Bioresource and Agricultural Engineering Commons^™

Deep-Learning-Enhanced Automated Coherent-Light Diffraction System For High-Speed, Highly Accurate Strain-Specific Foodborne Bacterial Recognition, Yang Tian, Ziyu Liu, Yinuo Huang, Ramesh Bahadur Bist, Yiting Xiao, Samantha Marrianne Howe, Tsung Cheng Tsai, Terry Howell, Jeyam Subbiah, Michael L. Looper, Dongyi Wang

Biological and Agricultural Engineering Faculty Publications and Presentations

Rapid, accurate differentiation of bacterial pathogens at both species and strain levels is critical for clinical diagnostics, food safety, and epidemiological surveillance. We report a fully automated laser-diffraction platform that achieves rapid, label-free identification of bacterial pathogens at both species and strain levels. The system integrates dual cameras, an automated X-Y stage, and deep-learning classifiers to deliver sub-second, nondestructive diagnostics without reagents or culture. Using diffraction patterns from eight strains, including Escherichia coli O157:H7, K12, ATCC 25922, F18, Salmonella enterica, Listeria monocytogenes, Listeria innocua, and Staphylococcus aureus, a custom YOLO11x model attained 100 % Top-1 accuracy under five-fold stratified cross-validation …

Evaluation Of Robotic Swabbing And Fluorescent Sensing To Monitor The Hygiene Of Food Contact Surfaces, Siavash Mahmoudi, Clark Griscom, Pouya Sohrabipour, Yang Tian, Chaitanya Palleria, Philip G. Crandall, Dongyi Wang

Biological and Agricultural Engineering Faculty Publications and Presentations

Effective environmental monitoring is critical for preventing microbial and allergenic cross-contamination. However, manual swabbing methods, commonly used to verify hygienic conditions, are prone to inconsistent results because of variability in pressure, coverage, and techniques. Two novel solutions will be explored to address these challenges: a robotic swabbing system with tactile sensing control, and a fluorescence/absorbance spectrometer for non-contact, protein-based residue detection. The robotic system was evaluated against trained and untrained humans, measuring water pickup, surface coverage, and pressure consistency. Concurrently, the fluorescence system analyzed model poultry protein soil to correlate spectral patterns with contamination levels. The robotic system demonstrated statistically …

Quantitative Imaging Of Individual Bacterial Cells: E. Coli And B. Subtilis Via Terahertz Scattering-Type Scanning Near-Field Optical Microscopy, Haneol Lee, Youngil Moon, Donghyun Lee, Jinwoo Kim, Gyuseok Lee, Haewook Han

Biological and Agricultural Engineering Faculty Publications and Presentations

Significance: Terahertz (THz) waves have gained significant attention as an imaging technology due to their ability to provide physical and chemical information in a label-free, noninvasive, and nonionizing manner. Notably, their low energy enables nondestructive inspection of internal structures without damaging samples, making them well-suited for biomedical applications. However, the use of THz imaging has been constrained by limited spatial resolution due to the diffraction limit. Aim: This study introduces an approach using THz scattering-type scanning near-field optical microscopy, an advanced technique capable of overcoming these limitations and enabling single-cell scale measurements to image and distinguish individual bacterial cells, specifically …

Conservation Management Effects On Soil And Agronomic Properties In A Furrow-Irrigated Corn System In East-Central Arkansas, Jeferson P. Pimentel, Christopher G. Henry, Kris R. Brye, Benjamin R. Runkle, Amanda J. Ashworth, Edgar Mersiovsky, Kevin C. Thompson

