Emulation and backtracking of HPLC chromatographic profiles for glucosinolate valuation from total sulphur concentrations in oilseed rape seeds*
Emulation und Verifizierung von HPLC Chromatogrammen für die Abschätzung des Glucosinolatgehaltes aus Gesamtschwefelkonzentrationen in Rapssaat
Journal für Kulturpflanzen, 68 (4). S. 102–111, 2016, ISSN 1867-0911, DOI: 10.5073/JfK.2016.04.02, Verlag Eugen Ulmer KG, Stuttgart
The relationship between the total glucosinolate (GSL) concentration calculated from the total sulfur concentration which had been measured by means of X-ray fluorescence spectroscopy and the content of glucobrassicanapine, glucobrassicine, gluconapine, napoleiferine, progoitrine and 4-hydroxiglucobrassicine in the seeds which were measured by chromatographic methods was determined in the line of quality assessment studies of oilseed rape standard reference materials. The constant ratio between individual aliphatic GSLs which is independent of the total GSL content allows to emulating the concentration of individual GSLs from the total GSL content on basis of the total S content. As indol GSLs represent a constant background value of the total GSL content their estimated concentration is added to the calculated sum of aliphatic GSLs in order to obtain an emulated total GSL content. In a simple program written in BASIC the typical background variability of individual GSLs can be randomly added to the results which yields different chromatograms that are statistically not different from true HPLC chromatograms. This may assist in distinguishing true experimental effects in studies targeting effects on individual GSLs from those of background analytical error variability. The program may also be used for an independent verification of HPLC chromatograms of GSLs in oilseed rape as it allows backtracking of a given total GSL content to its expected individual GSL concentrations in chromatographic analysis. *
Key words: Glucobrassicanapine, glucobrassicine, gluconapine, glucosinolates, HPLC, napoleiferine, oilseed rape, progoitrine, sulfur, 4-hydroxiglucobrassicine, X-ray fluorescence, X-RF method
Aus Daten zur Zertifizierung der Gehalte an Schwefel, Gesamt- und Einzelglucosinolaten dreier EU Standardreferenzmaterialen aus Rapssaat und Literaturdaten wurden die Beziehungen der Gehalte zueinander und deren methodisch bedingte Variabilität bestimmt. Kernergebnis ist, dass die Gehalte einzelner Glucosinolate (GSL) eine Funktion des Gesamt-GSL-Gehaltes sind. Dabei ist die Variabilität der Einzel-GSL-Gehalte signifikant höher als die ihres summarischen Gesamtgehaltes, insbesondere aber signifikant höher als die aus Gesamtschwefelgehalten (mittels wellenlängendispersiver Röntgenfluoreszenzanalyse) berechneten Gesamt-GSL-Gehalte. In diesem Beitrag wird ein BASIC Script vorgestellt, welches aus Gesamtschwefelgehalten den Gesamt-GSL-Gehalt an Hand der für die EU Standardmethode (X-RF Methode) vorgeschriebenen Funktionen berechnet und diesen Gesamtgehalt auf die 6 in der EU HPLC-Standardmethode identifizierten Einzel-GSLe (Glucobrassicanapin, Glucobrassicin, Gluconapin, Glucosinolate, Napoleiferin, Progoitrin, und 4-Hydroxiglucobrassicin) aufteilt. Zusätzlich kann das Programm die Einzel-GSL-Gehalte mit einer aus den analytischen Daten ermittelten, zufällig verteilten, aber methodenspezifischen Variabilität der chromatographischen Analyse ausgeben, oder aus vorgegebenen Gesamt-GSL-Gehalten die zu erwartenden Gehalte an Einzel-GSL berechnen. Das Programm ermöglicht damit die unabhängige Überprüfung von HPLC Analysen. Umgekehrt können mit dem Programm bei Vorgabe eines Gesamt-GSL-Gehaltes die bei chromatographischer Analyse zu erwartenden Konzentrationen an Einzel-GSLen bestimmt werden.
