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A scanning device is utilized to obtain a high resolution image of a sample of barley kernels. Algorithms are then applied to detect and segment each individual kernel captured in the image. Subsequently, each individual kernel is analyzed by a Convolutional Neural Network (CNN) with a layer structure that has been specifically selected and developed for analyzing and classifying agricultural commodities. The CNN is trained with verified information (also known as "ground truth") so that it can differentiate barley varieties. The ground truth consists of pure samples of kernels from different barley varieties that were previously digitized using the device and comprises the full data set (artificial intelligence models). In order to obtain accurate artificial intelligence models, the algorithms must be trained to recognize the wide range of variability present in the pure samples, such as those collected from varieties grown in different regions and under varying conditions as well as from various crop years. The purpose of training is to teach the algorithms to understand and detect the patterns unique to each variety that can be used to distinguish it. Once trained, the algorithms are capable of accurately predicting the varietal purity of an unknown sample of barley kernels, provided that the variety has been integrated into the artificial intelligence models.

Solids contained in the wort are separated by filtration at a temperature of approx. 85 °C and measured by weighing.

The hot break material (trub) and any hop particles which may be present in the wort, must first be removed. After the wort has been cooled to 2 °C, it is filtered through a glass fiber filter. The residue remaining on the filter is dried and then weighed.

Cold break material or cold trub refers to all material that settles out in the process of chilling wort after separation of the hot trub or hot break material. Cold trub can be filtered out of the wort and primarily consists of proteins (48–57 %), tannins (11–26 %) and carbohydrates (20–36 %). The amount of cold break material in wort depends on the quality and composition of the raw materials, brewhouse equipment and wort handling. In academic and professional circles, opinions regarding the significance of cold break material for downstream processes and for the quality of the finished beer are strongly divided [1, 2, 5]. Under certain circumstances, the quantity of cold break material in wort may exceed 250 mg/l, especially where accelerated fermentation is practiced. Ultimately, this can detract from the flavor of the finished beer [3]. Breweries, where removal of the cold break material has been practiced successfully, determine the quantity of cold break in their pitching wort at regular intervals, in order to evaluate the efficacy of their separation equipment.

The fermentation cellar yield is calculated using the value determined for the amount of extract contained in a batch of wort relative to the amount of extract present in the raw materials used to produce the wort.

The moisture content of adjuncts is determined through the loss in mass during a standardized drying process, in which ground malt is dried at a defined temperature within a specified time in an electrically heated drying oven.

The moisture content is determined through the difference in the weight of the adjuncts prior to and after drying.

For samples with a moisture content greater than 17 % (for corn over 15 %), the sample has to be dried prior to conducting the analysis.