Biological and Agricultural Engineering Faculty Publications and Presentations

Cover crops can improve soil physical properties and help to sustain agricultural crop yields. A 6-year study conducted from 2017 to 2022 examined the effects of conservation soil management practices in a furrow-irrigated continuous corn (Zea mays L.) system on a silt-loam soil (Typic Albaqualf) in the Lower Mississippi River Delta region of eastern Arkansas. This study compared the effects of conventional tillage (CT), no-tillage (NT), and no-tillage with cover crops (CC) in selected soil physical and chemical properties (i.e., soil bulk density (D b), porosity (& fnof;t), field capacity (Theta FC), Permanent wilting point (Theta PWP), Plant available water …

Nutrient Dynamics In Restored And Unrestored Urban Streams In The Piedmont Ecoregion Of South Carolina, Emily J. Jordan, Debabrata Sahoo, Calvin B. Sawyer, Jeremy W. Pike, Dara M. Park, Sarah A. White, Brian E. Haggard

Biological and Agricultural Engineering Faculty Publications and Presentations

The United States invests billions of dollars annually to perform stream restoration projects, yet few studies have investigated the effects this ecosystem manipulation has on nutrient cycling and associated water quality. Water quality improvement remains a substantial motivation for mitigating catchment-scale disturbances, especially in urban streams. Various urban land use practices impact the transfer and transport of nutrients such as soluble reactive phosphorus, ammonium, and nitrate plus nitrite from land into the streams and rivers. The uptake length (Sw), or the distance a dissolved nutrient travels downstream within a stream reach, can be measured using short-term nutrient injections, where shorter …

Modeling Rice Leaf Area Index And Canopy Height In The Us Mid-South Region, Ellie J. Kuhn, Beatriz Moreno-Garcia, Michele Reba, Kusum Naithani, Benjamin R. Runkle

Biological and Agricultural Engineering Faculty Publications and Presentations

Crop growth modeling plays a critical role in addressing the global challenges of food scarcity, carbon cycling, and water management. By simulating crop development from environmental factors, these models help predict harvest yield and carbon or water cycle terms and thus can inform policy and investment decisions. However, for some agricultural regions, such as the US Mid-South, there is a lack of comprehensive data specific to rice (Oryza sativa) cultivars and their growing conditions. Here, we use 30 field seasons of observational data to predict leaf area index (LAI) and canopy height (Hcan), key inputs for crop growth models, for …

The Rapid Detection Of Foreign Fibers In Seed Cotton Based On Hyperspectral Band Selection And A Lightweight Neural Network, Yeqi Fei, Zhenye Li, Dongyi Wang, Chao Ni

Biological and Agricultural Engineering Faculty Publications and Presentations

Contamination with foreign fibers-such as mulch films and polypropylene strands-during cotton harvesting and processing severely compromises fiber quality. The traditional detection methods often fail to identify fine impurities under visible light, while full-spectrum hyperspectral imaging (HSI) techniques-despite their effectiveness-tend to be prohibitively expensive and computationally intensive. Specifically, the vast amount of redundant spectral information in full-spectrum HSI escalates both the system's costs and processing challenges. To address these challenges, this study presents an intelligent detection framework that integrates optimized spectral band selection with a lightweight neural network. A novel hybrid Harris Hawks-Whale Optimization Operator (HWOO) is employed to isolate 12 …

Cost-Effective Active Laser Scanning System For Depth-Aware Deep-Learning-Based Instance Segmentation In Poultry Processing, Pouya Sohrabipour, Chaitanya Palleria, Amirreza Davar, Siavash Mahmoudi, Philip G. Crandall, Wan Shou, Yu She, Dongyi Wang

Biological and Agricultural Engineering Faculty Publications and Presentations

The poultry industry plays a pivotal role in global agriculture, with poultry serving as a major source of protein and contributing significantly to economic growth. However, the sector faces challenges associated with labor-intensive tasks that are repetitive and physically demanding. Automation has emerged as a critical solution to enhance operational efficiency and improve working conditions. Specifically, robotic manipulation and handling of objects is becoming ubiquitous in factories. However, challenges exist to precisely identify and guide a robot to handle a pile of objects with similar textures and colors. This paper focuses on the development of a vision system for a …

