|Title||Plant science meets food science: genetic effects of glucosinolate degradation during food processing in Brassica|
|Source||University. Promotor(en): Tiny van Boekel, co-promotor(en): Guusje Bonnema; Matthijs Dekker; Ruud Verkerk. - S.l. : s.n. - ISBN 9789461736345 - 167|
Laboratory of Plant Breeding
Food Quality and Design
|Publication type||Dissertation, internally prepared|
|Keyword(s)||glucosinolaten - brassica - voedselverwerking - thermische afbraak - genetische effecten - glucosinolates - food processing - thermal degradation - genetic effects|
|Categories||Chemistry of Food Components|
Phytochemicals in plant-based foods have been linked to a reduced incidence and progression of diseases. Glucosinolates (GLs) are phytochemicals that are typical for Brassicaand other Cruciferousplants, such as cabbage, broccoli, Brussels sprouts, Chinese cabbage, mustard and horseradish. The intake of GLs has been associated with lowered risks of several types of cancer and other diseases. To reach a high level of GLs in the vegetables at the stage of consumption, research along the food chain aims to increase the concentrations of certain GLs and to lower the losses during food processing; however, effects of the different steps in the food chain are mostly investigated separately. In this thesis an interdisciplinary approach, combining food science and plant science, was applied to explore the possibilities to retain GLs throughout the food chain. The objective of this thesis was to investigate genetic effects related to GL degradation during food processing in order to test if food processing parameters can be used as phenotypic traits and breed for vegetables with improved GL retention.Methods
One challenge of integrating plant science and food science is the high number of samples to be analysed to apply quantitative genetics to food technological traits. The analysis of GLs, as desulpho-GLs, was optimized to reach accurate results using a high throughput method. Kinetic modelling was applied to describe GL thermal degradation in a quantitative way, therefore an appropriate model was identified. Furthermore, genetic and environmental effects of GL thermal degradation were investigated in a broccoli and a Chinese kale genotype in two seasons. GL thermal degradation was determined in a segregating population, developed by crossing the broccoli and Chinese kale genotype investigated in the previous study. Thermal degradation rate constants were combined with molecular marker information to identify genetic regions associated with GL thermal degradation (quantitative trait loci). Moreover, a subset of the segregating population was tested for environmental variation. An untargeted metabolomics approach was applied to test if metabolites are associated with the thermal degradation rate constants and hence influence thermal degradation.Results
The desulphation procedure applied to determine GLs as desulpho-GLs is crucial for the analytical result. For the first time an inverse effect of the sulphatase concentration on the peak area of a GL, glucotropaeolin, which is often used as internal standard, was shown, leading to a substantial overestimation of GL concentrations. We recommend the application of a purified sulphatase preparation to obtain accurate results for a broad range of samples.
The research conducted in this thesis demonstrates that GL thermal degradation is partly genetically regulated. Furthermore, environmental factors, such as season and growing year, influence GL thermal degradation. The findings provide the methodology to breed for vegetables with increased GL retention during food processing. More studies are required to test the stability of the identified QTL in different environments and growing years to apply GL retention as breeding trait. Furthermore, one method was shown towards the identification of metabolic factors causing the variation of GL thermal degradation in different vegetables, which also requires future research to confirm these findings. In order to improve specific quality attributes of plant-based foods, breeding for quantitative food processing traits is a promising and challenging approach. It has potential to improve the nutritional quality of food products by combining the disciplines food and plant science to select and breed for varieties with not only higher initial amounts of phytochemicals but also with a high retention during processing.