The use of a portable robotic sparkling wine pourer and image analysis to assess wine quality in a fast and accurate manner
Sparkling wines, which contain dissolved carbon dioxide (CO2) are economically important for Australia, France, Spain, Italy, USA, and Chile among other countries. Climate change is expected to influence the final quality of sparkling wine due to predicted increments in ambient temperature during grapegrowing. This effect which will likely produce: i) flavour and aroma changes of grapes and wines, ii) decrease protein concentration and iii) increase alcohol content in wines. Balanced protein and alcohol concentration are related quality traits of sparkling wines as foamability and foam stability are affected by these parameters. Quality of sparkling wines can be assessed visually using parameters such as colour, bubble behaviour, appearance (bead) and foam persistence (mousse). Robotics allows consistent repeatability of assessment, by standardising pouring style, speed, angle, shape and type of glass as well as wine ambient temperature. When combined with chemometrics and standardised assessments, robotics can be correlated to traditional measures of quality. This paper discusses the development of a robotic bottle pourer to standardise time and wine volume of pouring into a glass. Images from foam dynamics in glasses were collected automatically with a digital video camera attached to the pourer and transferred to a computer. Data were then analysed by image analysis algorithms, which convey the information into bubble size, foamability (ability of the wine to produce foam), foam persistence and stability, and collar stability. Results showed that the automated robotic pourer and image analysis techniques are comparable to most common chemometrics and sensory panel results to assess quality of sparkling wine.
Lima, B., Fuentes, S., Caron, M., Needs, S. and Howell, K. (2016). The use of a portable robotic sparkling wine pourer and image analysis to assess wine quality in a fast and accurate manner. Acta Hortic. 1115, 69-74
chemometrics, foam stability, sensory analysis, Matlab programming, multivariate data analysis