Method for establishing baseline in liquid chromatography

Abstract

To provide a method capable of simply and easily calculating an optimum peak start point and a peak end point and establishing a base line even in various peak shapes or the like in a liquid chromatograph.SOLUTION: A first step of designating a virtual peak start point time range and a virtual peak end point time range of a peak to create a baseline and calculate a peak area, changing the virtual peak end point to create a baseline and calculate a peak area, calculating a rate of change from a peak area obtained at a previous virtual peak end point, and calculating a virtual peak end point at which a change in the peak area within the virtual peak end point time range is minimum; Second step: The virtual peak end point obtained in the first step is fixed, the virtual peak start point is changed in the same manner, and the peak start point at which the change in peak area is minimal is calculated. Third step: The first step and the second step are performed twice or more to establish a baseline.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to a method for calculating a simple, easy, and optimal peak start point (base start point) and peak end point (base end point) and establishing a baseline, even when there are various peak shapes in a liquid chromatograph or when there are peaks before and after the peak of a target component that interfere with detection. [Background technology]

[0002] Liquid chromatography is frequently used as an analytical method to separate mixed components and quantify / qualify them. When performing qualitative analysis, a standard sample is measured in advance and a judgment is made based on whether there is any difference in the elution time. When performing quantitative analysis, it is common to measure standard samples at multiple concentrations in advance, create a calibration curve from the peak area or height, and then apply the peak area or height of an unknown sample to the calibration curve to calculate the concentration.

[0003] In qualitative and quantitative analysis, it is important to be able to reliably detect the peak of the target component. In other words, it is necessary to accurately identify the start and end points of the peak and the baseline.

[0004] The peak detection method involves setting a certain value (threshold) in advance, and the point where the detector output exceeds this value is set as the peak start point, and the point where it falls below this value is set as the peak end point, as shown in Figure 1. This method is very simple, but because it is difficult to accurately capture the "rising and falling parts of the peak" where there is little change in the detector output, it is effective for qualitative analysis where the time of the peak top is important, but is not suitable for quantitative analysis where peak area and height are required.

[0005] Another commonly used method is to detect peaks from the rate of change of the detector output. The rate of change of the peak (called "peak sensitivity" or "slope") is set in advance, and the point at which the rate of change of the detector output exceeds that value is considered the peak start point, and the point at which it falls below that value is considered the peak end point (see Figure 2a). Furthermore, when multiple peaks are present and not completely separated, separate parameters are often used to determine their separation. For example, parameters equivalent to the slope of the baseline (called "slope value" or "drift value") are often used. When the valley point of the two peaks is above the baseline, as in Figure 2b, it is considered a "vertical slice." When the valley point of the two peaks is below the baseline, as in Figure 2c, it is considered a "base peak."

[0006] However, actual chromatography results in diverse and complex separation patterns, and the above-described processing frequently fails to accurately and reliably detect peaks. For example, while chromatographic peaks theoretically follow a normal distribution, in reality they often exhibit a "leading" (a gradual rise) and a "tailing" (a gradual fall). In this case, the slopes near the peak start (near the base start) and peak end (near the base end) differ significantly, making accurate detection impossible with a single peak detection sensitivity value. Furthermore, detectors have noise from multiple sources, and adjusting peak detection sensitivity can sometimes result in more erratic peak detection due to the effects of noise.

[0007] In another example, if there are negative peaks before and after the target component peak, it is difficult to accurately detect the target component peak. If there is a negative peak before the target component peak, the valley of the negative peak may be determined to be the peak start (base start), which may cause problems in detecting the target component peak. Conversely, if there is a negative peak after the target component peak, the valley of the negative peak may be determined to be the peak end (base end), which may cause problems in detecting the target component peak.

