Beer is defined as the alcoholic beverage obtained through the yeast fermentation of malted cereals with added hops [1]. Quality factors are extremely important to take into account in beer production due to the fact that consumers preferences have been constantly changing and, nowadays, they are demanding more premium products [2]. Amongst the most significant quality components to focus on are the visual attributes such as foam stability, foam texture which is given by the bubbles size, colour and clarity, as they constitute the first impression that consumers perceive. Nevertheless, other parameters such as alcohol content that determines the strength of beer, amount of carbon dioxide (CO2), flavour stability (as bottled beer is likely to
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Furthermore, bitter resins and tannins derived from hops contribute to the bitterness, colour and the astringent sensation that characterise beers. The colour of the beer is also affected by the malts used in its production and the Maillard reaction of the sugars according to the temperature applied when drying malts [7]. The alcohol content and sweetness are given by the type of yeast, its flocculence and level of attenuation. Thus fast flocculating yeasts will result in low attenuation, which produces sweeter beers with lower levels of alcohol as yeasts are not capable of fermenting all available carbohydrates. Likewise, low flocculating yeasts will present high attenuation, resulting in a dry beer, which is the desired high quality product [8, …show more content…
The RoboBEER incorporates an iPhone 5S camera (Apple Inc., Cupertino, CA. USA) to record videos for further image analysis with a customised Matlab® code which is capable of calculating parameters such as the maximum volume (MaxVol), life time of foam (LTF) and total life time of foam (TLTF), and three sensors to measure alcohol gas content, temperature and release of CO2 within the period of video capturing. In this paper, the functionality of RoboBEER is presented as well as a descriptive sensory analysis to determine the intensities of the most representative attributes in beer to compare the robot and human performances in the assessment. The results from foam measurements were used to create a model for pattern recognition using Artificial Neural Networks (ANN) to classify beers according to their type of fermentation based only on automated outputs from the
Furthermore, bitter resins and tannins derived from hops contribute to the bitterness, colour and the astringent sensation that characterise beers. The colour of the beer is also affected by the malts used in its production and the Maillard reaction of the sugars according to the temperature applied when drying malts [7]. The alcohol content and sweetness are given by the type of yeast, its flocculence and level of attenuation. Thus fast flocculating yeasts will result in low attenuation, which produces sweeter beers with lower levels of alcohol as yeasts are not capable of fermenting all available carbohydrates. Likewise, low flocculating yeasts will present high attenuation, resulting in a dry beer, which is the desired high quality product [8, …show more content…
The RoboBEER incorporates an iPhone 5S camera (Apple Inc., Cupertino, CA. USA) to record videos for further image analysis with a customised Matlab® code which is capable of calculating parameters such as the maximum volume (MaxVol), life time of foam (LTF) and total life time of foam (TLTF), and three sensors to measure alcohol gas content, temperature and release of CO2 within the period of video capturing. In this paper, the functionality of RoboBEER is presented as well as a descriptive sensory analysis to determine the intensities of the most representative attributes in beer to compare the robot and human performances in the assessment. The results from foam measurements were used to create a model for pattern recognition using Artificial Neural Networks (ANN) to classify beers according to their type of fermentation based only on automated outputs from the