Tribo-electrostatic separation (TES) as a dry fractionation technique for the separation of protein was performed in this work. The experiments were carried out using a custom-built solid particle dispenser, coupled with a triboelectrostatic separator, with the latter comprising of a cubic chamber with two electrodes on which the separated particles were deposited. Both cereal and protein flours of known particle sizes were tested with the electrostatic separator via the particle dispenser with air as the dispersing medium. Using a tribocharging tube, Faraday cup, and an electrometer, the type of charge (positive or negative) acquired by the components of the flour sample and their chargeability in coulombs per unit mass were established prior to separation. A high voltage generator was utilized to supply the electric field required to ensure proper separation within the separator. The effects of electric field strength (100 – 200 kV/m) and air flow rate, varied between 5 – 15 l/min on the yield, protein enrichment and separation efficiency were explored. Scanning Electron Microscopy (SEM) analysis of the structure was carried out on the pre- and post-TES materials which further confirmed high separation efficiency of the process. The positive results from these experiments prove that the TES technique is a viable means for the commercial fractionation of both cereal and pulse flours without the drawbacks associated with existing wet fractionation techniques. Further experiments comparing the functional properties of the post-TES with the pre-TES materials are currently underway to explore the effect of this technique on these and other feed materials.

Peanut is the one of the top 10 allergens that is causing product recalls in Canada. Current strategies to identify such allergens are mostly reactive and often compounded by the delays in sampling, laboratory testing, decision making and traceability challenges. The current study focuses on using NIR spectrometry to identify the peanut allergen contamination by automating data collection, apply machine learning algorithm to predict the allergen contamination and to provide real-time feedback. The current study leverages the Texas Instruments DLP® NIRscan™ Nano Evaluation Module(900 – 1700 nm) that is integrated with Raspberry Pi Module 3 to collect the spectral signature of the wheat flour . The samples contained two categories: pure and contaminated wheat flour. First, the spectral signature of pure wheat sample are obtained. The wheat flour is contaminated with Peanut contaminated samples are acquired. Applying a machine learning pipeline that is being split into the following phases - training-test split, feature preprocessing, model selection, hyperparameter tuning, feature selection and model evaluation on the test set. The Light Gradient Boosting Machines (LGBM) and eXtreme Gradient Boosting machines (XGBoost) achieved the best average balanced accuracy. The final trained models were then evaluated on the test set, which was also used to calculate their final SHAP values. The random forest and XGBoost models were found to be the most effective classifiers, outperforming SVCs, decision trees, and the more computationally efficient Light Gradient Boosting Machine (LGBM) algorithm. The model predictions achieve above 90% balanced accuracy that predicts the presence or absence of allergen in question

The present antinutrients and unpleasant flavours constrain consumers’ acceptance of kidney bean flour. Extrusion can remove antinutrients by heat, pressure, and shear. However, its ability to modify beany flavour has not been well-investigated. While researchers have investigated the effects of extrusion temperature and feed moisture, the effects of acid or alkali injection into the extruder are yet to be systematically elucidated. This study investigated the effects of injecting acetic acid or sodium carbonate solutions, at three levels of concentration (0.05, 0.10, 0.15 mol/L), combined with three levels of temperature profile (die temperature set at 90, 110, 130°C) and two levels of feed moisture (25, 30%) during extrusion on the removals of antinutrients (condensed tannins, trypsin inhibitor activity, raffinose family oligosaccharides) and beany flavour (volatile compounds) in whole kidney bean flour. Results showed that all concentration levels of acetic acid and sodium carbonate solution increased the reduction of condensed tannin compared with water, especially at 130°C extrusion temperature. The addition of acetic acid and sodium carbonate at 0.15 mol/L concentration resulted in 72 and 90% reduction of total raffinose oligosaccharide content, as compared with 17% when water alone was added. The addition of sodium carbonate under three investigated concentrations reduced the total volatile compound in the bean flours by 45-58% as compared with water (23-33%) and acetic acid (11-27%), primarily due to aldehydes, alcohols, and aromatic hydrocarbons. These results suggest that the injection of sodium carbonate solution during extrusion could effectively reduce antinutrients and beany flavour compounds in kidney bean flour.

Ensuring food safety of eggs is crucial to preventing the risk of foodborne illnesses for consumers. However, the traditional egg surface decontamination method, washing with hot water containing disinfecting chemicals can inadvertently damage the eggshell cuticle, acting as a natural barrier, preventing bacterial access inside egg, and maintaining egg quality during storage. To address this challenge, it is essential to explore innovative technologies for egg surface decontamination. Non-thermal emerging technologies, such as engineering water nanostructures (EWNS) and cold plasma, offer promising alternatives, in which their effectiveness in deactivating bacteria on egg surface without any adverse impact on egg quality have been proved in our previous studies. However, understanding the impact of these technologies on the eggshell cuticle structure is crucial for informed decision-making regarding their practical application. In this study, the effects of non-thermal emerging technologies on eggshell cuticle chemical composition and coverage were evaluated, utilizing ATR Infrared spectroscopy and synchrotron-based X-ray micro-CT tomography. Our findings indicate that unwashed eggs (control) with intact cuticles exhibit a highly intense polysaccharide band, signifying strong glycosylation of the cuticle. In contrast, washed eggs show a weak polysaccharide band and strong carbonate absorption peaks due to cuticle thickness reduction during the washing process, and significantly lower cuticle coverages. On the other side, no significant differences in the eggshell chemical compositions and coverage of unwashed eggs and those treated with EWNS, and cold plasma were observed, suggesting that these methods do not have any adverse impacts on the eggshell cuticle chemical composition and coverage.

Leafy vegetables, particularly lettuce (Lactuca sativa), are prone to postharvest deterioration due to high water content and rapid loss of green color following harvest. This research aimed to investigate the effects of different storage light spectra on shelf life and visual characteristics of lettuce while minimizing postharvest quality losses. Since green light does not induce stomatal opening and as the consequence minimal impact on wilting of the product, in the present study the impact of two wavelengths of green LEDs with peaks at 500 nm and 530 nm, compared to the white LEDs (400–700 nm), and dark storage (control) over a 14-day storage period were assessed. Lettuce leaves were exposed to constant light intensity (10 µmol m-2 s-1), photoperiod (12 h-d), and air temperature (5°C). Lettuce stored under 500 nm and 530 nm green LEDs exhibited a significantly extended shelf life compared to dark storage. Noteworthy improvements in stiffness, and maintaining color were obvious by postharvest exposure to green LEDs. Exposure to 530 nm green LEDs led to notably higher chlorophyll index compared to other treatments. Photosynthesis was run over an extended duration, resulting in higher levels of total soluble sugar (TSS), while lower transpiration compared to samples under dark storage and white LEDs. Under green light, relative water content (RWC) was higher than its value under dark storage and white LEDs. These findings highlight the positive impact of green LEDs on quality retention and visual attributes of lettuce, offering valuable insights for postharvest practices.

The bin piler is a mechanical arm used to pile tubers within a bulk storage facility. This study evaluates a localization system designed to track the position of the bin-piler, enabling the creation of a 3D quality map of a tuber storage facility. Conducted at Dalhousie University, the research involved two experiments to determine localization accuracy in a 32 m^3 grid using stationary anchors at varied and uniform heights. The varied setup had a total anchor height range of 2.09 m, while the uniform setup held all anchors at an equal height of 0.52 m. Initial tests yielded accuracies of 1.19 m and 75 m, respectively, revealing geometric limitations in the localization algorithm.

Implementing a multivariate Support Vector Machine regressor model improved localization accuracy to 0.23 m and 0.49 m for varied and uniform anchor heights. Further optimization of hyperparameters was conducted, training models using a series of values for both the regularization parameter and epsilon, ranging from 0.1 – 100 and 0.1 – 1, respectively. With optimized regularization and epsilon, the accuracy further improved to 0.18 m for the varied anchor height setup, and 0.32 m for uniform heights. The synchronization of the localization information with other sensors that detect quality information of tuber, such as size, would create storage quality maps for better traceability.

Key Words:

Food traceability

UWB sensors

Wireless sensing

Yield quality

There is increasing interest in Ontario about the impact of grain dryer sound emissions on neighbours as rural populations increase. Predicting the sound levels at particular distances from a dryer is complicated because different types of dryers produce different amounts of sound, and grain dryers are partially or fully surrounded by other structures, most commonly large steel grain storage bins. Prior studies by the research team measured sound levels in the areas around multiple Ontario grain dryers. However, since actual sites are complex, it is difficult to use measured data at one site to accurately predict sound conditions at a different site. Acoustic modelling software provides an opportunity to simulate specific sites as well as general configurations of dryers and structures to get insights needed to provide general guidelines for sound propagation at grain dryers and to model how different mitigations (like barriers or operational changes) would impact sound levels at neighbouring locations. This study used SoundPLAN software to trial three different sound propagation models (ISO 9613-2, CnossosEU and Nord 2000) to predict sound level distribution around actual grain dryers. Simulation accuracy was quantified using the degree of agreement with measured sound levels collected by the research team at four different grain drying sites in southern Ontario. It was found that error levels of less than 5 dB(A) could be consistently achieved using the more accurate CnossosEU model. Specific recommendations for simulating sound propagation from grain dryers and similar agricultural facilities will be reviewed.