[0008] In this way, when accurate peak detection is not possible automatically, the only option is for the operator to manually correct the peak start (base start) and peak end (base end) and then perform qualitative / quantitative analysis. However, this is not only time-consuming, but can also lead to artificial manipulation of the results, making it undesirable. A method that can automatically determine the peak start (base start) and peak end (base end) more easily and accurately is desired. Summary of the Invention [Problem to be solved by the invention]

[0009] The present invention provides a method for calculating a simple, easy, and optimal peak start point (base start point) and peak end point (base end point) and establishing a baseline, even when there are various peak shapes in a liquid chromatograph or when there are peaks before or after the peak of a target component that interfere with detection. [Means for solving the problem]

[0010] As a result of intensive research and development carried out by the present inventors to solve the above problems, the present invention has been developed. That is, the present invention includes the following aspects.

[0011] [1] A method for establishing a baseline for liquid chromatography, comprising the steps of: As the first step, Specify the time range of the virtual peak start point (base start point) and the time range of the virtual peak end point (base end point) of the peak to be detected, fix the virtual peak start point (base start point) within the virtual peak start point (base start point) time range, create a baseline at the minimum value (minimum time) of the virtual peak end point (base end point) time range, calculate the peak area, change the virtual peak end point (base end point) at regular time intervals to create a baseline, and calculate the peak area. The rate of change from the peak area obtained at the previous virtual peak end point (base end point) is calculated, and this operation is performed within the time range of the virtual peak end point (base end point), to calculate the peak end point (base end point) at which the change in peak area is minimal. As the second step, The peak end point (base end point) obtained in the first step is set as a virtual peak end point (base end point) (time), and a baseline is created at the virtual peak start point (base start point) at the minimum value (minimum time) of the virtual peak start point (base start point) time range to calculate the peak area, and the virtual peak start point (base start point) is changed at regular time intervals to create a baseline and calculate the peak area, The rate of change from the peak area obtained at the previous virtual peak start point (base start point) is calculated, and this operation is performed within the time range of the virtual peak start point (base start point), to calculate the peak start point (base start point) at which the change in peak area is minimal. As the third step, A baseline determination method in which the first step and the second step are carried out two or more times to calculate the peak end point (base end point) and peak start point (base start point).

[0012] [2] A method for establishing a baseline for liquid chromatography, comprising the steps of: As the first step, Specify the time range of the virtual peak end point (base end point) and the time range of the virtual peak start point (base start point) of the peak to be detected, fix the virtual peak end point (base end point) within the virtual peak end point (base end point) time range, create a baseline at the minimum value (minimum time) of the virtual peak start point (base start point) time range, calculate the peak area, change the virtual peak start point (base start point) at regular time intervals to create a baseline, and calculate the peak area. The rate of change from the peak area obtained at the previous virtual peak start point (base start point) is calculated, and this operation is performed within the time range of the virtual peak start point (base start point), to calculate the peak start point (base start point) at which the change in peak area is minimal. As the second step, The peak start point (base start point) obtained in the first step is set as a virtual peak start point (base start point) (time), and a baseline is created at the virtual peak end point (base end point) at the minimum value (minimum time) of the virtual peak end point (base end point) time range to calculate the peak area, and the virtual peak end point (base end point) is changed at regular time intervals to create a baseline and calculate the peak area, The rate of change from the peak area obtained at the previous virtual peak end point (base end point) is calculated, and this operation is performed within the time range of the virtual peak end point (base end point), to calculate the peak end point (base end point) at which the change in peak area is minimal. As the third step, A baseline establishment method in which the first step and the second step are carried out two or more times to calculate the peak start point (base start point) and peak end point (base end point).

[0013] [3] The baseline establishment method according to [1] or [2], characterized in that in the second and subsequent baseline establishments, the amount of change over time at the fixed time interval is made smaller than in the first baseline establishment. [Effects of the Invention]