Stichwörter: Glucobrassicanapin, Glucobrassicin, Gluconapin, Glucosinolate, HPLC, Napoleiferin, Progoitrin, Raps, Röntgenfluoreszenz, Schwefel, 4-Hydroxiglucobrassicin, RFA-Methode
Double low oilseed rape varieties produce seeds with much lower concentrations in eruic acid and GSLs than found in native genotypes. During the introduction of double low oilseed varieties in agricultural production in the 1980s it became clear that there was a lack of suitable, fast and accurate analytical methods to separate seeds according to their total GSL content (Schnug, 1989a, b; Wathelet et al., 1995). The breakthrough was the invention of the so-called X-RF method which relies on the close relationship between total sulfur and total GSL content in oilseeed rape seeds (Schnug and Haneklaus, 1987). During the rigorous testing of the X-RF method against various competing chromatographic methods it became clear that the variability of the results arising from calculating the total GSL content by means of the total S concentration was significantly smaller than the variability caused by assessing the total GSL content by summing up the concentrations of the six individual GSLs prescribed in the EU HPLC method (glucobrassicanapine, glucobrassicine, gluconapine, napoleiferine, progoitrine and 4-hydroxiglucobrassicine).
This paper describes a BASIC program that calculates not only the total GSL content of oilseed rape seeds by determining the total S concentration, but also permits the differentiation of individual GSLs. In addition, a true HPLC chromatogram can be employed to cross-check for errors in the software-controlled division of individual GSLs. As an extra option the program permits to add typical variability inherent to chromatographic methods which may help to distinguish true experimental effects on individual GSLs in studies from background analytical error variability.
In general, the relationship between the total S content of oilseed rape seeds and the total GSL content has been checked excessively during the time the EU was seeking for a proper, says fast and accurate method to distinguish between rapeseed batches of different GSL content for granting subsidies (Schnug, 1988). The breakthrough in terms of accuracy, repeatability and speed was finally the so-called X-RF (X-ray fluorescence) method. The X-RF method determines the total S concentration in rapeseeds by means of wavelength dispersive X-ray fluorescence analysis in a simple three step procedure (Schnug and Haneklaus, 1986, 1987a, b). The calculation formulas for computing the total GSL content from the total S concentration provided by Schnug and Haneklaus (1988) have been verified in a large number of inter-laboratory comparisons (Schnug and Kallweit, 1987) and these formulas were finally adopted by the EU in combination with wavelength dispersive X-RF as compulsory standard method. The concentration range for total S in rapeseeds is divided in two ranges: above 11 mg/g S the original calibration function of the X-RF method, which has been also verified by stoichiometric assessments (Schnug et al, 1992b, Zhao et al., 1992) is applied (Annex: line 600), but below 11 mg/g S a calibration function considering the non-linear relationship between total S and total GSL content is used (Schnug and Haneklaus, 1990; annex: line 800). This non-linear function compensates slightly changes of the total protein concentration in seeds with low GSL concentration due to environmental factors like for instance S deficiency in the growth medium.
In line 920 (annex) a correction factor for systematic error deviations of the HPLC method can be brought into consideration if required. In the recent program description the adjustment is made to the latest results of EU standardization.
The analytical data for establishing the regression equations between total GSL analyzed by X-RF and individual GSL concentration in oilseed rape seeds were collected from a number of method inter-comparisons conducted by the Bureau of Standards (BCR) of the European Commission (EU) performed on oilseed rape standard reference materials (Schnug et al., 1992; Wathelet et al., 1988, 1991, 1992). The standardized regression equations for calculating individual GSLs from the total GSL content can be found in the program script (see annex) in lines 1000–1600.
During the exhaustive evaluation procedure of the EU standard methods for GSL determination in rapeseeds the urgent need for standard reference materials (SRM) became an obvious task given to the then operating Community Bureau of Standards (BCR) (Wagstaffe et al., 1992; Wathelet et al., 1988). As a result three SRMs (BCR SRM 190, BCR SRM 366, BCR SRM 367) with certified total contents for GSLs and S were released. Any efforts to certify the concentration of individual GSLs failed utterly. The remarkable phenomenon was that although the sum of 6 individual GSLs analyzed by means of the EU protocol for HPLC was successful, the certification of the individual concentration proved to be not feasible (Wathelet et al., 1987, 1989). The reason is most likely some methodically inherent incapability of the HPLC to differentiate distinctively and sharp enough between individual GSLs.
In the mathematical procedure the variability of the individual GSLs observed in HPLC analysis (Wathelet et al., 1987) was standardized and randomized (see annex lines 2000–4700), and then added to the individual GSL concentrations calculated from the total S content (see annex lines 5300–5800).
In addition to the previously described features the program allows also backtracking of a given total GSL content to its corresponding total S content and based on this data to calculate an expected concentration of individual GSLs (annex line 30000–38735). This procedure is flawed slightly in the lower ranges of GSL concentrations, because the re-calculation is based on an inverted linear calibration function for calculating the total S concentration from GSLs (annex line 34500). This procedure was necessary as the resolution of the cubic function used in line 800 of the annex provided non-conclusive results. This error is, however, well beyond the background error of any HPLC analysis.
