When you draw a calibration curve is always the slope is higher than the original point at its intersection with the y-axis, with the knowledge that the solution used is blank solution.
and when to get on the value of intercept the least possible?
I looks like you have a carry over problem. Have you tried injecting the blank immediately after you ran the highest concentration of standard? If so, do you see any of the analyte? I suggest you try rinsing the sample loop or sampling syringe (or autosampler) better after each injection. For rinsing use a solvent the will dissolve away the analyte then rinse mobile phase through the cleaned injection path.
Well, there could be more than one possible causes, as listed by other answers, now I am going to analyze all the responses and hopefully, will give you a plausible answer.
1) Blank error: Blank had some residual sample. Now, lets say i spiked my blank intentionally and ran it. What would i see, my Computer has considered it as baseline, right? So, spiking a blank will not shift the line but may induce an negative error in your final result.
Also, i would like you to have this explanation confirmed.
2) Just noise: Instruments usually have some background noise which usually has small magnitude since most of it is cancelled by the blank. So this might explain the very small difference from the zero of y-intercept.
3) Scattered points: Assuming you are using linear regression, if top points gets lowered by small amount, it will decrease the slope and hence, increasing the y-intercept value. Where I am going with this is, change in concentration of calibration standards can lead to increase in y-intercept value.
It seems like point 3) could be one of the issue in the plot you attached along.
There might be other factors, which I am not aware of, so advise you to research more into concepts such as zero-intercept test, residuals, which will provide a better picture.
Dear Sir,
as it seems you have received the calibration curve to an insensitive method. The background and instrument noise have been discussed now, as the y-axis intercept is not necessarily a mistake in your regression but is a hint for the capabilities of your method.
Therefore in this case it is strongly advised to measure so called 'blank samples' as a control sample. That means a sample with the same solvent and matrix, but without the analyte under investigation.
Additionally, the carry over effect can be considered. Did you measure the calibration samples in the order of increasing concentration?
Kind regards
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