The quantification of simple sugars can be challenging due to their high polarity, low volatility, their lack of a chromophore and their common occurrence in complex matrices [1–3]. HPTLC can separate mono- and oligosaccharides after minimal sample preparation and can sensitively detect these compounds after post-chromatographic derivatization. The published method for quantification of sugars in honey [2] allows analyzing multiple samples on a single plate within approximately 3.7 hours. With the method transferred to the new HPTLC PRO System, this test can be accomplished in about 2.5 hours. An alternative method developed for HPTLC PRO requires just 1.3 hours per plate.

HPTLC allows quantification of sugars in honey and other complex matrices at low running costs. Depending on the level of equipment used, the speed, automation and reliability of the obtained quantitative results can be increased. With the new method developed for the HPTLC PRO System, the main sugars in honey can be investigated in short time and other sugars, such as oligomers present in fermentation processes, can be analyzed at the same time.

Individual sugars are dissolved in 50% aqueous acetonitrile with sonication to obtain a final concentration of 1.0 mg/mL for qualitative tests, method transfer and method development. For quantification and during determination of the working range, a mixture of fructose, maltose, sucrose, and glucose at concentration levels between 12.5 μg/mL–1000.0 μg/mL is used in 50% aqueous acetonitrile.

The samples are dissolved in 50% aqueous acetonitrile with sonication to obtain a final concentration of 1.0mg/mL for qualitative tests and are applied in 20-fold dilution for quantification of the two main sugars in honey (fructose, glucose).

HPTLC plates silica gel 60 F₂₅₄ (Merck), 20 x10 cm are used.

Samples and standard solutions are applied as bands with the Automatic TLC Sampler (ATS 4, quantitative settings, 10 μL syringe) or the HPTLC PRO Module APPLICATION using the default settings (two rinsing solutions), 20 tracks, band length 6.0 mm, distance from left edge 18.0 mm, track distance 8.5 mm, distance from lower edge 8.0 mm. 1.0–3.0 μL for sample solutions and 1.0 μL for standard solutions are applied.

(1) Plates are developed in the ADC 2 with chamber saturation (with filter paper, 60 min), after activation at 33% relative humidity (*) for 10 min using a saturated solution of magnesium chloride, followed by 5 min pre-conditioning, development with n-butanol – isopropanol – aqueous boric acid (5 mg/mL) 3:5:1 (V/V) to the developing distance of 85 mm (from the lower edge), followed by drying for 15 min** [2]. (2) Plates are developed in the HPTLC PRO Module DEVELOPMENT after activation at 0% relative humidity (*molecular sieve) for 10 min, followed by 90 s pre-conditioning at 30% pump power, development with n-butanol – isopropanol – aqueous boric acid (5 mg/mL) 3:5:1 (V/V) to the developing distance of 70 mm (from the lower edge), followed by drying for 15 min. (3) Plates are developed in the HPTLC PRO Module DEVELOPMENT after activation at 0% relative humidity (molecular sieve) for 10 min, development with ethyl acetate – methanol – boric acid (5 mg/mL) – acetic acid 50:40:10:2 (V/V) to the developing distance of 70 mm (from the lower edge), followed by drying for 5 min.

Note: *methods (1) and (2) are very robust and no significant differences for the R_Fvalues were obtained between 0 and 33% relative humidity; **deviation from [2]

Aniline-diphenylamine-phosphoric acid reagent (ADPA reagent): 2.0 g of diphenylamine and 2.0 mL of aniline are dissolved in 80.0 mL of methanol, 10.0 mL of o-phosphoric acid (85%) are added and the mixture is shaked until any precipitate is dissolved, then again 10.0 mL of methanol are added. The plate is sprayed with the Derivatizer (yellow nozzle, spraying level 6), heated at 110°C for 10 min on the TLC Plate Heater.

Images of the plate are captured with the TLC Visualizer 2 at UV 366 nm and white light after derivatization.

Absorbance measurement at 370 nm [3] is performed with TLC Scanner 4 and visionCATS 3.0 (slit dimension 5.00 mm x 0.30 mm, scanning speed 50 mm/s, data resolution 25 μm/step for single-wavelength scan, spectra recording from 350–800 nm).