The program “EMU” (see annex), which performs the above described tasks has been written in BASIC 3.11 in an ancient MSDOS 3.2 environment. However, x86 DOS emulators available from the internet still allow to run this kind of program in recent operation systems (e.g. WINDOWS 10). Installation instructions are provided in the annex.
Table 1 displays in 9 steps example runs with “EMU”. The first decision to make is whether a HPLC chromatogram of GSLs in a rapeseed sample shall be emulated from its total S concentration, or if an existing total GSL content in rapeseeds shall be broken down into estimates for individual GSL concentrations (Table 1, step 3).
Table 1. Operational steps and output of the program EMU for the emulation and backtracking of glucosinolates in oilseed rape
DOSBox 0.74, Cpu speed: 3000 cycles, Framskip 0, | Step |
DOSBox Status Windows | 1: The program is written in BASIC and to run it on any WINDOWS computer first load the emulator software DOSBOX and the BASIC interpreter into the same directory where the script is stored as “EMU.bas”. After starting DOSBOX first key in: keyb gr < return > to activate the German keyboard layout and MOUNT the directory where “EMU.bas” is stored to “C”. |
******************************** Proceed and confirmation press < RETURN> | 2: Any alphanumerical input has to be in UPPER CASES! This program script supports no printout. If hardcopies are required you should use the screendump option of your operating system or simply SNIPE and copy it. |
modus: HPLC-create (1) HPLC-check (2) | 3: Choose "1" to generate total and individual GSLs from total S input. Choose "2" to estimate individual GSLs from total GSL content. |
With variability no (1) or yes (2) | 4: Choose "1" to add typical “normal” variability to generate total and individual GSLs from total S input. Choose "2" to estimate individual GSLs from total GSL. |
Total sulphur content in seeds (mg/g) | 5: Input is in mg/g total S in air dry seeds (8% H2O) with 42% fat. |
Emulation without variability | 6: The program calculates the total GSL content from the total S content according to the calibration formulas prescribed for employing the X-RF method according to the EU standard method and the individual GSLs as described in the text. |
Emulation without variability | 7: When “2” for results with variability was chosen in the previous menu, the program adds a random variability to the results which reflects the one observed during ring tests for individual GSLs with HPLC. |
modus: HPLC-create (1) HPLC-check (2) | 8: Choosing "2" generates a set of individual GSL concentrations expected at the given input of GSL in μmol/g dry (8% H2O) seeds with 42% fat. |
If the first option (HPLC emulation) is chosen another decision has to be made if the results shall be static or with a random variability conform to the common range of HPLC determination (Table 1, step 4). After entering the total S concentration in mg/g S the results are processed either without or with variability (Table 1, steps 6 and 7). It should be mentioned that emulating GSL concentrations from total S analysis requires S determination which is highly accurate and repeatable, features which are only fulfilled by wavelength dispersive X-RF analysis (Wagstaffe et al., 1992). Energy dispersive X-RF, combustion methods, spectroscopic analyses and gravimetry following wet digestion of the sample do not comply with the quality standards of wavelength dispersive X-RF (Haneklaus et al., 1994), hence the quality of the emulated GSL content in terms of accuracy and repeatability will be significantly diminished when S concentrations obtained by these methods are fed into EMU.
In the “without variability” mode the program will provide for a defined S concentration consistently the same GSL concentration. In case the option “with variability” is chosen (Table 1, step 4) then an emulated amount of variability is added to this concentration, which meets the variability for the analysis of individual GSLs assessed during the fruitless certification attempt by BCR (Wathelet et al., 1987).
Repeated entry of the same S concentration in this mode will generate GSL patterns according to step 6 (Table 1), but with a random amount of variability. For instance: the input of 5 mg/g S at step 5 (Table 1) provides a result of 29.2 μmol/g total GSL when the mode “without variability” had been chosen in step 4 (Table 1); the 10 times repeated input of 5 mg/g S at step 5 gives a series of 31.7, 32.6, 27.0, 26.7, 28.5, 31.7, 28.0, 26.3 and 34.2 μmol/g total GSL. In step 7 the difference between results with and without variability for the particular input at step 4 is shown. With each repetition of the same input of total S the average of the collected results will approximate the value achieved in the mode “without variability”, says for an infinite number of repetitions of the same input for mg/g S the deviation of the averaged emulated results from X-RF in the “with variability” mode (Table 1, step 7) approximates zero. One practical application is to check and verify effects on individual GSLs claimed in variety or growth experiments where no sufficient statistics is provided. Many of such effects reported in the literature (e.g. Marquardt and Schlesinger, 1987) fall into the range of uncertainty of the analytical method and thus may become doubtful, at least from a statistical point of view.
