Recently, Land O’Lakes researchers set out to improve a new deli process cheese formulation, without impacting its other attributes.
Senior scientist Mostafa Galal, Ph.D., and senior technologist Michael Scheller, who used Stat-Ease’s Design-Expert® experiments (DOE) software, created a general factorial design using two factors: emulsifier ratio (four levels) and emulsifier type (two). The goal was to find out which ratio and type of emulsifier salt (referred to hereafter as “emulsifier”) would result in the desired improvement in appearance without affecting the other responses.
Cheese sauce makeover
“We are continually examining the recipes of our current products in order to find ways to exceed our customers’ expectations,” Scheller said. “Recently, Mostafa Galal developed a new process-cheese formulation that seemed promising but exhibited some Maillard browning when the product was melted in finished product applications. The browning had no effect on the taste or safety of this product; however, most consumers prefer to have cheese maintain its white color when melted in queso sauce.” Maillard browning is caused by a chemical reaction between an amino acid and a reducing sugar, usually requiring heat.
“This problem was not easy to solve because the formula contains many different ingredients and multiple processing steps,” Scheller says. “The effects of these ingredients and the processing steps could interact with each other, which makes it difficult to get a grip on the problem using conventional one-factor-at-a-time (OFAT) experiments. We began using DOE because it lets us look simultaneously at the effects of all the factors. It also provides statistical analysis that helps separate the single factor and multiple factor effects and allows us to optimize the values of each factor.”
Designing the experiment
Two different emulsifiers are used in the product. Their total amount is fixed, but the relative amount of each emulsifier can vary. Scheller decided to use the ratio of the two as a single factor instead of treating each emulsifier separately. This reduced the number of factors required from three to two, which in turn substantially reduced the number of runs for the experiment. The factors are:
A) Emulsifier type (Type 1 or Type 2). Emulsifier “type” refers to the emulsifier source and delivery system, which are not explicitly stated for reasons of confidentiality.
B) Ratio between different emulsifiers used in product (A, B, C or D)
The goal was to reduce the browning without having any negative effects on either flavor or meltability. Browning can be measured using the Hunter Lab Colorimeter. Using the Hunter, the color space variable “a” is the parameter most useful for monitoring browning in queso sauce. Positive “a” is red, and negative “a” is green. One of the objectives in this experiment is reducing the Hunter “a” level, which corresponds to less browning.