New approaches to energy supply for low temperature grain drying have the potential to reduce energy costs, improve grain quality and yield climate benefits. Current options for drying grain using alternative energy sources are few, necessitating the development of new dryers optimized for this type of drying. This research project is studying a full-scale prototype of an electrically-powered air source heat pump, horizontal flow, low temperature batch dryer. Initial drying experiments have been completed in the prototype dryer with corn. The initial tests quantified the energy intensity and energy consumption of corn drying in the prototype dryer. Further analysis of the efficiency of the dryer will be included in future research and used to inform refinement of the prototype dryer design. Supporting lab-scale experiments have also been conducted to replicate drying processes to predict likely drying efficiency with other grains in a range of operating conditions. These lab tests provide supplemental data under controlled conditions to analyze how different variables impact the drying process. Tests of multiple drying iterations were conducted with cycles of rehydrated and dried grain. The low temperature drying cycles were shown to have negligible impact on grain germination rates. This ongoing research using full-scale field studies and laboratory experiments has already provided insights into the potential benefits of low temperature drying at a larger scale, which may include reduced greenhouse gas emissions, and lower and less variable energy costs than conventional high temperature drying with fossil fuels.

The main objective of this research was to develop a numerical model to simulate the transport phenomena involved in grain drying processes in mixed-flow grain dryers by coupling the discrete element method (DEM) and computational fluid dynamics (CFD), and utilize the proposed model for the design assessment and optimization of mixed-low grain dryers. The proposed model was validated against experimental literature data in terms of grain temperature and moisture content distribution, as well as grain movement and airflow pattern. Close agreements were achieved between simulated results of the coupled CFD-DEM model and published experimental data, with an average difference of 4.3% for grain temperature and 2.5% for grain moisture content. Using empirical models in the literature, risks of germination reduction and fissure (stress cracking) of grain kernels during drying was predicted based on the grain conditions simulated by the coupled CFD-DEM model. The proposed model provides a versatile numerical tool to assess the performance of mixed-flow grain dryers by quantify the uniformness of grain moisture content and temperature, as well as the risk of germination reduction and stress cracking of grain kernels. The model was applied to assessment of different duct designs and layouts in mixed-flow grain dryers. It was found that the air ducts with 60-degree angles resulted in the best drying performance among the five layouts that were simulated. The best layout had the ratio of vertical distance to duct height of 1.35 and the ratio of horizontal distance to duct width of 1.5.

Drying is essential for grain corn production to preserve harvested goods in high humidity. Current processes rely on fossil fueled heat sources, greatly contributing to their global warming potential (GWP) through greenhouse gas (GHG) emissions. A proposed solution for improving grain drying is the use of electric air source heat pumps (HPs) which are proven to increase efficiency while decreasing GHG emissions. This study uses a life cycle assessment to justify the environmental feasibility of transitioning from fossil fuels to HPs. The project boundaries included the manufacturing of heating units to sufficiently dry corn. Different electricity sources were assessed. For Ontario, a GWP reduction of more than 22.5 times was achieved by using HPs over fossil fuel heaters. For other provinces, 100% natural gas, and 100% coal sourced electricity, reductions in GWP over fossil fuel dryers were shown. The effect of the coefficient of performance (COP) on the GWP was studied. Assuming higher COP resulted in lower GWP: a COP of 9.5 had 2.4 times smaller GWP than a COP of 3.5. However, the COP of 3.5 still achieved 15.4 and 13.0 times less GWP than using natural gas and propane heaters respectively. The HP construction contributed significantly to its overall GWP (13.8%). The working fluid (R134a) was a major contributor to GWP (15.0%) but could be mitigated by choosing a cleaner working fluid (e.g. R1234z(E)). In summary, using electric HPs in Ontario grain drying appears to be an environmentally feasible substitute for propane and natural gas heaters.

Drying stands as a pivotal process in manufacturing, essential for removing moisture from materials. However, its energy-intensive nature leads to substantial energy consumption, accounting for more than 12% of total industry energy usage. Moreover, conventional thermal drying systems exhibit low energetic performance, contributing to environmental harm. The study aimed to introduce and compare three novel exergy-based real-time control schemes for manipulating and adjusting the recycle ratio of outflow air in dryers to enhance energetic and exergetic performance. The control schemes developed in the study include Scheme I, based on the thermophysical exergy efficiency, Scheme II, which considers the outflow wet exergy rate below a constant threshold value and Scheme III, which incorporates a varying threshold value for the outflow wet exergy rate. The drying process for poplar wood chips involved examining two drying air temperatures (55-70 ºC) and two air volume flow rates (360‒450 m3/h). Additionally, the total exergy of air exhaust from the drying chamber was also fractionated into thermophysical and wet exergies for further assessing the effect of the recycle fraction. The study found that the universal exergetic efficiency of the drying chamber varied from 30.2% to 95.5%, and the overall functional exergetic efficiency of the drying system suggested that implementing developed control schemes could enhance the functional exergetic efficiency of the dryers. This study revealed that control scheme III, demonstrating the highest improvement of up to 75%, could be implemented on industrial dryers to improve the energetic performance and environmental sustainability by recovering exergy from outflow air.

Atmospheric Freeze Drying (AFD) has emerged as a promising alternative to the conventional freeze-drying method (VFD). This technology is characterized by its ability to operate under atmospheric conditions, offers lower energy consumption, continuous processing, and cost-effectiveness, especially in cold climates where natural cooling can be exploited. Despite its advantages, AFD faces challenges such as prolonged drying times and potential product shrinkage, which are addressed through innovative hybrid techniques, incorporating thermal or mechanical energy inputs to enhance drying efficiency. This literature review presented a comprehensive analysis of recent advancements in AFD technology by examining both the fundamental principles underlying the process and innovative approaches designed to improve its efficiency. The investigation of AFD fundamentals demonstrated the importance of vapor partial pressure gradients and external factors such as boundary layer effects in enhancing the drying process. Hybrid approaches, such as heat pumps, vortex tubes, expanders, ultrasonic and microwave assistance, adsorbent usage, and fluidization, have shown significant savings in energy consumption and improvements in product quality. Additionally, this review examined the influence of process parameters such as drying temperature, air velocity, and sample characteristics on drying kinetics and product attributes, offering insights into optimal process conditions. Finally, the review explored modeling approaches, including diffusion models and the Uniformly Retreating Ice Front (URIF) model to provide a comprehensive understanding of drying kinetics, facilitating the optimization of drying processes. Despite the promising advancements, this review emphasized the need for ongoing research to and extend the applicability of advanced AFD technologies across various industrial sectors.

With rising concerns on sustainability, fuel sourcing for continuous dryers is shifting towards natural gas and propane, however, carbon dioxide (CO2) emission is inevitable, subject to levies. The continuous drying process, reliant on electrical energy along with fuel, results in a total emission of 0.209 tonnes (t) of CO2 equivalent/Gigajoule. The levy is expected to increase at $15/year until 2030 capping at $170/tCO2e on the top of the actual fuel cost. To address these issues, a three-year (2021-2023) on-farm study was conducted with 5 different dryers in Alberta. The initial grain moisture of 15 to 23% wet basis (wb) was dried at 49-93.3℃ with discharge rates of 10,402-51,709 kg/h (385-1800 bu/h). Actual energy was calculated with weather-normalized fuel and electricity consumption. Results showed that levies were 47% (average) higher than fuel costs for any dryer. Double-flow dryer emitted the lowest emission with the lowest cost due to its air-recirculation system. Approximately 20% cost increment was observed per point of initial moisture decrease from 23 to 18% wb. However, a 32% cost increase was observed from 17 to 15% wb. This showed that grain moisture below 17% wb should not be dried in high-temperature dryers unless waste heat is reused for operations to promote drying sustainability.

Drying and storage at sub-zero temperatures affects the quality of stored grains and oilseeds. This review explored the efficacy of sub-zero temperatures in prolonging the viability of food grains and oilseeds. Seed survival mechanisms, particularly the formation of intracellular glasses, play a crucial role in preserving biological structures in seeds. The focus was primarily on orthodox seeds, which are characteristic of most agricultural crops and known for their desiccation tolerance at sub-zero temperature conditions. Drying at these low temperatures along with a high airflow inhibits ice crystal formation and slows down metabolic processes. This property eventually helps in prolonging the seed survival. The review also discussed the varying moisture content thresholds for different seeds and the risk of spoilage and maintaining nutritional quality. Additionally, the review highlighted the environmental benefits of this approach, aligning with the objectives of sustainable agriculture by minimizing emissions and maximizing resource efficiency.

Retrieving crop nitrogen (N) status is crucial for sustainable N management in agriculture. Nowadays, remote sensing and machine learning (ML) have made it feasible to non-destructively estimate crop N status. However, most ML models heavily rely on labeled training samples, potentially compromising their robustness under changing conditions. To address these issues, this study proposed a physics-guided ML approach that integrates physics-based radiative transfer models and empirical ML models. The proposed method was validated using hyperspectral data collected at both leaf and canopy levels. At the leaf level, we employed an ASD LabSpec spectrometer to acquire leaf VIS-NIR-SWIR spectral reflectance, followed by manual measurements of leaf chlorophyll a+b concentration. At the canopy level, VIS-NIR hyperspectral images were captured using a hyperspectral camera mounted on an Unmanned Aerial Vehicle at various study sites. Concurrently, crop N content was destructively sampled. Compared to the standard ML method, the proposed method demonstrated superior performance, particularly when only a small fraction (less than 5%) of the total training samples were available at the leaf level. At the canopy level, the proposed method achieved on average higher accuracy than ML and vegetation indices for leaf N content (RRMSE ranging from 10.08% to 10.84%) and canopy N content (RRMSE ranging from 13.89% to 25.21%) estimation. These findings underscore the benefits of integrating physics-based models and empirical ML models in the proposed approach. This approach offers a promising alternative for accurate estimation of crop N status, with potential applicability to other crops and typical crop traits.

