Chemical Composition and Sensory Evaluation of Saffron.

HPLC/DAD (High Performance Liquid Chromatography) analysis descriptive sensory analysis picrocrocin saffron safranal

Journal

Foods (Basel, Switzerland)
ISSN: 2304-8158
Titre abrégé: Foods
Pays: Switzerland
ID NLM: 101670569

Informations de publication

Date de publication:
27 Oct 2021
Historique:
received: 28 09 2021
revised: 22 10 2021
accepted: 25 10 2021
entrez: 27 11 2021
pubmed: 28 11 2021
medline: 28 11 2021
Statut: epublish

Résumé

The quality and economic value of saffron, one of the most counterfeited spices, are based on three key substances that are relatively easy to measure: crocines (colour); picrocrocines (bitter); safranal (odour impact). Despite being well-known, as their concentration is correlated to sensory intensity, a detailed sensory evaluation, performed by a trained panel, supported by advanced analytical approaches, may better show the relationships between saffron composition and sensory perception. Three saffron samples of different Italian origins (Sardinia and Tuscany) were evaluated by a trained sensory panel and their chemical composition was determined by HPLC (High Performance Liquid Chromatography) and spectrophotometry. Safranal concentration and the perceived odour intensity were positively correlated while relationships between picrocrocine and bitter perception were more complex to detect. By correlating (Multiple Factor Analysis) saffron sensorial and chemical profiles, this work aims at improving saffron characterisation while providing better information on the quality of this valuable spice.

Identifiants

pubmed: 34828885
pii: foods10112604
doi: 10.3390/foods10112604
pmc: PMC8618029
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Stefano Predieri (S)

IBE-CNR, Institute of BioEconomy, c/o Area della Ricerca di Bologna, Via P. Gobetti, 101, 40129 Bologna, BO, Italy.

Massimiliano Magli (M)

IBE-CNR, Institute of BioEconomy, c/o Area della Ricerca di Bologna, Via P. Gobetti, 101, 40129 Bologna, BO, Italy.

Edoardo Gatti (E)

IBE-CNR, Institute of BioEconomy, c/o Area della Ricerca di Bologna, Via P. Gobetti, 101, 40129 Bologna, BO, Italy.

Francesca Camilli (F)

IBE-CNR, Institute of BioEconomy, Via Caproni 8, 50145 Firenze, FI, Italy.

Pamela Vignolini (P)

Phytolab, Department of Statistics, Informatics, Applications "G.Parenti", DiSIA, University of Florence, Via Ugo Schiff 6, 50019 Sesto Fiorentino, FI, Italy.

Annalisa Romani (A)

Phytolab, Department of Statistics, Informatics, Applications "G.Parenti", DiSIA, University of Florence, Via Ugo Schiff 6, 50019 Sesto Fiorentino, FI, Italy.

Classifications MeSH