The methods have been compared for their consumption of time and consumables, and their repeatability: method (1) with the conditions from [2] by using the ATS 4 and ADC 2, method (2) with the developing solvent from [2] by using the HPTLC PRO Modules APPLICATION and DEVELOPMENT, and method (3) with an alternative developing solvent by using the HPTLC PRO Modules APPLICATION and DEVELOPMENT. All three methods are well suited for quality control of honeys.

The UV/VIS spectra recorded after derivatization show a high signal response for all analytes at 370 nm. Therefore, LODs/LOQs have been determined for the four relevant sugars in honey at this wavelength to facilitate evaluation in routine quality control by using scanning densitometry at a single wavelength (LOD_{370 nm}/LOQ_{370 nm} for fructose and sucrose: 6.0/18.0 ng/zone, for maltose and glucose: 12.0/48.0 ng/zone). The linear working range extends from LOQ_{370 nm} to 125.0 ng/zone.

For the quantification of fructose, maltose, sucrose, and glucose, method (2) is recommended. In this case, the best separation of the four analytes in an optimum R_F range is achieved in significantly less run time compared to method (1). To proof the suitability of the method (2) for quantification, four samples of honey have been selected of which one was mixed with maple syrup 1:1 to determine the recovery. The results are listed in Table 2.

Method (3) is best suited for the analysis of sugars of different sizes (mono- and oligomers) and sugar acids of high polarity (e.g. glucuronic acid). The entire migration distance is used for separation whereas methods (1) and (2) are optimized for the separation and quantification of mono- and dimers.

With the three methods described herein, the principal sugars of honey can be analyzed at low running costs. The instrument investment costs for method (1) are lower, but more time and manual intervention is required for each analysis. Methods (2) and (3) have been developed for routine quality control and a high sample throughput. In this case, the level of automation and reduced time per sample are of greater importance, making the HPTLC PRO System the better choice. Method (3) can be used for sugar analysis in general, e.g. for optimization and monitoring of fermentation processes and for analysis of sugar containing products in divers matrices.

Contact: Dr. Melanie Broszat, CAMAG, Sonnenmattstrasse 11, 4132 Muttenz, Switzerland, melanie.broszat[at]camag.com

Honey is derived from nectar collected by honey bees from a range of floral sources. After collection, numerous processes take place outside and also within the hive, such as exposure to bee related enzymes and removal of moisture, which ultimately convert the nectar into honey. Honey can be considered a complex natural product, consisting of a high amount of sugars (>70%), residual moisture (typically 17–20%) and a small portion (approx. 3%) of non-sugar constituents, including minerals, vitamins, protein, phenolics and flavonoids. These minor constituents are directly related to the honey’s nectar source and thus play a critical role in the authentication of honeys. They also influence the honey’s organoleptic and physicochemical characteristics as well as its level of bioactivity. Antioxidant activity is linked to high concentrations of phenolics, phenolic acids, anthocyanins, hydroxycinnamic acid derivatives and flavonoids. DPPH* (2,2-diphenyl-1- picrylhydrazyl, C₁₈H₁₂N₅O₆) is a powerful radical used for the antioxidant screening of compounds, mixtures of constituents, extracts and biological matrices, such as wine, fruit juices, salivary secretions and plant extracts, and also, as demonstrated in this study, honey.

The phytochemical composition of honeys depends on the floral nectar source and thus on the geographic origin and time of harvesting. It might also be influenced by processing and storage conditions, by the bee species collecting the nectar and the bee enzymes the nectar and honey come in contact with. Despite this complexity, honeys from the same floral species present characteristic constituent patterns, which can be used in the authentication of their floral source. These patterns can be effectively captured by HPTLC analysis of honeys’ organic extracts and can thus assist in the authentication of their floral origins.

As a major source of energy, carbohydrates, including simple sugars such as glucose, fructose, sucrose, maltose or galactose, play an important role in human nutrition. The determination of their content in various botanical products and food items is therefore of interest. However, the quantification of simple sugars is not without challenges due to their high polarity, low volatility and lack of a sizeable chromophore. Furthermore, these sugars are often found in complex matrices, which require their separation from proteins, fats, and / or minerals as well as other matrix constituents prior to analysis.

Herein, three different methods for the analysis of honey samples are presented. Method A is suited for the honey floral source identification by HPTLC fingerprinting, method B enables a fast assessment of antioxidant zone activity, and method C allows to quantify sugars and to detect sugar adulterants in honey.

