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At least 1,117 records · Page 62

SIF and Vegetation Indices in the US Midwestern Agroecosystems, 2016-2021, Carbon Monitoring System (CMS)

This dataset contains half-hourly ground solar-induced chlorophyll fluorescence (SIF) and vegetation indices including NDVI, EVI, Red edge chlorophyll index, green chlorophyll index, and photochemical reflectance index at seven crop sites in Nebraska and Illinois for the period 2016-2021. Four sites were located at Eddy Covariance (EC) tower sites (sites US-Ne2, US-Ne3, US-UiB, and US-UiC), and three sites were located on private farms (sites Reifsteck, Rund, and Reinhart). The sites were either miscanthus, corn-soybean rotation or corn-corn-soybean rotation. The spectral data for SIF retrieval and hyperspectral reflectance for vegetation index calculation were collected by the FluoSpec2 system, installed near planting, and uninstalled after harvest to collect whole growing-season data. Raw nadir SIF at 760 nm from different algorithms (sFLD, 3FLD, iFLD, SFM) are included. SFM_nonlinear and SFM_linear represent the Spectral fitting method (SFM) with the assumption that fluorescence and reflectance change with wavelength non-linearly and linearly, respectively. Additional data include two SIF correction factors including calibration coefficient adjustment factor (f_cal_corr_QEPRO) and upscaling nadir SIF to eddy covariance footprint factor (ratio_EC footprint, SIF pixel), and measured FPAR from quantum sensors and Rededge NDVI calculated FPAR. The data are provided in comma-separated values (CSV) format.

Ameriflux↗

Chemical and Structural Changes in Corn Stover After Ensiling: Influence on Bioconversion

Production of biofuels, bioproducts, and bioenergy requires a well-characterized, stable, and reasonably uniform biomass supply and well-established supply chains for shipping biomass from farm fields to biorefineries, while achieving year-round production targets. Preserving and stabilizing biomass feedstock during storage is a necessity for cost-effective and sustainable biofuel production. Ensiling is a common storage method used to preserve and even improve forage quality; however, the impact of ensiling on biomass physical and chemical properties that influence bioconversion processes has been variable. Our objective in this work was to determine the effects of ensiling on lignocellulosic feedstock physicochemical properties and how that influences bioconversion requirements. We observed statistically significant decreases (p < 0.05) in the content of two major structural carbohydrates (glucan and xylan) of 5 and 8%, respectively, between the ensiled and non-ensiled materials. We were unable to detect differences in sugar yields from structural carbohydrates after pretreatment and enzymatic hydrolysis of the ensiled materials compared to non-ensiled controls. Based on this work, we conclude that ensiling the corn stover did not change the bioconversion requirements compared to the control samples and incurred losses of structural carbohydrates. At the light microscopy level, ensiled corn stover exhibited little structural change or relocation of cell wall components as detected by immunocytochemistry. However, more subtle structural changes were revealed by electron microscopy, as ensiled cell walls exhibit ultrastructural characteristics such as wall delimitation intermediate between non-ensiled and dilute-acid-pretreated cell walls. These findings suggest that alternative methods of conversion, such as deacetylation and mechanical refining, could take advantage of lamellar defects and may be more effective than dilute acid or hot water pretreatment for biomass conversion of ensiled materials.

09 BIOMASS FUELS↗

Hofmeister Effect in RT-QuIC Seeding Activity of Chronic Wasting Disease Prions

Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy (TSE) that causes a fatal neurodegenerative disease in cervids. Cases of CWD are rapidly increasing in North America among wild and farmed cervid populations, and potential for zoonotic transmission is not yet determined. Therefore, in order to manage the disease, it is imperative to devise a system that can detect CWD during its early phases to prevent spread to new captive herds through introduction of CWD-affected animals into otherwise CWD-free herds. Real-time quaking–induced conversion (RT-QuIC) assays have been applied to detect the presence of disease-associated prions from various samples in both animals and humans. In this study, we have tested the use of five Hofmeister anions that range from weakly hydrating to strongly hydrating: Na 3 citrate, Na 2 SO 4 , NaCl, NaI, and NaClO 4 in RT-QuIC reactions for CWD seeding activity using different recombinant prion proteins as substrates. This work shows how the ionic environment of the RT-QuIC reaction can enhance or diminish the seeding activity. The use of Na 2 SO 4 or NaI as the sodium salt for RT-QuIC using bank vole recombinant prion substrate for the detection of CWD using brain samples reduces the lag time to detect with reasonable specificity. For detection of the CWD in fecal samples, only NaI showed comparable reduction in lag time relative to NaCl but required reduced temperature to alleviate spontaneous fibril formation in negative control samples. Selection of the proper ion environment and recombinant prion protein substrate will make RT-QuIC a powerful diagnostic tool for early detection of CWD prions, further supporting CWD surveillance in wild and captive cervids.

