Understanding the data analysis of the ORAC Assay: Where it does come from?

Have you ever questioned what the units of the ORAC assay mean? Or why does everybody come up with a different formula for it? In this post we will carefully break down the steps that lead to the formula that nobody speaks about.

## ORAC Assay. First, some background

The ORAC assay is meant for the measurement of antioxidant capacity, in various types of samples like food and biological. A fluorescent indicator and a free radical generator are used together. The radicals produced when the free radical generator is activated damage the indicator, which loses its properties. This can be detected in a **fluorimeter as a decrease in the signal.**

When you add your sample rich in antioxidants to this mixture, the antioxidants protect the probe, and the decrease in the fluorescence is **slowed down**.

The measurement is typically done over a **long period of time**, like one hour and a half, so you can detect antioxidants with different kinetics, the ones that act first and the second ones that act when the first have been depleted, and so on.

After that, you will obtain a plot similar to that attached

## And what can you do with these data?

The usual way is to make a relative measure of the **lost of the initial fluorescence**. This way you standardize the data to enable comparisons.

To do this, you divide each individual measurement by its initial value, so you know the remaining amount of unoxidized probe.

Where f_{n} is the fluorescence at a specific point time and f_{0} is the first measurement of fluorescence in each well.

Once you have the **values relativized**, you are able to compare every well. The usual measurement is to calculate the **area under the curve**:

## Calculating the area under the curve

For this, a **normal integral** is used. First, the total area is divided in the smaller section possible (between two measurements).

The area of the **individual sections** is calculated as follows:

## Data analysis

We could simplify this equation by calling CT (cycle time) the form ), which is the **periodicity** of the measurements and further by:

Then, we need to apply it as t**he sum of all the sections**, if we substitute the n with the value for each time point, from 0 to 90 minutes in the case of BQCkit ORAC.

That is the reason why, depending on the CT, the first value can change and be 1 for two minute-interval measurements, 2, for 4 minute-interval measurements and so on.