Qualitative analysis of broccoli (Brassica oleracea var. italica) glucosinolates: Investigating the use of mid-infrared spectroscopy combined with chemometrics
dc.contributor.author | Langston, F | |
dc.contributor.author | Redha, AA | |
dc.contributor.author | Nash, GR | |
dc.contributor.author | Bows, JR | |
dc.contributor.author | Torquati, L | |
dc.contributor.author | Gidley, MJ | |
dc.contributor.author | Cozzolino, D | |
dc.date.accessioned | 2023-07-21T13:05:46Z | |
dc.date.issued | 2023-07-12 | |
dc.date.updated | 2023-07-21T12:11:16Z | |
dc.description.abstract | Glucosinolates are phytochemicals with important health and nutritional benefits. This study reports the use of high-performance liquid chromatography (HPLC) and mid-infrared (MIR) spectroscopy to characterise and differentiate between broccoli varieties and systems of production (organic vs. non-organic) depending on their glucosinolate content and infrared fingerprint. Broccoli samples (n = 53) from seven varieties were analysed using MIR spectroscopy and HPLC. Differences in the MIR spectra of the individual broccoli varieties were observed in the carbohydrate fingerprint region (950–1100 cm-1) and between 1340 and 1615 cm-1 assigned to specific glucosinolates. Principal component analysis (PCA) of the MIR fingerprint spectra enabled the differentiation between samples with relatively high (200–500 mg/100 g DW) and low (< 200 mg/100 g DW) glucobrassicin content. Linear discriminant analysis (LDA) and PCA-LDA were used to classify broccoli varieties according to the system of production (organic vs. non-organic) and variety (common vs. Tenderstem® broccoli). The classification rates indicated that > 70 % of the samples were correctly classified as organic and non-organic, while > 90 % of the samples were correctly classified as common broccoli and Tenderstem®. This study demonstrates that MIR spectroscopy could be used as a potential tool to classify and monitor broccoli samples according to their variety and system of production. | en_GB |
dc.description.sponsorship | PepsiCo | en_GB |
dc.description.sponsorship | QUEX Institute | en_GB |
dc.format.extent | 105532- | |
dc.identifier.citation | Vol. 123, article 105532 | en_GB |
dc.identifier.doi | https://doi.org/10.1016/j.jfca.2023.105532 | |
dc.identifier.uri | http://hdl.handle.net/10871/133636 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_GB |
dc.rights | © 2023 The Authors. Published by Elsevier Inc. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | en_GB |
dc.subject | Broccoli | en_GB |
dc.subject | Mid infrared | en_GB |
dc.subject | Chemometrics | en_GB |
dc.subject | Glucosinolates | en_GB |
dc.subject | Glucobrassicin | en_GB |
dc.title | Qualitative analysis of broccoli (Brassica oleracea var. italica) glucosinolates: Investigating the use of mid-infrared spectroscopy combined with chemometrics | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2023-07-21T13:05:46Z | |
dc.identifier.issn | 0889-1575 | |
exeter.article-number | 105532 | |
dc.description | This is the final version. Available from Elsevier via the DOI in this record. | en_GB |
dc.description | Data Availability: No data was used for the research described in the article. | en_GB |
dc.identifier.eissn | 1096-0481 | |
dc.identifier.journal | Journal of Food Composition and Analysis | en_GB |
dc.relation.ispartof | Journal of Food Composition and Analysis, 123 | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2023-07-11 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2023-07-12 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2023-07-21T12:55:34Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2023-07-21T13:05:52Z | |
refterms.panel | C | en_GB |
refterms.dateFirstOnline | 2023-07-12 |
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This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.