Terry Howell
Researcher
faculty
Biological and Agricultural Engineering
4 h-index
11 pubs
71 cited
Research Areas
Biography and Research Information
OverviewAI-generated summary
Terry Howell's research focuses on the development and application of biosensing technologies for the rapid detection of foodborne pathogens. His work has involved creating portable and wireless systems, such as piezoelectric immune-biosensors, designed for on-site identification of specific bacterial strains like E. coli O157:H7. Howell also investigates methods for inactivating food contaminants, including studies on the antimicrobial efficacy of gaseous chlorine dioxide on dried herbs. His recent publications utilize advanced techniques, such as deep learning, to enhance the speed and accuracy of bacterial recognition systems, distinguishing between different bacterial strains. Howell collaborates with researchers at the University of Arkansas at Fayetteville and the Arkansas Agricultural Experiment Station, with shared publications totaling up to four with specific colleagues. His scholarship metrics include an h-index of 4, with 10 total publications and 70 total citations.
Metrics
- h-index: 4
- Publications: 11
- Citations: 71
Selected Publications
-
Portable Broadband Dielectric Impedance Immunosensor Based on IDEs for Rapid, Label-Free Whole-Cell E. coli Detection (2026)
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Deep-Learning-Enhanced Automated Coherent-Light Diffraction System for High-Speed, Highly Accurate Strain-Specific Foodborne Bacterial Recognition (2025)
Collaboration Network
Top Collaborators
Jeyamkondan Subbiah
University of Arkansas at Fayetteville
5 shared publications
In database
- Antimicrobial efficacy of gaseous chlorine dioxide for inactivation of Salmonella and Enterococcus faecium NRRL B-2354 on dried basil leaves
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
- Deep-Learning-Enhanced Automated Coherent-Light Diffraction System for High-Speed, Highly Accurate Strain-Specific Foodborne Bacterial Recognition
- Portable Broadband Dielectric Impedance Immunosensor Based on IDEs for Rapid, Label-Free Whole-Cell E. coli Detection
Dongyi Wang
University of Arkansas at Fayetteville
4 shared publications
In database
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
- Deep-Learning-Enhanced Automated Coherent-Light Diffraction System for High-Speed, Highly Accurate Strain-Specific Foodborne Bacterial Recognition
- Portable Broadband Dielectric Impedance Immunosensor Based on IDEs for Rapid, Label-Free Whole-Cell E. coli Detection
Yiting Xiao
University of Arkansas at Fayetteville (US)
3 shared publications
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
- Portable Broadband Dielectric Impedance Immunosensor Based on IDEs for Rapid, Label-Free Whole-Cell E. coli Detection
Chaitanya Pallerla
University of Arkansas at Fayetteville
3 shared publications
In database
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
- Portable Broadband Dielectric Impedance Immunosensor Based on IDEs for Rapid, Label-Free Whole-Cell E. coli Detection
Ramesh Bahadur Bist
University of Arkansas at Fayetteville (US)
3 shared publications
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
- Deep-Learning-Enhanced Automated Coherent-Light Diffraction System for High-Speed, Highly Accurate Strain-Specific Foodborne Bacterial Recognition
Siavash Mahmoudi
University of Arkansas at Fayetteville
3 shared publications
In database
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
- Portable Broadband Dielectric Impedance Immunosensor Based on IDEs for Rapid, Label-Free Whole-Cell E. coli Detection
Yang Tian
2 shared publications
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
Lisa Kelso
2 shared publications
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
Ziyu Liu
2 shared publications
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
Hongbo Xiong
2 shared publications
- Palm-Size Wireless Piezoelectric Immune-Biosensing System for Rapid E. coli O157:H7 Detection
- Palm-size wireless piezoelectric immune-biosensing system for rapid E. coli O157:H7 detection
Tushar Verma
University of Nebraska–Lincoln (US)
1 shared publication
- Antimicrobial efficacy of gaseous chlorine dioxide for inactivation of Salmonella and Enterococcus faecium NRRL B-2354 on dried basil leaves
Xinyao Wei
University of Nebraska–Lincoln (US)
1 shared publication
- Antimicrobial efficacy of gaseous chlorine dioxide for inactivation of Salmonella and Enterococcus faecium NRRL B-2354 on dried basil leaves
Byron D. Chaves
University of Nebraska–Lincoln (US)
1 shared publication
- Antimicrobial efficacy of gaseous chlorine dioxide for inactivation of Salmonella and Enterococcus faecium NRRL B-2354 on dried basil leaves
Yang Tian
University of Arkansas at Fayetteville (US)
1 shared publication
- Deep-Learning-Enhanced Automated Coherent-Light Diffraction System for High-Speed, Highly Accurate Strain-Specific Foodborne Bacterial Recognition
Ziyu Liu
University of Arkansas at Fayetteville
1 shared publication
In database
- Deep-Learning-Enhanced Automated Coherent-Light Diffraction System for High-Speed, Highly Accurate Strain-Specific Foodborne Bacterial Recognition
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