Flour is the backbone ingredient of almost all cookie types. Understanding the role of flour in a cookie formulation is important to control finished product attributes such as surface appearance, diameter, color, structure, and eating quality. Flour for cookie applications is generally milled from soft wheat that is grown in the central part of the U.S. This region includes the states of Illinois, Indiana, Ohio, and Tennessee. There is also some soft wheat grown in the East Coast states around Virginia and Maryland. Wheat in these regions is generally classified as Soft Red Winter, is planted in the fall of the year, and harvested in late spring/early summer. There is also some Soft White Wheat grown in the Pacific Northwest that can be milled into flour for cookie applications.

Desired characteristics for cookie flour include the ability to mix with other ingredients into a homogenous mass with minimal added moisture, provide good machining properties, control the expansion and spread of the dough during baking to give the finished product dimensions desired, and readily release moisture during baking to optimize production.

Cookie flour can be analyzed using a number of testing methods to characterize its performance in a formulation. Soft wheat flours typically contain 8 to 10 percent protein. These proteins have some potential to develop gluten structure. The proteins in soft wheat flour will absorb water and will influence the amount of added water needed to form a machinable dough. Wheat flour is approximately 70 to 75 percent starch. During the milling process, some of this starch is damaged due to the mechanical action of the roller mills. Damaged starch will absorb nearly four times the amount of water as undamaged starch, so this is a significant parameter to measure and will impact development of the desired dough characteristics. The large number of cells in the starch/protein matrix include a thin cell wall made up of pentosans (hemicellulose). The pentosans component makes up approximately 2 to 3 percent of the flour weight, but can absorb as much as 10 times their weight in water.

These three factors—gluten proteins, damaged starch, and pentosans—combine to determine the amount of added water needed for good cookie dough character and desired finished product attributes. Solvent retention capacity (SRC) testing can profile all of these attributes. Flour samples are mixed with one of four “solvents”: water, 50 percent sucrose, 5 percent lactic acid, or 5 percent sodium carbonate. After processing, the amount of solvent retained by the flour sample is measured. Each solvent is indicative of the influence of the flour components described above. The sucrose solution is indicative of the absorption capacity of the pentosans present. Lactic acid retention is influenced by one of the gluten-forming proteins (glutenins) present in the flour, both by quantity and quality. The sodium carbonate solvent result is influenced by the amount of damaged starch present in the flour. All three of these factors are reflected in, and will influence, the amount of water solvent retained through the test method.

In the full scope of flour testing methodology, SRC is a fairly new test utilized by the cookie industry. It was initially developed by scientists at the USDA soft wheat quality lab and principal scientists at Nabisco (Mondelez). It can give significant insight into the subtle performance differences of flour during crop year changes. It also can be used to highlight potential differences between flour suppliers, supply location, and—in some instances—lot to lot performance. SRC pairs well with a cookie bake test, such as AACC Method 10-53, to help characterize the flour in a laboratory setting while providing insight on behavior at a full production scale.

When applying any flour test results to performance in a bakery, it’s important to understand the basics of how flour impacts cookie quality—water absorption, structure development and setting, and finished product attributes. Choosing and understanding the proper tests can help avoid negative quality issues in production and the associated material waste and potential downtime.