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