Insights From Consumers' Exposure To Environmental Nutrition Information On A Dashboard For Improving Sustainable Healthy Food Choices, Prince Agyemang, Ebenezer M. Kwofie, Jamie L. Baum, Dongyi Wang

Biological and Agricultural Engineering Faculty Publications and Presentations

Over the last decade, there has been a growing demand for tools to support sustainable healthy lifestyles, including food choices. Through a survey, this study examined the influence of environmental nutrition information conveyed with aids such as nudges and traffic light labels through a Dashboard for Improving Sustainable Healthy (DISH v1.0) food choices on consumer purchase intentions. DISH is an application that enables end-users to envisage and compare the potential impacts of their choices before purchasing. In the early stage of the technological development of DISH, the environmental nutrition information of two fast-food menus, plant-based and animal-based burgers, was tested …

Economic Impact Of Energy Accounting Schemes For Commercial Systems On A Broiler Farm With Power Demand And Generation, Yi Liang, Michael Popp

Biological and Agricultural Engineering Faculty Publications and Presentations

The aim of this study was to assess the impact of the on-farm solar photovoltaic (PV) generation to offset grid electricity consumption on a commercial poultry farm in the US. Hourly electricity production by PV systems was estimated using the System Advisor Model (SAM) of the National Renewable Energy Lab (NREL) and compared with the estimated electric load demand of a broiler house. We analyzed the economic benefits of installing solar systems of three capacities under net energy metering and net energy billing pricing scenarios. Results suggested that a smaller PV installation of 35 kWp, while substantially short of meeting …

Environmental-Health Convergence: A Deep Learning-Oriented Decision Support System For Catalyzing Sustainable Healthy Food Systems, Prince Agyemang, Ebenezer M. Kwofie, Jamie I. Baum, Dongyi Wang, Emmanuel A. Kwofie

Biological and Agricultural Engineering Faculty Publications and Presentations

To generate evidence to address food system challenges, we developed an adaptable framework for multimodel assessment of the convergence effect of health and environmental drivers in food systems. We achieved this goal by developing a modeling framework that facilitates testing and applying four deep-learning algorithms using a case study of the United States's food system. Among the models tested, the bidirectional and single-layer long short-term memory models outperformed the others with α_E(2.75) and α_H(3.51) when predicting environmental drivers and health drivers, respectively. All the models tested performed better at predicting environmental than health drivers. The best-performing …

Unlocking The Phosphorus Circularity Potential Of Corn Belt Watersheds With Biorefinery Phosphorus Recovery Incentives, Kenneth Ruffatto, Arghajeet Saha, Rebecca L. Muenich, Andrew J. Margenot, Roland D. Cusick

Biological and Agricultural Engineering Faculty Publications and Presentations

As global phosphorus (P) stores rapidly decline, P fed algal blooms continue to threaten critical freshwater resources across the globe. In the Midwestern United States (US), particularly the Corn Belt, biorefineries could play a key role in addressing this issue. By recovering P from the byproducts of ethanol production these facilities could reduce the P content of distillers grain feed, thereby reducing P excreted in manures. This process could potentially divert P away from concentrated animal feeding operations (CAFOs) and toward renewable P (rP) fertilizer production utilizing the recovered P. To foster the inclusion of P recovery incentives in state …

New Insights Into Fertilisation With Animal Manure For Annual Double-Cropping Systems In Nitrate-Vulnerable Zones Of Northeastern Spain, Dolores Quilez, Monica Guillen, Marta Valles, Arturo Dauden, Beatriz Moreno-Garcia

Biological and Agricultural Engineering Faculty Publications and Presentations

Maize double-cropping production systems in Mediterranean areas have a great nitrogen extraction capacity and high nitrogen (N) requirements. This study aims to assess whether in these farming systems, animal manure can be applied, using adequate management practices, at levels exceeding the maximum annual amount of livestock manure established in the European Nitrate Directive for vulnerable zones (170 kg N ha-1) without increasing the risk of water nitrate contamination. We compare the risk of nitrate leaching under two fertilisation strategies, one with synthetic fertilisers and the second with a maximised application of pig slurry, exceeding the limits of the EU Nitrate …