The developed authentication method (A) is rapid, reliable, and repeatable and can therefore be used as a convenient analytical tool in routine honey quality control. The method involves a simple solvent extraction step followed by a short chromatographic development time (9 –10 min). It requires minimal solvent and reagent input while allowing the simultaneous analysis of up to 14 samples on a single plate. HPTLC-DPPH analysis (B) is advantageous over traditional assays which measure the total antioxidant activity, as it can detect individual active compounds and quantify their respective contribution to the overall antioxidant effect. The analytical approach is easy and fast to perform and powerful in visualizing antioxidant compounds. Further, their respective< activity can be quantified as gallic acid equivalents, even if their chemical identity is unknown. The developed method for sugar analysis (C) is convenient and easy to perform in a single development step with minimal sample pre-treatment. Moreover, only small sample quantities (approx. 100 mg) and small volumes of development solvent (approx. 35 mL) are needed for the analysis of multiple samples in a single run, which makes the method also a very cost effective approach to easily detect and quantify major sugars in honey.

(A) Figure 1 shows the HPTLC fingerprints of three different honeys, labelled as Jarrah, Banksia and Marri, obtained at UV 366 nm and white light after derivatization. The two sets of images show a unique pattern for each honey within a R_F range of 0.05 to 0.60, representative of each honey’s specific fingerprint.

Four different honeys, all purchased labelled as Jarrah honeys, were analyzed at UV 366 nm and at white light after derivatization (Figure 2). Though obtained from different suppliers, all honeys share common zones between R_F 0.05 to 0.60 in their fingerprint, which can serve as a convenient authentication tool.

As a natural product, the composition of honey, even when derived from the same floral nectar, can be expected to exhibit some natural variation between samples. In order to obtain a representative fingerprint and to limit the impact of natural variation on the effectiveness of the method as an authentication tool, individual samples were pooled to produce an ‘average’ fingerprint, in which major deviations from the norm were ‘diluted out’ and key compounds, representative of the floral source across all samples, were amplified.

The effectiveness of this approach is demonstrated in Figure 3 where a pooled HPTLC fingerprint captures the key features of five individual samples, all labelled as Manuka honey. Slight variations present in the Manuka samples (e.g. zones at R_F 0.41 at UV 366 nm after development and at R_F 0.55 and R_F 0.38 at UV 366 nm after derivatization, as well as individual zone intensities, which correspond to compound concentrations) are no longer evident in the pooled fingerprint.

(B) After derivatization, the plate background appeared dark pink, reflecting the color of DPPH* in its reduced state. Where constituents with antioxidant activity reacted with DPPH*, the intensity of the background color was diminished, visualizing compounds with antioxidant zone activity. The stronger the antioxidant activity, the brighter white the active zone appeared against the pink background. Gallic acid was detected on the plate at R_F 0.29 after derivatization.

For the quantitative analysis of antioxidant zone activity of honey as gallic acid equivalents, the obtained images were converted into peak profiles (PPI), which were used to derive calibration curves of absorbance vs concentration. Using the trend line equations from the calibration curves, the LOD and LOQ were found to be 16.5 ng and 50.0 ng for gallic acid in honey and 14.3 ng and 43.3 ng for pure gallic acid in methanol [3]. As there were no noticeable differences between the LOD and LOQ of gallic acid in methanol and in the honey matrix, it could be concluded that the honey matrix did not have an interfering effect.

The accuracy of the method (expressed as mean recovery) was within 99.9 to 101.5%. Precision (intra-day and inter-day) and repeatability expressed as standard deviation (SD) and %RSD were between 0.69 and 2.29 (SD) and between 1.01 and 3.07% (%RSD). Repeatability was found to fall within a range of 0.49 – 1.83 (SD) and 0.60 – 2.25% (%RSD). The above parameters were all within the International Conference on Harmonization (ICH) guidelines and, thus, confirmed the validity of the method.

The validated HPTLC-DPPH analysis was used to visualize and quantify as gallic acid equivalents the antioxidant activity of individual zones found in Manuka and UNF honey extracts. Four antioxidant zones were detected in Manuka and three active zones in UNF honey extracts.

(C) At white light individual sugars presented distinct, bright colors: glucose was dark ash, fructose orange, sucrose dark brown and maltose dark green colored. Their corresponding R_F values were for fructose R_F 0.14, maltose R_F 0.20, sucrose R_F 0.27 and glucose R_F 0.32 [5].

