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');--grs:50px;--gtaos:105px;--gtaosi:-105px;--gtaof:210px;--gbes:calc(100% + 105px);--gbef:calc(100% + 210px);--gbet:translateX(-105px);--gbeti:translateX(105px);--vgc:repeat(12, 1fr);--gc1:repeat(12, 1fr);--gc2:repeat(6, 1fr);--gc3:repeat(4, 1fr);--gc3h:1/4;--gc4:repeat(3, 1fr);--gcm:8.333%;--gac:1fr;--gcw50:50%;--gc2tp:0 calc(var(--grs) * 2) 0 0;--gc2sw:var(--gbes);--gc2slpl:0 0 0 105px;--gc2srpf:0 105px 0 0;--gc2sof:1;--gc2sol:2;--gc50:4/span 6;--gc48a:1/5;--gc48b:5/-1;--gc84a:1/9;--gc84b:9/-1;--gc39a:1/4;--gc39b:4/-1;--gc93a:1/10;--gc93b:10/-1;--gc615a:1/7;--gc615b:8/-1;--gc516a:1/6;--gc516b:7/-1;--tppr:0;--bgp:42px;--s_cn:0;--s_ces:4px;--s_cest:4px 4px 0 0;--s_cesb:0 0 4px 4px;--s_cs:8px;--s_cm:12px;--s_cl:16px;--s_cls:16px 0 0 16px;--s_cle:0 16px 16px 0;--s_clt:16px 16px 0 0;--s_cel:28px;--s_celt:28px 28px 0 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One recent addition to her laboratory is the ability to create dynamic dewpoint isotherms and use them to save time and make predictions about new products.
In our recent conversation, we discussed how AQUALAB has partnered with Hostess – from product predictions in R&D to quality control metrics and production optimization.
Product development, especially in the food industry, comes with its own set of challenges. Most of these challenges are centered around the time it takes to take a food from formulation to final product.
Depending on the type of product, Dr. Allen says that R&D timelines can be quite tight – like during limited edition runs or when supply chain kinks cause ingredient shortages.
“My team works on 3-5 projects at time,” Allen says. “Sometimes reinvention or modification of the product really takes time. For example, if a product is totally new and we haven’t made it before, or if there are a lot of changes, the project might last maybe one or two years. But smaller projects like ... flavor or color changes, maybe 6 months or less. It really depends.”
In addition, developing new flavors or using natural coloring can change formulas enough to essentially become their own recipes. Keeping or lowering food costs by changing types of ingredients can have technical impacts like shelf life and storage stability.
And, of course, even a perfect product formulation doesn’t do any good unless it lines up with the consumer insights and marketing plan.
Dr. Allen and Hostess have overcome some of these challenges by focusing on what they call the “Three Ms of Moisture:” Mastering, Measuring and Managing.
For Dr. Allen’s research team, acquiring an AQUALAB Vapor Sorption Analyzer was a significant step towards moisture mastery.
Before using the VSA, Dr. Allen’s team created isotherm models for each product and ingredient, but every isotherm was made manually – by painstakingly collecting at least 10 data points or more from each product, graphing the points and analyzing the result to map the relationship between water activity and moisture content. With each data point taking anywhere from 3 to 30 minutes to collect, making these isotherms was a slow and tedious process.
With a VSA on the bench, her team has been able to quickly create moisture sorption isotherms, model formulation changes, and gain greater insight in less time.
“If we were to run a whole shelf life test, it would be at least two to three months, so it might take too long for each product,” Dr. Allen says. “So if we can use this technology to predict shelf life, we can know early and shorten the timeline.”
In a couple of days, the VSA automatically produces the data Dr. Allen’s team used to collect manually – and at about ten times the resolution. The team can then use that isotherm to set product specs, maximize moisture content to increase palatability and prevent microbial growth, establish critical water activity points, and evaluate packaging.
To measure moisture content, Hostess adopted the AQUALAB 3. Prior to the AQUALAB 3, Dr. Allen’s team measured moisture content with a moisture balance, but was dissatisfied with the often imprecise results.
“The problem is with flavors and heat. If you set the temperature on this kind of moisture meter, they can be volatile. So the flavor will be calculated as lost moisture,” Allen says.
Heating a sample with flavoring can cause those volatile compounds to evaporate, giving a false moisture reading. So while the actual moisture content is 20%, with flavor loss it could be calculated at 24%. This could lead to broad moisture ranges in production and batch to batch variation. “But since we changed to these isotherm models, they’re more accurate and there’s less gap.”
Because the AQUALAB 3 doesn’t heat samples, volatiles don’t evaporate and the inaccuracies were resolved. This helped Dr. Allen’s team shorten timelines and reduce moisture variation between batches.
To manage moisture during the production process, Hostess installed SKALA Delta T. Delta T is a closed-loop system that automatically adjusts production line belt speed to ensure that products are always within spec. Delta T helps Hostess reduce variation between products and batches, optimize yields, avoid rework, and achieve the perfect quality Hostess customers expect. So far, Hostess has begun implementation of SKALA Delta T on their donut production line.
“[T]his new tool might help our bakery,” Allen says. “They could reduce the moisture content and variation between foods, improving the production efficiency and quality while lowering energy consumption and waste.”
By implementing these new technologies, Dr. Allen’s product development team has been able to save time and resources to produce perfect products every time.
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