Nitrogen has a major physiological impact on grapevines. Therefore, it is crucial to accurately analyze the nitrogen content of leaves since it directly affects both the productivity of the vineyard and the quality of wine produced.

For this research hyperspectral images of grapevine leaves were taken during two vital growth phases—bloom and veraison—from a ground-based hyperspectral sensor. There were two cultivars Chardonnay and Pinot Noir in two different experiment sites in Oregon state. The study employs a comprehensive approach combining hyperspectral imaging data (spectral features) and chemical analysis (measured nitrogen content) of each grapevine leaf to assess nitrogen content in grapevine leaves. The data is processed using machine learning techniques, specifically ensemble feature selection and partial least square regression feature selection method. Both feature selection methods select a set of features (Wavelength bands) in visible and near infra-red range to assess nitrogen in grapevine leaves.

The results of Chardonnay showed a good predictive performance with a coefficient of determination (R²) value of 0.68. The Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) are 0.28% and 0.22%, respectively. The results of Pinot Noir showed predictive performance with an R² value of 0.54. The RMSE and MAE are 0.24% and 0.19%, respectively. The nitrogen estimation results showed a reliable degree of accuracy that outperformed conventional chemical analysis methods in terms of time, workforce, and non-destructiveness.

The results highlight that hyperspectral imaging can be used to assess the nitrogen content in grapevine leaves and can improve nitrogen control in agriculture.

Central to success in precision agriculture (PA) is the accurate characterization of the spatiotemporal variability of soil information, including physical and hydrological properties and state variables. Researchers have studied soil information using near-surface geophysical methods such as Ground-penetrating Radar (GPR) and Electromagnetic Induction (EMI). Recently, the integrated GPR-EMI approach has gained attention for providing comprehensive insights into soil investigation while overcoming their intrinsic limitations. This review explores the advancements, challenges, and potential applications of the integrated GPR-EMI technique. GPR offers non-invasive, high-resolution imaging of subsurface and soil water content (SWC), facilitating precise delineation of soil stratigraphy and hydrological features. EMI exploits subsurface soil electrical conductivity variations to infer properties and state variables like soil texture, SWC, and salinity. Integrating these two leads to interactive benefits, enabling a comprehensive understanding of the variability and dynamics inherent in soil. Over the past several years, field experiments were conducted with an integrated GPR-EMI technique for predicting different soil information. Findings reveal that GPR has the potential to calibrate EMI for estimating SWC covering similar sampling volumes. Furthermore, the integrated technique improves the prediction accuracy of soil bulk density non-destructively in the studied site. Integrated GPR-EMI opens challenges like requirements for high-quality data, detailed data processing, and site-specific calibration requirements. Future research should focus on refining integration techniques by incorporating geophysics with petrophysical models, standardizing protocols, advancing data analysis using artificial intelligence and validating findings across diverse agricultural settings to realize the full potential of this integration to support precision agriculture.

This research explores the application of Detectron2 for detecting Colorado potato beetles in high-resolution images from a moving vehicle in agricultural fields. The study addresses challenges like the small size of beetles and distortion from resizing images, which can make them nearly invisible, compounded by the variable backgrounds and lighting of outdoor settings. To mitigate these issues, we implemented an image preprocessing strategy to boost detection performance which depends on cropping 1920x1080 to 640x640 to maintain beetle representation accuracy. Our images were taken using an imaging system mounted on a sprayer boom at 500 mm above the canopy - resulting in a dataset of 331 training and 41 testing images, all while exposing the system to diverse field conditions. We trained two models: one on original resolution images and another on cropped images. Testing showed the cropped image model improved detection rates from 48% to 70%, and F1-Score from 62% to 82%. To further enhance detection accuracy, a transfer learning approach was adopted to overcome the small size of the original dataset. Rather than utilizing a pre-trained model with the open-source images, a model was trained on a dataset of static, 4k images captured through a handheld device, cropped to 640x640. This new model was then fine-tuned with the original, moving vehicle dataset (640x640), and detection accuracy was increased to 85%, with an F1-Score of 92%. Our results offer a promising path forward for spot-spraying technologies, minimizing agrochemical usage while managing pests, in line with the principles of precision agriculture.

Understanding pesticide flow dynamics in the vadose and saturated zones in the soil profile is crucial for protecting the environment. Although predictive computational tools have effectively modeled pesticide flow within the soil, the flow through a biobed has not been reported. Hence Hydrus, a predictive modeling tool widely used in the simulation of water, heat, and solute in a variably saturated media, will be used to simulate pesticide flow in a Biobed. The Biobed, a system that consists of biomix (2:1:1v/v mixture of straw, soil, and peat) is an effective proven technology for the treatment of pesticide residues in rinsate water. This study evaluated the effectiveness of Hydrus 1D model in simulating the flow of pesticide rinsate through biobed located at the Ian Morrison Research Farm, Carman, Manitoba. A 1D domain depth profile was set up with five observation nodes located at 10 cm, 20 cm, 30 cm, 40 cm, and 50 cm depths. The measured volumetric water content of the biobed at these depths were compared to the simulated volumetric water content. The initial hydraulic parameters θs, α, n, l, Ks, and θr were estimated by fitting the van Genuchten equation from the biomix-water characteristics curve, textural values, and bulk density. The biomix hydraulic parameters were optimized using inverse modelling methods. The measured and predicted volumetric water contents were compared and assessed using statistical analysis. The result showed high efficiency in the model performance, this showed the Hydrus 1D model of the biobed represented the field conditions well.

Bioplastics represent promising alternatives to petroleum-based plastics, yet their degradation mechanisms remain insufficiently understood. Identifying bacteria and enzymes capable of degrading bioplastics could enhance end-of-life management practices. Proteobacteria, known for their remarkable metabolic versatility, present a promising avenue for exploration. Many proteobacteria produce diverse enzymes capable of breaking down various substrates for carbon utilization. This enzymatic diversity suggests a potential capability to degrade polymers such as bioplastics, even when they are not their natural substrates. We hypothesize that Burkholderia and Stenotrophomonas species will adapt to available nutrients, activating various metabolic processes, including the degradation of medium-chain-length polyhydroxyalkanoate (mcl-PHA). Through a screening method targeting extracellular mcl-PHA depolymerases, we identified several strains, including B. gladioli, B. multivorans, B. vietnamiensis, and S. maltophilia, capable of degrading extracellular mcl-PHA. Furthermore, these strains demonstrated the ability to degrade triglycerides under similar screening conditions, suggesting either substrate promiscuity or the production of multiple degradation enzymes. To elucidate the genetic basis of this activity, we performed transposon mutagenesis on B. vietnamiensis and identified several putative genes associated with extracellular mcl-PHA degradation. These genes include triacylglycerol lipase, lipase chaperone, type II secretion system components, HTH-type transcriptional activator, and polyhydroxyalkanoate synthesis repressor. To validate these genetic elements, we will generate insertional mutants using a CRISPR-associated transposase system (CAST). CAST system, employing Tn7-like transposase subunits and a V-K CRISPR effector (Cas12k), facilitates targeted DNA integration. We have successfully adapted this system for several Burkholderia species and intend to leverage its capabilities to elucidate the genetic determinants of PHA degradation further.

Massive plastic utilization has increased plastic pollution dramatically around the world. Biodegradable polymers are now displacing recalcitrant synthetic polymers to mitigate plastic pollution. However, those biodegradable plastics are not easily degraded or composted at ambient temperatures. For example, Polylactic acids (PLA) and other biodegradable and compostable bioplastics have different chemical and physical characteristics than other organic compounds (usually food wastes) in compost systems. Specifically, biodegradation of PLA requires a temperature of 58-60 ℃. As a result, they are mostly disposed of in landfills, where they do not fully degrade, resulting in production of microplastics which contaminate soil, water, and air, and create risks to human and animal health. Our study focuses on isolating PLA-degrading microorganisms from compost (industrial and backyard), optimizing the culture conditions, and exploiting them to degrade PLA completely under environmental conditions. This study will help reduce plastic pollution by enabling 100% biodegradation of PLA.

Polyethylene terephthalate (PET), a widely used synthetic polymer, is found in various products, from beverage bottles to textile fibers. Concerns about its long-term impact on humans have prompted research into mitigating its accumulation. After discovery of the efficient enzyme “PETase” from Ideonella sakaiensis in 2016, tremendous research was focused on application of the wild-type or engineered forms. Previously, we developed a hybrid construct fusing the signal peptide of a membrane-anchored Escherichia coli lipoprotein to express and deliver PETase to the outer membrane, aiming to streamline the soluble production and purification processes. However, traditional plasmid-based techniques utilized in this approach are susceptible to genetic instability and depends on the addition of inducers and antibiotics, which pose challenges for industrial scalability and application. To address these problems, we employed a “CRISPR-assisted transposition” approach to integrate a DNA payload containing the LPP-PETase gene cassette, under control of constitutive promoter, to develop a cell surface-displayed PETase capable of serving as a whole-cell biocatalyst. Stable expression and proper localization of the membrane anchored PETase were confirmed and evaluated via enzyme kinetic analysis and Western Blotting. Enzyme kinetic parameters were calculated utilizing a chromogenic substrate, and high-performance liquid chromatography quantification of Bis(2-Hydroxyethyl) terephthalate (BHET, PET derivative) hydrolysis. Our findings illustrate that the engineered whole-cell biocatalyst can present continuous functional PETase activity under controlled culture conditions. Genetically engineered "plastic-consuming" bacteria in fermenters, with plastic-degrading enzymes on their cell surfaces, offer a viable waste plastic disposal strategy. This closed, biosafe system converts plastic into valuable biomass sustainably.

