Glycaemic index of food and its determination

The purpose of this thesis was to elaborate a literature recherche on a given theme with focus on analytical methods to estimate the glycaemic index of food. This bachelor thesis is divided into three main chapters. First chapter describes general characteristics of glycaemic index of foods and influencing factors. In this chapter states the influence of high and low glycaemic index foods on health, wellbeing and glycaemia in humans. Subsequent part of this chapter is dealing with many other factors that influence the absolute amount of glucose in blood in 2 hour interval after meal. Chapter two initiates into conventional and continual methods of glycaemia measurement.It highlights the advantages and limitations of each of these methods. Third, the most extensive chapter is dealing with methods of glycaemic index assessment. This chapter is broken down into two parts. First part specifies clinical methods that are also called in vivo, and the second part is focusing on in vitro methods. Clinical methods require blood glycaemia measurement in healthy volunteers after consuming a test meal. With this method we are able to reliably state the glycaemic index of certain foods. The limiting factor of this method is that it is rather time-consuming and it requires higher financial means. These measurements take place under a strict control, according to guidelines and only with the approval of ethical committee. Analytical methods are based on simulation of human digestion. In vitro methods use hydrolysis index to obtain the glycaemic index. The final values are only an assessment of glycaemic index of given food. Other method that is described is measurement of fast and slowly available glucose and starch in given test foods. It is based on measurement of released glucose from the test food with HPLC method, time incubation and standardized conditions. Last method includes partitioning of a test food, and subsequent HPLC analysis of carbohydrates and sugar alcohols. The HPLC results are processed in artificial neural network to reveal glycaemic index values. The advantages and disadvantages of each mentioned method are stated in conclusion of this work. I compared and contrasted reliability, elaborateness, budget demands of analytical methods with clinical assessment methods