Yet another feature of the program is that it permits to backtrack a given total GSL content to its corresponding total S content and to calculate from this data an expected concentration for individual GSLs (Table 1, step 3). An example for the output of the program is given in Table 2.
Table 2. Backtracking individual GSLs in oilseed rape seeds from the total GSL content and comparison of backtracked GSLs with individual GSLs emulated from the total S content by means of the program “EMU“
Glucosinolate | Backtracking* from 33 μmol/g total GSL (μmol/g) | Emulation** from 5 mg/g total S (μmol/g) |
Progoitrine | 19.1 | 18.1 |
Napoleiferine | 0.66 | 0.63 |
Gluconapine | 7.94 | 7.6 |
Glucobrassicanapine | 1.42 | 1.4 |
4-OH-glucobrassicine | 3.06 | 3.1 |
Glucobrassicine | 0.13 | 0.13 |
Sum | 32.3 | 30.1 |
* Program “EMU” Modus “HPLC-check“ | ||
This procedure is flawed a little in the lower ranges of GSL concentration, because the re-calculation is done by employing the inverted linear calibration function for calculating the total S concentration from GSLs (annex line 34500) and as a matter of fact resolving the cubic function used in line 800 of the annex gives non-conclusive results. But this error shall be well beyond the background error of any HPLC analysis.
The “HPLC-check” modus of “EMU” may be used for an independent verification of HPLC chromatograms of oilseed rape GSLs as it allows sourcing a given total GSL content to its expected individual GSL concentrations in a chromatographic analysis.
The following program emulates HPLC analyses according to the EU standard method from total sulfur analyses in rapeseeds. The program is written in BASIC and to run it on any WINDOWS computer first the emulating software DOSBOX (DOSBOX, 2016) and a BASIC (GW-BASIC, 2016) interpreter have to be loaded in the same subdirectory, where the script is stored as “EMU.bas”. The script below must be copied from line 10–40000 and saved in plain ASCII as emu.bas in the same directory as the basic interpreter and a batch file “emu.bat” which contains one line with the command “basica emu” in. After starting DOSBOX first key in: keyb gr < return > to activate the German keyboard layout and then use the BASIC command “MOUNT” to access the directory where your program files are stored.
The program itself starts after the command > basic emu < return > is keyed in. The input is case sensitive and accepts only upper cases for alphanumeric inputs.
If you are unable to retrieve the script in ACII from this file you can download it from this source (DOI: 10.13140/RG.2.1.1128.8089):
The program supports no printer, if hardcopies are required simply SNIPE the result tables and print directly from the SNIPE program provided with the operating system.
“EMU” program script for BASIC Interpreters (GW-BASIC 3.11, or newer) |
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10 REM Script EMU.bas use TRON to assist any debugging |
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96 INPUT” **************************************>>: ", MODUS |
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5700 OH4V = OH4 + VAR4OH |
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9850 GOTO 210 |
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DOSBOX, 2016: DOSBox, an x86 emulator with DOS. http://www.dosbox.com/.
GW-BASIC, 2016: Download the last release: 3.23 http://www.gw-basic.com/downloads.html.
Haneklaus, S., F. Murray, E. Schnug, 1994: Application of low resolution energy dispersive X-ray fluorescence spectroscopy to total glucosinolate determination in rapeseed. Fat Sci. Technol. 96, 204-206.
ISO/CD, 1991: 9167-1 Rapeseed – Determination of glucosinolates content – Part 1: Method using high-performance liquid chromatography (HPLC).
ISO/CD, 1991: 9167-2 Rapeseed – Determination of total glucosinolates content – Part 2: Method using X-Ray Fluorescence Spectrometry (XRF).
Linsinger, T., N. Kristiansen, N. Beloufa, H. Schimmel, J. Pauwels, 2001: The certification of three rapeseed (colza) materials. BCR-190R, -366R and -367R.BCR Information EUR 19764 EN.
Marquardt, R., V. Schlesinger, 1985: Methodische Untersuchungen zur Glucosinolatbestimmung bei Raps. Fette Seifen Anstrichmittel 87, 471-476.
Schnug, E., 1988: Einflüsse der Umwelt auf den Glucosinolatgehalt von Winterraps. Bericht über das 1. Semundo-Rapssymposium, 14-32, Hamburg.
