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- Machine learning (2)
- Multi-mode spectroscopy (2)
- Artificial intelligence (1)
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- Compositional analysis (1)
- DPPH antioxidant activity (1)
- Data fusion (1)
- Deep learning (1)
- Dispute models (1)
- Extracellular vesicles (1)
- Fish fraudulence (1)
- Fish freshness (1)
- Fish species identification (1)
- Focus group study (1)
- Food quality (1)
- Ghana (1)
- Homogenization (1)
- Pasteurization (1)
- Pentadesma butyracea seeds (1)
- Shelf-life assessment (1)
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Articles 1 - 5 of 5
Full-Text Articles in Food Processing
A Novel Machine-Learning Framework Based On A Hierarchy Of Dispute Models For The Identification Of Fish Species Using Multi-Mode Spectroscopy, Mitchell Sueker, Amirreza Daghighi, Alireza Akhbardeh, Nicholas Mackinnon, Gregory Bearman, Insuck Baek, Chansong Hwang, Jianwei Qin, Amanda M. Tabb, Jiahleen Roungchun, Rosalee S. Hellberg, Fartash Vasefi, Moon Kim, Kouhyar Tavakolian, Hossein Kashini Zadeh
A Novel Machine-Learning Framework Based On A Hierarchy Of Dispute Models For The Identification Of Fish Species Using Multi-Mode Spectroscopy, Mitchell Sueker, Amirreza Daghighi, Alireza Akhbardeh, Nicholas Mackinnon, Gregory Bearman, Insuck Baek, Chansong Hwang, Jianwei Qin, Amanda M. Tabb, Jiahleen Roungchun, Rosalee S. Hellberg, Fartash Vasefi, Moon Kim, Kouhyar Tavakolian, Hossein Kashini Zadeh
Food Science Faculty Articles and Research
Seafood mislabeling rates of approximately 20% have been reported globally. Traditional methods for fish species identification, such as DNA analysis and polymerase chain reaction (PCR), are expensive and time-consuming, and require skilled technicians and specialized equipment. The combination of spectroscopy and machine learning presents a promising approach to overcome these challenges. In our study, we took a comprehensive approach by considering a total of 43 different fish species and employing three modes of spectroscopy: fluorescence (Fluor), and reflectance in the visible near-infrared (VNIR) and short-wave near-infrared (SWIR). To achieve higher accuracies, we developed a novel machine-learning framework, where groups of …
Comparison Of Dna Extraction Methods For The Detection Of Canned Tuna Species With Dna Mini-Barcoding, Aubrey J. Emmi, Biola Fatusin, Rosalee S. Hellberg
Comparison Of Dna Extraction Methods For The Detection Of Canned Tuna Species With Dna Mini-Barcoding, Aubrey J. Emmi, Biola Fatusin, Rosalee S. Hellberg
Food Science Faculty Articles and Research
Tuna is susceptible to species mislabeling due to its high demand, quick rate of production, and wide range of price points. DNA barcoding, a sequencing-based technique, allows for the detection of species mislabeling by targeting a standardized region of DNA. A mitochondrial control region (CR) DNA barcode has been found to be capable of species discrimination for tuna, but it is challenging to recover the entire DNA fragment from canned tuna. While a short fragment of CR, referred to as a “mini-barcode,” has shown some success with canned tuna species identification, more research is needed to improve identification rates. The …
Homogenization And Thermal Processing Reduce The Concentration Of Extracellular Vesicles In Bovine Milk, Anna P. Colella, Anuradha Prakash, John Miklavcic
Homogenization And Thermal Processing Reduce The Concentration Of Extracellular Vesicles In Bovine Milk, Anna P. Colella, Anuradha Prakash, John Miklavcic
Food Science Faculty Articles and Research
Extracellular vesicles (EVs) in bovine milk confer beneficial physiologic effects to consumers. Industrial processing treatments may affect the amount or bioactivity of EVs intrinsic to bovine milk. We investigated how the content and concentration of EVs were affected by homogenization and thermal processing of raw bovine milk. Raw milk was processed by homogenization, low-temperature (LT) heat, or pasteurization [high-temperature short-time (HTST) and ultra-high-temperature (UHT)] in a pilot processing facility. EVs were isolated from the raw and processed bovine milk using differential ultracentrifugation and quantified using a nanoparticle tracking analyzer. Bovine milk EVs were assessed for total miRNA and protein concentrations …
Pentadesma Butyracea In Ghana – Indigenous Knowledge, Uses, And Seed Characterization, Josephine Akuba Timtey, Francis Alemawor, William Otoo Ellis, Nana Baah Pepra-Ameyaw, Jacob K. Agbenorhevi
Pentadesma Butyracea In Ghana – Indigenous Knowledge, Uses, And Seed Characterization, Josephine Akuba Timtey, Francis Alemawor, William Otoo Ellis, Nana Baah Pepra-Ameyaw, Jacob K. Agbenorhevi
Food Science Faculty Articles and Research
This study ascertained the indigenous knowledge and uses of Pentadesma butyracea plant through a focus group study. The proximate, mineral, antinutritional compositions, and antioxidant activity of P. butyracea seed were also determined using standard analytical methods. The results of the focus group study showed that P. butyracea is essentially used for its butter which is prepared by women processors who hand down the skill of butter processing to their children. The butter is used for cooking, frying, and preparing traditional delicacies, and the plant is known to possess some therapeutic potential. The seed recorded the following mean proximate values: fat …
Rapid Assessment Of Fish Freshness For Multiple Supply-Chain Nodes Using Multi-Mode Spectroscopy And Fusion-Based Artificial Intelligence, Hossein Kashani Zadeh, Mike Hardy, Mitchell Sueker, Yicong Li, Angela Tzouchas, Nicholas Mackinnon, Gregory Bearman, Simon A. Haughey, Alireza Akhbardeh, Insuck Baek, Chansong Hwang, Jianwei Qin, Amanda M. Tabb, Rosalee S. Hellberg, Shereen Ismail, Hassan Reza, Fartash Vasefi, Moon Kim, Kouhyar Tavakolian, Christopher T. Elliott
Rapid Assessment Of Fish Freshness For Multiple Supply-Chain Nodes Using Multi-Mode Spectroscopy And Fusion-Based Artificial Intelligence, Hossein Kashani Zadeh, Mike Hardy, Mitchell Sueker, Yicong Li, Angela Tzouchas, Nicholas Mackinnon, Gregory Bearman, Simon A. Haughey, Alireza Akhbardeh, Insuck Baek, Chansong Hwang, Jianwei Qin, Amanda M. Tabb, Rosalee S. Hellberg, Shereen Ismail, Hassan Reza, Fartash Vasefi, Moon Kim, Kouhyar Tavakolian, Christopher T. Elliott
Food Science Faculty Articles and Research
This study is directed towards developing a fast, non-destructive, and easy-to-use handheld multimode spectroscopic system for fish quality assessment. We apply data fusion of visible near infra-red (VIS-NIR) and short wave infra-red (SWIR) reflectance and fluorescence (FL) spectroscopy data features to classify fish from fresh to spoiled condition. Farmed Atlantic and wild coho and chinook salmon and sablefish fillets were measured. Three hundred measurement points on each of four fillets were taken every two days over 14 days for a total of 8400 measurements for each spectral mode. Multiple machine learning techniques including principal component analysis, self-organized maps, linear and …