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Computer Vision Method in Beer Quality Evaluation—A Review

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beverages Review Computer Vision Method in Beer Quality Evaluation—A Review Jasmina Lukinac 1 , Kristina Mastanjevi´c 1,* , Krešimir Mastanjevi´c 1 , Gjore Nakov 2 and Marko Juki´c 1 1 Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, Franje Kuhaˇca20, 31000 Osijek, Croatia; [email protected] (J.L.); [email protected] (K.M.); [email protected] (M.J.) 2 Department of Biotechnology and Food Technology, University of Ruse Angel Kanchev, Branch Razgrad, Aprilsko vastanie Blvd. 47, Razgrad 7200, Bulgaria; [email protected] * Correspondence: [email protected]; Tel.: +385-3122-4356 Received: 8 April 2019; Accepted: 16 May 2019; Published: 1 June 2019 Abstract: Beers are differentiated mainly according to their visual appearance and their fermentation process. The main quality characteristics of beer are appearance, aroma, flavor, and mouthfeel. Important visual attributes of beer are foam appearance (volume and persistence), as well as the color and clarity. To replace manual inspection, automatic, objective, rapid and repeatable external quality inspection systems, such as computer vision, are becoming very important and necessary. Computer vision is a non-contact optical technique, suitable for the non-destructive evaluation of the food product quality. Currently, the main application of computer vision occurs in automated inspection and measurement, allowing manufacturers to keep control of product quality. This paper presents an overview of the applications and the latest achievements of the computer vision methods in determining the external quality attributes of beer. Keywords: beer; computer vision; image analysis; quality 1. Introduction Beer is one of the oldest (low) alcoholic beverages in the world and the third most widely-consumed drink (after water and tea). Today, besides industrial commercial beers, craft beer has gained great popularity among consumers [1]. Beer is produced in a brewing process from malt, water, brewer’s yeast, and hops. The basic quality characteristics of beer are divided into visual and sensory attributes. Appearance is the first attribute that consumer experiences (and evaluates) when he/she gets a glass of beer. Important visual characteristics of beer are foam appearance (volume and persistence), as well as color and clarity of the beer. Perception and acceptability of beer are also determined by other properties e.g., the alcohol content (expressed as Alcohol by volume, ABV or Alcohol by weight, ABW), carbon dioxide content, the presence/absence of off-flavors in bottled beer [2–4], aroma, mouthfeel and bitterness (listed in International Bitterness Units, or IBUs). The main collections of the standard methods of beer analysis used worldwide are methods of the Institute of Brewing and Distilling (IBD), American Society of Brewing Chemists (ASBC), European Brewery Convention (EBC), and Central European Commission for Brewing Analysis (MEBAK). Beers are differentiated mainly according to their visual appearance (depends on its color and turbidity) and their fermentation process. Regarding the yeast used and the fermentation temperature, beer can be categorized in the three main categories: top-fermented (ale), bottom-fermented (lager), and naturally fermented beer. Beer classification can be done regarding the color during the production process. Beer color is determined by the malt color that develops during the Maillard reactions and Beverages 2019, 5, 38; doi:10.3390/beverages5020038 www.mdpi.com/journal/beverages Beverages 2019, 5, 38 2 of 21 Beverages 2019, 5, x FOR PEER REVIEW 2 of 21 tocaramelization distinguish bright, in themalting red, dark and and roasting black process beer color. [5]. Therefore,The aforementioned it is possible beer to distinguish color is actually bright, differentred, dark shades and black of beeryellow, color. red, The brown aforementioned and black; t beerhe most color common is actually color diff erentis a pale shades amber of yellow, produced red, frombrown pale and malts. black; theCommonly most common used methods color is a palefor beer amber classification produced from are flame pale malts. atomic Commonly spectroscopy, used linearmethods discriminant for beer classification analysis [6], are nuclear flame atomic magnetic spectroscopy, resonance linear and discriminantmultivariate analysisanalysis [ 6[7],, nuclear8], and Fouriermagnetic transform resonance infrared and multivariate spectroscopy analysis analysis [7 [9].,8], Trained and Fourier human transform inspectors infrared usually spectroscopy perform an inspectionanalysis [9 ].of Trained food sensory human quality, inspectors but usuallythis method perform is unreliable an inspection because of food the