup to train the models. These models were deployed to detect weeds in aerial images and videos (near real-time). CSPMobileNet-v2 and YOLOv4-lite are recommended models for weed detection using edge platform. Abstract. Deep learning (DL) techniques have proven to be a successful approach in detecting weeds for site-specific weed management (SSWM). In the past, most of the research work has trained and deployed pre-trained DL models on high-end systems coupled with expensive graphical processing units (GPUs). However, only a limited number of research studies have used DL models on an edge system for aerial-based weed detection. Therefore, while focusing on hardware cost minimization, eight DL models were trained and deployed on an edge device to detect weeds in aerial-image context and videos in this study. Four large models, namely CSPDarkNet-53, DarkNet-53, DenseNet-201, and ResNet-50, along with four lightweight models, CSPMobileNet-v2, YOLOv4-lite, EfficientNet-B0, and DarkNet-Ref, were considered for training a customized DL architecture. Along with trained model performance scores (average precision score, mean average precision (mAP), intersection over union, precision, and recall), other model metrics to assess edge system performance such as billion floating-point operations/s (BFLOPS), frame rates/s (FPS), and GPU memory usage were also estimated. The lightweight CSPMobileNet-v2 and YOLOv4-lite models outperformed others in detecting weeds in aerial image context. These models were able to achieve a mAP score of 83.2% and 82.2%, delivering an FPS of 60.9 and 61.1 during near real-time weed detection in aerial videos, respectively. The popular ResNet-50 model achieved a mAP of 79.6%, which was the highest amongst all the large models deployed for weed detection tasks. Based on the results, the two lightweight models, namely, CSPMobileNet-v2 and YOLOv4-lite, are recommended, and they can be used on a low-cost edge system to detect weeds in aerial image context with significant accuracy. Keywords: Aerial image, Deep learning, Edge device, Precision agriculture, Weed detection.
{"title":"Aerial-Based Weed Detection Using Low-Cost and Lightweight Deep Learning Models on an Edge Platform","authors":"Nitin Rai, Xin Sun, C. Igathinathane, Kirk Howatt, Michael Ostlie","doi":"10.13031/ja.15413","DOIUrl":"https://doi.org/10.13031/ja.15413","url":null,"abstract":"Highlights Lightweight deep learning models were trained on an edge device to identify weeds in aerial images. A customized configuration file was setup to train the models. These models were deployed to detect weeds in aerial images and videos (near real-time). CSPMobileNet-v2 and YOLOv4-lite are recommended models for weed detection using edge platform. Abstract. Deep learning (DL) techniques have proven to be a successful approach in detecting weeds for site-specific weed management (SSWM). In the past, most of the research work has trained and deployed pre-trained DL models on high-end systems coupled with expensive graphical processing units (GPUs). However, only a limited number of research studies have used DL models on an edge system for aerial-based weed detection. Therefore, while focusing on hardware cost minimization, eight DL models were trained and deployed on an edge device to detect weeds in aerial-image context and videos in this study. Four large models, namely CSPDarkNet-53, DarkNet-53, DenseNet-201, and ResNet-50, along with four lightweight models, CSPMobileNet-v2, YOLOv4-lite, EfficientNet-B0, and DarkNet-Ref, were considered for training a customized DL architecture. Along with trained model performance scores (average precision score, mean average precision (mAP), intersection over union, precision, and recall), other model metrics to assess edge system performance such as billion floating-point operations/s (BFLOPS), frame rates/s (FPS), and GPU memory usage were also estimated. The lightweight CSPMobileNet-v2 and YOLOv4-lite models outperformed others in detecting weeds in aerial image context. These models were able to achieve a mAP score of 83.2% and 82.2%, delivering an FPS of 60.9 and 61.1 during near real-time weed detection in aerial videos, respectively. The popular ResNet-50 model achieved a mAP of 79.6%, which was the highest amongst all the large models deployed for weed detection tasks. Based on the results, the two lightweight models, namely, CSPMobileNet-v2 and YOLOv4-lite, are recommended, and they can be used on a low-cost edge system to detect weeds in aerial image context with significant accuracy. Keywords: Aerial image, Deep learning, Edge device, Precision agriculture, Weed detection.","PeriodicalId":29714,"journal":{"name":"Journal of the ASABE","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135600667","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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