All the major sugars in honeys were clearly separated from the matrix and the sugars themselves were clearly separated from each other, forming distinct individual zones. The working range of the evaluated method was determined within the range of 250‒1250 ng/zone. The sensitivity of the method (LOD/LOQ) was calculated; LOD/LOQ for glucose: 33.0/100.0 ng; fructose: 22.0 ng/66.6 ng; sucrose: 21.2 ng/64.2 ng; maltose: 63.5 ng/192.5 ng, respectively. The accuracy, precision (intra-day and inter-day), repeatability and robustness of the developed method were also assessed and were within the acceptable ranges outlined in the International Conference on Harmonization (ICH) guidelines.

Fructose and glucose contents were readily quantifiable in all honey samples, but maltose and sucrose, if present, were below the LODs in the volumes (3.0 μL) applied (though they can be detected at higher application volumes). In all purposefully adulterated honeys, next to fructose and glucose other sugars like maltose and sucrose were easily quantifiable as they were within the working range.

Thus, mixing honey with sugar syrups leads to significant changes in the amount of sugars such as maltose and sucrose that normally are only present in minor quantities. These changes are easily detected by HPTLC analysis, as described here, and the method can, therefore, be used not only to quantify major sugars in honey but also as quality control tool to detect sugar syrup adulterations in honey.

(A) HPTLC fingerprint profiling of honey extracts is a quick visual screening method that can also be used for quality control to authenticate a honey’s floral origin. The predominant nectar source can be confirmed, additionally unknown or non-specific zones can be investigated for potential additional floral and non-floral compounds, which might assist in detecting adulteration cases. The method is convenient and cost-effective due to the ability to run multiple samples (up to 14) on a single plate.

(B) The study herein used honey as a model matrix to demonstrate the ability of HPTLC-DPPH analysis to visualize and quantify the antioxidant activity of individual constituents in a complex matrix even if their respective chemical identity is not (yet) known. It is anticipated that the approach can also be adopted for the analysis of other matrices with antioxidant activity like plant extracts. The method established here, provides guidance on how to examine other complex systems for potential matrix effects and to capture antioxidant activities of individual constituents.

(C) The HPTLC method for the detection and quantification of simple sugars in honey is easy to perform and offers a convenient approach to not only quantify the major sugars found in honey but also to identify potential adulteration with sugar syrups. The absence of any pre-treatment steps prior to analysis is a major advantage, which might make the method also an interesting analysis approach for the determination of simple sugars in other botanicals and foods.

[1] C. Locher et al. J Planar Chromatogr (2017) 30(1):57–62.
[2] C. Locher et al. J Planar Chromatogr (2018) 31(3):181–189.
[3] M. K. Islam et al. J Planar Chromatogr (2020) 33(3):301–311.
[4] M. K. Islam et al. J Planar Chromatogr (2020) 33(5):489–499.
[5] M. K. Islam et al. Molecules (2020) 25(22).

Contact: Dr. Cornelia Locher, CRC for Honey Bee Products and Division of Pharmacy, School of Allied Health, University of Western Australia, Crawley, Western Australia, 6009, Australia, connie.locher[at]uwa.edu.au

An SST is commonly used in routine quality control to validate the performance of an analytical system, including the method and the apparatus. In chromatography, the SST is a process that analyzes the behavior of specific reference substances under certain chromatographic conditions to know whether the method is reproducible, robust, and suitable for the intended application. In HPTLC, the SST often qualifies only a limited region of the chromatogram (e.g., specific R_F values or small R_F ranges due to the need for having barely separable substances). If no deviation from the acceptance criteria is observed, the entire chromatographic system is considered compliant. However, in practice, the chromatographic quality of the other regions remains unknown. Additionally, HPTLC methods using developing solvents of different polarity and selectivity may require different sets of substances for SST. Some substances are costly and not readily available, which can increase the cost of analysis. To overcome these problems, a Universal HPTLC Mix (UHM) for use in SST was developed [1].

With the UHM, HPTLC laboratories have a single solution, applicable as SST to a wide range of chromatographic systems, with different polarities and selectivities. Its low price, stability in solution, and capability to detect small chromatographic variations make the UHM particularly attractive. The replacement of conventional substances for SST by the UHM will help laboratories to save time and money required for laborious investigation of specific reference substances for each method to be qualified. Different fields of application can benefit from the UHM concept, such as herbal drugs, forensics, pharmaceuticals, cosmetics, etc.

