# Sensory shelf life analysis in Excel tutorial

This tutorial will help you set up and interpret a sensory shelf life analysis in Excel using the XLSTAT statistical software.

## Dataset for sensory shelf life analysis

The data used in this tutorial correspond to the evaluation of a fresh fruit juice by 19 assessors at different times. The juices have been tested 6 times at day 1, 2, 3, 4, 5 and 6. The assessors have given their liking (yes/no) for all these times. In the data, the assessors' evaluations are coded using 0 when the evaluation is negative and 1 when it is positive.

Here is the data format: You can change the value (0/1) to any other value in XLSTAT (yes/no for example).

## Goal of the sensory shelf life analysis

The goal of this analysis is to visualize the best period to put a product in a shelf for selling it. Parametric survival models are used to model the time at which an event occurs.

## Setting up a sensory shelf life analysis

Once XLSTAT is activated, select the XLSTAT-Sensory data analysis / Sensory Shelf Life Analysis command (see below), or click the corresponding button of the XLSTAT-Sensory data analysis toolbar. Once you have clicked on the button, the dialog box appears. Select the assessor x date table as presented above and a column with the value associated to each date in the time data box. We use the Weibull distribution to fit the model.

Other options are left with their default values.

## Interpreting the results of a sensory shelf life analysis

After you have clicked on the OK button, the computations start.

The first table corresponds to basic summary statistics associated to the time data. A graphic is also displayed giving an overview of the answers of the assessors.

This plot shows a decrease in the number of assessors that appreciate the orange juice. At the end of the analysis, only 4 assessors still like the product.

The tables displayed afterward are similar to those displayed in a parametric survival curve. A Weibull curve is fitted to the model. We can see that both parameters are significant.

The preference distribution function plot based on a Weibull distribution is as follows : Finally, the quantiles are obtained and are very useful for decision making.

We can see that median time is between 4 and 5 days after the product has been put on the shelf.

Many more analysis and decisions can be taken with sensory shelf. Explanatory variables associated to each assessor can be added.