1. Near Infrared Reflectance Spectroscopy: A potential tool for predicting abalone meat quality Miriam Fluckiger Supervisors: Louise Ward, Malcolm Brown & Natalie Supervisors: Louise Ward, Malcolm Brown & Natalie Moltschaniwskyj Ph.D Candidate, Australian Seafood Cooperative Research Centre, University of Tasmania, CSIRO Marine and Atmospheric Research

2. Evaluating meat quality Expensive and time consuming Subjective sensory assessments Chemically wasteful extractions Destructive sampling

3. 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

4. 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

5. A B C B C A Foot of abalone scanned in three locations NIRS and abalone

6. 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)

7. Discriminating holding treatments PC 1 PC 2

8. Discriminating between species 80 frozen abalone obtained from grower 20 Greenlip 20 Blacklip 20 Hybrid 20 Greenlip x Hybrid Abalone thawed overnight and scanned with NIR

9. PC 1PC 2 Discriminating species

10. Discriminating between freezing 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

11. PC 2 PC 1 Discriminating freezing methods

12. Developing a model for moisture Spectral Data Chemometric modelling

13. Model for moisture in abalone

14. 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 amino acids and glycogen?

15. Acknowledgements Abalone sample providers: Great Southern Waters Abalone Indented Head, Victoria Cold Gold Abalone Dunalley, Tasmania Southern Australian Seafoods Port Lincoln, South Australia

16. Thank you Miriam Fluckiger Ph.D Candidate Australian Seafood CRC University of Tasmania, NCMCRS CSIRO Marine and Atmospheric Research GPO Box 1538 Hobart, Tasmania 7001, Australia Ph:(03) 62325224, Fax:(03) 62325000 miriamf@utas.edu.au

19. Seasonal glycogen levels

20. Free amino acid concentrations (mg FAA/g wet weight)

21. 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