Storage and Complete Automatic Computation of Gas Chromatographic Data H. W. JOHNSON, Jr. Shell Developmenf Co., Emeryville, Calif.
b As the use of gas chromatographic analysis continues to expand, the need for more efficient handling of raw chromatographic data increases. Previously reported devices for handling these data are not entirely satisfactory because they either require manual scanning of chromatograms to locate peaks or use automatic locators that are not sufficiently accurate. A system is described in which the chromatographic detector output is converted to a frequency and temporarily stored on magnetic tape. The tape is played back by a special attachment, connected directly to a computer. The computer locates peaks, corrects for base line drift, applies calibration factors, normalizes, and prints the finished analytical report. The accuracy of the system for nonoverlapped peaks is evaluated.
G
chromatographic (GC) analysis continues to increase in popularity as an effective process to separate even very complex mixtures and provide both qualitative and quantitative estimates of composition. But the GC apparatus does not perform this entire feat itself. It only produces a chromatogram, which is a plot of effluent composition vs. time. Although the technically difficult part of the analysis has thereby been completed, the interpretation of the chromatogram to provide the desired percentage composition analysis can be tedious and time-consuming. The most difficult step in the interpretation is the measurement of certain areas of the chromatogram in order to estimate the quantity of each component. Each such area is called a peak area and is bounded above by a positive cxcursion of the curve, and below by an estimate of the course of the curve if the subitance causing the excursion had not been present. These t n o boundaries are called the peak and peak base, respectively (6). d variety of instruments have been described that assist in all or part of the peak area-measuring step. Some of these devices (S), including the familiar hall-disk integrator, are limited to the AS
response time and dynamic range of strip chart recorders and, therefore, involve considerable manual processing because of the numerous attenuation steps involved in recording a typical analysis. Some also require manual scanning of the chromatogram to locate the beginning and end of each peak ( 3 ) . Such devices require too much manual attention and are not discussed further in this report. Most of the remaining devices utilize voltage-to-frequency converters and are capable of good dynamic range and very accurate integration. Vnfortunately, this type of integration measures areas in which the lon-er boundary corresponds to a horizontal line, called the integrator zero, on a chromatogram. I n most of these devices (4, 5 ) the integrator zero must be adjusted manually to coincide with the peak base as often as necessary. Thus, for unattended applications these devices are restricted to drift-free :GC analyses. One device (1) provides for subsequent automatic correction for a discrepancy between the peak base and integrator zero, but this correction is accurate only if base line drift during the passage of a peak is negligible. These units all have a more serious limitation that is generally ignored. The devices must estimate the beginning and end of each peak in order to establish integration limits. This function mill be called peak sensing. Although the accuracy of the integration will depend on it, reports on these systems describe methods of evaluation that minimize or completely neglect the influence of peak sensing. Even though pertinent data for these units are not available, it will be shown that the type of electronic sensing used in these devices is inherently capable of large errors with typical chromatograms. This paper describes a system that overcomes both limitations of these devices. Each peak area is corrected for peak base position regardless of the amount of base line drift, and peak sensing is accurate. Effective response time of the sensing process is zero. Except for the handling of magnetic tapes on which raw chromatographic data are stored, the analysis from sample injection to finished analytical report is entirely automatic.
