Glucose Standard Curve Calculator

While it is possible to directly quantify the concentration of glucose in solution through UV-spectrophotometry (λ_Max ≈ 270 nm), this method is liable to many interferences due to the abundance of biomolecules which absorb light in this wavelength range. For example, if a glucose sample is cross-contaminated with peptides or proteins, which absorb light at 280 nm, the absorbance reading at 270 nm for glucose will be greatly skewed. Because of the wide array of biological interferences possible, a colorimetric or fluorimetric approach is highly recommended when accurate measurements of glucose sample concentration is required. These methods utilize a glucose specific enzyme (glucose-oxidase) to activate a secondary detection system, ensuring that the detected signal is a result of varying glucose concentration rather than potential biological interferences.

A colorimetric or fluorimetric assay requires the generation of a standard curve in order to determine the concentration of an unknown sample of glucose. The standard curve is created by measuring the responses of a known set of glucose standards, which are either provided by the manufacturer of the assay or can be easily generated through serial dilution of a glucose stock solution. A best fit regression model is applied to the glucose standards and their respective response values. This regression model can then be used to calculate the concentration of any unknown glucose sample.

This tool will generate four different regression models for any given experimental data set. They are, in order, 1) linear 2) linear-logarithmic 3) logarithmic-linear 4) logarithmic-logarithmic. Choose the best regression model based on which R-squared value is closest to 1. Then enter the sample response value into the table to view the sample concentration.