How is a standard curve prepared for a spectrophotometric assay?

How is a standard curve prepared for a spectrophotometric assay?

• A. Plot a curve of unknown concentrations against measured signal.
• B. Use a calibration table instead of a curve.
• C. Plot concentration against time using random standards.
• D. Prepare standards with known concentrations; measure signal; plot concentration vs signal to derive a linear equation; use to interpolate unknown sample results.

Answer: (D)

The main idea is to build a calibration relationship between the signal you measure and known concentrations, so you can convert the signal from an unknown sample into its concentration. To do this, you prepare several standards with known concentrations that span the range you expect in your samples. For each standard, you measure the spectrophotometric signal (often absorbance). Then you plot the known concentrations on the x-axis versus the measured signals on the y-axis and fit a line (or curve) to establish the equation that relates signal to concentration. With that calibration equation, you measure the unknown sample’s signal and interpolate its concentration. This works because, within the instrument’s linear range, signal is proportional to concentration (Beer’s law), so the calibration curve provides the necessary conversion from the measured signal to concentration. The other options don’t establish that required relationship: one would need known concentrations to construct the curve, not unknowns; a calibration table is not the active curve you interpolate from; and plotting concentration against time with random standards does not relate signal to concentration.

The main idea is to build a calibration relationship between the signal you measure and known concentrations, so you can convert the signal from an unknown sample into its concentration. To do this, you prepare several standards with known concentrations that span the range you expect in your samples. For each standard, you measure the spectrophotometric signal (often absorbance). Then you plot the known concentrations on the x-axis versus the measured signals on the y-axis and fit a line (or curve) to establish the equation that relates signal to concentration. With that calibration equation, you measure the unknown sample’s signal and interpolate its concentration.

This works because, within the instrument’s linear range, signal is proportional to concentration (Beer’s law), so the calibration curve provides the necessary conversion from the measured signal to concentration. The other options don’t establish that required relationship: one would need known concentrations to construct the curve, not unknowns; a calibration table is not the active curve you interpolate from; and plotting concentration against time with random standards does not relate signal to concentration.