[0014] When accurate peak detection is not possible automatically, the operator must manually correct the peak start (base start) and peak end (base end) and then perform qualitative / quantitative analysis, but this is not only time-consuming but can also lead to artificial manipulation of the results, making it undesirable.The present invention provides a method that can simply, easily, and accurately determine the peak start (base start) and peak end (base end) even in cases where there are diverse peak shapes or peaks that interfere with detection before or after the peak of the target component, thereby reducing labor hours and optimizing analytical results. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a diagram schematically illustrating an example of peak detection using a conventional method (threshold). [Figure 2] FIG. 1 is a diagram schematically illustrating an example of peak detection using a conventional method (slope). [Figure 3] FIG. 1 is a diagram schematically illustrating an example in which peak detection is difficult using a conventional method. [Figure 4] FIG. 1 is a diagram showing an example of a flow chart illustrating the procedure of a baseline determination method according to the present invention. [Figure 5] 1 is a pseudo-chromatogram used to clarify the procedure of the baseline determination method of the present invention. [Figure 6] FIG. 1 is a diagram schematically illustrating an example of a baseline determination method according to the present invention. [Figure 7] FIG. 1 is a diagram showing peak areas and area variation rates from previous values ​​in the baseline determination method of the present invention. [Figure 8] FIG. 1 is a diagram showing baseline fluctuations in the baseline determination method of the present invention. [Figure 9] FIG. 1 shows the results of the baseline determination method of the present invention. [Figure 10] FIG. 1 shows the results (chromatogram) of separation of SRM706, a secondary molecular weight standard sample, by SEC in Example 1. [Figure 11]FIG. 1 shows the results of applying the baseline determination method of the present invention to the separation of SRM706, a secondary molecular weight standard sample, by SEC in Example 1. [Figure 12] FIG. 1 shows the results of applying the baseline determination method of the present invention to the separation of SRM706, a secondary molecular weight standard sample, by SEC in Example 1. [Figure 13] FIG. 1 shows the peak area and the rate of area variation from the previous value in the baseline determination method in Example 1. [Figure 14] FIG. 1 shows the fluctuation of the baseline in the baseline determination method in Example 1. [Figure 15] FIG. 1 shows the final baseline obtained in Example 1 (FIG. a). For comparison, FIGS. b to d show baselines (peak detection) that tend to occur in a typical peak detection method. [Figure 16] 1 shows a chromatogram obtained in Example 2 when the baseline determination method of the present invention was applied to anion analysis by ion chromatography (a mixture of seven standard anions). [Figure 17] FIG. 10 is a diagram showing the results of applying the baseline determination method of the present invention to anion analysis by ion chromatography in Example 2. [Figure 18] FIG. 10 is a diagram showing the results of applying the baseline determination method of the present invention to anion analysis by ion chromatography in Example 2. [Figure 19] FIG. 10 is a graph showing the peak area and the rate of area change from the previous value in the baseline determination method in Example 2. [Figure 20] FIG. 1 shows the fluctuation of the baseline in the baseline determination method in Example 2. [Figure 21] FIG. 1A shows the final baseline obtained in Example 2. FIG. 1B shows, for comparison, baselines (peak detection) that tend to occur in a general peak detection method. [Figure 22] FIG. 1 shows the configuration of a chromatograph used in Examples 1 and 2. DETAILED DESCRIPTION OF THE INVENTION

[0016] The present invention will be described in detail below. However, the present invention can be embodied in various forms and is not limited to the following embodiments and examples.

[0017] Specify the time range for the virtual peak start point (base start point) and the time range for the virtual peak end point (base end point) of the peak you want to detect. Fix the value (time) of either the peak start point (base start point) or peak end point (base end point), and gradually change the other within the time range, and calculate the peak area based on the resulting baseline. Also calculate the rate of change from the area obtained at the previous time. The time when the rate of change in the peak area is minimal is the appropriate peak start point (base start point) or peak end point (base end point).

[0018] Next, the points fixed in the previous step are changed and the same operation is carried out. For ease of understanding, a detailed description will be given here assuming that the peak end point (base end point) is fixed and the peak start point (base start point) is changed in this order.

[0019] Figure 4 shows the calculation flow. The time range of the virtual peak start point (base start point) and the time range of the virtual peak end point (base end point) of the peak to be detected are specified. The virtual peak start point (base start point) is fixed within the time range, a baseline is created at the minimum value (minimum time) of the time range of the virtual peak end point (base end point), and the peak area is calculated.