DESCRIPTION OF SYSTEM
An outline of the components in the system, and a step-by-step handling of the data from a typical chromatographic peak, are shown in Figure 1. The output from a GC detector is connected to the input of a voltage-tofrequency converter (Model 260B, Vidar Corp., Mountain View, Calif.), which produces a frequency proportional to the detector output. Gain is adjusted so that the greatest peak maximum expected will not produce more than 5000 c.p.s. Sensitivity of the smallest peaks ordinarily measurable on a 1-mv. recorder mill be adequate if the highest peak is not greater than 50 mv. The output from the voltage-tofrequency converter is passed through a rectifier and filter to provide the desired wave form and is connected to the input of an audio-type, magnetic tape recorder to produce a conventional frequency-modulated recording. A set of these components must be available for each GC apparatus that is to be used simultaneously. Several GC apparatus can be accommodated with the playback installation described below. The magnetic tape is played back on another audio-type tape recorder, specially modified to provide tape speeds up to 20 times as fast as recording speeds. The pulses read from the magnetic tape are electronically counted. Constant-interval signals periodically transfer the count to a one-word memory and reset the counter to zero. The delay for the transfer and reset is 20 microseconds. This transfer process provides the one-word memory with a number for the computer (Model G15D, Bendix Corp., Los Angeles, Calif.) during each count interval. The computer is programmed to use this set of numbers to determine the locations of peaks, correct for base line drift, and resolve overlapped peaks by, for example, estimating the location of the minimum between them and splitting the area a t that point. Resulting areas are corrected by calibration factors (entered into the computer as a function of retention volume) and then normalized to 1007,. The retention volume, calibration factor selected, and percentage composition are typed out for each peak. If desired, the computer can also type out a code number for each peak that will inform the sample submitter of any peculiarities VOL. 35, NO. 4, APRIL 1963
521
Output
Component
1I 1I
Chromatographic Detector
I Vo!tage-to-Frequency
Q
a
e
J
P u l s e Shaper I
I.
1
1
I
Each
.Al-
is Changed t o
I
I
I
I
I
I
I
I
E l e c t r o n i c Counter
I
One-Word M e m o r y
4
II
I
Computer
COMPARISON OF PEAK-SENSING TECHNIQUES
Some of the integrating systems discussed can be modified so that the estimated peak areas and retention volumes can be fed to a computer. The computer is evidently justified on the basis of the time and errors it can save in applying calibration factors, normalizing, and providing a printed analytical report. If a computer is to be used, i t seems inefficient to confine its application to the simple arithmetic part of the calculation and to Ieave the difficult peak sensing and area-measuring steps to relatively naive, external devices. The present system is designed so that the computer can perform all these operations. However, this concept is not just an optional alternative if accuracy is consistently required, for a no-memory device such as the differential amplifier ANALYTICAL CHEMISTRY
f
I' 11
1
10
I
6
I P r i n t e d Report
1
Data handling in an integrating system for gas chromatography
the computer detected in the input data that might warrant an examination of the chromatogram. If necessary, the chromatogram can be produced from the magnetic tape (1). A frequency meter (Model 500B, Hewlett-Pacbrd Co., Palo Alto, Calif.), connected between a tape recorder and a strip chart recorder, is convenient for this purpose.
522
I 1
I
Figure 1 .
I
I
I'
6
I
I
1
I
I
I I
I
1 1
I
I
I
I
I
a
A
I
I
Same as Above I
k
I I IllI
I I I I I I I I I I I I I I ~ I I I I I IIII I I I I I I I I I
Magnetic Tape
I
c
I1 I I 1 I
IIIII1111111
Converter
used as a peak sensor in most integrating systems cannot accurately sense relatively low, broad peaks. A differential amplifier is triggered by a certain minimum increase (or decrease) in signal occurring within a certain time limit. For example, the maximum . sensing sensitivity might be 1 ~ v per second. At this sensitivity the short, broad peak of Figure 2 would not be sensed. The intermediate peak in Figure 3 would be sensed near its inflection point. The errors involved depend on whether or not the device attempts to correct for base line position, and are shown in the figure. Unfortunately, it is not always possible to remedy this defect by more sensitive triggering, because base line noise may then cause false peak sensing. For example, for the actual chromatographic data discussed in this paper, only one tenth this sensitivity, or 10 pv. per second could be safely used without possible false peak sensing. For any specified triggering sensitivity there are analyses in which peaks would be sensed significantly late or false peak sensing would occur. By contrast, a human analyst has no trouble in establishing the peak limits of even very short, broad peaks with
acceptable precision, by scanning the chromatogram more than once. The first time only significant excursions from the base line are noted. Then for each excursion that is considered to be a peak, a forward and backward search is made to estimate where the peak meets the base line. These two steps afford accurate peak sensing even in the presence of relatively high base line noise. This type of sensing cannot be simulated by a no-memory device. A digital computer was selected as the most convenient memory device because of its other uses in the over-all interpretation process. However, a digital computer cannot accept the analog signal of a GC detector directly. This problem was encountered earlier, when it was desired to perform arithmetic operations on detector output to measure detector performance ( 7 ) . The procedure devised is also applicable to chromatogram interpretation. Sufficient data for sensing peaks and measuring peak areas can be obtained from the set of constant-interval areas produced by the process described in Figure 1. The intervals need not be small enough to describe the shape of the curve accurately. The processes of peak sensing, base line correction
LOST A X E A FOR NOXCOMPENSATING INTEGRATOP.
