Dear Mohammad, contour levels do not affect volume integration in 2D spectra. Contours are simply lines drawn the same height along a peak. Just like cotour lines connect places of same elevation on a geographical map.

2D volume integration is a much more complex subject. There are different ways to achieve the task. Most integration routines sum up all data points within a peak. The problem really lies where to stop. The definition of the area that should be included in the integration is the most important issue. Some packages will allow the definition of an area as a square or ellipsoid or some will allow you to define a lower threshold where the integration cuts off.

But I would also like to add that in humble opinion only the same cross peak of the same compound can be used for quantification in 2D HSQC's. It is also recommended to use at least a two point reference line from known concentrations to determine the concentration of an unknown. Typically crosspeaks from other CH pairs of the same molecule show significantly different volumes. Variations of +/- 20% are not unusual even with the most so called quantitative sequences. 

Comparing the volume of a cross peak of one molecule with that of another molecule is not a reliable method of quantification. Wild guess is better.

Regards

Clemens

Thank you very much for your answer. But I am still confused. If you increase the contour level your cross peak area becomes bigger so thats why I dont know which area I need to select. Is there any reference or any method that describes the volume integration technique ? I need to learn. 

It may be easier to think in terms of 1D integration (2D is really no different).  We integrate a peak by moving from the centre of the peak to a point where we hit baseline on either side of the peak.  This defines the region that we will integrate.  In 2D, we are doing this in both dimensions.

It is the definition of "baseline" which gives rise to error.  It is seldom simple to do and increasing the vertical scale may make us move the width of the integration region further out (because NMR peaks have quite wide bases).  Also, noise may make it hard to identify baseline. 

With 2D data, you have the added problem of poor resolution in one or more dimensions.  This means that identifying the baseline contour can be tricky (and hence the integral extent).  In a single spectrum, you just need to be consistent about selection around cross peaks in the same way as you are consistent about selecting the integral extent in 1D spectra.

As Clemens says, using cross peaks to quantify between spectra is to be avoided.  

(note that 1D integral selection is made even more complex by the presence of 13C satellites.) 

Thank you John but the problem that we have is we are doing 2dnmr on wood! and if you look at only 1D it tells you nothing and you cant do integration in 1D I mean you can but the peaks are way overlapped. I am just looking for a publication or any standard protocol which explains volume integration in HSQC 2d nmr and I have not found anything useful so far. I need a method that describes the criteria in selecting the baseline contour for example.

If it is your only approach, then you need to be aware that the size of the cross peak is related to the 1JCH coupling constant.  There are ways to J-compensate but these lead to decreases in sensitivity.  As Clemens mentioned the automatic approach is to use ellipsoids.  There are good routines in Topspin, ACD Spectrus and MestreNova that should work for you.  If your HSQC is really crowded then you may need to resort to manual integration which will be more subjective.  Good luck!

Thank you John

Like Clemens mentioned, integration is independent of contour levels. Contour levels are more of a visual aid. What matters is your boundaries of the integral region and the threshold. 

In my opinion. you should report errors/uncertainty is measurements. You could do this by integrating at least 3 times separately, each time slightly modifying the boundaries of your integral region. That will allow you to calculate the uncertainty. We did that here: http://www.sciencedirect.com/science/article/pii/S0043135417303354

And needless to say, be wary of any 'quantification' using 2D data, some carbons will always be underrepresented due to weak Jch. 

You should be able to find papers on Wood NMR which define integral regions for specific groups (such as lignin). That will help you determine the boundaries.

Thank you Rudraksha

rNMR should do a good job.