59 BASIC BIOLOGICAL SCIENCES↗

The transmission ramifications of social and environmental siting considerations on wind energy deployment

Increasing the capacity of wind power is critical to achieving climate goals, however its continued deployment faces environmental and social siting challenges. For example, the United States government is increasingly emphasizing the importance of a just energy transition by considering the social impacts of energy and environmental justice (EEJ). In this study, we investigate the impact of considering available EEJ metrics and environmental impacts into siting wind power and transmission by applying SimWIND PRO . SimWIND PRO is an infrastructure optimization tool that can site wind energy technologies and transmission by concurrently considering wind resource potential, transmission costs, EEJ, and environmental impacts. We demonstrate the impacts of considering EEJ and environmental factors in the context of Midcontinent Independent System Operator’s (MISO) western region, which includes some of the best wind energy potential in the United States. We show that prioritizing EEJ and environmental considerations in wind deployment can result in exponentially more transmission deployment for the same amount of wind power delivered, and results in selecting different wind farm sites. Our results also show that, depending on how it is considered, it is possible that constraining sites based on EEJ and environmental factors can reduce the available capacity of wind energy enough that energy transition capacity targets cannot be met.

17 WIND ENERGY↗

Modeling Yield, Biogenic Emissions, and Carbon Sequestration in Southeastern Cropping Systems With Winter Carinata

Sustainable aviation fuel (SAF) production from lipids is a technologically mature approach for replacing conventional fossil fuel use in the aviation sector, and there is increasing demand for such feedstocks. The oilseed Brassica carinata (known as Ethiopian mustard or simply carinata) is a promising SAF feedstock that can be grown as a supplemental cash crop over the winter fallow season of various annual crop rotations in the Southeast US, avoiding land use changes and potentially achieving some of the soil carbon sequestration and ecosystem service benefits of winter cover crops. However, carinata may require more intensive management than traditional cover crops, potentially leading to additional soil greenhouse gas (GHG) emissions through increased carbon losses from soil tillage and nitrous oxide (N 2 O) emissions from nitrogen fertilizer application. In this work, the 2017 version of the process-based DayCent ecosystem model was used to establish initial expectations for the total regional SAF production potential and associated soil GHG emissions when carinata is integrated as a winter crop into the existing crop rotations across its current suitability range in southern Alabama, southern Georgia, and northern Florida. Using data from academic and industry carinata field trials in the region, DayCent was calibrated to reproduce carinata yield, nitrogen response, harvest index, and biomass carbon-to-nitrogen ratio. The resulting model was then used to simulate the integration of carinata every third winter across all 2.1 Mha of actively cultivated cropland in the study area. The model predicted regional average yields of 2.9–3.0 Mg carinata seed per hectare depending on crop management assumptions. That results in the production of more than two million Mg of carinata seed annually across the study area, enough to supply approximately one billion liters of SAF. Conventional management of carinata led to only modest increases in soil carbon storage that were largely offset by additional N2O emissions. Climate-smart management via adopting no-till carinata establishment or using poultry litter as a nitrogen source resulted in a substantial net soil GHG sink (0.23–0.31 Mg CO 2 e ha -1 y -1 , or 0.24–0.32 Mg CO2e per Mg of seed produced) at the farms where carinata is cultivated.