/
CRITICAL SLOPE
(I MICROVOLT P E R SECOND)
P E R SECOND)
-
Figure 2.
LOST AREA FOR BASE LINE-COMPENSATING I:.JTEGRATOR
APPROXIMATE SENSING.
Undetected peak Figure 3.
and area measurement will be illustrated with tlie set of interval areas shown in Table I. By scanning these numbers more than once it is easily established that a peak begins with interval number 10. This could not be determined until some subsequent intervals had been examined, because the difference between intervals 10 and 9 is less than that between 2 and 1, and the latter must be attributed to base line noise. But after subsequent intervals indicate that a peak is being encountered, it is clear that the first interval area higher than the base line average (15 for intervals 4 through 9) is 16 for interval 10. By applying a similar reasoning process to the descending side of the peak, it is found that base line has been reached a t interval 23, but this is not known until several additional intervals have been examined. The average interval area for base line intervals 23 through 28 is 17. The 13 intervals constituting the peak total 420 counts. After correction for the average base line (13 intervals X 16), the peak area is found to be 212 counts. A differential amplifier monitoring comparable continuous data would have t o be set to ignore the 2 counts per interval noise occurring in the base line. I t could not sense the peak until interval 14. It would also be incapable of averaging the beginning and ending base line t o correct for the peak base position. These deficiencies would result in very substantial errors. Since slicing a curve up into intervals is usually associated with approximation techniques, it should be pointed out t h a t this procedure is not merely an approximation, because once the locations of peaks have been established, the appropriate interval areas are recombined. Thus, a continuous flow of analog information accurately describing a GC curve to a no-memory electronic device cannot provide for accurate peak sensing and area measurement. But the areas of discrete intervals, each including a substantial portion of a peak, can provide all the information necessary for accurate, base line-cor-
Area lost b y inadequate peak sensing
rected peak areas if the device handling the data has a memory. PERFORMANCE
Scope of Tests. Two types of processes are involved in the interpretation of a typical chromatogram. One is the measurement of isolated peaks. If the detector is linear, there will be a proportional relationship between the true area on the chromatogram and the amount of sample used. It is the task of the integrator system to measure t h a t area as accurately as possible. When two or more peaks are incompletely separated, the peak area that must be accurately measured comprises several peaks. The interpretation must include the additional step of apportioning the area among the overlapped peaks. Just how this is to be done is not clear. For a good integrating and sensing system, the area-measuring step should be more accurate than the experimental steps, but it would seem impossible to make the area apportionment step more accurate because the only criterion for a satisfactory division is how well the results agree with the known composition of a test sample. Thus, the processes of measuring peak areas and resolving overlapped peaks are based on different principles and should be considered separately. This paper is confined to reporting how well the system can measure peak areas.
Table I.