LDPE is highly recalcitrant to natural biodegradation processes, and is among the most abundant plastic wastes in the environment. The high degree of crystallinity is thought to play a significant role in the resistance of LDPE to biodegradation. We previously identified three species of bacteria, Cupriavidus necator H16, Pseudomonas putida LS46, and Pseudomonas chlororaphis PA2361, with the ability to utilize untreated LDPE as a sole carbon source. Here we report changes in the molecular structure of LDPE after incubation with these bacteria. The changes in polymer structure were analyzed using Time-domain Nuclear Magnetic Resonance, High-Temperature Size-Exclusion Chromatography, Differential Scanning Calorimetry, X-Ray Diffraction, and Gas Chromatography. Overall, limited degradation of the LDPE powder was seen to occur in first 30 days of incubation with the bacteria. Residual LDPE from bacterial cultures showed a significant decrease in the percentage of amorphous regions (from > 47% to 40%), while the percentage of crystalline regions remained constant. The weight-average molecular numbers (Mw) and number-average molecular numbers (Mn) increased, while the polydispersity ratios decreased, indicating that branches of the LDPE with lower molecular weight were preferentially degraded. The limited degradation of LDPE was confirmed to occur in the low molecular weight branches, while the main branch remained untouched. LDPE hydrolysis products were detected in the supernatant with the majority being linear alkanes (heptane and undecane). The study is the first to report the connection between the structure of LDPE, and the degradability of the polymer, and explains the resistance of LDPE to complete biodegradation.

This study utilized vermicompost for the remediation of contaminated soils in Nigeria. Two soil washing methods adopted were batch and column processes. Characterization of the Vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of the washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental data. Artificial Neural Network (ANN) and Adaptive neuro fuzzy inference system (ANFIS) were used in modelling the removal efficiency of the process. The result showed removal efficiency of 97.8% for batch process remediation and 72.44% for column process. Optimization of the experimental factors gave optimal removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R^2) for ANN was (0.9974) and (0.9852) for batch and column process, respectively. The RSM coefficient of determination (R^2) for batch and column processes was (0.9712) and (0.9614), which also demonstrates agreement between observed and predicted. The coefficient of determination for the ANFIS model were (0.7115) and (0.9978) for the batch and column processes respectively. Machine learning models (ANN and ANFIS) accurately predict removal of crude oil from contaminated soil using vermicompost

Disposable paper (DP) cups, a staple in on-the-go beverage culture, contribute to environmental challenges due to non-biodegradable polyethylene (PE) liners. This research presents an eco-friendly alternative, harnessing fungal mycelium with North American wetland biomass. The study involves the evaluation of three fungal species—Ganoderma lucidum, Pleurotus ostreatus, and Polyporus squamosus to produce mycelium composite materials. These fungi are cultivated on canola straw (Brassica napus L.) and cattail substrates (Typha sp.) Among them, Ganoderma lucidum demonstrates superior mycelial growth and structural integrity when paired with cattail substrate over a 14-day period. The cultivation process involves utilizing Potato Dextrose Agar (PDA) for initial growth assessment, with subsequent optimization achieved through Yeast Extract Peptone Dextrose (YEPD) liquid media. The mycelium composite demonstrates several promising attributes, including notable thermal stability exceeding 260 °C, inherent hydrophobic properties surpassing a 100° water contact angle, and biodegradability within 45 to 60 days. Despite advancements in mycelium cup production, challenges related to cup morphology, labor-intensive processes, warranting ongoing research. To address this, alternative methodologies, including mycelium composite sheets, are explored for potential industrial-scale production pathways. However, challenges persist in mycelium composite sheet brittleness and low mechanical properties compared to traditional paper. Results highlight a need for further research and optimization, proposing strategies such as utilizing alkali-treated fibers, incorporating biopolymer as a binder. This research affirms mycelium materials as a sustainable alternative in beverage cup production, showcasing positive results in thermal stability, hydrophobicity, and biodegradability. Addressing mechanical shortcomings is crucial, urging ongoing research for successful integration into mainstream use.

Cattail biomass is an abundant, low-cost source of fiber in the Prairie region. While eco-friendly disposable tableware has been developed using non-wood biomass, no studies have investigated the use of waste fibrous Cattail biomass to produce paper combined with a biodegradable PLA polymer coating to make fully compostable beverage cups. In the current research, fibers were extracted from the leaves of Cattail plants (32% yield) using optimized alkali retting of 2.5% NaOH at 90 °C for 4 hours and used to manufacture paper sheets. The optimal pulping process involved a 1.5% consistency, and a blending time of 3.5 minutes, with beating agitation at 2,300 rpm. The average weight and thickness of the paper sheets produced were 282 g/m2 and 0.70 mm, respectively, and the tensile index, modulus, and bursting index were found to be 14.11 Nm/g, 1.06 GPa, and 0.04 kPa.m2/g. The cattail paper-coated sheets were manufactured by spraying 4 layers of Polylactic acid (PLA) polymer solution (3%, 4%, and 5% w/v in dichloromethane solvent) onto the paper sheets, using compressed air (15 psi), at room temperature. The polymer-coated paper sheets were tested for mechanical (tensile & bursting strength), thermal (thermal conductivity), and hydrodynamic (wettability) properties. Investigation of optimum polymer coating application considering coated paper sheet characterization as well as comparing to available commercial coffee cup-grade paper sheets are currently ongoing. Finally, this study will enable the development of affordable, environmentally friendly paper cups for the food and beverage industry and provide an opportunity to maximize the utilization of local biomass resources.

Canola fiber is a renewable resource for producing structural and non-structural biocomposite materials due to its abundance, low cost, and low density. Canola stalks, typically discarded after harvesting the seeds for oil, were used in this study to produce biobased fiber. Canola fibers were extracted using a mechanized water retting system. The retting parameters were optimized by manipulating the water flow rate (between 50 and 150 ml/min), retting time (25 and 47 h), and temperature (30 and 60°C). The fibers acquired through water retting persist as fiber bundles. Hence, the fibers were further treated with KOH solution at 90°C. The concentration of KOH and the treatment time were varied between 0.5 – 5% and 10 – 180 min, respectively, to investigate the optimal treatment conditions for refining the fibers, which were subsequently used to manufacture the mats. Alkalized canola fibers exhibited ∼51 and 92% reductions in fiber weight and diameter, respectively, compared to control fibers obtained through water retting alone. The removal of lignin and wax from canola fiber during alkalization is believed to have enhanced its refinement, resulting in a decrease in both fiber weight and diameter. The fibers obtained after alkalization were preformed into mat by laying the fibers manually. Canola fiber composites were manufactured using vacuum-assisted resin transfer molding (VARTM) and cured at room temperature for 24 h. Cured canola composites were tested for density and mechanical properties and compared with those of composites with cattail, flax, and hemp to evaluate the suitability of canola fibers in composite applications

Brassica fibre, also known as canola fibre, has gained attention in recent years due to its natural abundance using waste stream of canola seed. It is being considered for application in textiles and composites, driven by environmental concerns with other fibres, such as cotton and polyester. This fibre requires water retting for separation from the plant stalks. The retting performance of fibres under different water heights and altered water flow rates was studied using a retting chamber fabricated by the Department of Biosystems Engineering at the University of Manitoba. The statistical data on fibre surface geometry and fibre yield (%) show that there is no significant difference for water height variation (N=12), as well as water flow rate in the retting chamber. When waterfalls, it experiences a frictional drag that counteracts the downward force of gravity. When gravity and frictional drag are balanced, water drops reach an equilibrium fall speed known as the terminal velocity of the object, which remains relatively consistent along the fall path. The outcome of the research revealed the utilized design of the retting chamber is efficient for variable water height and positioning of fibre stalks in crates on different heights along its body.

Canola fiber is produced from the stalks using water and alkaline retting. However, it is currently impractical to produce canola fiber for commercial usage because it relies on hand-extraction techniques. A separating equipment is fabricated in this study to mechanically decorticate the fibers from canola stalks, which consists of a pair of feed rollers and brushing rollers, control unit, and a storage container. The machine uses retted canola stalks as an input and utilizes a combination of pressure and friction based separation. The stalks are fed into the lower brushing rollers via the upper feed rollers, where the feed rollers apply gripping and compression forces to propel the stalks toward the brushing rollers. The brushing rollers provide an abrasive texture that facilitates the wiping action on the retted stalks, leading to disruption of adhesion between the fibrous component and the woody core. The stalks are then carried through a storage container, where the separated fibers and woody cores are collected. The retting condition (time), roller speed, distance between the rollers determine the separation efficiency and quality. Hence, the experiments for fiber production using this equipment are repeated for moderately and over retted stalks by varying the roller speeds between 16 and 64 rpm, adjusting the relative speeds within the brushing rollers between 1:1 and 1:3, and varying the distances between brushing rollers from -1 to +1 mm to determine optimal process parameters. The decorticated fibers were tested for physical and morphological properties and compared with those obtained from hand-extraction method

This study aims to optimize compression molding parameters for recycled tire rubber to enhance mechanical properties while reducing dependency on binders. In the tire recycling process, tires undergo shredding and granulation to separate the rubber, steel wires, and fibers. While all three components are recyclable, fibers are commonly disposed of in landfills. As recycled tire rubber is typically vulcanized, recycling of Ground Tire Rubber (GTR) commonly involves the use of binders and additives. This research seeks to reduce or eliminate the need for binders and investigate the incorporation of fibers to mitigate the environmental and economic impact. We explore the influence of temperature and pressure on the compaction and sintering of GTR particles with and without binders, fibers, and additives. By varying the molding parameters, we aim to enhance bonding among GTR powder, potentially eliminating or reducing the requirement for binders and additives. This research holds significant implications for waste management in the tire recycling industry, offering potential pathways towards more sustainable and cost-effective practices. The findings provide innovative techniques for utilizing recycled tire rubber in various applications, thereby reducing landfill waste and promoting environmental sustainability.