Sustainable Poultry Farming Practices: A Critical Review Of Current Strategies And Future Prospects, Ramesh Bahadur Bist, Keshav Bist, Sandesh Poudel, Deepak Subedi, Xiao Yang, Bidur Paneru, Sudhagar Mani, Dongyi Wang, Lilong Chai

Biological and Agricultural Engineering Faculty Publications and Presentations

As global demand for poultry products, environmental sustainability, and health consciousness rises with time, the poultry industry faces both substantial challenges and new opportunities. Therefore, this review paper provides a comprehensive overview of sustainable poultry farming, focusing on integrating genetic improvements, alternative feed, precision technologies, waste management, and biotechnological innovations. Together, these strategies aim to minimize ecological footprints, uphold ethical standards, improve economic feasibility, and enhance industry resilience. In addition, this review paper explores various sustainable strategies, including eco-conscious organic farming practices and innovative feed sources like insect-based proteins, single-cell proteins, algal supplements, and food waste utilization. …

Compact Solar-Powered Plasma Water Generator: Enhanced Germination Of Aged Seed With The Corona Dielectric Barrier Discharger, Yiting Xiao, Yang Tian, Haizheng Xiong, Ainong Shi, Jun Zhu

Biological and Agricultural Engineering Faculty Publications and Presentations

Seed aging adversely affects agricultural productivity by reducing germination rates and seedling vigor, leading to significant costs for seed banks and companies due to the need for frequent seed renewals. This study demonstrated the use of plasma-activated water (PAW), generated by a solar-powered corona dielectric barrier discharger, to enhance germination rates of spinach seeds that had been stored at 4 °C for 23 years. Treating seeds with PAW at 17 kV for 15 min improved germination (by 135%) and seedling growth compared to untreated seeds. Through detailed analysis, beneficial PAW properties for seed development were identified, and a molecular mechanism …

Effective Nutrient Management Of Surface Waters In The United States Requires Expanded Water Quality Monitoring In Agriculturally Intensive Areas, Christopher Oates, Hactor Fajardo, Khara Grieger, Daniel Obenaur, Rebecca Muenich, Natalie G. Nelson

Biological and Agricultural Engineering Faculty Publications and Presentations

The U.S. Clean Water Act is believed to have driven widespread decreases in pollutants from point sources and developed areas, but has not substantially affected nutrient pollution from agriculture. Today, the highest nutrient concentrations in surface waters are often associated with agricultural production. In this Perspective, we explore whether challenges stemming from the Clean Water Act’s inability to mitigate agricultural nutrient pollution are also exacerbated by coarse nutrient monitoring. We evaluate the current state of nutrient monitoring in surface waters of the contiguous U.S. relative to agricultural nutrient inputs to assess how monitoring effort varies across agriculturally intensive areas. The …

Identifying Hidden Factors Influencing Soil Olsen-P In An Alkaline Calcareous Soil Using Machine Learning And Geostatistical Techniques, Moussa Bouray, Mohammed Bayad, Adnane Beniaich, Ahmed G. El-Naggar, Rebecca Muenich, Kahlil El Mejahed, Abdallah Oukarroum, Mohamed El Gharous

Biological and Agricultural Engineering Faculty Publications and Presentations

Phosphorus (P) deficiency is one of the major constraints for sustainable crop production in calcareous soils. This study aimed to elucidate the key soil characteristics modulating the variability of soil Olsen P in these typical soils. A comprehensive soil sampling initiative (1.5 samples per hectare) was conducted on a 100-ha farm, considering 31 attributes that included soil physical and chemical properties, and geographic attributes. Three machine learning algorithms—partial least squares regression (PLSR), random forest (RF), and cubist regression (CR)—were employed to understand key variables controlling soil Olsen P. Furthermore, the same data set was used to spatially map the …

