Optimum Level of Salt in French-Type Bread. Influence of Income Status, Salt Level in Daily Bread Consumption, and Test Location

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

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 cheese milk, 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.

How thick do consumers' want their meat and how thick do they get it? The case of deep-fried breaded beef

The main objective was to estimate the optimum thickness of meat from a consumers' perspective. Breaded beef (known as "milanesa" in Spanish speaking countries and as "schnitzels" in Austria) is a food product prepared with a slice of meat that is dipped in beaten egg to then be covered in bread crumbs; thus prepared it is fried. This product was used as a case study. Breaded beef was evaluated in three different stages: raw slice of meat, appearance of meat after frying, and during mastication. Breaded beef prepared with meat of varying thicknesses were presented to consumers who evaluated if the thicknesses were too thin, ok or too thick. Survival analysis statistics were used to estimate the optimum thicknesses. Results for each stage were: raw slice of meat = 6.7 ± 0.2 mm, appearance of the cut fried breaded beef = 8.4 ± 0.3 mm and during mastication = 7.6 ± 0.3 mm. The average thickness of the meat cut by butchers for breaded beef was 5.9 mm, not too far from the optimum. However, the average thickness of the meat in the breaded beef ready for frying sold by the same butchers 3.7 mm, clearly thinner than the optimum.