[0020] Next, the virtual peak end point (base end point) is increased at regular intervals to create a baseline, and the peak area is calculated. At this time, the rate of change from the peak area obtained at the previous virtual peak end point (base end point) is calculated. This operation is performed within the time range of the virtual peak end point (base end point), and the peak end point (base end point) at which the change in peak area is minimal is calculated. Next, the virtual peak end point (base end point) is set to the value (time) obtained above, and the virtual peak start point (base start point) is changed in the same way to calculate the peak start point (base start point) at which the change in peak area is minimal. This operation is repeated multiple times to calculate the optimal peak end point (base end point) and optimal peak start point (base start point). This operation must be performed at least twice, but considering the calculation load, about three sets is preferable, and sufficient results can be obtained.

[0021] To clarify the procedure and effects of the present invention, we will explain it again using a composite chromatogram. The composite chromatogram was created by adding a normal distribution function with positive values ​​that mimics the calculation target, a normal distribution function with negative values ​​that mimics interfering peaks, and a linear function that mimics detector drift. Figure 5a shows the composition of the composite chromatogram, and Figure 5b shows the final composite chromatogram. This is a chromatogram with drift and a negative peak immediately after the calculation target peak. This pattern makes accurate peak detection difficult automatically. This type of chromatogram is also a pattern commonly observed in size exclusion chromatography (SEC).

[0022] For this composite chromatogram, the time range of the virtual peak start point (base start point) and the time range of the virtual peak end point (base end point) are specified. Here, the range of the virtual peak start point (base start point) is set to 9:00 to 13:00 minutes, and the time range of the virtual peak end point (base end point) is set to 14:00 to 18:00 minutes.

[0023] Here, the peak start point (base start point) value (time) is first changed to approximately 11:00 min, and the peak end point (base end point) is changed in 0.20-min increments over the specified time range (14:00-18:00 min). The peak area is calculated based on the resulting baseline. The rate of change from the area obtained at the previous time is also calculated. Figure 6a shows the baseline fluctuations, Table 1 lists the areas, and Figure 7a shows the area and rate of area change.

[0024] The later the peak end point (base end point), the gentler the baseline becomes, eventually resulting in a negatively sloping baseline in this range. The area gradually increases, the change decreases at a certain range, and then it rises sharply. In this case, the peak end point (base end point) shows a minimum around 16.55 minutes. This point is a candidate for the base end point.

[0025] Next, the peak end point (base end point) value (time) was fixed at 16.55 minutes, and the peak start point (base start point) was changed in 0.20-minute increments within the specified time range of 9.00 to 13.00 minutes. The peak area was calculated based on the resulting baseline. The rate of change from the area obtained at the previous time was also calculated. Figure 6b shows the baseline fluctuations, Table 2 lists the areas, and Figure 7b shows the area and rate of area change.

[0026] The later the peak end point (base end point), the stronger the positive slope of the baseline. The area changes little within a certain range at the beginning, but becomes extremely small after a certain time has passed. The rate of change of the area reaches a minimum around 10.57 minutes after the peak start point (base start point). This point is a candidate for the base start point.

[0027] This operation is repeated multiple times to calculate the optimal peak end point (base end point) and peak start point (base start point). Figure 7c shows the area and area change rate when searching for the second peak end point (base end point), Figure 7d shows the second peak start point (base start point), Figure 7e shows the third peak end point (base end point), and Figure 7f shows the third peak start point (base start point).

[0028] In the first search for the peak end point (base end point) and peak start point (base start point), the time was changed in 0.2 minute intervals, but from the second search onwards, the time change amount was reduced, which is preferable as it allows more optimal peak end point (base end point) and peak start point (base start point) to be calculated.

