Journal of the ASABE最新文献

{"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":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":"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}

{"title":"Microcystin Shows Thresholds and Hierarchical Structure With Physicochemical Properties at Lake Fayetteville, Arkansas, May Through September 2020","authors":"B. Haggard, E. Grantz, B. Austin, A. Lasater, L. Haddock, Alyssa M. Ferri, Nicole D. Wagner, J. Scott","doi":"10.13031/ja.15273","DOIUrl":"https://doi.org/10.13031/ja.15273","url":null,"abstract":"Highlights Despite little to no dissolved nutrient supply in surface water, harmful algal blooms are sustained throughout the 2020 growing season. Sediment phosphorus release was high in a lake that has annual harmful algal blooms, and it is an important piece of the watershed management puzzle. Thresholds and hierarchical structure with individual physicochemical properties and pigment fluorescence at this lake explain a large portion of microcystin variability. Abstract. Harmful algal blooms (HABs) in freshwaters are a global concern, and research has focused on the nutrient drivers of cyanobacterial growth and toxin production. We explored the importance of nutrients on sustained cyanobacterial HABs producing measurable microcystin at Lake Fayetteville, Arkansas, USA. The specific objectives were to (1) quantify sediment phosphorus (P) flux and estimate potential equilibrium P concentrations (EPC0) in July 2020, (2) assess water quality conditions in the lake from March through September 2020, and (3) evaluate physicochemical thresholds (or change points, CPs) and hierarchical structure with total microcystin concentrations. The sediments were a potential P source under both oxic and anoxic conditions, and the SRP concentrations in the lake water were continuously less than the EPC0 estimated for bottom sediment (~0.03 mg L-1); sediments are likely a potential P source for cyanobacterial HABs at Lake Fayetteville. The physicochemical changes at Lake Fayetteville over the 2020 growing season were typical of small, hypereutrophic reservoirs, with low biomass in winter when nutrient supply was greatest and the greatest cyanobacterial growth and microcystin toxin as nutrient supply diminished into the growing season. Microcystin concentrations were elevated above 1 µg L-1 from mid-June through mid-August 2020, and most physicochemical parameters in this study showed thresholds or change points with microcystin. Hierarchical structure existed with total microcystin concentrations, showing the potential importance of cyanobacterial biomass, N supply, and total P on elevated microcystin. Nutrients and algal pigment raw fluorescence explained 83% of the variation in total microcystin concentrations at Lake Fayetteville during the 2020 growing season. Nutrients (both N and P) from external and internal sources are likely important drivers of these blooms and toxicity at Lake Fayetteville. Keywords: Harmful Algal Blooms, Nutrient Drivers, Sediment Phosphorus Release, 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":"75323174","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}

{"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":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":"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}

{"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":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":"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}

{"title":"A Methodology for Combine Performance Analyses in Wheat Harvests with GNSS Data","authors":"Yang Wang, Yaguang Zhang, Dennis R. Buckmaster, James V. Krogmeier","doi":"10.13031/ja.15388","DOIUrl":"https://doi.org/10.13031/ja.15388","url":null,"abstract":"Highlights Proposed a novel methodology for fully automated, low-cost, and high-resolution harvest performance analyses. Described methods for estimating key features, such as the center of the header, using noisy positioning data. Introduced metrics Swath Utilization and Spatial Field Capacity to evaluate temporal and spatial performances. Provided case studies of using these two new metrics to compare combine performances by machines and by years. Abstract. Combine harvesters’ performance during wheat harvests can be analyzed using various methods. These methods typically rely on traditional field-level metrics, such as those defined by ASABE, to address average performances in terms of field or machine. However, next-generation digital agriculture technologies have significantly increased the operation precision of agricultural activities. As a result, the evaluation of instantaneous performance becomes possible. This work introduces a novel methodology that enables fully automated, low-cost, and high-resolution (both in time and space) instantaneous combine performance analyses based on global navigation satellite system (GNSS) positioning records. The methodology incorporates a multi-step, easy-to-follow workflow with customizable modules for efficient and effective data processing. This way, the computation of traditional field capacity metrics can be fully automated even if multiple combines cooperate in harvesting the same field. Furthermore, two groups of novel metrics are proposed: Swath Utilization and Spatial Field Capacity. They enhance traditional metrics by analyzing machine performances both temporally and spatially on a finer scale. As a case study, we computed these metrics for seven fields in Colorado, USA, during wheat harvests across five different years. We compared the results with typical values from ASABE standards to validate the correctness of our data processing methodology. We also provided four analysis examples with a rich set of temporal and spatial visualizations to showcase how our metrics can accurately assess combine performances, quantitatively uncover harvest details, and effectively compare operations in different fields/years for better practice. These new analyses enabled by our methodology are required to harness the full potential of digital agriculture. Keywords: Combine harvester, Field capacity, Global navigation satellite system (GNSS), Kalman filter, Optimization, Positioning data, Wheat harvest performance.","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":"135710170","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}

