Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 429691
Title Rapid estimation of glucosinolate thermal degradation rate constants in leaves of Chinese kale and broccoli (Brassica oleracea) in two seasons
Author(s) Hennig, K.; Verkerk, R.; Bonnema, A.B.; Dekker, M.
Source Journal of Agricultural and Food Chemistry 60 (2012)32. - ISSN 0021-8561 - p. 7859 - 7865.
DOI https://doi.org/10.1021/jf300710x
Department(s) Product Design and Quality Management Group
Laboratory of Plant Breeding
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) var. italica - red cabbage - isothiocyanates - sprouts - vegetables - metabolism - excretion - health - napus
Abstract Kinetic modeling was used as a tool to quantitatively estimate glucosinolate thermal degradation rate constants. Literature shows that thermal degradation rates differ in different vegetables. Well-characterized plant material, leaves of broccoli and Chinese kale plants grown in two seasons, was used in the study. It was shown that a first-order reaction is appropriate to model glucosinolate degradation independent from the season. No difference in degradation rate constants of structurally identical glucosinolates was found between broccoli and Chinese kale leaves when grown in the same season. However, glucosinolate degradation rate constants were highly affected by the season (20-80% increase in spring compared to autumn). These results suggest that differences in glucosinolate degradation rate constants can be due to variation in environmental as well as genetic factors. Furthermore, a methodology to estimate rate constants rapidly is provided to enable the analysis of high sample numbers for future studies.
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