[0029] [Table 1]

[0030] [Table 2]

[0031] [Table 3] [Example]

[0032] To verify the effectiveness of the present invention, experiments were performed using chromatograms commonly observed in actual liquid chromatography. In liquid chromatography, qualitative and quantitative analysis is performed using peaks representing signals on the positive side of the baseline. However, for various reasons, peaks can appear on the negative side, making it difficult to detect the desired positive peak. Example 1 illustrates the presence of a "solvent-derived peak" on the negative side, which is commonly observed in size exclusion chromatography (SEC), while Example 2 illustrates the presence of a "water dip" solvent-derived peak on the negative side, which is commonly observed in ion chromatography (IC). Example 1 In this example, size exclusion chromatography (SEC) was used. The Tosoh Corporation HLC-8420GPC high-speed GPC system was used. The detector was a built-in refractometer. The system configuration is shown in Figure 22, and the analytical conditions are shown in Table 4. The sample used was SRM706 (NIST), a commonly used secondary standard for polystyrene. Figure 10 shows the chromatogram obtained. In SEC using a refractometer, peaks of the polymer components are typically observed, followed by a "negative peak" at the void position (column volume) of the system due to the solvent in which the sample was dissolved. Furthermore, for polymers with a large molecular weight distribution, the peak shape is not asymmetric, resulting in a tailing pattern. These factors often make it difficult to accurately determine the base end point (peak end point).

[0033] [Table 4]

[0034] In this example, the baseline of the SRM706 peak, which elutes at approximately 6.7 minutes, was determined. The initial virtual base start point range was set to 4,000 to 7,000 minutes, and the initial virtual base end point range was set to 8,000 to 12,000 minutes. The base start point was initially fixed at 5,000 minutes, and the base end point was sequentially changed within this range starting from 8,000 minutes, calculating the peak area at each point. The rate of change in area from the previous point was also calculated. Figure 11 shows an excerpt of the baseline change (legend: the thick line is the baseline).

[0035] The baseline changes from a positive slope to a horizontal slope to a negative slope. Figure 13a shows the change in area (left) and the rate of change of area (right). It can be seen that the later the base end point, the gradually increasing, before rising sharply at approximately 10.5 minutes. Looking at the rate of change of area, it can be seen that the later the base end point, the gradually decreasing, before rising / falling sharply at approximately 10.5 minutes. The point where the rate of change of area rises / falls sharply is the region where the base end point reaches a negative peak, as shown in Figure 11f. The point where the rate of change of area is minimal is a good candidate for the base end point. In this case, 10.385 minutes is the candidate.

[0036] Next, the virtual base end point range is fixed at 10.385 minutes, as determined above, and the base start point is sequentially changed within this range, starting from 4.000 minutes, to calculate the peak area at each point. The area change rate from the previous point is also calculated. Figure 12 shows an excerpt from the baseline change. The baseline changes from horizontal to a positive slope. Figure 13b shows the area change (left) and area change rate (right). It can be seen that the area gradually decreases as the base start point becomes later, and then decreases sharply at approximately 5.2 minutes. Looking at the area change rate, it can be seen that there is little change until the base start point reaches approximately 5.0 minutes, and then it increases sharply after this point. The point where the area change rate increases sharply is the region where the base start point is after the peak of the main component peak, as shown in Figure 12d. Points with minimal area change rates are good base start point candidates. In this case, 4.600 minutes is the candidate.

[0037] Next, the base start point is set to 4,600 minutes obtained above, and a second search for the base end point is performed to calculate the best base end point. This process is repeated to determine the best base start point and base end point. In this example, a total of six repetitions were performed. Table 5 shows the results of the six repetitions. The shaded sections indicate the time of the base start point and base end point that were determined to be the best in that step. In this example, the base start point is 4.197 minutes, and the base end point is 9.200 minutes.

[0038] Figure 14 shows the changes in the baseline determined to be the best in the first base end point search, the baseline determined to be the best in the first base start point search, the baseline determined to be the best in the second base end point search, the baseline determined to be the best in the second base start point search, the baseline determined to be the best in the third base end point search, and the baseline determined to be the best in the third base start point search.

