Olive oil - en

Introduction

In november 2020 @stephane asked to have a look at the products in the olive oil category. The category was in need of cleaning up. An olive oil should have a Nutriscore D or C, but other values were seen. So I had a look at the products and cleaned a bit. This post is a log of my observations.

Background

Olive oils are a special category for Nutriscore, as they are a special case for the score calculation. Olive oil is seen as one of the better oils, and thus may get a better score. This exception was recently introduced (a refrence here?).

However all oils are bad, so olive oil will never get a better score than C. This has provoked a lot of resistance in Italy and Spain, as olive oil is seen as a major export product. Those countries might leave out olive oil from the Nutriscore obligation.

Definition

https://en.wikipedia.org/wiki/Olive_oil is a simple product: it has only one ingredient: olives. The extraction process and origin might influence the actual composition of oils. This might be visible in the nutritional values and labelling on a product.

Completeness

On 13 dec 2020 the https://world.openfoodfacts.org/category/olive-oils is comprised of 6118 products. There might be olive oil products, which are not labelled as such.

Robotoff comes here to the rescue, as it might have found some eligible products. On 13 dec 2020 there were no remaining questions on Robotoff.

Interlopers

Are all the products in the Olive oils category indeed olive oils. We need to find the products that are not olive oils (the interlopers).

Number of ingredients

A first check is to look at the number of ingredients. And it turns out that are some products that seem wrongly classified.

Note that of the 6118 products only 1967 seem to have ingredients defined.

Not sure how I can list the products with more than 1 ingredient.

Fat percentage

Another way to find interlopers (or wrong data) is to look at the fat percentage.

There are 6 products with more than 100% fat, so lets correct those first. It easier to list those with a query and correct them.

For these products the wrong data has been added. One product had a fat content of 101g though.

Now we can graph the fat content again. Now we see we have an issue with products with a fat percentage that is much to low. So next edit round.