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The effect of cooking on the phytochemical content of vegetables
Open accessAbstract
Cooking induces many chemical and physical modifications in foods; among these the phytochemical content can change. Many authors have studied variations in vegetable nutrients after cooking, and great variability in the data has been reported. In this review more than 100 articles from indexed scientific journals were considered in order to assess the effect of cooking on different phytochemical classes. Changes in phytochemicals upon cooking may result from two opposite phenomena: (1) thermal degradation, which reduces their concentration, and (2) a matrix softening effect, which increases the extractability of phytochemicals, resulting in a higher concentration with respect to the raw material. The final effect of cooking on phytochemical concentration depends on the processing parameters, the structure of food matrix, and the chemical nature of the specific compound. Looking at the different cooking procedures it can be concluded that steaming will ensure better preservation/extraction yield of phenols and glucosinolates than do other cooking methods: steamed tissues are not in direct contact with the cooking material (water or oil) so leaching of soluble compounds into water is minimised and, at the same time, thermal degradation is limited. Carotenoids showed a different behaviour; a positive effect on extraction and the solubilisation of carotenes were reported after severe processing. © 2013 Society of Chemical Industry
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Metadata
- Authors
- Palermo, M., Pellegrini, N., & Fogliano, V.
- Venue
- Journal of the Science of Food and Agriculture
- Publisher
- Wiley
- Published
- 2013-12-13
- Volume
- 94
- Issue
- 6
- Pages
- 1057-1070
- ISSN
- 0022-5142 (ISSN-L)
- 1097-0010
- OpenAlex
- W2168056739
- Cited by
- 401
- References
- 126
- FWCI
- 8.18
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
