Evidence map›Paper›PMID 38017697›Full record

ArticleJournal of the science of food and agriculture2025

Assessment of fruity aroma intensity in olive oils from different Spanish regions using a portable electronic nose.

Alessandro Bianchi, Pablo Cano Marchal, Diego M Martínez Gila, Fabio Mencarelli, Javier Gámez García

Abstract readEvaluation Study
In one paragraph

Article in Journal of the science of food and agriculture, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Alessandro BianchiDepartment of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.ORCID https://orcid.org/0000-0001-6482-527X
Pablo Cano MarchalUniversity Institute of Research on Olive and Olive Oils (INUO), Electronics and Systems Engineering Department, University of Jaén, Jaén, Spain.ORCID https://orcid.org/0000-0001-6669-8016
Diego M Martínez GilaUniversity Institute of Research on Olive and Olive Oils (INUO), Electronics and Systems Engineering Department, University of Jaén, Jaén, Spain.ORCID https://orcid.org/0000-0002-4150-5967
Fabio MencarelliDepartment of Agriculture, Food and Environment, University of Pisa, Pisa, Italy.ORCID https://orcid.org/0000-0003-0677-5010
Javier Gámez GarcíaUniversity Institute of Research on Olive and Olive Oils (INUO), Electronics and Systems Engineering Department, University of Jaén, Jaén, Spain.

Funding

Ministerio de Ciencia y Tecnología PID2019-110291RB-I00
6 · The paper itself

Abstract

backgroundThe organoleptic profile of an olive oil is a fundamental quality parameter obtained by human sensory panels. In this work, a portable electronic nose was employed to predict the fruity aroma intensity of 199 olive oil samples from different Spanish regions and cultivar varieties ('Picual', 'Arbequina', and 'Cornicabra'), with special emphasis in testing the robustness of the predictions versus cultivar variety variability. The primary data given by the electronic nose were used to obtain two different feature vectors that were employed to fit ridge and lasso regressions models to two datasets: one consisting of all the samples and another just the cv. Picual samples.

resultsThe results obtained showed mean average error (MAE) values below 0.88 in all cases, with an MAE of 0.67 for the 'Picual' model. These MAE values and the similarities in the model parameters fitted for the different data folds are in agreement with the results obtained in previous studies.

conclusionThe large number of samples analyzed and the results obtained show the robustness of the approach and the applicability of the methods. Also, the results suggest that better performance can be obtained when specific models are fitted for particular cultivars. Overall, the proposed methods are capable of providing useful information for a fast screening of the fruity aroma intensity of olive oils. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Indexed as

Electronic NoseFlavoring AgentsFruitOleaOlive OilHumansOdorantsSpainTasteVolatile Organic CompoundsFlavoring AgentsOlive OilVolatile Organic Compoundse‐nosefeature extractionmetal oxide semiconductor sensormultivariate analysisolive oil qualityorganoleptic assessment

Identifiers

PMID38017697
PMCPMC11726602

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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.