[0039] Figure 15a shows the final baseline obtained, with a base start point of 4.197 minutes and a base end point of 9.200 minutes. Figures 15b-d show peak detection (baseline) results using a typical peak detection method (detection based on slope and sensitivity). In Figure 15b, the peak end is detected earlier than expected, resulting in a rising baseline. Figure 15c shows the result of lowering the peak detection sensitivity to resolve this issue. However, in this case, the influence of noise causes the main component peak to be identified as two. If the drift value (base determination value) is adjusted to resolve this, the main component becomes a single peak and the baseline becomes almost horizontal, but the base end becomes vertically cut. As such, with SEC, it is extremely difficult to automatically process the baseline so that it is not affected by the negative peak that appears after the main component peak and is almost horizontal. Using the method of the present invention, a more accurate baseline can be established.

[0040] [Table 5]

[0041] Example 2 In this example, anion chromatography (IC) was used. The IC device used was a high-speed ion chromatograph IC-8100 manufactured by Tosoh Corporation. A built-in conductivity meter was used as the detector. The device configuration is shown in Figure 22, and the analytical conditions are as shown in Table 6. A diluted standard sample manufactured by Fujifilm Wako Pure Chemical Industries, Ltd. was used as the sample. Figure 16 shows the chromatogram obtained by the measurement. In anion chromatography, a "negative peak" (water dip) derived from water generally appears at the void position (column space volume) of the system, after which each ion is eluted. The earlier an ion species elutes, the more difficult it is to accurately determine the peak start point (base start point) due to the influence of the water dip.

[0042] [Table 6]

[0043] In this example, the baseline of the fluoride ion (F) peak eluting at approximately 2.0 minutes was determined. First, the initial virtual base start point range was set to 1,000 to 2,100 minutes, and the initial virtual base end point range was set to 2,000 to 2,500 minutes.

[0044] First, the base end point is fixed at 2.200 minutes, and the base start point is sequentially changed within the range from 1.000 minutes, calculating the peak area at each point. The area change rate from the previous point is also calculated. Figure 17 shows an excerpt of the baseline change (legend: the thick line is the baseline). The baseline gradually changes horizontally with a positive slope. Figure 19a shows the area change (left) and area change rate (right). It can be seen that the area gradually decreases as the base start point becomes later, with a decrease occurring at approximately 1.90 minutes. Looking at the area change rate, it can be seen that the area gradually decreases as the base start point becomes later, with a sudden increase occurring at approximately 1.9 minutes. The point where the area change rate rises sharply is the region where the base start point is the rise of the fluoride ion peak, as shown in Figure 17e. The point where the area change rate is minimal is a good candidate for the base start point. In this case, 1.900 minutes is the candidate.

[0045] Next, the range of the virtual base start point is fixed at 1,900 minutes obtained above, and the base end point is sequentially changed within the range from 2,000 minutes, calculating the peak area at each point. The area change rate from the previous point is also calculated. Figure 18 shows an excerpt of the baseline change. The baseline changes from a positive slope to a horizontal slope to a positive slope. Figure 19b shows the area change (left) and the area change rate (right). It can be seen that the base end point rises sharply and stabilizes at approximately 2.1 minutes. Looking at the area change rate, it can be seen that the base end point decreases until approximately 2.3 minutes, then rises. The point with the smallest area change rate is a good candidate for the base start point. In this case, 2,300 minutes is the candidate.

[0046] Next, the base end point is set to 2,300 minutes obtained above, and a second search for the base start point is performed to calculate the best base start point. This process is repeated to determine the best base end point and base start point. In this example, a total of six repetitions were performed. Table 7 shows the results of the six repetitions. The shaded sections indicate the time of the base end point and base start point that were determined to be the best in that step.

[0047] Here, the base end point is 2.250 minutes and the base start point is 1.890 minutes. Figure 20 shows the changes in the baseline determined to be the best in the first base start point search, the baseline determined to be the best in the first base end point search, the baseline determined to be the best in the second base start point search, the baseline determined to be the best in the second base end point search, the baseline determined to be the best in the third base start point search, and the baseline determined to be the best in the third base end point search. Figure 21a shows the baseline finally obtained, with a base end point of 2.250 minutes and a base start point of 1.890 minutes. Figure 21b shows the peak detection (baseline) using a general peak detection method (detection based on slope and sensitivity).