Interval number 1 2 3 4 5
6
7
8 9 10
Although the computer program provides for resolution of overlapped peaks, they are not considered here. Evaluation Problem. Even without overlapped peaks the evaluation of a n integrator system is complicated by the lack of a correct answer with which to compare results. Quantitative GC analyses always involve the use of calibration factors, so measured areas and known sample composition cannot be directly compared. For a chromatogram of some complexity, several experienced analysts would all probably calculate slightly different results. The task for the designer of an integrating system is to build the system so that the human processes of interpretation are satisfactorily simulated. This is considered to have been achieved by the peak analysis process applied t o the data of Table I. But comparing answers with those obtained manually has little significance; there is no way of deciding which is more correct. Comparing the answers obtained with several different devices is also inconclusive. This statement is substantiated by a paper (8) in which several devices were compared: “The results with the voltage-to-frequency integrator are believed to be the most accurate because of its high degree of accuracy and linearity, and its independence of recorder errors.” Thus, information not obtained from their test results had to be used to arrive a t a decision. Testing a single integrating system
Synthetic Data for Illustrating Peak Area Calculation
Interval area 14 16 14 16 14 15 16 14 15 16
Interval number 11 12 13 14 15 16 17 18 19 20
Interval area 18 20 22 28 48 91 50 40 30 20
Interval number
Interval area
21 22 23 24 25 26 27 28 29 30
VOL. 35, NO. 4, APRIL 1963
19 18
17 18 16 16 17 18 17 16
0
523
Table II.
Precision of Interval Areas
Range
Approx.
S o . of
recorded frequency,
interval areas
Xean count per
c.p.s. 50 500 2000 4000
examined
interval
180
175 1,648 6,524 13;244
180
1so 78
by repeated GC analysis of the same sample is also indecisive. If results are poor, they can be attributed to the experimental part of the process (1). If results are uniform, this is a measure of precision, not accuracy (b). Extending the tests to other samples or sample sizes again introduces the possibility of experimental errors. With systems utilizing tape recording of the raw GC data, it is possible to perform repeated interpretations of the same GC analysis, but the results of this test will be misleading if a nomemory system is used. Regardless of how late the peak sensor may be triggering, precision would be expected to be high even though accuracy might be very poor. The significance of this test for the present system is discussed later. All the above procedures are unsatisfactory because they measure precision, whereas only accuracy is significant for an integrating system. Since overall accuracy cannot be evaluated directly, the only solution appears to be t o test the accuracy of individual steps. For the present system, it is convenient to divide the process into two parts: the data storage and retrieval system, and the computer programming. Data Storage and Retrieval. Manufacturer’s specifications for the voltage-to-frequency converter are: linearity, 0.025%) over-all accuracy, 0.1%; response, settling time less than 2 milliseconds. These specifications surpassed those of devices available in the laboratory t o test them and were assumed to be accurate. The only test necessary t o establish the performance of the storage and retrieval system was to feed various constant voltages to the converter, record the resulting frequencies on magnetic tape, play the tape back into the computer with the equipment of Figure 1, and program the computer to print out all the numbers it received. The numbers for each input voltage were compared for uniformity. The results are summarized in Table 11. With the exception of the highest frequency, the ranges are approximately proportional to the count. The range for the worst group of 20 adjacent intervals at each frequency, and the maximum first difference at each fre524
ANALYTICAL CHEMISTRY
Range, counts 2 12 62 14
for 20 3Iaximuni Relative adjacent first range for intervals, difference, 20 intervals, rounts counts A % 1
2 12 14
1 2 5 11
0.29 0.06 0.09 0.04
quency, are also approximately proportional to the count, but substantially lower (a range less than 1 is impossible). The maximum and minimum interval areas a t each frequency control the range for the entire set. These areas were separated by a t least 50 intervals a t each frequency and, therefore, correspond to a “noiseJ’ with a period of several minutes. This type of noise can be safely ignored in this system. If peaks are relatively narrow, the noise will be regarded as drift and corrected for by the computer. If peaks are relatively \\-vide, the total area count for the peak will be very high compared to the count per interval, and the relative precision will improve suhstantially. The 20 interval range is considered a realistic but still conservative estimate of precision. The relative precision is better than 0.1% except for the lowest frequency. The latter corresponds to a base line position, and the range of 1 count at this frequency is equivalent to a displacement of the base line by 2.5 pv. a t the usual converter gain setting. This corresponds to l/poo of full scale on a 1-mv. recorder. It can be concluded that the data storage and retrieval system describes a base line at least as precisely as a 1-mv. recorder on full sensitivity and describes peaks with a precision of 2 counts or 0.l%, whichever is