{"title":"Corn Yield Increase Under Constant Fertilizer Did Not Reduce Nitrate Export","authors":"Chelsea Connair Clifford, Emily R. Waring, Carl H. Pederson, Matthew J. Helmers","doi":"10.13031/ja.15538","DOIUrl":"https://doi.org/10.13031/ja.15538","url":null,"abstract":"Highlights Corn yields increased from 1989 to 2021 in Iowa experimental plots at nitrogen fertilizer rates consistently just above current recommendations. Increased corn yields did not result in a decrease in drainage nitrate exports. Findings required long-term (>10 years) experiments and monitoring. Abstract. Aquatic problems from the export of nutrients, especially nitrate, from row crops are recalcitrant in the Mississippi-Atchafalaya River Basin and globally severe. Previous studies have proposed to reduce these problems in part by improving crop yields, particularly corn, leaving less nitrate surplus to export. Simultaneous increases in fertilizer application rates and grain yields in recent decades have made testing this notion with large-scale agricultural statistics difficult. This experiment in Iowa featured a corn-soybean rotation with corn fertilized with nitrogen at a nearly consistent rate from 1989 to 2021. Corn yields increased at a rate not statistically distinguishable from the surrounding county’s (144 vs. 148 kg ha-1 yr-1), but drainage nitrate concentration and loading remained flat overall, oscillating with precipitation. Results suggest that increasing corn yield, and thereby partial factor productivity, with standard shifts in cultivars over time, cannot alone solve the U.S. Corn Belt’s nitrate surplus problem, supporting previous recommendations for active and multi-layered conservation efforts. Five- to ten-year positive and negative sub-trends in nitrate export within the longer dataset reaffirm the importance of truly long-term experiments and monitoring to accurately assess the impacts of management. Keywords: Keywords., Corn, Loading, Nitrate, Water quality, Yield.","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":"136003843","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}

{"title":"High-Power Short Duration Microwave Drying of Rice Versus Fissuring and Milling Yields","authors":"S. Boreddy, K. Luthra, G. Atungulu","doi":"10.13031/ja.15410","DOIUrl":"https://doi.org/10.13031/ja.15410","url":null,"abstract":"Highlights MW specific energy ranging from 422.5 to 507.0 kJ/kg of rice can dry rice to 12.5% moisture content in a single pass. Fissuring percentage was significantly lower for lower drying durations as compared to 3 min drying durations for all power levels. RR dried for one minute with MW at 16-20 kW results in higher head rice yields. Abstract. The utilization of microwave (MW) drying technology to dry rough rice (RR) is considered a promising method for high-moisture RR drying with high throughput. Milling quality is a significant factor in stakeholders adoption of this method. Therefore, experiments were conducted using an industrial MW dryer operating at 915 MHz to examine the effects of different MW power levels and heating durations on RR drying. Single pass drying was performed using 16, 18, and 20 kW power levels and 1, 2, and 3 min heating durations. A control sample was dried in an environmentally controlled chamber at 25°C and 56% relative humidity (RH). The moisture content, surface temperature, fissuring, and head rice yield (HRY) of RR were measured. The initial moisture content of RR was 21.22% w.b. The moisture content of RR after 3 minutes of drying at the studied power levels was close to the recommended rice milling moisture content of 13%, indicating the feasibility of single pass MW drying. The maximum surface temperature of RR at severe (20 kW for 3 min) and least severe (16 kW and 1 min) treatment conditions was 91.9°C and 62.6°C, respectively. Fissuring percentages of 86.2% and 85.3% were observed in RR drying at 20 kW for 3 min after one day and after seven days of fissure examination, respectively. Fissuring percentages of 84.2% and 84.3% were observed at 16 kW for 3 min drying after one day and after seven days, respectively. The HRY at MW drying conditions of 16-20 kW for 1 min was higher than that of RR gently dried at 25°C and 56% RH. MW drying shows promise for reducing drying duration compared to conventional methods. Keywords: Head rice yield, Microwave drying, Moisture content, Rice drying, Rice fissuring.","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":"86607043","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}

