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Thyme (Satureja hortensis) is a popular spice for food, which is also often used as a medicine for various ailments. This paper presents an artificial intelligence method applied for the objective determination of the most important physico-chemical variables affecting the quality of thyme, i.e. Principal Component Analysis (PCA). The results show that the main properties which significantly influence the nutritional value of thyme are moisture (MOIST), dry matter content (DRYM), protein content (PROT) and, to a lesser extent, carbohydrate content (CARB). Humidity is strongly and negatively correlated with the latter three variables. The main variable that ensures the similarity between the thyme samples having the same geographical origin is the monosodium glutamate content, which generates its delicious (umami) taste.

IDENTIFICATION OF THE MAIN PHYSICO-CHEMICAL PROPERTIES INFLUENCING THE QUALITY OF THYME (SATUREJA HORTENSIS)