54 ENVIRONMENTAL SCIENCES↗

Perennializing marginal croplands: going back to the future to mitigate climate change with resilient biobased feedstocks

Managing annual row crops on marginally productive croplands can be environmentally unsustainable and result in variable economic returns. Incorporating perennial bioenergy feedstocks into marginally productive cropland can engender ecosystem services and enhance climate resiliency while also diversifying farm incomes. We use one of the oldest bioenergy-specific field experiments in North America to evaluate economically and environmentally sustainable management practices for growing perennial grasses on marginal cropland. This long-term field trial called 9804 was established in 1998 in eastern Nebraska and compared the productivity and sustainability of corn (Zea mays L.)—both corn grain and corn stover—and switchgrass (Panicum virgatum L.) bioenergy systems under different harvest strategies and nitrogen (N) fertilizer rates. This experiment demonstrated that switchgrass, compared to corn, is a reliable and sustainable bioenergy feedstock. This experiment has been a catalyst for other bioenergy projects which have also expanded our understanding of growing and managing bioenergy feedstocks on marginal cropland. We (1) synthesize research from this long-term experiment and (2) provide perspective concerning both the knowledge gained from this experiment and knowledge gaps and how to fill them as well as the role switchgrass will play in the future of bioenergy.

09 BIOMASS FUELS↗

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗

Tidal energy extraction modifies tidal asymmetry and transport in a shallow, well-mixed estuary

Tidal energy extraction is increasingly being studied as a potential renewable energy resource in estuaries worldwide. Although it is understood that energy extraction via tidal stream turbines can modify currents and transport within estuaries, it is not clear how the underlying nonlinear physical mechanisms dictating tidal hydrodynamics are modulated. This research investigates the influence of a hypothetical tidal stream turbine array on barotropic tidal processes in a shallow, well-mixed system: the Piscataqua River – Great Bay (PRGB) estuary, using a numerical model. The modeled turbine farm includes 180 turbines which would extract an estimated 44.7 GWh of energy, annually. The tidal hydrodynamic model for the existing condition is validated with in-situ observations of currents and water level before analyzing tidal asymmetry and transport with and without tidal turbines. Results indicate that the tidal turbine array will decrease tidal elevation and current magnitudes system-wide, but generally reduce ebb currents and transport more than flood over most of the estuary footprint, thereby diminishing tidal asymmetry. The smaller asymmetric distortion compared to the no-turbine case is attributed to reductions in the storage volume of water over the estuary’s extensive tidal flat regions between low and high waters which decreases the associated nonlinear intertidal storage mechanism up to 25%. This leads to weakened ebb dominance over estuary sections from the mouth to mid-reaches, where depths are deep enough to keep the combined nonlinear shallow water and frictional effects from asserting control over the storage mechanism. Even in upstream shallow regions where depth-dependent friction controls asymmetry in both cases, the frictional mechanism is reduced only by 10% with turbines. Some environmental considerations of this work are discussed, with focus on sediment transport, water quality, and ecology.

16 TIDAL AND WAVE POWER↗

Natural Horizontal Gene Transfer of Antimicrobial Resistance Genes in Campylobacter spp. From Turkeys and Swine

Antibiotic-resistant Campylobacter constitutes a serious threat to public health. The clonal expansion of resistant strains and/or the horizontal spread of resistance genes to other strains and species can hinder the clinical effectiveness of antibiotics to treat severe campylobacteriosis. Still, gaps exist in our understanding of the risks of acquisition and spread of antibiotic resistance in Campylobacter. While the in vitro transfer of antimicrobial resistance genes between Campylobacter species via natural transformation has been extensively demonstrated, experimental studies have favored the use of naked DNA to obtain transformants. In this study, we used experimental designs closer to real-world conditions to evaluate the possible transfer of antimicrobial resistance genes between Campylobacter strains of the same or different species (Campylobacter coli or Campylobacter jejuni) and originating from different animal hosts (swine or turkeys). This was evaluated in vitro through co-culture experiments and in vivo with dual-strain inoculation of turkeys, followed by whole genome sequencing of parental and newly emerged strains. In vitro, we observed four independent horizontal gene transfer events leading to the acquisition of resistance to beta-lactams (blaOXA), aminoglycosides [aph(2")-If and rpsL] and tetracycline [tet(O)]. Observed events involved the displacement of resistance-associated genes by a mutated version, or the acquisition of genomic islands harboring a resistance determinant by homologous recombination; we did not detect the transfer of resistance-carrying plasmids even though they were present in some strains. In vivo, we recovered a newly emerged strain with dual-resistance pattern and identified the replacement of an existing non-functional tet(O) by a functional tet(O) in the recipient strain. Whole genome comparisons allowed characterization of the events involved in the horizontal spread of resistance genes between Campylobacter following in vitro co-culture and in vivo dual inoculation. Our study also highlights the potential for antimicrobial resistance transfer across Campylobacter species originating from turkeys and swine, which may have implications for farms hosting both species in close proximity.