{"title":"Modeling Neonatal Piglet Rectal Temperature with Thermography and Machine Learning","authors":"Y. Xiong, Guoming Li, Naomi C Willard, Michael Ellis, R. Gates","doi":"10.13031/ja.14998","DOIUrl":"https://doi.org/10.13031/ja.14998","url":null,"abstract":"Highlights The rectal temperature and maximum ear base temperature were measured for neonatal piglets after birth. Piglets’ rectal temperature dropped on average 5.1 °C and reached 33.6 °C 30-min after birth. Machine learning algorithms were evaluated to predict piglet rectal temperature using ear temperatures. Machine learning model performance was compared to that of a direct regression using maximum ear base temperature. The best machine learning model was 0.2°C more accurate than the direct linear regression model. Abstract. Piglet body temperature can drop rapidly after birth, and the magnitude of this drop can delay recovery to homoeothermic status and compromise the vigor of piglets. Understanding piglet body temperature changes provides critical insights into piglet thermal comfort management and preweaning mortality prevention. However, measuring neonatal piglet body temperature at birth is not generally practical in production facilities, and alternative sensing and modeling methods should be explored. The objectives of this research were to (1) quantify the rectal temperature of wet neonatal piglets without any drying treatments across the first day of birth; (2) develop and evaluate thermography and machine learning models to predict piglet rectal temperature within the same period; and (3) compare the machine learning model’s performance with a simple regression model using the piglets’ thermographic information. Rectal temperatures and thermal images of the back of the ears were obtained at 0, 15, 30, 45, 60, 90, 120, 180, 240, and 1440 minutes after birth for 99 neonatal piglets from 9 litters. Maximum ear base temperature extracted from thermal images, piglet gender, initial weight, and environmental variables (room temperature, relative humidity, and wet-bulb temperature) were used as inputs for machine learning model evaluation. A simple regression and fourteen machine learning models were compared for their performance in predicting piglets’ rectal temperature. Piglets dropped an average of 5.1°C in rectal temperature and reached the lowest temperature (33.6 ± 2.2°C) 30 (±15) minutes after birth, demonstrating a significant reduction from their birth rectal temperature (38.7 ± 0.8°C). The maximum ear base temperature had the highest feature importance score (= 0.606) among all input variables for the machine learning model’s development. A direct regression of maximum ear base temperature against measured rectal temperature produced a standard error of prediction of 1.7°C, while the best-performing machine-learning model (the Lasso regressor) produced a standard error of prediction of 1.5°C. Either prediction model is appropriate, with the direct regression model being more straightforward for field application. Keywords: Computer vision, Farrowing, Precision livestock farming, Pre-wean mortality.","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":"87797346","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}