Blackberry Growth Monitoring And Feature Quantification With Unmanned Aerial Vehicle (Uav) Remote Sensing, Akwasi Tagoe, Alexander Silva, Cengiz Koparan, Aurelie Poncet, Dongyi Wang, Donald Johnson, Margaret Worthington

Biological and Agricultural Engineering Faculty Publications and Presentations

Efficiently managing agricultural systems necessitates accurate data collection from crops to examine phenotypic characteristics and improve productivity. Traditional data collection processes for specialty horticultural crops are often subjective, labor-intensive, and may not provide accurate information for precise management decisions in phenotypic studies and crop production. Reliable and standardized techniques to record and evaluate crop features using agricultural technology are essential for improving agricultural systems. The objective of the research was to develop a methodology for accurate measurement of blackberry flowers and vegetation coverage using UAV remote sensing and image analysis. The UAV captured 20,812 images in the visible spectrum, and …

Water Quality Impacts Of Recycling Nutrients Using Organic Fertilizers In Circular Agricultural Scenarios, W. Lisenbee, A. Saha, P. Mohammadpour, R. Cibin, Jason Philip Kaye, C. Grady, Indrajeet Chaubey

Biological and Agricultural Engineering Faculty Publications and Presentations

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A Simple Sandwich Electrochemical Immunosensor For Rapid Detection Of The Alzheimer’S Disease Biomarker Tau Protein, Mingzhu Yang, Yihong Chen, Hongyu Sun, Dujuan Li, Yanbin Li

Biological and Agricultural Engineering Faculty Publications and Presentations

As a typical biomarker of Alzheimer’s disease, rapid and specific detection of tau protein can help improve the early diagnosis and prognosis of the disease. In this study, a simple sandwich electrochemical immunosensor was developed for rapid detection of tau protein. Primary monoclonal antibodies (mAb1) against the middle domain of tau protein (amino acids 189–195) were immobilized on the gold electrode surface through a self-assembled monolayer (SAM) of 3,3′-dithiobis (sulfosuccinimidyl propionate) (DTSSP). Then the tau protein was captured through the specific adsorption between the antigen and the antibody, resulting in a change in the impedance. Secondary monoclonal antibodies (mAb2) against …

Flexible Biosensors For Food Pathogen Detection, Sonatan Biswas, Md Shariful Islam, Fei Jia, Yunteng Cao, Yanbin Li, Changyong Cao

Biological and Agricultural Engineering Faculty Publications and Presentations

Food contamination poses a significant threat to public health, the economy, and human health worldwide, occurring at any stage of the food supply chain, from farm to fork. Efficient and effective real-time monitoring methods for the early identification and rapid detection of pathogen contamination are critical to preventing possible food safety issues. In the past decade, flexible electrochemical biosensors have rapidly expanded in the detection of foodborne pathogens, owing to their ability to function well at biological interfaces that may be soft, intrinsically curvy, irregular, or deformable. The most important features of flexible sensors are their flexibility, multifunctionality, low cost, …

Global-To-Local Dependencies In Phosphorus Mass Flows And Markets: Pathways To Improving System Resiliency In Response To Exogenous Shocks, Justin Baker, Nathan Schunk, Matt Scholtz, Ashton Merck, Rebecca Muenich, Paul Westerhoff, James J. Elser, Owen W. Duckworth, Luke Gatiboni, Minhazul Islam, Anna-Maria Marshall, Rosangela Sozzani, Brooke K. Meyer

