Determination of optimum ripening time in hard cooked cheeses (Reggianito type) using survival analysis statistics: Modified versus traditional cheese making technology.

Abstract

In this work, we determined optimum ripening time of hard cooked cheeses made by traditional technology or by an innovative process aimed at accelerating flavor formation. For that purpose, we applied survival analysis statistics. Experimental cheese making (E) included homogenization of milk fat, unpasteurized\xa0cheese\xa0milk, changes in cooking temperature, and a curd-washing step, while traditional cheese making (T) followed a classic hard-cooked cheese making. Cheeses were ripened for 215 days and samples were analyzed at 76, 112, 128, 152, and 215 days. Consumers (250) were recruited and divided into five groups of 50 consumers for each stage. At each sampling time, consumers assessed whether the sample was under-ripe, ok, or over-ripe. Optimum ripening time could be estimated only for E cheeses, with a high percentage of rejection. For T cheeses, it was not possible to determine the optimum ripening time because the rejection by over-ripening was never reported. We verified consumer segmentation: a small percentage found E cheese under-ripe and a high percentage found it over-ripe. Many consumers qualified E cheeses as too spicy, especially at the end of ripening. Spicy flavor is usually perceived before than the texture and evidenced an acceleration of the flavor formation. We concluded that the innovative intervention in cheese making technology was successful in accelerating cheese ripening. It also had potential to develop a new cheese product targeted at consumers who chose/prefer good spicy flavor. PRACTICAL APPLICATION: Survival analysis is a useful methodology to determine the optimum ripening time of foods based on consumer data. In this work, it evidenced that the proposed innovative cheese making was successful in accelerating the formation of cheese flavor, and had the potential to develop a new cheese product targeted at consumers who chose/prefer good spicy flavor.