less favorable. The delay between successive counting cycles in the computer attachment (approximately 20 microseconds) corresponds to less than 1 count per interval even at highest frequencies. Furthermore, the generation and storage of the converter pulses also constitute the integration. If the converter is accurate, as has been assumed, nothing in the storage and retrieval system could affect linearity and accuracy without affecting precision. Accordingly, it is assumed that the storage and integration process has an accuracy of better than 0.1% of the peak area except for very small peaks, where accuracy map deteriorate to 2 counts per peak. Computer Programming. For these tests the computer was programmed t o search for peaks and measure peak areas according t o the process described for t h e d a t a of Table I. There are various methods of program-
ming a computer to do this, and this paper does not describe any particular program in detail. Since the computer operates digitally, it is possible to predict exactly how the computer will interpret any particular set of interval areas. Five factors are discussed. REJPOSSETIME. The response to square waves is often included in evaluating a n integrator. This is affected by the response time of the integrator, but for voltage-to-frequency converters this response time is so short that losses in counting can be attributed entirely to the response time of the peak sensor. A qquare wave and a corresponding set of interval areas are shown in Figure 4. The location of the square wave and its “peak area” can be readily calculated by subtracting the “base line” level from each count and then summing the adjacent, nonzero counts. Although the interval areas have obscured the shape of the curve, the calculated peak area is exact, with no response time loss. dccordingly, the effective response time of the peak sensing in this system is zero. DRIFT. The interpretation procedure described for Table I allows for the possibility that the base line positions at the beginning and end of the peak may differ. In the data of Table I, the base line moved 2 counts per interval (from 15 to 17) during passage of the peak. Since the peak occupied 14 intervals, this amount of drift would affect first differences by an average of count per interval. This quantity is negligible compared to other factors that affect first differences (Table 11). This same result is observed for real data with acceptable GC detectors. The effect of drift on first differences can be ignored, but the change in base line during the passage of a peak must be allowed for. TIMEISTERVAL. When interval times are increased, noise will not usually increase proportionally. Moreover, the larger interval areas provide a more sensitive indication of peaks. These statements are substantiated by some actual interval areas given in Table 111. The leading side of the peak has several negative first differences in the small intervals because of noise. B y contrast, the leading side of the peak forms a monotonically increasing set of interval areas for the larger intervals. Doubling the size has increased the maximum first difference from 3 to only 4 on the base line but from 4 to 12 on the side of the peak. For these reasons, larger intervals are favored to obtain more sensitive peak sensing. On the other hand, smaller intervals give a more accurate description of the actual shapes of curves and are desirable when peaks are overlapped, in order to provide good resolution of the valley between them.
Table 111.
Actual 4-second intervals
Calcd. S-second intervals
Interval Areas from Relatively Noisy Data
Actual 4-second intervals
1135
Calcd. 8-second intervals
1136
2270 1135 1136
2272
1136 1137
Calcd. 8-second intervals
1162
2327
1165 1168
22270
1134 1136
Actual 4second intervals
2336
2275 1138 1138
1168 1170
22271
2343
2277
1135 1134
1173 1172
1139 1141
22270 1136 1134 2267 1133 1136
2345
2283 1173 1175
1142 1145
2347
2292 1172 ii72
1147
1146 2271
2342
2296
1135 1134
1150 1153
1170 1169
2269
2337
2~x06
1135 1137 1135 Time mmutes
Figure 4. Chromatogram of data used for calculations of Table IV
Intervals corresponding to from 4 to 32 seconds of recording time have been found satisfactory for typical 30-minute analyses. Very rapid analyses would require proportionally shorter intervals. Although this paper has not considered overlapping peaks, 4-second intervals were used in actual tests described later, to simulate the most difficult noise conditions likely to be encountered. PHASING. Once the computer has been properly programmed, i t will make exactly the same calculation each time it receives exactly the same set of interval areas. However, the computer will probably not receive the same set of interval areas when a data tape is replayed, because the relationship between the data on the tape and the constant time intervals (Figure I) may differ. This relationship will be called phasing. For the square wave of Figure 4, phasing presents no problem. Even if the phasing were such that the first interval containing part of the peak had only 1 extra count, an examination of the calculating process will show that the same peak area would be obtained, because a noiseless base line was assumed. When a base line is noisy, phasing can cause changes in interpretation. The interval in which a peak appears to begin may be shifted, and the calculated base line levels adjacent t o the peak may be changed. Phasing could have two effects on interval areas: the rearrangement of noise caused by very slight phasing changes and the rather different descrip-
Table IV.