results sensory may quality, vary but due this to subjectivemethod is unreliableevaluation becauses by the inspectors. the results may vary due to subjective evaluations by the inspectors. Given the unreliability of the human inspectors, there is a need for a precise, objective, and reproducible instrumentalinstrumental method method that that could could imitate imitate human human testing methods.testing methods. Based on thisBased assumption, on this assumption,researches try researches to develop try an to instrumental develop an methodinstrumental to evaluate method the to external evaluate and the internal external appearance and internal of appearancethe product non-destructively.of the product non Due-destructively. to a visual inspection,Due to a visual monitoring inspection, the external monitoring quality the attributes external qualityis time-consuming, attributes is time and- theconsuming, computer and vision the computer method enablesvision method to perform enables this to task perform automatically. this task automatically.Remembering Remembering that a way to that improve a way brewing to improve techniques, brewing techniques, rapid feedback rapid from feedback quality from control quality is controlrequired. is Therefore,required. Therefore, the development the development and implementation and implementation of new methods of new are ofmethods great importance are of great in importancethe beer industry. in the This beer paper industry. covers This an overview paper covers of the currentan overview achievements of the current in applying achievements the computer in visionapplying methods the computer to determine vision the methods external to qualitydetermine attributes the external of beer. quality attributes of beer. 2. Computer Computer V Visionision and I Imagemage A Analysis-Basicsnalysis-Basics Computer vision system (CVS) is a non-destructivenon-destructive technique that includes several different different technologies, e.g., e.g., optical, mechanical mechanical and and electromagnetic instrumentation, and and digital image processing [10]. [10]. CVS CVS is isthe the automatic automatic extraction extraction of information of information from from digital digital images. images. CVS is CVS a rapid, is a objectiverapid, objective and effective and eff alternativeective alternative over the over destructive the destructive methods methods [11,12]. Computer [11,12]. Computer vision includes vision severalincludes operations: several operations: image capturing, image capturing, processing processing and image and analysis image (Figure analysis 1). (Figure After1 image). After capture, image therecapture, is a there process is a of process digitization of digitization (transformation (transformation images into images numbers) into numbers) [13,14]. [13,14]. Figure 1. Components of a computer vision system. CVS can measure the external features of products, recognize objects and extract quantitative information from from digital digital images images [15]. [15 Currently,]. Currently, the main the application main application of CVS occurs of CVS in the occurs automated in the inspectionautomated providing inspection constant providing control constant of product control ofquality. product Configuration quality. Configuration of CVS is relatively of CVS is standard, relatively basicstandard, components basic components are illumination are illumination device device(lights), (lights), a device a device for forimage image acquisition acquisition (digital camera/scanner), frame grabber (in the case of an analog camera), and computer hardware and software (algorithms for image analyzing and pre-processing) [16,17]. Beverages 2019, 5, 38 3 of 21 camera/scanner), frame grabber (in the case of an analog camera), and computer hardware and software (algorithms for image analyzing and pre-processing) [16,17]. 2.1. Illumination With the camera, one of the most important elements of the CVS system is the illumination. The illumination device is used for object illumination under test. There are many properties of illumination (light angle of incidence, light source color, direct/diffuse light technique), which must be selected in such a way to reduce disturbances (shadows, reflections, noise) or enhance image contrast [14,18,19]. Suitable illumination increases the quality of captured images and improves the accuracy of the analysis. There are several simple rules and good practices that can help select the proper illumination and improve the image quality: maximizing the contrast of the features that must be inspected or measured • minimizing the contrast of the features of no interest • getting rid of unwanted variations caused by ambient light and differences between items that are • non-relevant to the inspection task. To view
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