Evidence map›Paper›PMID 38276603›Full record

ArticleMolecules (Basel, Switzerland)2024

Chemical Data and Relationships for a Scoring Algorithm of Extra Virgin Olive Oil's Nutritional Value.

Lorenzo Cecchi, Filippo Conticelli, Bruno Zanoni, Carlotta Breschi, Maria Bellumori, Nadia Mulinacci

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lorenzo CecchiDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Piazzale Delle Cascine 16, 50144 Florence, Italy.ORCID 0000-0002-9332-704X
Filippo ConticelliPlacet srls, Via Donizetti 21/1, Empoli, 50053 Florence, Italy.
Bruno ZanoniDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Piazzale Delle Cascine 16, 50144 Florence, Italy.ORCID 0000-0002-9020-6883
Carlotta BreschiDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, Piazzale Delle Cascine 16, 50144 Florence, Italy.
Maria BellumoriDepartment of Neuroscience, Psychology, Drug and Child Health, Pharmaceutical and Nutraceutical Section, University of Florence, Via Ugo Schiff 6, Sesto Fiorentino, 50019 Florence, Italy.ORCID 0000-0003-3583-012X
Nadia MulinacciDepartment of Neuroscience, Psychology, Drug and Child Health, Pharmaceutical and Nutraceutical Section, University of Florence, Via Ugo Schiff 6, Sesto Fiorentino, 50019 Florence, Italy.ORCID 0000-0001-7873-5259

Funding

Agritech National Research Center - European Union Next-GenerationEU - PNRR CN2 CN00000022
6 · The paper itself

Abstract

Extra virgin olive oil (EVOO) is a valuable product and is highly appreciated by consumers for its great nutritional value. However, to date, there has been a lack of uniform systems capable of ranking the nutritional value of EVOO based on its chemical composition in terms of macro- and micronutrients (including phenolic compounds and tocopherols). The aim of this study was to propose a scoring algorithm to rank the nutritional value of EVOO samples, considering their chemical composition in macro- and micronutrients and their sensitivity to oxidation phenomena. Data from more than 1000 EVOO samples were used to assess the variability of the data, considering the selected negative parameters (free acidity, peroxide value, spectrophotometric indices) and positive components (composition in tocopherols via HPLC-DAD, phenolic compounds via HPLC-DAD, and fatty acids via GC-MS) so as to ensure the universal validity of the scoring algorithm. The dataset included samples from the main producing countries worldwide, in addition to Australia, across several production years; data were selected to represent different production realities. A mathematical model was set up for each chemical component, resulting in six variable values. By combining these values with a dimensionless constant value, the algorithm for computing the nutritional value score (NVS) was defined. It allows the nutritional value of an oil to be ranked on a scale of 0 to 100 based on its chemical composition. The algorithm was then successfully tested using chemical data from about 300 EVOO samples obtained from laboratories from different Italian regions. The proposed NVS is a simple and objective tool for scoring the nutritional value of an EVOO, easy to understand for both producers and consumers.

Indexed as

OleaMicronutrientsNutritive ValueOlive OilPhenolsTocopherolsMicronutrientsOlive OilPhenolsTocopherolsantioxidantsEFSA health claimfatty acids compositionnutraceuticalNutri-Scorenutritional qualityolive oil polyphenolsoxidative stabilityphenolic compoundstocopherols

Identifiers

PMID38276603
PMCPMC10818574

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.