In the first step of the investigation, the suitable substances for the UHM were selected. The researchers [1] considered the following criteria, which lead to a list of 56 candidates: 1) Low hazard (not harmful and non-toxic substances); 2) Detectability at UV 254 and 366 nm prior to derivatization; 3) Stability in solution for at least two months; 4) Low cost (<50 CHF/g).

The chromatographic behavior of those 56 standards was evaluated with 20 developing solvents, covering a wide range of polarity and selectivity. The objective was to find a smaller group of substances that achieves an even distribution throughout the entire chromatogram for the maximum number of different developing solvents. Additionally, each developing solvent should achieve baseline separation for at least 3 – 4 substances. The chosen substances and their fingerprints in eight different developing solvents are shown in the following image.

To evaluate, whether the UHM responds to variations of the chromatographic conditions, three experiments were performed. In the first, plates were conditioned to different relative humidity (from 0% to 90%) prior to development. As shown in the image below, the UHM is sensitive to variations in relative humidity, particularly to the higher ones. The differences are more expressive if the developing solvent contains no water.

In the second experiment, the individual proportion of the solvents in developing solvents B and F was changed (±10%), and the effect on the chromatography was evaluated. A difference of up to 0.06 R_F units was observed from the mean R_F values of the control track. In the third experiment, different levels of chamber saturation were tested: unsaturated, partially saturated (20 min, no filter paper), and saturated (20 min, with filter paper). R_F values increased with partial saturation, but then decreased with full saturation, proving that the UHM can detect chamber saturation problems.

The UHM performance was evaluated in intra- and inter-laboratory tests based on the ΔR_F in developing solvents B, F and G. For the intra-laboratory test, the confidence interval ΔR_F was 0.03, while for the inter-laboratory test, this value was 0.04.

[1] T. K. T. Do, M. Schmid, M. Phanse, A. Charegaonkar, H. Sprecher, M. Obkircher, E. Reich. Development of the first universal mixture for use in system suitability tests for High- Performance Thin-Layer Chromatography. J Chromatogr A, 1638 (2021). DOI: 10.1016/j.chroma.2020.461830.

Contact:

Dr. Tiên Do, CAMAG Laboratory, Sonnenmattstrasse 11, 4132 Muttenz, Switzerland, tien.do[at]camag.com

For more information about the Universal HPTLC Mix (UHM), please visit the Sigma-Aldrich website.

Gemmotherapy, also known as phytoembryotherapy, is an alternative phytotherapeutic treatment that uses extracts prepared mainly from the embryonic tissues of plants, e.g., emerging shoots and buds of various trees and shrubs. This type of therapy is used in European countries, such as Germany, France, Belgium, and Italy [1] [2]. The herbal drug is typically collected during spring, at the peak time of the tree’s or shrub’s germination. Gemmotherapy claims, that shoots and buds are exceptional parts of a plant in space and time. They develop substances not contained in the adult plants and provide high concentrations of minerals, vitamins, plant hormones, etc. [2]. It also claims to have higher biological activity in comparison to other traditional treatments with herbal drugs [2]. For preparation of the gemmotherapy medicines, the fresh buds or shots of the plant are macerated for 21 days with a mixture of alcohol and glycerine, at a ratio of 1:20 fresh plant material : mixture. The extracts are then filtered and diluted 1:10 with a mixture of glycerine, alcohol and water [3].

In her high school diploma work, Ms. Brunner qualitatively investigated the chemical differences between the fingerprints of the buds and mature leaves of four herbal drugs used in gemmotherapy: birch (Betula pubescens EhRh.), hazel (Corylus avellana L.), ash (Fraxinus excelsior L.), and dog rose (Rosa canina L.). Samples of each specimen have been collected at different germination periods between spring (when sprouting started) and summer of 2019 (mature leaves). The focus of the investigation was on secondary metabolites, which are generally considered as active principle of herbal drugs. Ms. Brunner was honoured with the “Simply Science” prize of the “Schweizer Jugend forscht” contest in 2020 [4].

System Suitability Test (SST): verbascoside and quercitrin are prepared in methanol at concentrations of 1 mg/mL and 0.5 mg/mL, respectively.

