Grant: Applied Research Tools and Instruments Grants
Lethbridge Community College
$150,000.00
Quality inspection of agri-food products using near-infrared (NIR) hyperspectral imaging
EF 2019-20
Résumé
Southern Alberta has a rich diversity of crop production including wheat, canola, pulses, corn, potatoes, and sugar beets. The region generates over $3.11 billion in farm revenues and provides high quality raw material for over 120 established agri-food businesses located near Lethbridge, including many world-leading foodprocessors. Robust quality measurement of agri-food products throughout the supply chain is critical, asrequired by food safety regulations and increased consumer demand for high quality and safe food.The food processing industry is looking for rapid and non-destructive methods for quality and safetyinspection. Near Infrared (NIR) Hyperspectral imaging is emerging as rapid, non-destructive andmulti-analytical technology for quality and safety inspection of agri-food products with improved measurementaccuracy. Hyperspectral imaging provides the spectral information in a spatially resolved manner; therefore, each pixel of a scanned sample has its own spectrum. The vast amount of compositional information alongwith spatial labeling, can be used for quality (texture, flavor, shape, nutritional value, and composition) and safety (chemical and microbial contamination, foreign material, impurity, and adulteration) inspection ofagri-food products such as: cereals and other grains, meat, fruits and vegetables, dairy products, and processed food.
Programme
Applied Research Tools and Instruments Grants
Bénéficiaire
Emplacement
Alberta, Canada
Type de bénéficiaire
Other
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
548196-2019
Name nom
Corscadden, Kenneth
Department département
Head Office
Organization id
1694
Institution établissement
Lethbridge Community College
Province en
Alberta
Province fr
Alberta
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2019
Award amount
150000
Program id
CARTI
Program name en
Applied Research Tools and Instruments Grants
Program name fr
Subventions d'outils et d'instruments de recherche appliquée
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
1562
Committee name en
Applied Research Tools and Instrument Grants
Committee name fr
Subventions d'outils et d'instruments de recherche appliquée
Area of application code
1209
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Agriculture
Area of application fr
Agriculture
Research subject code
1200
Research subject group en
Agricultural engineering
Research subject group fr
Génie rural
Research subject en
Agricultural engineering
Research subject fr
Génie rural
Installment
inst:1 - 1
Partie
1
Nb partie
1
Application title
Quality inspection of agri-food products using near-infrared (NIR) hyperspectral imaging
Keyword
NSERC
Application summary
Southern Alberta has a rich diversity of crop production including wheat, canola, pulses, corn, potatoes, and sugar beets. The region generates over $3.11 billion in farm revenues and provides high quality raw material for over 120 established agri-food businesses located near Lethbridge, including many world-leading foodprocessors. Robust quality measurement of agri-food products throughout the supply chain is critical, asrequired by food safety regulations and increased consumer demand for high quality and safe food.The food processing industry is looking for rapid and non-destructive methods for quality and safetyinspection. Near Infrared (NIR) Hyperspectral imaging is emerging as rapid, non-destructive andmulti-analytical technology for quality and safety inspection of agri-food products with improved measurementaccuracy. Hyperspectral imaging provides the spectral information in a spatially resolved manner; therefore, each pixel of a scanned sample has its own spectrum. The vast amount of compositional information alongwith spatial labeling, can be used for quality (texture, flavor, shape, nutritional value, and composition) and safety (chemical and microbial contamination, foreign material, impurity, and adulteration) inspection ofagri-food products such as: cereals and other grains, meat, fruits and vegetables, dairy products, and processed food.