A wide range of environmental issues associated with traditional plastics have resulted in the need for efficient pathways that focus on sustainability. Therefore, attention has been drawn to naturally-derived polymers such as starch. To date, commercial starches from potatoes, corn, and rice have been dominating the polymer industry. Faba bean starch, on the other hand, has received little material application despite its strong gelling ability and high final viscosity. The present study utilized tunicate-sourced cellulose nanocrystals to mitigate the water barrier properties of faba bean starch of different degrees of purity (air-classified and isolated). Tunicate CNC (varying between 0.2 and 0.6 mL) was added to starch (3% w/v) and glycerol (1 mL). 25 mL of the starch/glycerol/tunicate CNC was then crosslinked with 5 mL of sucrose and 5 mL of citric acid, basically minimizing retrogradation and enhancing antimicrobial properties. The films were characterized for their physico-chemical, mechanical, and thermal properties. The environmental footprint of the film specimens provides a competitive advantage in reducing carbon emissions over low-density polyethylene.

Plant proteins are gaining in popularity and are increasingly being considered as an alternative to animal protein, thus a sustainable, yet comparable source of plant protein is highly recommended. To this end, the current study was conducted to investigate the structural, thermal, physical, and functional attributes, as well as the volatile profile of sugar maple leaves (SML) protein. To this end, SML protein was extracted by homogenization (10000 rpm, 5 min) pretreated ultrasound-assisted extraction (120000 J, 60% amplitude, 5:5 pulse, 25°C, and 15 min) at varying pH (8−10) and compared with conventionally extracted SML protein. Among the different protein extracts, sonicated extract (pH9) provided a good protein yield (up to 7%) having higher protein content (210 mg Bovine serum albumin/g dry matter), thermal stability (onset of denaturation temperature:114°C), and functional properties (solubility, emulsion capacity, water holding capacity, and antioxidant activity). On contrary, the characteristic green aroma, caused by 3-hexen-1-ol and nonanal, was found higher in sonicated protein extracts than that of macerated extracts. Having said that, this study showed the versatile properties of SML protein fractions that can be used as plant-based food ingredients.

Structure and texture formation in plant proteins based meat-analog (MA), is still a big challenge. This study utilized different plant-based composites to develop restructured MA. Physicochemical, thermal, mechanical, structural, and sensory properties of formulated MA as well as batter-coated fried MAs were studied, and compared with a commercial product. Protein (23.27-24.68%), moisture (57.05-58.78%), pH (7.19-7.57), color (L:64.76-66.84, a:0.62-1.98, b:18.84-20.49), and textural (MF:0.22-0.52N, GF:0.07-0.24N/sec, FA:0.74-1.92 N.sec) attributes of formulated MAs were substantially impacted by the ratio of soy-protein-isolate (SPI) and wheat-gluten (WG). Incorporation of higher WG and lower SPI resulted in the formation of chicken-like fibrous and porous structure, hence, increased consumers acceptability of MA-based coated fried products. Microporosity (crust:51.14-58.35%, core: 63.57-71.55%), surface opening (5.67-14.75%), and fractal dimension (2.586-2.402) of coated fried MAs were dependent on the formulation of batter-coating. MA-based coated fried products surface moisture-fat (SMR:0.51-187.20 au; SFR: 2.01-20.17 au) profile significantly (p<0.05) varied with the formulations of batter-coating. Negative glass-transition-temperature (around -23°C) is prime concern for MA-based fried products stability at room environment.

Micronization is vital in altering the microstructural properties of pulse seeds, aiming to tailor them for various applications. This study evaluated the impact of micronization processing on the microstructural and physico-chemical attributes of three key pulses: chickpeas, lentils, and yellow peas, using different infrared (IR) exposure times (60, 80, 100, and 120 s) at a surface temperature of 180°C. Morphometric parameters (porosity, pore size, and pore distribution) were quantitatively and qualitatively analyzed using X-ray micro-CT, while physico-chemical parameters such as moisture loss (%), color change (ΔE), hardness (N), swelling/hydration capacity, and cooking time (min) were assessed using AOAC methods. Results demonstrated a significant increase (p<0.05) in moisture loss, ranging from 2.16 ± 0.29% to 12.24 ± 1.62% at prolonged IR exposure, along with noticeable discoloration of micronized seeds at 100 s and 120 s. Chickpeas and yellow peas exhibited increased hardness with extended IR exposure, whereas green lentils showed a significant reduction (p<0.05) in hardness at 120 s (158.01 ± 41.47N). All three pulses showed a substantial reduction in cooking time when micronized at 100 s, showing optimal cooking times of 120 ± 2 min, 50 ± 2 min, and 20 ± 2 min by chickpeas, yellow peas, and green lentils, respectively. Pulses micronized at 100 s demonstrated improved porosity, swelling/hydration capacity, and decreased cooking time, indicating their suitability for diverse applications. This study underscores the importance of understanding the microstructural and physico-chemical changes induced by pulse micronization, offering insights to develop predictive models to meet specific consumer/industrial requirements.

The growing need for plant protein has resulted in the increased demand for many pulse grain fractionation and refining industries. Field pea grains, which are produced worldwide have high protein concentration ranging from 25% to 30% (dry basis). However, the pea starch, a byproduct of the protein refining industry does not find any place in the agri-food sector because of their high amylose concentration (~40%), which could lead to rapid retrogradation. Therefore, in this study, a novel in-house spraying procedure was used to synthesise starch nanoparticles, to encapsulate natural antimicrobial compounds such as essential oils to find a value-added application of the underutilized starch byproduct. The synthesis of oil-encapsulated starch nanoparticles (OESNP) was further optimized using a Box-Behnken experimental design to study the influence of the processing parameters such as the initial starch concentration (10, 30 and 50 mg/ml), homogenization speed (5000 to 15000 rpm), duration of homogenization (1 to 10 min), sample injection rate (100 to 1000 µl/min), and quantity of antisolvent (1:1 to 1: 10). The produced OESNP were further characterized to investigate their molecular interactions, size and structure of the nanoparticles using Dynamic light scattering (DLS), X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and Fourier transform infrared (FTIR) spectrophotometry. The optimized sample showed an 80-90 % entrapment efficiency and particle size (<500 nm). The OESNP also showed significant antimicrobial properties against common plant pathogens suggesting their potential use in agri-food sector.

The growing demand for plant protein ingredients has increased the attention towards pulse starch, a major byproduct of protein fractionation. North America is the largest producer of pinto beans in the world. Different milling techniques are used to produce pinto bean flour which is further processed for protein or starch isolation. Each mill has a unique impact on the starch molecules that influence the yield and properties of isolated starches. In this study, the effect of blade mill, burr mill, stone mill, and hammer mill on the physical properties of pinto bean flour was correlated with conventional isoelectric precipitation-based starch isolation, and the characteristics of starch isolates. In all mills, the increase in milling intensity resulted in lower particle sizes and subsequent increase in starch damage in flour. However, the degree of size reduction and starch damage varied among different mills. The larger particles were observed in burr milled flours followed by stone mill, blade mill and hammer mill. The starch yield significantly increased with reduction in flour particle size. The degree of crystallinity, conclusion temperature during gelatinization and the enthalpy of gelatinization of starch isolates were also reduced with a reduction in particle size of flours.

A particularly wicked problem faced by modern farmers is the safe storage and preservation of cereal grains. A common approach to find the bulk moisture content of grain uses the electrical permittivity. Permittivity is a complex quantity, consisting of both real and imaginary parts. Most common capacitive moisture sensors operate by measuring the real part only and use the permittivity of water to make inference to volumetric moisture content of grain. However, valuable information is stored in both real and imaginary parts of the permittivity. Due to the close relationship with density, temperature and moisture content, a true understanding of the electrical permittivity of grain is vital for high-accuracy physical measurements.

We have obtained the full complex electrical permittivity of cereal grains using a coaxial transmission-line device (the ``permittivity cell'', or PC) in the frequency range 400 kHz to 1.3 GHz. Analysis is performed using a combination of numerical and analytical methods, including HFSS. We calibrate the device using fluids described by the Debye model. With non-parametric numerical inversion we recover the both components of the complex permittivity from the scattering matrix elements. We perform simultaneous inversion of both open and short cap measurements, ensuring the physicality of recovered solutions. Using the Kramers-Kronig approach, we find that non-parametric cereal grain permittivity results can be represented by an analogous parallel RC circuit. The implications of these findings and the possibility of utilizing this approach for advanced sensing applications will be discussed.