59 BASIC BIOLOGICAL SCIENCES↗

Antimicrobial resistance and genomic characterization of Escherichia coli from pigs and chickens in Zhejiang, China

Escherichia coli is considered an opportunistic pathogen and an indicator for antimicrobial resistance (AMR) monitoring. Despite many reports on its AMR monitoring, studies based on genome-based analysis of AMR genes are still insufficient. Here, 181 E. coli strains were isolated from anal swab samples collected from pigs and chickens of animal farms located in Eastern China and sequenced through the Illumina platform. The results showed that 87.85% (159/181) of the E. coli isolates were multidrug-resistant (MDR). Ampicillin (AMP)- spectinomycin (SPT)- tetracycline (TET)- florfenicol (FFC)- sulfisoxazole (SF)- trimethoprim/sulfamethoxazole (SXT) was the predominant AMR pattern. By whole-genome sequencing, we found that ST10 (10.49%, 19/181) and ST48 (7.18%, 13/181) were major sequence types. IncFIB and IncX1 were the most prevalent plasmid replicons. The AMR genes bla NDM-5 (1.10%, 2/181), mcr -1 (1.10%, 2/181), tet (X4) (1.10%, 2/181), and cfr (6.08%, 11/181) were also found in these isolates. In addition, among the 169 virulence genes detected, we identified ast A (37.02%, 67/181), hly A (1.66%, 3/181), hly B (1.66%, 3/181) and hly D (1.66%, 3/181), which were closely related to heat-stable enterotoxin 1 and α-hemolysin. In addition, there were 33 virulence genes associated with the iron uptake system, and 46 were adhesion-related genes. Our study highlighted the need for routine surveillance of AMR with advanced genomic approaches, providing up-to-date data on the prevalence of AMR for the development and execution of antimicrobial stewardship policy.

Zhou, Wei↗

A triton X-100 assisted PMAxx-qPCR assay for rapid assessment of infectious African swine fever virus

Introduction African Swine Fever (ASF) is a highly infectious disease of pigs, caused by African swine fever virus (ASFV). The lack of vaccines and drugs makes strict disinfection practices to be one of the main measurements to curb the transmission of ASF. Therefore, it is important to assess if all viruses are inactivated after disinfection or after long time exposure in their natural conditions. Currently, the infectivity of ASFV is determined by virus isolation and culture in a biosafety level 3 (BSL-3) laboratory. However, BSL-3 laboratories are not readily available, need skilled expertise and may be time consuming. Methods In this study, a Triton X-100 assisted PMAxx-qPCR method was developed for rapid assessment of infectious ASFV in samples. PMAxx, an improved version of propidium monoazide (PMA), can covalently cross-link with naked ASFV-DNA or DNA inside inactivated ASFV virions under assistance of 0.1% (v/v) TritonX-100, but not with ASFV-DNA inside live virions. Formation of PMAxx-DNA conjugates prevents PCR amplification, leaving only infectious virions to be detected. Under optimum conditions, the limit of detection of the PMAxx-qPCR assay was 2.32log 10 HAD 50 /mL of infectious ASFV. Testing different samples showed that the PMAxx-qPCR assay was effective to evaluate intact ASFV virions after treatment by heat or chemical disinfectants and in simulated samples such as swine tissue homogenate, swine saliva swabs, and environmental swabs. However, whole-blood and saliva need to be diluted before testing because they may inhibit the PCR reaction or the cross-linking of PMAxx with DNA. Conclusion The Triton X-100 assisted PMAxx-qPCR assay took less than 3 h from sample to result, offering an easier and faster way for assessing infectious ASFV in samples from places like pig farms and pork markets.

Liu, Huan↗

The mutation atlas of giant kelp (Macrocystis pyrifera): a mutation database resource for natural knockouts

Giant kelp (Macrocystis pyrifera) is a paramount species of immense ecological and economic importance. It forms dense underwater forests, providing crucial habitat and serving as a foundation species for diverse marine ecosystems. Understanding the genetics of giant kelp is essential for conservation and sustainable farming, safeguarding these valuable ecosystems and their benefits. By analyzing mutations based on their impact, we can gain insights into the potential functional consequences and implications for the organism, helping to identify critical genes or regions that may play a significant role in adaptation, development, and environmental response. To achieve this, we annotated the effects and impact of spontaneous mutations in 559 giant kelp individuals from four different populations. We found over 15.9 million mutations in genes of giant kelp, and classified them into modifier, low, moderate, and high impact depending on their predicted effects. The creation of this mutation effect database, attached to the seedbank of these individuals, offers several applications, including enhancing breeding programs, aiding genetic engineering with naturally occurring mutations, and developing strategies to mitigate the impact of environmental changes.