Biological and Agricultural Engineering Faculty Publications and Presentations

Uneven global distribution of phosphate rock deposits and the supply chains to transport phosphorus (P) make P fertilizers vulnerable to exogenous shocks, including commodity market shocks; extreme weather events or natural disasters; and geopolitical instability, such as trade disputes, disruption of shipping routes, and war. Understanding bidirectional risk transmission (global-to-local and local-to-global) in P supply and consumption chains is thus essential. Ignoring P system interdependencies and associated risks could have major impacts on critical infrastructure operations and increase the vulnerability of global food systems. We highlight recent unanticipated events and cascading effects that have impacted P markets globally. We discuss …

Memo: Dataset And Methods For Robust Multimodal Retinal Image Registration With Large Or Small Vessel Density Differences, Chiao-Yi Wang, Faranguisse Kahki Sadrieh, Yi-Ting Shen, Shih-En Chen, Sarah Kim, Victoria Chen, Achyut Raghavendra, Dongyi Wang, Osamah Saeedi, Yang Tao

Biological and Agricultural Engineering Faculty Publications and Presentations

The measurement of retinal blood flow (RBF) in capillaries can provide a powerful biomarker for the early diagnosis and treatment of ocular diseases. However, no single modality can determine capillary flowrates with high precision. Combining erythrocyte-mediated angiography (EMA) with optical coherence tomography angiography (OCTA) has the potential to achieve this goal, as EMA can measure the absolute RBF of retinal microvasculature and OCTA can provide the structural images of capillaries. However, multimodal retinal image registration between these two modalities remains largely unexplored. To fill this gap, we establish MEMO, the first public multimodal EMA and OCTA retinal image dataset. …

Computational Fluid Dynamics Analysis And Empirical Evaluation Of Carboxymethylcellulose/Alginate 3d Bioprinting Inks For Screw-Based Microextrusion, Sungmin Lee, Minjae Son, Juo Lee, Iksong Bun, Jin-Woo Kim, Jungsil Kim, Hoon Seonwoo

Biological and Agricultural Engineering Faculty Publications and Presentations

Three-dimensional microextrusion bioprinting technology uses pneumatics, pistons, or screws to transfer and extrude bioinks containing biomaterials and cells to print biological tissues and organs. Computational fluid dynamics (CFD) analysis can simulate the flow characteristics of bioinks in a control volume, and the effect on cell viability can be predicted by calculating the physical quantities. In this study, we developed an analysis system to predict the effect of a screw-based dispenser system (SDS) on cell viability in bioinks through rheological and CFD analyses. Furthermore, carboxymethylcellulose/alginate-based bioinks were used for the empirical evaluation of high-viscous bioinks. The viscosity of bioinks was determined …

Ssnet: Exploiting Spatial Information For Tobacco Stem Impurity Detection With Hyperspectral Imaging, Chao Zhou, Zhenye Li, Dongyi Wang, Sheng Xue, Tingting Zhu, Chao Ni

Biological and Agricultural Engineering Faculty Publications and Presentations

Tobacco stems are a critical component in cigarette production in China. However, accurately and promptly identifying impurities in tobacco stems remains a challenge with current deep learning methods, often failing to meet industry standards. This study introduces the Spectral-Spatial Network (SSNet), which is specifically optimized for rapid and precise detection of impurities in tobacco stems, leveraging spatial information in hyperspectral imaging. Designed to align with the high-speed requirements of industrial processing, SSNet effectively overcomes the complexities associated with analyzing hyperspectral data. The integration of spatial information particularly enhances recognition accuracy, especially in areas affected by fringe patterns. Our experiments reveal …

We Need A Solid Scientific Basis For Nature-Based Climate Solutions In The United States, Kimberly A. Novick, Trevor F. Keenan, William R. L. Anderegg, Caroline P. Normile, Benjamin R. Runkle, Emily E. Oldfield, Gyami Shrestha, D. D. Baldocchi, Margaret E.K. Evans, James T. Randerson, Jonathan Sanderman, Margaret S. Torn, Anna T. Trugman, Christopher A. Williams

Biological and Agricultural Engineering Faculty Publications and Presentations

Nature-based climate solutions (NbCS) have courted both enthusiastic support and considerable controversy (1–8). Defined as deliberate human actions that manipulate ecosystems to improve the planet’s greenhouse gas balance, NbCS provoke disagreement, in large part because their implementation has so far outpaced a science-based understanding of their long-term climate mitigation potential.