Effect of Phasing and Noise Allowance on Interpreiation of
Peak Overretention all volume range 7.5 10.2 14.6 20.3 26.8
0.16 0.08 0.44 0.42
0.25
Approximately fiame phasing 1 2 3 4 18.04 2.19 23.37 39.84 16.55
18.05 2.23 23.35 39.72 16.62
17.89 2.18 23.27 39.88 16.76
tion of a peak that would be obtained by, for example, having the maximum of a peak occur either in the center or a t the edge of an interval. To test both these effects, a tape was played back into the computer four times with the phasing duplicated as exactly as possible. The pulse density was approximately 100 counts per inch of tape for the base line, so the small variations referred to above were bound to occur. The tape was then replayed tn-ice with the phasing deliberately
Figure 5. wave
Peak area of a square
18.03 2.19 22.95 40.01 16.80
Changed phasing 1 17.97 2.15 23.14 40.05 16.58
2 18.01 2.17 23.13 39.92 16.5s
GC Analysis
Changed noise allowance 1 17.98 2.20 22.93 39.63 16.76
2 18.03 2.16 23.31 39.90 16.62
shifted so that the time interval signals occurred in the middle of the intervals used for the first four tests. The chromatogram for the data used is shown in Figure 5 . This curve has considerable noise and so can provide a realistic test of the phasing problem. Results are shown in Table 11-. Deliberate phase changes cause no more difficulty than the variations caused by slight displacements. This is the desired result for an acceptable system. The significance of the variations that occurred is discussed later. NOISE ALLOWANCE.The last t n o columns in Table IV take into account the possible effect of computer noise allowance: the number of counts per interval by which some interval must exceed the previous base line before the computer will consider an excursion a peak. For example, for the data of Table I, the maximurn interval count is 91, and the beginning base line level is 15 counts per interval. Any noise allowance less than 7 6 would cause the computer to treat the data as a peak. It follow that there should be a relatively wide range of noise allowances which should not affect results, because regardless of which interval meets the VOL. 35, NO. 4, APRIL 1963
525
noise allowance requirement, the computer should always go back to the same interval as the start of the peak. The last two columns in Table IV had only 5 counts as the noise allowance; the others had 10. This change had no significant effect on results. This change corresponds roughly t o doubling the sensitivity of a peak sensor in a no-memory system. The extreme sensitivity of certain shapes of peaks to such a change is illustrated in Figures 2 and 3. DISCUSSION
The results in Table IV indicate the performance of the system with rather noisy data. If the GC analysis were t o be repeated exactly, then, as has been shown by the accuracy of the storage and retrieval process, the new magnetic tape would differ from the first only within 0.1% or 1 count per interval, whichever is larger. The only other change would be a relocation of the noisiest intervals (a maximum first difference of 3 counts per interval in these tests) with respect to the chromatogram. However, even after the filtering action of a 2-second strip chart recorder, individual noise peaks in the base line correspond to more than 3 counts each (Figure 4). A representative variation of noise with respect t o the chromatogram should have been
obtained by the phasing changes during repeated playback. Accordingly, the range of variation in Table IV should be a good indication of the accuracy of the system on repeated analysis of the sample used. Since the computer programming will handle othrr shapes and sizes of peaks in the same way, it can be concluded that the over-all accuracy is within 1% of true value for each peak a t the relatively high noise level of these data. If peaks were to be smaller with respect to this high noise, accuracy would fall off, as it would for manual For less noisy exinterpretation. perimental results, accuracy of the system would approach the 0.1% accuracy of the storage and retrieval system because of the principles discussed for square wave measurement (Figure 5). Only the phasing problem makes this type of accuracy estimation possible. Repeated playback of a data tape into a no-memory device would not have the same significance. In fact, precision under these conditions should be extremely good if the playback and peaksensing amplifiers are performing consistently. APPLICATION OF SYSTEM T O OTHER COMPUTERS