Plant Sciences↗

Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination

Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties–including data circularity–were demonstrated. The emergent patterns helped identify 11 counties as ‘disseminators’ or ‘facilitators’ (F) and 264 counties as ‘barriers’ (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.

60 APPLIED LIFE SCIENCES↗

Rye as an Energy Cover Crop: Management, Forage Quality, and Revenue Opportunities for Feed and Bioenergy

Harvesting a winter rye energy cover crop (Secale cereale L.) could help sustain growing food and energy demand, provide new revenue streams, and enhance ecosystem services without inducing land-use change. A two-year field experiment with three planting methods and three N fertilization rates (0, 60, and 120 kg N ha -1 ) that produced >5.0 Mg ha -1 yr -1 of biomass was evaluated for (1) fresh and anaerobically digested rye forage quality; (2) revenue potential from renewable bioenergy, carbon markets, and digestate feed protein; and (3) potential greenhouse gas (GHG) offsets. We showed that rye can be harvested as forage for animals or anaerobically digested to produce renewable natural gas (RNG), with the residue after digestion (digestate) still available as a feed protein concentrate. Anaerobically digesting rye improved forage quality indicators. Digestion significantly decreased acid- and neutral-detergent fiber (ADF and NDF) by 5.2% and 17.8%, respectively, while significantly increasing crude protein (CP) (33.6%), total digestible nutrients (TDN) (2.0%), relative feed value (RFV) (23.6%), net energy for lactation (8.3%), maintenance (7.5%), and gain (20.0%). Using market prices for RNG, high protein feed, and GHG mitigation, potential on-farm revenue ranged from USD 307 Mg -1 and USD 502 Mg -1 dry matter with an average of USD 402 Mg -1 . However, there are substantial costs associated with RNG and the revenue potential does not represent the profitability of this system. Evaluation of the integrated system showed GHG emissions associated with rye fertilization were more than offset by the benefits of increasing yield in the 60 kg N ha -1 treatment. The overall carbon footprint of the integrated system was strongly carbon negative, confirming the potential of this strategy to sustainably intensify land use in the Midwestern United States.

09 BIOMASS FUELS↗

Mitigation of Gaseous Emissions from Stored Swine Manure with Biochar: Effect of Dose and Reapplication on a Pilot-Scale

Rural communities are affected by gaseous emissions from intensive livestock production. Practical mitigation technologies are needed to minimize emissions from stored manure and improve air quality inside barns. In our previous research, the one-time surficial application of biochar to swine manure significantly reduced emissions of NH3 and phenol. We observed that the mitigation effect decreased with time during the 30-day trials. In this research, we hypothesized that bi-weekly reapplication of biochar could improve the mitigation effect on a wider range of odorous compounds using a larger scale and longer trials. The objective was to evaluate the effectiveness of biochar dose and reapplication on mitigation of targeted gases (NH3, odorous, volatile organic compounds VOCs, odor, greenhouse gases (GHG)) from stored swine manure on a pilot-scale setup over 8-weeks. The bi-weekly reapplication of the lower biochar dose (2 kg/m2) showed much higher significant percentage reductions in emissions for NH3 (33% without and 53% with reapplication) and skatole (42% without and 80% with reapplication), respectively. In addition, the reapplication resulted in the emergence of a statistical significance to the mitigation effect for all other targeted VOCs. Specifically, for indole, the percentage reduction improved from 38% (p = 0.47, without reapplication) to 78% (p = 0.018, with reapplication). For phenol, the percentage reduction improved from 28% (p = 0.71, without reapplication) to 89% (p = 0.005, with reapplication). For p-cresol, the percentage reduction improved from 31% (p = 0.86, without reapplication) to 74% (p = 0.028, with reapplication). For 4-ethyl phenol, the percentage emissions reduction improved from 66% (p = 0.44, without reapplication) to 87% (p = 0.007, with reapplication). The one-time 2 kg/m2 and 4 kg/m2 treatments showed similar effectiveness in mitigating all targeted gases, and no statistical difference was found between the dosages. The one-time treatments showed significant percentage reductions of 33% and 42% and 25% and 48% for NH3 and skatole, respectively. The practical significance is that the higher (one-time) biochar dose may not necessarily result in improved performance over the 8-week manure storage, but the bi-weekly reapplication showed significant improvement in mitigating NH3 and odorous VOCs. The lower dosages and the frequency of reapplication on the larger-scale should be explored to optimize biochar treatment and bring it closer to on-farm trials.

