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According to DIN 38409 part 6 (January 1986) “hardness” is defined as the calcium and magnesium ion content of a water sample. In particular cases, barium and strontium ions may also contribute to hardness. Even though the term hardness is not a scientific one and in principle is even legally objectionable since no SI unit exists for it, hardness is still indispensable, as it simplifies the terminology. For this reason, the somewhat dated units are still deemed acceptable alongside the current mg/l, mval/l and mmol/l. The unit “Deutscher Grad” (degrees German hardness), 1 °d (in the past, also known as 1°dH) is equivalent (based on CaO) to 0.3566 mval = 0.179 mmol/l: *)

*) SI units recognized in legal and commercial transactions, whereby °d should be expressed in mmol/l

10.00 mg/l CaO = 7.15 mg/l Ca²⁺ = 0.3566 mval/l

7.19 mg/l MgO = 4.34 mg/l Mg²⁺ = 0.3566 mval/l

For the unit 1 mval/l, the values shown above are higher by a factor of 2.804 (1/10 of the CaO equivalent weight).

28.04 mg/l CaO = 20.04 mg/l Ca²⁺ = 2.804 °d

20.15 mg/l MgO = 12.15 mg/l Mg²⁺ = 2.804 °d

An alkaline earth ion concentration of 1 mg/l corresponds to:

1 mg/l Ca²⁺ = 0.1399 °d = 0.0499 mval/l hardness

1 mg/l Mg²⁺ = 0.2306 °d = 0.0822 mval/l hardness

Calcium and magnesium are the principal alkaline earth metal ions found in natural waters.

For certain applications and/or treatment processes, knowing the total hardness is insufficient, since understanding which alkaline earth metals are responsible for it is important (usually calcium or magnesium ions). These cations are also paired with anions, in which case the ions of carbonic acid play a significant role (carbonate and hydrogen carbonate ions).

The subgroups of hardness can be characterized as follows:

Calcium or lime hardness (Ca-H):

The portion of the water hardness caused by calcium ions.

Magnesium or magnesia hardness (Mg-H):

The portion of the water hardness caused by magnesium ions.

Total hardness (TH):

This term encompasses the sum of the individual types of hardness (Ca-H + Mg-H).

Carbonate hardness (CH):

The carbonate hardness corresponds to the concentration of alkaline earth metal ions equivalent to the hydrogen carbonate and carbonate ions present in the water. These ions are measured in mval/l through determination of the m value. Water that does not require acid for neutralization to reach the m value possesses no carbonate hardness (pH < 4.3). The m value corresponds to the carbonate hardness in mval/l. This is true as long as this value does not exceed the total hardness in mval/l, since by definition the carbonate hardness cannot exceed the total hardness. Water with an m value that exceeds the total hardness in mval/l is called “sodium alkaline” since it contains sodium. In selecting the treatment process, it is advisable to differentiate between calcium and magnesium carbonate hardness (Ca-CH and Mg-CH).

Non-carbonate hardness (NCH):

This is defined as the difference between total hardness and the carbonate hardness and thus, as that portion of calcium and magnesium ions for which no equivalent bicarbonate and carbonate ions are present in the water, but for which an equivalent quantity of other ions exist (e.g., hydroxide, chloride, sulfate, nitrate, phosphate, silicate, humate). Waters, whose m value is ≥ TH (mval/l), do not exhibit non-carbonate hardness.

Required analysis data:

• calcium ion content in mg/l or mval/l

• magnesium ion content in mg/l or mval/l

• acid required to reach the m value in mval/l

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.

The hop oil obtained through steam distillation (refer to links) is dissolved in an organic solvent, separated into its components by means of gas chromatography and determined with a flame ionization detector. The contents are expressed as a percentage of the area of each component compared to the overall area of the peak.

Volatile aroma compounds are driven out of the sample through steam distillation. The ethanolic distillate is saturated with NaCl. Potassium hydrogen sulfite is added to separate carbonyl groups that might interfere with the analysis. The extraction of the aroma compounds is performed by shaking out with dichloromethane and the phases separated by centrifuging.

This test detects the presence of most varieties of two-rowed and multi-rowed winter barley possessing a green aleurone layer. This test is based upon the reaction between HCl and the green pigment, which turns red in its presence.