[0048] Thus, when a large negative peak (water dip) is present immediately before the target component peak, the lowest point of the water dip is likely to be determined as the base start, making it impossible to accurately determine the target component peak. By using the method of the present invention, the target component peak can be accurately detected and accurate determination and quantification can be performed, even when a large negative peak is present immediately before it.

[0049] [Table 7] [Explanation of symbols]

[0050] 1. Eluent A 2. Eluent B 3. Degassing device A 4. Degassing device B 5. Liquid transfer pump A 6. Liquid transfer pump B 7. Sample injection mechanism 8. Sampling Needle 9. Sample 10.Analytical column 11. Reference Column 12. Constant temperature bath 13. Refractometer 14. Suppressor 15. Conductivity meter

Claims

1. A method for establishing a baseline for liquid chromatography, comprising the steps of: As the first step, Specify the time range of the virtual peak start point (base start point) and the time range of the virtual peak end point (base end point) of the peak to be detected, fix the virtual peak start point (base start point) within the virtual peak start point (base start point) time range, create a baseline at the minimum value (minimum time) of the virtual peak end point (base end point) time range, calculate the peak area, change the virtual peak end point (base end point) at regular time intervals to create a baseline, and calculate the peak area. The rate of change from the peak area obtained at the previous virtual peak end point (base end point) is calculated, and this operation is performed within the time range of the virtual peak end point (base end point), to calculate the peak end point (base end point) at which the change in peak area is minimal. As the second step, The peak end point (base end point) obtained in the first step is set as a virtual peak end point (base end point) (time), and a baseline is created at the virtual peak start point (base start point) at the minimum value (minimum time) of the virtual peak start point (base start point) time range to calculate the peak area, and the virtual peak start point (base start point) is changed at regular time intervals to create a baseline and calculate the peak area, The rate of change from the peak area obtained at the previous virtual peak start point (base start point) is calculated, and this operation is performed within the time range of the virtual peak start point (base start point), to calculate the peak start point (base start point) at which the change in peak area is minimal. As the third step, A baseline establishment method in which the first step and the second step are carried out two or more times to calculate the peak end point (base end point) and peak start point (base start point).

2. A method for establishing a baseline for liquid chromatography, comprising the steps of: As the first step, Specify the time range of the virtual peak end point (base end point) and the time range of the virtual peak start point (base start point) of the peak to be detected, fix the virtual peak end point (base end point) within the virtual peak end point (base end point) time range, create a baseline at the minimum value (minimum time) of the virtual peak start point (base start point) time range, calculate the peak area, change the virtual peak start point (base start point) at regular time intervals to create a baseline, and calculate the peak area. The rate of change from the peak area obtained at the previous virtual peak start point (base start point) is calculated, and this operation is performed within the time range of the virtual peak start point (base start point), to calculate the peak start point (base start point) at which the change in peak area is minimal. As the second step, The peak start point (base start point) obtained in the first step is set as a virtual peak start point (base start point) (time), and a baseline is created at the virtual peak end point (base end point) at the minimum value (minimum time) of the virtual peak end point (base end point) time range to calculate the peak area, and the virtual peak end point (base end point) is changed at regular time intervals to create a baseline and calculate the peak area, The rate of change from the peak area obtained at the previous virtual peak end point (base end point) is calculated, and this operation is performed within the time range of the virtual peak end point (base end point), to calculate the peak end point (base end point) at which the change in peak area is minimal. As the third step, A baseline establishment method in which the first step and the second step are carried out two or more times to calculate the peak start point (base start point) and peak end point (base end point).

3. 3. The baseline establishment method according to claim 1, wherein in second and subsequent baseline establishments, the amount of change over time at the fixed time interval is set smaller than in the first baseline establishment.

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