Post on 23-Dec-2015
Near Infrared Reflectance Spectroscopy:A potential tool for predicting abalone meat quality
Miriam Fluckiger
Supervisors: Louise Ward, Malcolm Brown & Natalie Moltschaniwskyj
Ph.D Candidate, Australian Seafood Cooperative Research Centre, University of Tasmania, CSIRO Marine and Atmospheric Research
Evaluating meat quality
• Expensive and time consuming
• Subjective sensory assessments
• Chemically wasteful extractions
• Destructive sampling
NIRS – What is it and how does it work?
• Chemical bonds in different organic molecules absorb infrared light at different wavelengths
• The NIR instrument measures the amount of reflected light giving rise to a spectrum
• Highly developed in grain and flour milling industry
• Used in meat industry to predict meat composition
NIRS and abalone meat quality
• Qualitative:
• Is NIRS a viable tool for discriminating different treatment groups?
• eg. Diet "A" versus Diet "B“
• Quantitative:
• Is NIRS capable of measuring different chemical components in the muscle tissue of abalone ?
• eg. Glycogen and moisture
AB
CB
C
A
• Foot of abalone scanned in three locations
NIRS and abalone
Discriminating between holding treatment
• 60 abalone collected from farm
• 30 abalone scanned with NIR probe on arrival at lab (same day processing)
• 30 abalone held overnight in plastic lined polystyrene boxes
• scanned with NIR 24 hours later (next day processing)
Discriminating holding treatments
PC 1
PC
2
Discriminating betweenspecies
• 80 frozen abalone obtained from grower
• 20 Greenlip• 20 Blacklip• 20 Hybrid• 20 Greenlip x Hybrid
• Abalone thawed overnight and scanned with NIR
PC 1
PC
2
Discriminating species
Discriminating betweenfreezing methods
• 12 abalone shucked and frozen by immersion in brine/ice slurry• Thawed and scanned with NIR
• 6 then steamed and scanned with NIR
• 12 abalone shucked and frozen in air at -20°C• Thawed and scanned with NIR
• 6 then steamed and scanned with NIR • 12 abalone shucked and fresh meat scanned
PC
2
PC 1
Discriminating freezing methods
Developing a model for moisture
Spectral Data
Chemometric modelling
Model for moisture in abalone
Summary – where to from here?
• Further develop NIRS calibration models
• Can NIRS discriminate between abalone fed different diets?
• Can NIRS be used to quantify taste-active Components such as free aminoacids and glycogen?
Acknowledgements
Abalone sample providers:
• Great Southern Waters AbaloneIndented Head, Victoria
• Cold Gold AbaloneDunalley, Tasmania
• Southern Australian SeafoodsPort Lincoln, South Australia
Thank you
Miriam Fluckiger
Ph.D CandidateAustralian Seafood CRCUniversity of Tasmania, NCMCRSCSIRO Marine and Atmospheric ResearchGPO Box 1538 Hobart, Tasmania 7001, AustraliaPh:(03) 62325224, Fax:(03) 62325000miriamf@utas.edu.au
Seasonal glycogen levels
Free amino acid concentrations (mg FAA/g wet weight)
Taste-active components in abalone
• Unique umami taste of abalone linked to
certain free amino acids (FAA) and nucleotides
• Glutamic acid & adenosine monophosphate
(AMP) intensify the savoury taste of abalone
• Glycogen & moisture content also contribute
to palatability