Computer Vision Method in Beer Quality Evaluation—A Review

Lukinac, Jasmina; Mastanjević, Kristina; Mastanjević, Krešimir; Nakov, Gjore; Jukić, Marko

doi:10.3390/beverages5020038

Cited by 36 publications

(27 citation statements)

References 55 publications

(70 reference statements)

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“…It is possible that a high concentration of polyphenols in beer can have a detrimental effect on beer foaming [2]. Although some authors show a positive effect of high polyphenols on beer foam stability [56]. The results obtained are contradictory.…”

Section: Organoleptic Analysismentioning

confidence: 99%

Assessment of Volatiles and Polyphenol Content, Physicochemical Parameters and Antioxidant Activity in Beers with Dotted Hawthorn (Crataegus punctata)

Gasiński

Kawa-Rygielska

Szumny

et al. 2020

Foods

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Beer with the addition of dotted hawthorn (Crataegus punctata) fruit and juice was prepared and analysed. The content of carbohydrates, glycerol and ethanol in beers was determined by high-performance liquid chromatography (HPLC). Analysis of the total content of polyphenols was also performed using the Folin-Ciocalteu method, as well as determining antioxidant capacity by DPPH• and ABTS+• assay, and the ability to reduce iron ions by FRAP assay. Content of volatile compounds was analysed by means of solid-phase microextraction and gas chromatography coupled with mass spectroscopy. Beers with addition of hawthorn, both juice and fruit, had higher antioxidative potential and higher polyphenols concentration compared to control beer. The content of polyphenols in beers was in the range 200.5–410.0 mg GAE/L, and the antioxidant activity was in the range of 0.936–2.04 mmol TE/L (ABTS+• assay), 0.352–2.175 mmol TE/L (DPPH• assay) and 0.512–1.35 mmol TE/L (FRAP assay). A sensory evaluation of beers was also carried out. Beer with hawthorn fruit addition obtained the best scores in sensory analysis for criteria such as aroma, taste and overall quality. This beer had the highest content of volatile compounds (287.9 µg/100 mL of beer), while the control beer had lowest concentrations (35.9 µg/100 mL of beer).

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Section: Organoleptic Analysismentioning

confidence: 99%

Assessment of Volatiles and Polyphenol Content, Physicochemical Parameters and Antioxidant Activity in Beers with Dotted Hawthorn (Crataegus punctata)

Gasiński

Kawa-Rygielska

Szumny

et al. 2020

Foods

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“…The procedure of CV consists of three main steps to follow for the image or video: (i) Acquisition, (ii) pre-processing, and (iii) analysis and interpretation. For (i) acquisition, the equipment needed consists of a camera or scanner and a constant and uniform lighting source [44]. For (ii) pre-processing and (iii) analysis and interpretation, the use of a computer and software with image analysis capabilities such as Matlab ® (MathWorks Inc., Natick, MA, USA), ImageJ ® (U. S. National Institutes of Health, Bethesda, MD, USA) or Image-Pro Plus (Media Cybernetics, Inc., Rockville, MD, USA) is required ( Figure 1) [45,46].…”

Section: Computer Vision Techniquesmentioning

confidence: 99%

Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages

et al. 2019

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Beverages is a broad and important category within the food industry, which is comprised of a wide range of sub-categories and types of drinks with different levels of complexity for their manufacturing and quality assessment. Traditional methods to evaluate the quality traits of beverages consist of tedious, time-consuming, and costly techniques, which do not allow researchers to procure results in real-time. Therefore, there is a need to test and implement emerging technologies in order to automate and facilitate those analyses within this industry. This paper aimed to present the most recent publications and trends regarding the use of low-cost, reliable, and accurate, remote or non-contact techniques using robotics, machine learning, computer vision, biometrics and the application of artificial intelligence, as well as to identify the research gaps within the beverage industry. It was found that there is a wide opportunity in the development and use of robotics and biometrics for all types of beverages, but especially for hot and non-alcoholic drinks. Furthermore, there is a lack of knowledge and clarity within the industry, and research about the concepts of artificial intelligence and machine learning, as well as that concerning the correct design and interpretation of modeling related to the lack of inclusion of relevant data, additional to presenting over- or under-fitted models.

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“…However, it must be considered that the energy use, and relative carbon footprint, can undergo important variations according raw materials, size, processing methods, logistics, etc. Generally speaking technologies have already been implemented within almost all the crucial steps, including mashing, fermentation, even for real-time management to optimize cleaning operations in the brewery [8] or to evaluate the product quality through rapid test based on advanced computer vision and image analysis techniques [9,10].…”

Section: Introductionmentioning

confidence: 99%

Internet of Beer: A Review on Smart Technologies from Mash to Pint

Violino¹,

Figorilli²,

Costa³

et al. 2020

Foods

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The beer production chain includes some crucial steps regarding processing, delivery, service, and consumption that can benefit from the implementation of IoT (Internet of Things) based technologies. Large breweries implemented the use of sensors and digitization before smaller ones among which are craft breweries. Internet of Beer (IoB) technologies are becoming accessible to mid and small sized brewing companies. Therefore, the objective of this work is to review mainly low-cost IoB smart technologies that can be implemented from the mash to the final product and its service, to improve the brewing production, control, delivery, and final quality increasing profitability. The reviewed applications were retrieved both from the scientific databases and from the web. The work is structured in three macro areas such as beer processing, product logistics and traceability, and service. The results show a future trend characterized by a very fast increase in the use of IoB (also open source) systems to drive efficiency, productivity, quality, and safety. This will be done by real-time monitoring and a data-driven decision support system (DSS). Crucial aspects needing further investigation are data ownership and data standardization. The access price of IoB devices and software is destined for a significant decrease while their diversification on the market will grow leading to a massive future implementation within all the production levels.

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Computer Vision Method in Beer Quality Evaluation—A Review

Cited by 36 publications

References 55 publications

Assessment of Volatiles and Polyphenol Content, Physicochemical Parameters and Antioxidant Activity in Beers with Dotted Hawthorn (Crataegus punctata)

Assessment of Volatiles and Polyphenol Content, Physicochemical Parameters and Antioxidant Activity in Beers with Dotted Hawthorn (Crataegus punctata)

Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages

Internet of Beer: A Review on Smart Technologies from Mash to Pint

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