For many years, we (Bruce Tharp, Steve Young, and Bill Sipple) have contemplated, created, and applied a number of mix analytics, notably the following:
- Mix composition (% fat, % total solids)
- Relative sweetness
- Mix and finished frozen dessert densities (pounds per gallon)
- Freezing point and freezing point profiling, (amount of water frozen as ice at any temperature below the freezing point of the mix)
- Freezer Index (amount of water frozen as ice at the exit temperature from the ice cream freezer)
- Heat Shock Index (HIS; amount of water that freezes, thaws, and refreezes between two temperatures below the freezing point of the mix, aka., texture stability index (TSI)
- Firmness/Stiffness Index (amount of water frozen as ice at extrusion, serving or eating temperatures),
- Hardness Index (amount of water frozen between distribution temperature and storage temperature)
All are ways to differentiate and compare mixes, not as exact absolutes, but before actual mix making, whipping/freezing, hardening, and distribution. Experience defines what is/is not significantly different when comparing data.
In 2005, Drs. Tharp and Young added another analytic, the Water Control Index (WCI), as a way to compare the ability of any given mix to interfere with the mobility of liquid water (i.e., change the behavior of liquid water), and, thus, interfere with the rate at which ice crystals grow in the final frozen dessert. Such influence can positively influence eating quality and shelf-life of the final frozen dessert.
While vetting the WCI, Drs. Tharp and Young reported on a proposed Fat Agglomeration Index (FAI) in its reference text, Tharp & Young on Ice Cream: An Encyclopedic Guide to Ice Cream Science and Technology (2012). Bill Sipple added inputs to FAI in 2019.
The FAI is meant to be a measure of the likelihood (or not) of products to agglomerate, or “partially coalescence,” during the ice cream-making process. The FAI also studies the extent of fat (milkfat, plant-based fats/oils, and/or blends thereof) to agglomerate during whipping/freezing. It also considers adding structure, air cell strength, bite/chew, the amount of richness/creaminess, and shelf-life stability of the finished frozen dessert.
A bit more about the current status of the WCI and the FAI:
WCI (aka, water mobility control) described in detail in 2012, is relatively well established, but still adding features relative to molecular weights of various hydrocolloid stabilizers, proteins, etc., that do, in fact, interfere with the mobility of water in a variety of ways. At the time of presentation in the mid-2000s, it was known that hydrocolloid stabilizers added significant but a relatively unknown degree of water mobility management.
Since then, we have added information related to the average molecular weights of individual hydrocolloids, ignoring factors such as purity of the source of the hydrocolloid, interactions between hydrocolloids, and whether the hydrocolloid “gels” and any condition(s) causing “gelling.” As a comparative tool, WCI is showing to be directionally significant and worthy of adding to the number of mix analytics already applied.
FAI was first proposed long before 2012 and includes factors that influence fat agglomeration such as amount/type/fatty acid distribution of the fat/oil in the unfrozen portion during whipping/freezing; the efficiency of whipping/freezing in the barrel of the IC freezer; the amount/type of lipophilic proteins (e.g., micellular casein); presence of any added emulsifier(s). It also looks at the hydrophilic/lipophilic balance (HLB) of any added emulsifier(s) — the more lipophilic, the more interaction with fat/oil droplets in the mix — the more fat is exposed to allow for agglomerates to form and, thus, the more influence on the fat droplets to coalesce. Post-homogenization fat/oil droplet size (the smaller the droplet size, the more surface area available to allow agglomeration), the aging of mix and mix viscosities, with lower viscosities allowing for more fat droplet interactions during whipping/freezing,
Despite the combination of quantitative and qualitative factors, we continue to propose the calculation of a single FAI number that can be used to compare mixes in advance of actual mix making, and whipping/freezing.
If individual ingredients had a known FAI “value,” formulating mixes to achieve a targeted degree of agglomeration, or “stiffness,” could be determined. This would be very useful not only in formulation, but also in predicting mix performance in products as varied as soft serve mixes, hard pack premium ice creams, and non-dairy alternatives. Given individual ingredient FAI’s, other factors, such as % casein, % milkfat, % proteins, etc., would allow calculation of a predictive FAI for any given mix thus allowing for mix-to-mix comparisons.
Though we continue to seek a comprehensive approach to FAI, use of comparative mix analytics, including WCI, have contributed greatly to commercial successes of numerous frozen desserts of varying forms, compositions, and market positionings. It’s far more than a simple academic exercise…