{"title":"Terminal Velocity of Corn Stover Stem Fractions","authors":"Alvin C. Womac, S. E. Klasek, D. Yoder, Doug G. Hayes","doi":"10.13031/ja.15340","DOIUrl":"https://doi.org/10.13031/ja.15340","url":null,"abstract":"Highlights Terminal velocity was measured for small, standardized sizes of corn stover stem fractions with a vertical wind tunnel built to aerodynamically suspend particles. Mean terminal velocity ranged from 2.84 m s-1 to 7.74 m s-1 for dry pith-internode and wet rind-node fractions, respectively. Anticipated separation of corn stover stem particles using terminal velocity differences was viable for dry (11% w.b.) particles of pith, rind, node, and internode. But, many wet (43% w.b.) fractions had similar terminal velocities, thereby reducing separation propensity. Abstract. Terminal velocity of corn stover stem fractions was determined for particles standardized to match particle sizes (1.3 cm long x 0.31 cm diameter) of switchgrass nodes and internodes. The practical application was to measure the potential aerodynamic conditions for sorting and separating size-reduced anatomical components of pith versus rind, node versus internode, and at two moisture contents (11% and 43%, wet basis). Terminal velocities grouped by dry pith, wet pith, dry rind, and wet rind resulted in a trend of increased mean terminal velocities of 3.28, 5.31, 6.38, and 7.68 m s-1, respectively, when averaged across node and internode. The increased moisture and the selection of the rind component had increased terminal velocity that was attributed to increased particle density. Terminal velocity for a node was generally statistically greater than that of an internode for a given condition, except for the statistically-equal terminal velocities for node and internode of wet rind. Also, terminal velocity for internode of dry pith and of wet pith were statistically equal. Thus, exceptions to the general trends were discovered. Mean terminal velocity ranged from 2.84 m s-1 to 7.74 m s-1 for dry pith-internode and wet rind—node particles, respectively. Practical separation of corn stover stem particles using terminal velocity differences was viable for dry (11% w.b.) particles of pith, rind, node, and internode. Many terminal velocities of wet (43% w.b.) fractions were statistically equal leaving only wet pith-internode available at this moisture for aerodynamic separation. Particle density varied almost 10-fold for the experiment, and this was attributed to the various anatomical component and range of moisture content. Highly significant correlations of particle density with terminal velocity may have represented a cause-and-effect factor. Keywords: Anatomical component, Biomass property, Corn Stover, Physical experiment, Separation, Sorting, Vertical wind tunnel.","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":"85227492","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}

{"title":"Effects of Soil Data Accuracy on Outputs of Irrigation Scheduling Tools","authors":"Mukesh Mehata, S. Datta, S. Taghvaeian, A. Mirchi, D. Moriasi","doi":"10.13031/ja.15323","DOIUrl":"https://doi.org/10.13031/ja.15323","url":null,"abstract":"Highlights The effects of soil data accuracy on estimated water fluxes by an irrigation scheduling model were investigated. Free and frequently used web soil survey (WSS) soil textural data underestimated sand particles in 89% of cases. Forty-nine percent of the estimated differences in seasonal irrigation based on WSS and measured soil data were within ±25 mm. In most cases, use of WSS data resulted in larger evaporation, smaller deep percolation, and larger runoff compared to those based on measured soil data. Abstract. A widely used irrigation scheduling method is based on modeling soil water balance, which requires several key inputs, including soil data. Many scheduling tools developed using this method rely on publicly available soil data, such as the United States Department of Agriculture's Web Soil Survey (WSS). While soil survey data are a valuable source of information for general farm and natural resource planning and management at large scales, inaccuracies in soil conditions at field and subfield scales can hamper efficient agricultural water management through irrigation scheduling tools. To illuminate the implications of the localized inaccuracies, this study estimated the errors in WSS soil textural data at 18 sites in three regions of western Oklahoma through comparison with in-situ sampling (ISS) data. The effects of errors on estimated water fluxes were also investigated for dominant crops of each region over a 15-year (2006-2020) period. The findings demonstrated that WSS soil textures were finer than ISS at most sites and soil layers, resulting in generally greater root zone total available water estimates. Differences in seasonal irrigation demand estimates when WSS data were used instead of ISS reached 20% at one site but were within ±9% among the regions. Half of the estimated seasonal irrigation differences for all sites, years, and crops were within ±25 mm. Soil evaporation, deep percolation, and runoff fluxes were also impacted by soil data source, albeit to a smaller degree than irrigation, at levels and directions (over or underestimation) that were dependent on the sign and magnitude of WSS errors, as well as precipitation amounts and timing. Overall, errors in WSS data may not have a major impact at regional scales, but the effects on individual irrigated farms may be severe depending on the magnitude of difference between WSS data and true soil conditions. Keywords: Irrigation demand, Soil water balance, SSURGO, Water fluxes, Web soil survey.","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":"91241208","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}