Grain storage is the process of holding back entropy; outside of removing waste, there is no known way to improve the quality of grain post-harvested. As a result, the farmer is faced with the difficult issue of storing grain, risking spoilage, or selling it at a lower price. Current grain management technologies are reactive and can only identify spoilage after it has occurred. In contrast, the challenge of a more predictive approach is that it requires a detailed understanding of the grain. One essential feature that needs to be understood to represent a grain bin is the pressure that the grain experiences, which affects grain compaction, aeration efficiency, and overall storage management.

An innovative approach to radial pressure distribution analysis in grain bins, utilizing a novel triaxial pressure sensor, is introduced in this study. Such sensors can be placed anywhere in a bin while filling to measure the x, y, and z pressures experienced by the grain in that specific region. Our objective involves using these sensors to refine and validate new mathematical models, specifically addressing the unknown variability of the vertical-to-lateral pressure ratio (k) throughout a bin. These sensors are deployed at strategic locations within a grain bin to generate a detailed pressure distribution map. This research aims to develop a comprehensive framework that improves our understanding of grain pressure fields and serves as a cornerstone for future predictive grain management approaches, including the application of digital twins to grain storage.

Ensuring a seamless and consistent flow of bulk grain is vital for efficient handling, processing, and storage, particularly with wheat, where impurities can significantly affect handling dynamics and storage properties. This study examined the impact of three dockage sizes (smaller than 1.1 mm, 1.1 to 2 mm, and larger than 3.3 mm) at four dockage percentages (from 0 to 10%) on the repose angle of dry wheat with 7.5% moisture content (wet basis). Employing an exponential growth model with two parameters as a regression framework, the study revealed complex relationships between dockage attributes and wheat's repose angle, assessed using both filling and emptying methods. The findings indicated variations between predicted and measured repose angles, with differences ranging from 0.01 to 1.62o for filling angles and from 0.56 to 4.56o for emptying angles. By illuminating the intricate interplay between dockage attributes and wheat behavior, especially in controlled silo environments, this research could enhance our understanding of storage condition optimization. These insights might offer valuable guidance for improving grain flow efficiency and ensuring optimal storage practices in agriculture.

Deoxynivalenol (DON) contamination from Fusarium graminearum colonization poses a significant challenge in Canadian wheat production. Both high atmospheric and interstitial CO2 concentration in field and storage, respectively, have been associated with fungal growth and mycotoxin production in grains. This study aimed to investigate DON production under different airtight conditions during the storage of wheat. Wheat samples with different moisture contents (17, 20 and 23%) were treated by: 1) natural infestation, 2) supplemental Fusarium inoculation, and 3) disinfestation followed by inoculation with Fusarium. The prepared samples were stored in sealed flasks at room temperature. The flasks were opened at intervals of 1, 3, 7, or 12 days. Prior to each opening, the concentrations of oxygen and carbon dioxide were measured using gas chromatography. Differences in CO2 and DON production under different storage condition were observed. The preliminary results will be presented.

Harvested grain is stored until the harvested grain is processed and delivered to customers for consumption. Insect infestation in stored grain not only causes nutrient degradation and dry matter loss, but also initiates mold growth inside the stored grain bulks. Detecting insect activities and monitoring insect populations is critical during storage as it helps in taking immediate corrective action to prevent further damage. Traditional sampling methods, although cheap, require skilled labor and are incapable of continuously monitoring insect activities and their population dynamics. Timely and in situ insect monitoring is needed. This study reviewed the application of in situ insect detection techniques combined with machine learning. Machine learning has been emerging for insect detection because it can classify various types of stored product insects. Technologies including image processing, acoustic measurements, mass spectroscopy, polymeric chain reaction (PCR) and electronic nose have been studied in literatures to produce real time detection of different species and different life stages of an insect in stored grain bulks. While suitable models including artificial neural networks, YOLO models, multivariate curve fittings are trained to classify or quantify the infestation level. These artificial intelligent-support techniques providing the next level of sensing and handling huge data at any point of time during the insect monitoring. The role of these new techniques in Integrated Pest Management of the stored grain products is also reviewed.

Plant breeding and genetic engineering have been used to establish high-yielding, drought-tolerant, disease-resistant, short-maturity corn varieties. However, there is no certainty that these varieties conform to the established thermal property values in literature, and the existing moisture content-based and proximate composition-based predictive models. This study evaluated the thermal properties of ten (10) corn varieties at five different moisture content levels, ranging from 13 to 21%. The aim was to examine the potential application of moisture content- and proximate composition models in predicting the thermal properties of corn varieties. Thermal properties were evaluated using existing reference scientific methods. The Moisture content – variety interaction significantly affected most of the thermal properties. The thermal conductivity, diffusivity, and specific heat ranged between 0.11 – 0.55 W m-1 K-1, 0.09-0.21 mm2 s-1, and 1.44 – 4.24 kJ kg-1 K-1, respectively. The predictive strength of both moisture content and proximate composition-based models varied greatly among corn varieties for thermal properties. The corn thermal properties were largely described by the Gaussian Process Regression (GPR) models compared to Linear Regression machine learning models. The existing moisture content and proximate composition-based predictive models are more suited for descriptive than predictive application with corn varieties in U.S.

Application of manure on agricultural lands may release considerable amounts of air pollutants, including gases, particulate matter, and odors, potentially impacting workers, animals, and community health. The objectives of this research are to quantify and compare fugitive emissions (gases, dust, and odors) from five manure types (swine, beef and dairy cattle, and poultry with and without litter) when applied on the field using six spreading methods. Three application techniques were used for solid manure: two conventional spreaders (horizontal and vertical beaters), and a novel prototype for direct incorporation of manure. The three other options were used for liquid manure: splash plate, dribble bar, and dribble bar with immediate incorporation. Each manure and spreader combination was performed in 3 repetitions, from June to November 2023. Preliminary results of field spreading experiments for swine manure showed that incorporation reduced odors and tended to decrease the concentration of ammonia (NH3). Carbon dioxide (CO2) and methane (CH4) concentrations increased slightly when spreading with a splash plate. Odor intensity was substantially greater with the splash plate compared to the dribble bar with incorporation (approximately 2–6 times). Moreover, the splash plate dispersed more particles during application than other methods. Additional findings on other manure types are currently being analyzed and will be included in the final paper.

In Wisconsin, America’s Dairyland, optimizing liquid manure application is crucial for sustainable and profitable farming. Traditional application methods pose environmental challenges, including nutrient runoff and odour emission. This study presents an innovative liquid manure applicator design, underpinned by extensive use of numerical simulations, specifically Finite Element Analysis (FEA), Discrete Element Method (DEM), and Computational Fluid Dynamics (CFD). These simulations played a pivotal role in every phase of the design process – from initial concept to final validation. They allowed for precise modelling of the structural integrity of applicator and soil and fluid dynamics, facilitating the development of three distinct and effective designs: a sweep injector, a disk injector, and a vertical tillage incorporation toolbar. Numerical simulations were integral in predicting the performance under various design alternations and operational conditions, ensuring resilience against mechanical stresses, and optimizing the environmental footprint. This comprehensive simulation-led approach was instrumental in developing the applicator that stands at the intersection of agricultural efficiency and environmental sustainability. By bridging advanced engineering techniques with practical agricultural needs, the project underscores the transformative potential of numerical simulations in modern agricultural/biosystems engineering.

Slurry and manure from animals are valuable sources of plant nutrients, including nitrogen, phosphorus, and potassium. However, over-fertilization poses a significant environmental challenge, leading to the volatilization of excess nitrogen and contributing to various issues such as air pollution, eutrophication, acidification, and greenhouse gas release. Effectively addressing ammonia emissions during manure spreading is crucial for mitigating these environmental problems. The mitigation of ammonia emissions not only brings environmental benefits but also holds social advantages by reducing the adverse effects of ammonia emissions on human health. Recognizing the growing interest in low-cost measurement methods due to their accessibility, affordability, portability, and user-friendly nature, this research aims to bridge a critical knowledge gap regarding the accuracy of these methods, particularly at low concentrations. To address this gap, the study compares ammonia emissions during manure spreading under controlled conditions, employing two low-cost methods: 1) a novel prototype of a passive flux sampler and 2) a dynamic chamber coupled with an acid trap. The experiment, conducted in four controlled rooms, involved the application of pig slurry to a layer of loamy clay soil (120 x 180 x 12 cm), with and without incorporation. The results not only validate the performance of the new low-cost ammonia sampler under controlled conditions but also enable a comprehensive comparison of the accuracy of each method. This research contributes valuable insights towards developing effective and affordable strategies for managing ammonia emissions during agricultural practices.

Understanding corn stalk cutting behaviors under the impact of disc is critical for designing disc for conservation tillage. In this study, three discs (notched, rippled, and plain disc) were examined on the effects of travel speed on corn stalk cutting behaviors using a stalk-disc-soil interaction model developed by the discrete element method. Soil was modelled using spherical particles. Corn stalk was modelled by bonded spherical particles, forming a solid and breakable model of corn stalk. During the simulation, model corn stalks were placed on soil surface and cut as the disc advanced. Dynamic attributes, including stalk cutting forces, stalk displacements, and soil sinkage under the pressure of stalks were monitored. Comparing the simulation values of stalking cutting force with experiment results in literature, the calibrated model parameters of corn stalk were 2 × 10^9 N m^-1 for bond stiffness, 8 × 10^6 Pa for bond strength, and 0.5 for particle friction. The anticipated results are that the model has a low relative error as comparing with measured in a soil bin test. Among three discs, the rippled disc has the least stalk cutting force, following by the notched disc and plain disc. Increasing the travel speed of discs increases stalk displacements, while reduces stalk cutting forces and soil sinkage. The results demonstrated that the stalk-disc-soil is feasible to obtain dynamic attributes of the interaction between soil, disc, and corn stalks during the process of tillage.

