Guide to Calibration Curve Preparation: Principle and Methodology

Guide to Calibration Curve Preparation: Principle and Methodology


  • Post By :

  • Source: Microbioz India

  • Date: 15 Jul,2023

The calibration curve, often known as the standard curve, is an essential curve in analytical chemistry.

Calibration curve preparation:

What is a calibration curve?

The calibration curve, often known as the standard curve, is an essential curve in analytical chemistry. It enables the device to determine the relationship between instrumental analysis and analyte concentration in an unknown sample. In this article, Microbioz will stroll exploring the Calibration curve in depth, as well as the step-by-step technique and precautions that ensure error-free results.

Principle of calibration curve:

Before generating a calibration curve, it is essential to grasp the concept underlying calibration curve formation. A calibration curve is a plot that is used to determine the concentration of an analyte in an unknown sample.  The calibration curve plot is a linear connection between an analyte (X-axis) and an instrument (Y-axis) that is reliant on the equation (y=mx+b). Plots that are not linear are regarded erroneous and are deleted because they exceed the limit of linearity. Furthermore, these plots serve as a guide for using instrumental measurements as a relevant data point.

Step-1 Selection of analyte and analytical technique

The first stage in calibration curve construction is the selection of an appropriate analyte and analytical method. To estimate the concentration of desired analyte and analytical technique, consider different parameters such as accuracy, precision, sensitivity, selectivity, robustness, ruggedness, scale of operation, analysis time, availability of equipment, and cost. This provides compatibility and precise measurement.

Also read:

HPLC calibration curve: Everything You Need to Know

Step-2 Standard solution to obtain linear calibration curve:

The linear calibration curve is heavily reliant on a known analyte concentration standard solution. A series of standard solutions are required to estimate the concentration of an unknown sample analyte by comparing it to a known standard analyte. Furthermore, the standard solution should have a concentration that spans the predicted range of the unknown sample analyte plot. To create a linear calibration curve, accurate preparation, pipetting, and dilution of stock or working standard solutions are required.

Perform Serial dilution:

Determine the appropriate dilution factor and label the microtubes to execute serial dilution. Fill a tube with a known concentration of the sample and the needed volume of solvent. Change the tip and transfer the solution from one tube to the next one at a time, diluting with the needed volume of solvent.

Step-3 Sample loading:

A sample of unknown concentration is placed into the appropriate equipment, such as a UV-spectrophotometer, to generate the calibration curve. And the absorbance of the sample must be recorded in order to plot the findings. To acquire correct findings, the container, such as a cuvette in the case of a UV-spectrophotometer, must be clean from the outside and set suitably in the direction of light while loading the sample.

Step-4 Calibration curve plot:

Data obtained from instruments must then be suitably plotted in order to generate an error-free linear calibration curve. In general, the X-axis depicts analyte concentration, while the Y-axis represents the peak and curve of Instrument. Various graphing applications may be used to visualise the instrumental response to compute unknown concentrations, limits of detection, and limits of quantitation. To depict the calibration curve of analysed data, plots such as scatter plots from various graphing tools can be utilised.

Step-5 Evaluating linearity and range of calibration curve:

Calibration curve evaluation needed linear and dynamic range assessment by R-square value (Coefficient of determination) or ANOVA (Statistical tests) tools. The R square value is directly linked to the predictability and accuracy of data, i.e., the higher the R-value, the greater the accuracy. It is used to assess the quality of fit of a calibration curve. R2 values vary from 0.0 to 1.0v (1.0 being reported as a perfect match). While evaluating the range, verify that the required concentration range is free of saturation and extrapolation concerns. Remember, concentration range that is non-linear, is limit of linearity.

Step-6 Documentation and reporting of calibration curve:

To enhance traceability and repeatability, proper recording, reporting, and expression of acquired calibration curve data are required. In your reports as well as in laboratory data, include the technique, calibration curve, absorbance, concentration range, curve fit equation, and any adjustments or deviations.

Note: To ensure the accuracy of findings, proper pipetting and weighing of solute and solvent are required. Also, keep in mind that some of the standards are light sensitive, so allow them to react in dark.

Authored By:

Aaysha Gupta- Ph.D (pursuing)

Jaypee institute of information technology, sec-62, Noida
Area of research (Medical biotechnology)

About Author