After collection, the samples are kept in the freezer to preserve freshness. Prior to extraction, any ice crystals on the frozen buds or leaves are removed mechanically. Then, the material is cut into small pieces with a knife. For the extraction, 500 mg of the cut material are mixed with 5mL of methanol and sonicated for 10minutes at room temperature. The mixture is centrifuged for 5 minutes and the supernatant is used as test solution.

HPTLC plates silica gel 60 F₂₅₄ (Merck), 20 x10 cm

Automatic TLC Sampler (ATS 4), 15 tracks, band length 8.0 mm, track distance 11.4 mm, distance from left edge 20.0 mm, distance from lower edge 8.0 mm, application volume 2.0 μL

In the ADC 2 with chamber saturation for 20 min (with filter paper) and after conditioning at 33% relative humidity for 10 min using a saturated solution of magnesium chloride, development with ethyl acetate, formic acid, water (15:1:1 v/v/v) to 70 mm (from the lower edge), drying for 5 min

The plate is heated at 100 °C for 3 min using the TLC Plate Heater, immersed into natural product (NP) reagent (1.0 g of 2-aminoethyl diphenylborinate dissolved in 200 mL of ethyl acetate) dried under cold air and documented. Subsequently, the plate is immersed into anisaldehyde-sulfuric acid (AS) reagent (1.0mL of p-anisaldehyde dissolved in 200 mL of a mixture of methanol, acetic acid and sulfuric acid 17:2:1 (v/v/v)) and then heated at 100 °C for 3 min.

TLC Visualizer 2 under UV 254 and UV 366 nm (prior to derivatization), UV 366 nm (after derivatization with NP reagent) and white light (after derivatization with NP plus AS reagents)

HPTLC analyses of birch, ash, hazel and dog rose samples were performed with samples from three individual plants of each species, collected in the Basel area in Switzerland. The buds and leaves of these plants were gathered eleven times between March and June of 2019. Results are shown in the figures below and are reported for one individuum of ash and dog rose. Their fingerprints were compared to those of the respective gemmotherapy products.

The following observations were made: first, the fingerprints of the buds are very different from those of the mature leaves, e.g., the young bud of ash (C368) and its respective mature leaf (C434), under several detections (see shown figures). Second, the younger buds contain generally a higher concentration of secondary metabolites than buds with first shots (leaves) or, in some cases, the matured leaves. For example, samples of young bud of ash (C368, C369, C370) show several blue intense zones under UV 366 nm after derivatization with NP (orange bracket), corresponding to hydroxycinnamic acid derivatives, not seen in the subsequent samples. Third, the transition from buds to young leaves is generally paralleled by a gradual change in the composition of the fingerprints. For example, the more mature the buds, the lower the content of hydroxy-cinnamic acid derivatives. In the case of dog rose, a decrease is observed in the content of hydroxy-cinnamic acid derivatives (green arrow) accompanied by an increase in the number of zones corresponding to flavonoids (yellow zones, yellow bracket).

The fingerprints of commercial gemmotherapy products show similarities with those of the buds, but fingerprints are generally fainter (e.g. blue frame). This was expected, because the products are usually prepared in a diluted form, following the homeopathic philosophy.

Additional experiments will be performed to investigate the variation in the composition more quantitatively and to remove the freezing process prior to extraction, in order to copy the industrial preparations for gemmotherapy.

[1] A.-D. Raiciu, “Gemmotherapy – Modern Medicine,” in Proceedings, 2019, vol. 29, p. 117.
[2] A. Sarkova and M. Sarek, “EAV and Gemmotherapy – Medicine for the Next Millennium? (technique as a means to link eastern and western medicine),” in Engineering in Medicine and Biology 27th Annual Conference, 2005, pp. 4943–4946.
[3] Seroyal, “Gemmotherapy. Embryonic tissue extracts to stimulate organ systems toxin elimination toward the emunctories,” Reference guide. [Online]. Available: https://www.seroyal.com/media/wysiwyg/seroyal/downloads/Gemmotherapy_Brochure.pdf. (accessed: 17.07.2020).
[4] https://sjf.ch/arbeiten-nationaler-wettbewerb/ (accessed: 20.07.2020)

Contact:

Débora Frommenwiler, CAMAG, Sonnenmattstrasse 11, 4132 Muttenz, Switzerland, debora.frommenwiler[at]camag.com