Schnug, E., 1989a: Double low oilseed rape in West Germany. Proc. National Conference on Double Low Oilseed Rape for the 1990 s. pp. 84-100 Peterborough (UK) 8. March 1989, SEMUNDO-Cambridge (Ed.).
Schnug, E., 1989b: Double low oilseed rape in West Germany: sulphur nutrition and levels. In: Production and protection of oilseed rape and other brassica crops. Aspects of Applied Biology 23, 67-82.
Schnug, E., S. Haneklaus, 1986: Eine Methode zur schnellen Bestimmung des Gesamtglucosinolatgehaltes von Rapssamen. Raps 4, 128-130.
Schnug, E., S. Haneklaus, 1987a: Indirekte Bestimmung des Gesamtglucosinolatgehaltes von Rapssamen mittels Röntgenfluoreszenzanalyse. Fresenius Z. Anal. Chem. 326, 441-445.
Schnug, E., S. Haneklaus, 1987b: Schnelle und präzise Bestimmung des Gesamtglucosinolatgehaltes von Rapssamen – Vergleich der Röntgenfluoreszenzanalyse mit Gaschromatographie und Hochdruckflüssigkeitschromatographie. Fett-Wissenschaft Technologie 89, 32-36.
Schnug, E., P. Kallweit, 1987: Ergebnisse eines Ringversuches zur röntgenfluoreszenzanalytischen Bestimmung des Gesamtglucosinolatgehaltes von Rapssamen. Fett-Wissenschaft Technologie 89, 377-381.
Schnug, E., S. Haneklaus, 1988: The sulphur concentration as a standard for the total glucosinolate content of rapeseed and meal and its determination by X-ray fluorescence spectroscopy (X-RF method). J. Sci. Food Agric. 45, 243-254, 1988.
Schnug, E., S. Haneklaus, 1990: Quantitative glucosinolate analysis in Brassica seeds by X-ray fluorescence spectroscopy. Phytochemical Analysis 1, 40-43.
Schnug, E., 1990: Glucosinolates – fundamental, environmental and agricultural aspects. In: Sulfur Nutrition and Sulfur Assimilation in Higher Plants (ed. H. Rennenberg et al.), pp 97-106, SPB Academic Publishing bv, The Hague, The Netherlands, 1990.
Schnug, E., A. Boenke, P.J. Wagstaffe, A.S. Lindsey, 1992a: The characterisation of three rapeseed reference materials and their utilisation in the indirect determination of total glucosinolates in rapeseed by X-RF. Fat Sci. Technol. 94, 297-301.
Schnug, E., S. Haneklaus, F. Zhao, E.J. Evans, 1992b: Relations between total sulphur and glucosinolate content in rapeseed – calibration of the X-RF method. Fat Sci. Technol. 94, 420-425.
Wagstaffe, P.J., A. Boenke, E. Schnug, A.S. Lindsey, 1992: Certification of the sulphur content of three rapeseed reference materials. Fresenius Z. Analyt. Chem. 344, 1-7.
Wathelet, J.P., P.J. Wagstaffe, A. Boenke, 1991: The certification of the total glucosinolate and total sulphur contents of three rapeseeds, CRM 190, 366 and 367. BCR Report EUR 13339-EN.
Wathelet, J.P., M. Marlier, M. Severin, 1989: Préparation d´un colza á teneur certifiée en glucosinolates totaux (CRM 190) Revue Francaise des CORPS GRAS 36,309-312.
Wathelet, J.P., M. Marlier, M. Severin, A. Boenke, P.J. Wagstaffe, 1995: Measurement of glucosinolates in rapeseeds. Nat Toxins. 3, 299-304.
Wathelet, J.P., P.J. Wagstaffe, R. Biston, M. Marlier, M. Severin, 1988: Rapeseed reference materials for glucosinolate analysis. Fresenius Z. Analyt. Chem. 332, 689-693.
Wathelet J.P., M. Marlier, R. Biston, 1987: Preparation de materiaux pour une intercomparison preliminaire entre les methods de dosage des glucosinolates dand les colzas et evaluation des resultants. Rapport préliminaire. Contrat 2806/1/5/307/87/7-BCR-B(10).
Zhao, F., E.J. Evans, P.E. Bilsborrow, E. Schnug, K.J. Syers, 1992: Correction for the protein content in the determination of total glucosinolate content of rapeseed by the X-RF method. J. Sci. Food Agric. 58, 431-433.
Footnotes:
in memoriam Prof. Dr. Richard Marquardt, Giessen (19.05.1938 – 16.12.2010) |
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