Some computers have no provision for accepting data from an external
1-word memory as outlined in Figure 1. Also, some computers compute so rapidly that tying their speed to the tape-reading speed of this system would be impractical from a cost standpoint. I n either event, this system can be adapted by substituting a card or tape punch for the computer in Figure 1. The cards or tape will then contain the interval areas in a form that can be read a t the proper rate by the computer in question with conventional computer accessories. LITERATURE CITED
(1) Addison, L. M., Lane, L. H., 2. anal. Chem. 189, 80 (1962). (2) ANAL.CHEW33, 480 (1961). (3) Gardiner, K. W., International Gaa
Chromatography Symposium, Michigan State Gniv., June 1961, Proceedings, p. 225. (4) Heigl, J. J., MacRitchie, A. L., Symposium on Analytical Chemistry, University of Maryland, June 1962. ( 5 ) Infotronics Gorp., Houston, Tex., “CRS-1 Digital Chromatograph Integrator,” Bull. CRS-102 (1962). (6) Johnson, H. W., J r , Stross, F. H., ANAL.CHEJI.30,1586 (1958). ( 7 ) Ibid., 31, 1206 (1959). (8) Sawyer, D. T., Barr, J. K., Zbid., 34, 1213 (1962). RECEIVED for review November 19, 1962. Bccepted January 28, 1963. International Symposium on Advances in Gas Chromatography, University of Houston, Houston, Tex., January 21-24, 1963.
Quantitative Aspects of Gas Chromatographic Separations in Biological Studies E. C. HORNING, K. C. MADDOCK, K. V. ANTHONY, and W. J. A. VANDENHEUVEL Lipid Research Cenfer, Baylor Universify College of Medicine, Housfon, Texas
b This study was carried out to define the nature of several problems involved in establishing procedures for the determination of steroids and long-chain fatty acid methyl esters. Column packings which show very little adsorption of solutes are required for best results. It is necessary to use appropriate derivatives in some instances, and the sample size should be appropriate for the specific application. Questions relating to matters of instrument design, preparation of column packings, temperature-programmed operation, and choice of detection systems have been studied.
T
widespread use of gas chromatographic techniques in the isolation, identification, and estimation of substances of biochemical or biological HE PRESENT
526
ANALYTICAL CHEMISTRY
interest is sufficient evidence of the value of this corpus of analytical methods in work in biology and medicine. However, experience with these procedures suggests that qualitative information may be obtained far more easily than quantitative data. The relative lack of published information about methods for establishing suitable conditions for quantification, and current differences in opinion about the degree of precision and accuracy which may be attained, have led to uncertainty in many laboratories about the future course of developments in this area. The experiments described in this paper were carried out to define the nature of several specific problems involved in quantification procedures for steroids and long-chain fatty acid methyl esters. The results indicate that satsifactory quantification may be obtained in a variety of applications, and some of the
causes of failure to obtain good results are illustrated by examples. The use of reference mixtures to evaluate new procedures and to validate day-to-day results also is the best way to estimate precision and accuracy in any given application. This practice should not be used t o determine “correction factors” which are used to convert basically inaccurate analytical data into “quantitative results.” Shortcomings arising from inadequate technique or poor instrument design are not likely to be overcome successfully by this approach. EXPERMENTAL
Instruments from three commercial sources were used. All required essential but easily carried out inodification in order to secure satisfactory quantita-