Air jet pumps allow the transportation of agricultural materials with no moving parts in the air stream. They function by using a jet of air to entrain and draw air through the duct, which draws in product and conveys it to its intended destination. This research examined the influence of duct shape on air entrainment in air jet pumps used for agricultural material conveyance. By employing computational fluid dynamics (CFD) modelling alongside experimental validation, various duct shapes were analyzed to determine their impact on air entrainment efficiency. The air jet pump was optimized by maximizing air entrainment for a given mass flow.

Common seed manifold designs involve complex interactions between seeds, air, and machine boundaries that are better understood through computer simulations. One-way coupling of Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) was applied to model seed dynamic attributes (trajectory, velocity, and force) in an air seeder manifold. Simulated field peas (Pisum sativum) were pneumatically conveyed at a rate of 0.07 kg/s, three air velocities (20, 25, and 30 m/s) and three manifold inclination angles (θ = 0°, 11°, and 22°). Model validation was conducted through experiments with a test bench replicating the simulated conditions. Simulated seed trajectories were evenly distributed within the vertical tube and were not significantly affected by manifold inclination angle or inlet air velocity. Median seed contact force ranged between 0.44 N and 3.52 N and was affected by location within the simulated manifold areas (elbow, vertical tube, and manifold head). Contact force data showed that inlet air velocity was a significant factor in simulated seed contact force, while manifold inclination angle did not have an effect. Model validation results revealed that one-way CFD-DEM coupling can replicate experimental observations related to overall seed distribution patterns (R2=0.90). Increasing inlet air velocity promoted more uniform seed distributions, while increasing the manifold inclination angle had the opposite effect. The proposed method lacked accuracy in determining the actual number of seeds per outlet (RMSE = 120 seeds). However, it is complementary to experimental data. This method could be appropriate in benchmarking multiple seed manifold arrangements relative to a baseline design.

Diverse activities, both natural and anthropogenic processes, notably the traffic of agricultural machinery, induce soil compaction in agricultural fields. This study quantifies the effects of vertical compaction on a sandy loam soil and its implications for the growth of canola. A John Deere 1023 E tractor equipped with ballasts traversed a field layout perpendicular to the direction of seeding. Three compaction levels were created by varying the number of tractor wheel passes. The effect on the soil properties and the performance of canola crops for each compaction level were determined in comparison to a control group (zero compaction). The results substantiated that vertical compaction exerted differential influences on the soil properties. Significant effects were observed between the average values of the control group and the other compaction levels in most measured parameters. Soil bulk density exhibited an average difference of 82.5 kgm-3, with a corresponding difference of 6 m-2 observed for crop count and a recorded difference of 0.046 kgm-2 for shoot biomass. However, no significant effect in terms of speed of emergence was recorded between the aforementioned compaction levels. The experimental findings serve as valuable resources for guiding further research into the interplay between soil compaction, soil dynamic properties, and canola growth.

Soil physical quality, more specifically soil compaction under cattle foot traffic caused by the intensive cattle grazing could cause long-term soil health problem for rangeland. Mature cattle can exert a static ground pressure of approximately 1.7 kg/cm2 of hoof-bearing area, which is equivalent or higher than the heavy-wheeled tractors. A little research has been conducted to understand the soil compaction under the cattle hoof. In addition, quantifying and visualizing the stress distribution in the top-soil layer is difficult to accomplish. To understand soil stress distribution, under the cattle hoof a discrete element model (DEM) will be developed. Model data will be calibrated and validated using laboratory experiments. A soil compaction test will be conducted using Loam soil for two different moisture contents. A predetermined soil mass for each soil moisture conditions was loosely filled into a square box (12”x12”'x15”) and the soil was compressed using a square plunger (150 mm) to the targeted soil bulk density levels of 1400 Mgm-3 on the bottom layer, 1550 Mg m-3 in the middle layer and 1250 Mg m-3 in the top layer. Soil resistance data will be measured using a cone penetrometer. A 3D printed life size cattle hoof will be used to apply compressive pressure on the compacted soil. Stress distribution under the cattle hoof for various compressive pressure, soil density, and soil moisture content will be determined using DEM. The results will be presented during the conference.

Obtaining information about spatially and temporally variable soil hydraulic properties is vital for many agricultural and environmental applications. However, challenges persist in acquiring such information due to the complexity, small-scale, and invasive nature of many of the current estimation methods. Our study investigated the potential of incorporating ground-penetrating radar (GPR) travel time data into a standardized infiltration procedure, like the Beerkan infiltration, to enhance estimates of soil hydraulic properties. The experiment was conducted on loamy sand-textured soil at Pasadena, Newfoundland, Canada, using a metal ring of 10 cm diameter and several doses of water of the same volume (200 mL). A surface GPR system with a center frequency of 500 MHz and 43 cm antenna offset was used to monitor wetting front movement during infiltration by collecting time-lapsed GPR traces every 5 s. Antenna separation of 43 cm was selected to clearly separate the direct ground wave from the air wave. The elapsed time required for complete infiltration of each volume of water was recorded. Estimated cumulative infiltration was obtained based on the GPR direct wave travel time relationship. The plot of the estimated cumulative infiltration with time was used to estimate soil-saturated hydraulic conductivity (Ks) and sorptivity (S) estimates according to the BEST-steady and BEST-intercept procedures. Preliminary results gave reasonable estimates of soil Ks and S based on the travel time of GPR direct waves and demonstrated the potential of obtaining soil hydraulic parameters from a convenient infiltration procedure.

Frequent and unpredictable occurrences of flood and drought events demand an efficient and sustainable water management system to cope with the moisture stress in field crops. A reliable design of combined irrigation and drainage system for the best- and worst-case scenario highly depends on soil water retention and permeability which depend on soil texture and structure. Soil structure is directly affected by management practices and crop root distribution. The objective of this study is to estimate soil hydraulic parameters in fine textured soil in Manitoba. HYDRUS inverse modelling coupled with PEST was used to estimate the van-Genuchten and Mualem soil hydraulic parameters. The observed soil water content determined at the site within 0-10, 10-30, 30-70 and 70-130 cm layers over the growing seasons from 2016 – 2019 under soybean-oat rotation was used for calibration and validation of the model. Results reflecting the changes in soil hydraulic parameters over the years will be presented along with its effect on water movement between the layers. The findings from this study will enhance the efficiency of subirrigation and drainage systems to produce a conducive environment for plant growth and performance.

Vertisolic soils (Vertisols) are pivotal for agricultural productivity in Manitoba due to their high fertility and superior moisture retention capabilities relative to other soil orders. However, managing Vertisols presents significant challenges due to their distinct swelling and shrinkage properties and low moisture buffer capacity. Consequently, these soils are prone to deformation, becoming excessively sticky and unworkable when wet, while they are rigid and develop cracks when dry, which severely restrict the window for field operations during the growing season. The behavior of Vertisols underscores the pressing need for innovative strategies to optimize agricultural practices and mitigate associated constraints. This requires a better understanding of their moisture dynamics as well as how they respond to extreme moisture conditions. The objective of this study was to investigate how Vertisols respond to extreme moisture relative to normal moisture conditions. Continuous soil moisture and weather data were collected from 17 study sites in the Red River Valley during the growing season (May to September) in 2018 – 2022. Soil water flux in the 0 - 5, 5 - 20, and 20 - 50-cm layers was determined. Results showing the soil water flux under different moisture conditions (extreme vs. normal) will be presented. Results from this study will contribute towards the development of effective soil water management strategies as well as adaption of agronomic management and field operations for sustainable crop production in Vertisols.

Excess soil moisture is typical of soils in Manitoba during the early growing season due to snowmelt and heavy rainfall. Managing soil moisture to attain optimal soil strength for trafficability is therefore crucial to ensure timely field operations in the region. Over the years, subsurface drainage has been the most popular approach for removal of excess soil water. However, this approach is not always feasible due to poor internal drainage and/or compromised soil structure. In this study, the potential of cover crops to improve soil strength for trafficability in Manitoba is explored. A multi-year study was initiated in the fall of 2020 near Cartwright, MB. Since fall 2022, rye has been grown at the site as a fall shoulder cover crop to assess its impact on soil moisture dynamics and its implications on soil strength for trafficability during spring field operations compared with no cover cropping. Continuous soil moisture measurements were taken in the 0-5, 5-15, 15-25, 25-35 and 45-55-cm layers. The critical soil moisture content for attaining soil strength sufficient to support trafficability was 90% of the lower plastic limit of the soil in the 0-25-cm layer. Preliminary results show that the fall rye cover crop significantly reduced soil moisture content in the 0-5-cm layer relative to no cover cropping. However, the fall shoulder cover crop fields did not meet the criterion for trafficability. Data on the impact of the 2023 fall rye cover crop on trafficability in spring 2024 will be analyzed and presented.

