Australian Institute of Food Science and Technology: 50th Anniversary Conference. Sydney – July 2017

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Accounting for Taste: Radio ABC National Interview

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Click on the image to listen to ABC National.

Taste is a complex thing. How and why we respond to food involves multisensory perception and can’t easily be separated from our cultural, social and personal histories.

So, can deliciousness be measured?

Researchers today are using biometric testing to make sense of our preferences and offer insight into the conscious and unconscious processes that determine how we taste.

Dr Sigfredo Fuentes, Senior Lecturer in Wine Science in the School of Agriculture and Food at the University of Melbourne

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New Paper: Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and artificial neural networks modelling techniques

By

Claudia Gonzalez Viejo 1, Sigfredo Fuentes 1*, Damir Torrico1, Kate Howell1, and Frank R. Dunshea1.

1 University of Melbourne, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, VIC 3010, Australia

* Correspondence: sfuentes@unimelb.edu.au; Tel.: +61 3 9035 9670

Journal of The Science of Food and Agriculture

Full Article: CLICK HERE

ABSTRACT:

Beer quality is mainly defined by its color, foamability and foam stability, which are influenced by the chemical composition of the product such as proteins, carbohydrates, pH and alcohol. Traditional methods to assess specific chemical compounds are usually time-consuming and costly. This study used rapid methods to evaluate 15 foam and color-related parameters using a robotic pourer (RoboBEER) and chemical fingerprinting using near infrared spectrometry (NIR) from six replicates of 21 beers from three types of fermentation. Results from NIR were used to create partial least squares regression (PLS) and artificial neural networks (ANN) models to predict four chemometrics such as pH, alcohol, Brix and maximum volume of foam.

NIRANN