We can get the negative concentration values sometimes but they are not very useful, In actual the concentrations may be greater than zero.

In literature, it can be seen that the negative values calculated, shows that the actual concentration of your sample lies below the lower end of your standard curve.

The more sensitive essay may help in this case, If possible. Another way is,  try to concentrate your sample more. you can also try to generate a new sample in order to determine the concentration more accurately.

Thanks, 

In effect, it will depend on the magnitudes of the values with the negative sign. If they are ignorable, they can be considered as zero. If they are too large to be ignored, it might mean that the calibration curve is not accurate. 

Did you develop your calibration curve using the extreme points? If not, do it. Let's say, your real data has a domain of [1 5], then if you try to use it for a data of domain [0 8], you can have this issue.

Hope that helps.

Dear Mariam, The concentration value you got from interpolating the calibration curve is an estimate. As such it has an uncertainty associated to it. Simplifying, this uncertainty is as small as closer to your standard solutions Y-values is your calibration line (which may be expressed, for instance, as the residual sum of squares, Mean Sq or Std y/x). So, if you have an estimated concentration of (estimate±Confidence Interval)  -1.23±3.21 then it may be considered as being zero and this is amost certainly due to (im)precision, which is the case well stressed by Fahim.

Another possible cause, addressed by Fahim, may be an inadequate calibration range. The concentration of sample(s) are expected to be calculated by interpolation not extrapolation of the calibration curve  which means that your sample analytical reading should lie between the lowest and the highest standard solution signal. If it is not the case your results may be inaccurate (and may simultaneously be imprecise).

If you share you calibration and sample(s) data (conc and analytical reading), I'm sure you will get a more focused feddback. Hope it helps.

 Thanks Syed. A. Taqvi, Fahim and Dr. Luis F. Gouveia, Your discussion is really helpful for me, I am try to prepare another calibration curve within the  range of sample signals. we had a nice discussion. 

i was also trying to calculate concentration for water samples but the values i got became negative but thanks to this post i know understand

Sometimes negative concentration may be as a result of using standards whose concentrations range is considerably higher than the actual concentration of the sample.

You can try rerunning your samples using standards of lower concentrations. This may give you positive concentrations

If you have considerable negative values, it is advised to do the following. from the regression equeation (y=ax+b) obtained from the calibration curve, the value obtained at y=0 (which meanse at pick area 0) must be subtracted from all values. This will adjust your concentration.

If the concentration is calculated as NEGATIVE, then the calibration table is flawed and the method used either invalid or incomplete. Sometime the signal response is not linear or the matrix contributes to the signal. In all cases, a proper method with enough calibration levels (points) must be used to define the full curve/response. Sometime is may not be linear, esp close to the lower limits. Use more cal standards at the lower concentration levels to better define the response.