Quantifying Wildfire Drivers And Predictability In Boreal Peatlands Using A Two-Step Error-Correcting Machine Learning Framework In Tefire V1.0, Rongyun Tang, Mingzhou Jin, Daniel M. Ricciuto, Anping Chen, Yulong Zhang

Biological and Agricultural Engineering Faculty Publications and Presentations

Wildfires are becoming an increasing challenge to the sustainability of boreal peatland (BP) ecosystems and can alter the stability of boreal carbon storage. However, predicting the occurrence of rare and extreme BP fires proves to be challenging, and gaining a quantitative understanding of the factors, both natural and anthropogenic, inducing BP fires remains elusive. Here, we quantified the predictability of BP fires and their primary controlling factors from 1997 to 2015 using a two-step correcting machine learning (ML) framework that combines multiple ML classifiers, regression models, and an error-correcting technique. We found that (1) the adopted oversampling algorithm effectively addressed …

Prediction Of Chlorophyll-A As An Index Of Harmful Algal Blooms Using Machine Learning Models, Ibrahim Busari, Debrabata Sahoo, R. Daren Harmel, Brian E. Haggard

Biological and Agricultural Engineering Faculty Publications and Presentations

The complex dynamics of freshwater harmful algal blooms (HABs) necessitate proactive monitoring approaches to mitigate their impacts. The rapid breakthrough in computing prowess and statistical advances is triggering the development of data-driven techniques such as machine learning (ML) models, which have been shown in different fields to be instrumental in finding patterns for explaining relationships in observed data. This study assesses the ability of ML models for HABs monitoring in a lake using chlorophyll-a concentration as the index. The selected models for this study were regression tree, random forest (RF), multilayer perceptron (MLP), support vector regression (SVR), long short-term memory …

Nutritional-Environmental Trade-Offs In Potato Storage And Processing For A Sustainable Healthy Diet, Aubin Payne, Ebenezer M. Kwofie, Prince Agyemang, Jamie Baum

Biological and Agricultural Engineering Faculty Publications and Presentations

Over the last decade, poor diets and limited access to nutritious foods have been critical drivers of micronutrient deficiency in human health. However, food fortification at an industrialized scale in developed countries has helped eliminate deficiency-related diseases. In developing countries, fortified foods and biofortified materials have been delivered to nutrient-deficient communities. While these strategies have produced significant and acclaimed results, reports from the Food and Agricultural Organization suggest that over a quarter of the world’s population suffers from micronutrient deficiency. This implies that there are still declines in micronutrients in food products at different nodes along the food value chain …

An Amplification-Free Crispr-Sers Biosensor For Specific, Sensitive And Rapid Detection Of Salmonella Typhimurium In Poultry, Fei Jia, Bingyan Li, Yawen He, Yafang Shen, Juhong Chen, Xingmin Li, Yanbin Li

Biological and Agricultural Engineering Faculty Publications and Presentations

CRISPR (Clustered regularly interspaced short palindromic repeats) has been a cutting-edge biotechnology in both gene editing and biosensing due to its desirable features, such as high base resolution and set-and-forget operation. However, as a nucleic acid detection method, an DNA/RNA amplification procedure is still inevitable in CRISPR biosensors. In this study, a highly-ordered nanopore array SERS substrate, coated with silver nanoparticles, was fabricated and utilized as a platform for the specific detection of Salmonella Typhimurium (S. Typhimurium) without the time-consuming DNA amplification step. The smart sensing strategy was established by introducing an ssDNA labeled with a Raman active molecule …