Chen, Baitong (ORCID:0000000266071253)↗

Assessment of Envelope- and Machine Learning-Based Electrical Fault Type Detection Algorithms for Electrical Distribution Grids

This study introduces envelope- and machine learning (ML)-based electrical fault type detection algorithms for electrical distribution grids, advancing beyond traditional logic-based methods. The proposed detection model involves three stages: anomaly area detection, ML-based fault presence detection, and ML-based fault type detection. Initially, an envelope-based detector identifying the anomaly region was improved to handle noisier power grid signals from meters. The second stage acts as a switch, detecting the presence of a fault among four classes: normal, motor, switching, and fault. Finally, if a fault is detected, the third stage identifies specific fault types. This study explored various feature extraction methods and evaluated different ML algorithms to maximize prediction accuracy. The performance of the proposed algorithms is tested in an emulated software–hardware electrical grid testbed using different sample rate meters/relays, such as SEL735, SEL421, SEL734, SEL700GT, and SEL351S near and far from an inverter-based photovoltaic array farm. The performance outcomes demonstrate the proposed model’s robustness and accuracy under realistic conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analysis of Random Forest Modeling Strategies for Multi-Step Wind Speed Forecasting

Although the random forest (RF) model is a powerful machine learning tool that has been utilized in many wind speed/power forecasting studies, there has been no consensus on optimal RF modeling strategies. This study investigates three basic questions which aim to assist in the discernment and quantification of the effects of individual model properties, namely: (1) using a standalone RF model versus using RF as a correction mechanism for the persistence approach, (2) utilizing a recursive versus direct multi-step forecasting strategy, and (3) training data availability on model forecasting accuracy from one to six hours ahead. These questions are investigated utilizing data from the FINO1 offshore platform and Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) C1 site, and testing results are compared to the persistence method. At FINO1, due to the presence of multiple wind farms and high inter-annual variability, RF is more effective as an error-correction mechanism for the persistence approach. The direct forecasting strategy is seen to slightly outperform the recursive strategy, specifically for forecasts three or more steps ahead. Finally, increased data availability (up to ~8 equivalent years of hourly training data) appears to continually improve forecasting accuracy, although changing environmental flow patterns have the potential to negate such improvement. We hope that the findings of this study will assist future researchers and industry professionals to construct accurate, reliable RF models for wind speed forecasting.

54 ENVIRONMENTAL SCIENCES↗

Reburning of Animal Waste Based Biomass with Coal for NO x Reduction, Part I: Feedlot Biomass (FB) and Coal:FB Blends

Cattle biomass (CB or manure from cattle) is proposed as reburn fuel under slightly fuel-rich conditions. The CB includes wastes from cattle feedlots (cattle grown in feedlots to slaughter weights of 450–640 kg) termed as Feedlot Biomass (FB) and cattle wastes from dairy farms termed as Dairy Biomass (DB). NOx emissions from coal-fired power plants can be reduced by using pure CB and Coal:CB mixtures as reburn fuels (10~30% by heat) injected after the primary combustion region. Experiments with Coal:CB mixtures as reburn fuels were performed using the 30 kW burner facility. Part I deals with results from experiments using pure FB and Coal:FB blends as reburn fuels while Part II presents results on extent of NOx reduction using pure DB and Coal:DB blends as reburn fuels (RF). In the current work, results on NOx emission are presented with FB and Coal:FB blends as RF. The parametric studies include: equivalence ratio in reburn zone (ERRBZ), vitiated air, angle of reburn nozzles, presence and absence of heat exchangers (HEXs), and baseline NOx concentration. The optimum operating conditions for FB reburning were found to be conditions with vitiation at ERRBZ = 1.1 with 45° upward counter-current injection in the presence of HEXs. NOx emissions were reduced by as much as 96%.

09 BIOMASS FUELS↗