Olive oil - en

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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.

Missing data

There are many products for which we have no nutritional data. Clearly there is a role for Robotoff to play here. It is impossible to do it by hand.

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.

BD5ADFBE-A639-47CE-87D9-CC1F4273A694.jpg

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.

Another way to fin interlopers is by looking for strange nutritional values, but that can also be due to wrongly entered data.

Data quality

Nutritional values check

A next step to correct wrong nutritional data, I started by looking 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.

OliveOilsFatPercentageDistribution.jpg

The next edit round looks at fat percentages lower than 88%.

The final result of the fat percentage distribution. Note that the distribution has two peaks, one around 100% and one around 90%. It seems that some producers assume that their olive oils consist of 100% fat and others really have it measured.

Now that I did the fat percentage, I realised that I have to go through all nutritional values and look at values that are out if the ordinary.

Other checks

The nutritional values check also allowed to remove wrongly assigned products (very few).

I also added ingredients images, did the recognition and added subcategories.

Typical errors

I repaired the following errors:

  • wrong classifications
  • mixup between per serving and per 100g data
  • all nutritional values set to 0
  • forgotten to check per serving
  • no total fat percentage on label
  • some yuka users converted the per serving to per 100g values

Olive oil conclusions and thoughts

States overview

After having repaired most of the olive oil products, we can make an overview of the states.

Some highlights (status on 16 dec 2020):

  • Total in category: 6043
  • Has nutritional values: 5380 (89%)
  • Has ingredients: 1971 (33%)

Ingredients

What are the ingredients. Now we see mostly written olive oil, or something like that. But does that convey anything? Preferably we would like to know the olive variety (or varieties). The origin of the olives and the processes applied to extract the oil. Words like virgin, extra virgin, cold-pressed, AOP, the origin of the olives, etc provides more information and is good information.

Serving size

The products sold in the note a serving size on 15 ml on their packaging, which is equivalent to 1 tablespoon. Instead of the 15 ml, a weight of 14 g can be given. This weight corresponds to the specific gravity of 0.911 of olive oils (wikipedia). On products sold in Europe a serving size of 10 ml can sometimes be found. The usefulness of having a serving size for a cooking aid can be debated. In fact 15 ml seems a lot.

Nutritional values

Energy

Many products use, what seems as, standard canonical values for nutritional values. The canonical values for energy (wikipedia) are 3700 kJ or 880 kcal. The products use 900 kcal instead. In total there are 1957 products with this value.

The distribution shows this effect even more clearly:

Energy (kcal) distribution for olive oils (16 dec 2020)

As expected the same double peak is also seen in distribution of Energy in kJoule.

Fat

The distribution of the fat percentage also shows a double peak:

Fat distribution of olive oils (16 dec 2020)

This seems more strange. You would expect that an oil consists of 100% fat, or maybe a bit less if there are impurities. The other peak lies around the 91%, very much like the specific gravity of 0.991.

Conclusion is that some producers report their nutritional values per 100g, some per 100ml and some use the canonical value of 100% (2193 products). A few product have values close to 100%, which seems most honest.

If we have a look at the 100ml sample:

Distribution of fat percentage smaller than 97% (16-dec-2020)

Interestingly we have another distribution with two peaks. So where does the upper peak come from. Looking at the origin of the data, it looks like these products have nutritional values listed per serving. The canonical fat per serving is 14g, which calculates to 93.3%, corresponding to this second peak.

Saturated Fat

The distribution of the saturated fat percentages no not present obvious multiple peaks (although the distribution does not seem symmetrical:

Distribution of saturated fat percentages (16-dec-2020)

Conclusion

In conclusion we have three different group of products, whose data we can not compare. So we need to normalize before we can analyse any further.

Subcategories

OFF has defined multiple subcatgories based on origin (country) or listed quality (virgin, extra virgin).

The virgin olive oils use a first pressing of olives. The second extraction is based on what is left over and are called pomace olive oil (wikipedia). OFF seems to have used refined olive oils as a label for this category. Not sure whether this refined category is the same as the pomace category, we should check the labels of the products.

Possible origins are now France (30 products), Greece (43 products) and Italy (49 products). We should add at least Tunisia, Maroc, Algeria, Spain, Argentina and South Africa to these.

In addition the countries can be subdivided into regions, which correspond to official PDO's.

It is unclear whether these subcategories exhibit also differences in nutritional values. Before we can determine that we need more categorisations.

New categories

By looking more closely at all the products we can identify other categories. Only if there are a lot of products in each category or if the nutritional values deviate to much, it is worthwhile to create these new products

  • pure olive oils: the current olive oils category should be renamed to pure olive oils to indicate that these products contain only one ingredient. This helps also to distinguish from the other olive oils.
  • olive oil sprays for olive oil contain other ingredients to make it sprayable. As the serving is only 0.25g, the nutritional values per serving are all zero (thanks to rounding).
  • enhanced olive oils: these olive oils have added vitamins for children(?)
  • flavoured olive oils: these olive oils have added flavours (garlic, etc.)
  • Olive oil blends: some oils are a blend of refined and virgin olive oils. Or a blend of virgin or extra virgin oils.
  • Unfiltered olive oils: some oils show that they are unfiltered. This might be another category.

Vitamins

Quiten often the Vitamin E and Vitamin A are indicated. Quite strange. As if you are going to take olive oil for your vitamins. I guess the producers want to improve the health standing of their products.

Fat details

NOVA

What should be the value of the NOVA-score for olive oils? It seems to be now mainly NOVA 2. But shouldn't it be NOVA 3 for non-virgin olive oils. The pomace oils are created through chemical processes. A NOVA downgrade seems appropriate. This would also mean that the standard value for the category Olive oils would be NOVA 2, only if the product would be assigned to Virgin olive oils, it would turn NOVA 2.

Nutriscore

Eco-score

OFF Conclusions and thoughts

  • OFF quality

During the cleanup I edited a lot of products. This gives an indication of the quality of the OFF data. The counter stands at 318 products if the 6115, i.e. 7%. This is not yet the final figure.

  • Quality indicators

Many olive oils sold in the USA show extra quality indicators (eg this one). We could add these parameters to the nutritional values. These are mainly expressed as limits (less than or more than).

  • US import issues?

Many US product are not indicated by serving. In the total fat field, the monounsaturated fats are shown. Did we have an import issue?

  • Quality check

Can the verified average values be used as a quality check on new products? A flag could be raised if one of the nutritional values is outside the allowed range.

  • Missing Ingredients

Many products have no Nova calculated as their ingredient list is empty. Could we default to olive oil as ingredient? We could define this category as a base food with a single ingredient. This in turn could be used as quality check.

  • Wrong nutritional values

Several products present nutritional values that is clearly wrong. Now I edited these out. I rather leave them and raise a flag, so that they are not used in the calculations.