Detection and Classification of Honey Adulteration Combined with Multivariate Analysis

Abstract

Honey is a natural sweetener with a yellowish substance made up of bee secretions and plant nectar extracts. Main composition of honey are sugars or carbohydrates and water in the chemical composition and contain a great number of minor components such as minerals, amino acids, proteins, acidity, and pH. Honey adulteration is a global concern due to lack of awareness of people and policies. There is a various method that has been conducted to detect honey adulteration such as SCIRA, DSC, FTIR, NIRS, and NMR and these methods mostly used multivariate data analysis to classify the adulteration of honey. PCA is the most used technique in the classification of honey adulteration where the data obtained is clustered according to adulteration level and type of the adulterant. This paper explains on different methods to detect honey adulteration and common technique used on classification of honey. It can be concluded that PCA is the most used technique based on different method of honey adulteration detection.