Disease transmission is a critical issue in the swine industry, and transport trailers are one of the routes of pathogen transmission between farms, significantly impacting animal health and the economy. In this study, electro-nanospray units were installed in an innovative prototype livestock trailer to assess the efficacy of the treatment units in preventing/minimizing the spread of diseases in animals during transport. This technology generates engineered water nanostructures (EWNS), which are responsible for bacterial inactivation through electrospraying and ionization of water. Two electro-nanospray units, each consisting of 16 spray injectors and housed in polycarbonate chambers, were installed inside the animal front compartment of the trailer. One Control and two Treatment sets of tests were performed during transport of pigs within and nearby towns of Saskatoon. The electro-nanospray units were turned on before starting the Treatment trip. Air quality and surface microbial population were monitored during each test/trip. Sampling was performed in the animal compartment at the start (after loading of pigs), in the middle, and at the end of the trip to collect samples. In the middle and end of the trials, average reductions in culturable bacteria were 40+-2% and 16+-6%, respectively. Additionally, a 24+-2% reduction in dust was achieved. Reductions in the microbial population on the metal surfaces of the animal compartment were also observed, with 78+-15% in the middle and 85+-15% at the end of the trial. These results indicate that the environmentally friendly electro-nanospray system can mitigate the transmission of dust and pathogens during the transport of pigs.

Stand-off pads (SOP) are uncovered outdoor yards built with absorbent materials overlying an impermeable lining with drainage pipes discharging into a manure tank, where cattle can be raised to minimize the environmental impact associated with nutrient runoff and gas emissions from manure management. Consequently, they emerge as a prospective alternative to traditional wintering pens, facilitating movement opportunities for dairy cows confined to tie-stalls. The objective of this study was to validate the potential of an improved SOP concept, composed of a filtering mixture aerated with the exhaust air from the adjacent barn, in contrast to a conventional wintering pen (WP), to provide outdoor exercise to dairy cows housed year-round in tie-stalls in the province of Quebec, Canada.

Both SOP and WP (28 m2) housed one Holstein dairy cow during 1.5 h, twice daily (morning and afternoon), throughout two 9-week periods (summer and winter). Results showed that the SOP was more efficient in removing biological oxygen demand, COD, TN, suspended solids, and E. coli (32.9, 194.2, 19.8, and 24.3 mg L−1, and 2.2 CFU 100-1 mL-1, respectively), relative to WP (95.3, 379.5, 54.2, and 43 mg L−1, and 197 CFU 100-1 mL-1, respectively). Aeration did not improve the removal of contaminants in the SOP but resulted in lower methane and nitrous oxide emissions compared to WP. A nitrogen balance was also calculated, obtaining 62% recovery for SOP and 45% in WP. The improved SOP represents a feasible solution for implementing environmentally compliant dairy cow exercise pen.

Animal transportation has proven to play a vital role in disseminating airborne viruses, thus a prototype trailer fitted with air filtration and ventilation systems was developed to protect the animals from airborne transmissible diseases during transport. The primary objective of this study was to evaluate the effectiveness of the filtered trailer in maintaining a pathogen-free environment inside the trailer loaded with pigs under actual transport conditions. Disease-challenge tests were conducted with the trailer filtration system in operation (Treatment) and without the filtration system (Control). For each test, a group of 10 pigs was loaded in the trailer, transported to a swine influenza A virus (IAV)-positive swine barn, and then the trailer was exposed to the exhaust air from the barn for 14 hours. After exposure, the pigs were observed for any clinical signs and symptoms of IAV infection for 14 days. Nasal swabs and blood samples were collected for serological testing to confirm infection. Results of the five completed disease-challenge tests showed that pigs in the trailer with an air filtration system remained healthy, and all blood and nasal swab samples collected were negative for IAV. However, pigs in the trailer without an air filtration system started to show signs and symptoms of IAV infection on Day 5 after the exposure. In addition, 7 out of 10 pigs were tested positive for IAV on Day 7. This result demonstrates that the air filtration system installed in the prototype trailer was capable of preventing airborne entry of pathogens into the animal compartment.

Antimicrobial resistance (AMR) persists as a significant threat to our society, with increasing implications for the health and productivity of livestock industry. An integral aspect of antimicrobial stewardship programs involves the efficient monitoring of the transmission of antimicrobial resistance genes (ARGs) from farm animals to manure and subsequently into the broader environment. This underscores the imperative for establishing comprehensive databases of ARGs that are specific to the microbiomes of economically significant species of farm animals. In this project, we conducted whole-genome sequencing of 130 bacteria isolated from the gastrointestinal tract of healthy pigs. The primary objective was to construct a thorough database encompassing prevalent ARGs found in the pig gut. Bioinformatics tools such as the Resistance Gene Identifier (RGI) and Comprehensive Antibiotic Resistance Database (CARD) were used to screen genomes for the presence of ARGs, resulting in the identification of 323 ARGs across 117 genomes. Genes predicted to confer resistance against tetracycline, lincosamide, beta-lactams, and fluoroquinolone were the most prevalent across all genomes. Importantly, our analysis extended to screening the adjacent regions of ARGs for the presence of signature genes of mobile genetic elements (MGEs), to assess potential transmissibility to other bacterial species. Of the identified ARGs, 60 were associated with various classes of MGEs, encompassing integrative and conjugative elements (n=36), bacteriophages (n=8), plasmids (n=3), and other potentially conjugative elements. Overall, our findings underscore the widespread presence of ARGs, including those conferring resistance to medically significant antimicrobials, across diverse lineages of the swine gut microbiota.

In cold-climate regions such as Saskatchewan, pigs are typically raised in fully enclosed and insulated barns which are heated using fossil fuels to keep the animals under optimal conditions for growth. However, with increasing electricity costs across the country, keeping the thermal demand in every barn brings setbacks to pig farmer’s financial income. Aside from that, existing environmental temperature recommendations for raising pigs were developed decades ago, and modern pigs nowadays are significantly different in terms of physiology and genetics, and housing systems have also evolved considerably compared to decades ago. Previous studies have shown that pigs prefer environmental temperatures significantly lower than the current industry setpoints. However, there is still critical need to evaluate the impact of raising sows at their preferred temperature on their long-term reproductive performance and welfare. The main goal of this study is to determine the optimum environmental temperature requirements of sows to reduce energy costs and environmental footprint while maintaining their overall productivity and performance. A series of experiments was conducted in two identical sow rooms at the Prairie Swine Centre barn facility, configured for group housing system. One room was designated as Control with the temperature maintained at current conventional setpoint of 16.5 °C, while another room designated as Treatment had temperature maintained at 8 °C, which was determined from a previous related study. The impact of this optimized temperature management approach on long-term reproductive performance and welfare of sows as well as on energy consumption and environmental carbon footprint will be presented.

The production and emission of particulate matter and greenhouse gases during egg production in layer facilities is connected with environmental pollution which consequently affects the public health and bird welfare. Ammonia (NH3) and airborne particulate matter (PM) are identified as the two major pollutants emitted from layer facilities. While nitrogenous compounds present in the poultry litter are the potential sources of NH3 production; airborne PM originates from the bird’s feather, skin, dander, excreta, bedding material, and existing microorganisms. Particulate matter in the PM10 and PM2.5 fraction are of particular interest primarily due to their capability of entering the respiratory system. The emitted ammonia can further react with acidic gases to produce secondary aerosols (SA). These aerosols are typically in the very fine size fraction and contribute to the formation of finer particulate matter (PM2.5). Furthermore, the emitted ammonia may be converted to nitrous oxide (N2O), which is a potent greenhouse gas. Due to animal welfare considerations, the egg production industry is transitioning from conventional battery cage system towards alternative systems (enriched cage, free-run (single-tier, and aviary), and free-range). Recent research indicates that alternative systems demonstrate higher emission rates, therefore it is vital to adopt efficient emission control strategies. Several management and control strategies are being developed which can be divided into four main categories: end-of-pipe treatment of the ventilation air, oil and water spraying, litter and manure amendments, and dietary manipulation. The current review aims to present the state of the science air pollution management strategies of poultry layer facilities.

Animal manures are a hotspot for the transmission of antimicrobial resistance genes (ARGs) and the emergence of antimicrobial resistance bacteria (ARB). This study aimed to determine the microbial groups associated with ARGs and Mobile Genetic Elements (MGEs) in bovine manures. Forty manure samples were collected, comprising 12 untreated and 28 subjected to various treatments: mesophilic anaerobic digestion (MAD, n = 15), thermophilic anaerobic digestion (TAD, n = 7), aerobic storage (n = 2), and the solids (n = 2) and liquids (n = 2) from a bedding recovery unit (BRU). DNA extraction and sequencing were conducted using an Illumina Miseq 250PE platform. Metagenomic reads were analyzed using diverse bioinformatic tools to determine microbial communities and ARG and MGE profiles. Spearman correlation and a co-occurrence model were employed to identify potential microbial groups linked with ARGs and MGEs. Results revealed that the phyla Bacillota and Pseudomonadota exhibited the highest number of microbial genera significantly and positively correlated with ARGs and MGEs, while Bacillota and Euryarchaeota showed negative correlations. Machine Learning techniques were employed to fit metagenomic data to simple regression models. The results indicated that total MGE levels served as a robust predictor of total ARG levels (R2 = 0.71). Furthermore, the relative abundance of Bacillota, Pseudomonadota, and Bacteroidota emerged as strong predictors (R2 = 0.66) for total ARG levels. Overall, this study provides valuable insights into microbial groups potentially harboring ARGs and MGEs, offering a foundation for developing targeted interventions to manage and mitigate Antimicrobial Resistance (AMR) in animal manures.