Due to the popularity of high‐protein bars, many new formulations are being generated to meet consumer preferences. New formulations may have different mechanical behaviors that can negatively impact processing ability, which makes determining the effect of ingredients on processing ability important. Thus, the objective of this study was to determine the effects of major ingredients in high‐protein bars on their rheological and tribological behaviors. Two response surface designs of model high‐protein bars comprising whey protein isolate (WPI), high‐fructose corn syrup (HFCS), and either canola oil (first design) or vegetable shortening (second design) were evaluated. Rheological tests, including adhesion, strain and frequency sweeps, large amplitude oscillatory shear, and wear testing, were conducted to determine the impact of individual ingredients on high‐protein bar mechanical behaviors. Oil‐based formulations had greater adhesion at higher levels of HFCS, while shortening‐based formulations were affected by WPI more than HFCS, resulting in lower overall adhesive maximum forces. Formulas with higher levels of WPI had lower phase angles and greater extent of nonlinear viscoelastic and strain‐hardening behaviors, while formulas with higher lipid and HFCS levels had higher phase angles. Overall, ingredient ratios had a notable impact on both oil‐ and shortening‐based high‐protein bar rheological and wear behaviors, suggesting that rheological and tribological testing could be useful for indicating processing ability of high‐protein bars. The information gained in this study can be used by food manufacturers that produce cold‐extruded or laminated food products. The results can help predict the ability of various formulations to be successfully processed, decreasing product development, and reformulation time and expense.

High‐protein bars are popular snack items that can have significant processing issues like sticking, clogging, and cold flow. These issues are primarily problematic during formulation development because current predictive testing is reliant on highly empirical bench tests or pilot plant testing, which is expensive and time‐consuming. Wear testing, which has been used in the medical field to evaluate the lifetime of soft materials used in joint replacements, may have promise in evaluating food processing ability. Wear and rheological testing were used to better understand high‐protein bar processing ability. The objective of this study was to determine bench‐level instrumental tests that would be able to predict processing ability for a given formulation. Two response surface designs were used for formulations of model bar systems comprising whey protein isolate (WPI), high fructose corn syrup (HFCS), and either canola oil or vegetable shortening. Ingredient formulation affected processing ability, wear behaviors, and rheological behaviors. Formulations with high ratios of WPI to HFCS and either shortening or oil exhibited good processing ability, lower wear rates, and increased elastic‐type behavior, indicating that processing ability is related to formulation. The results of this study indicated that material mechanical and wear behaviors were related to processing ability; both were controlled by formulation. Because it was shown to be a good indicator of high‐protein bar processing ability, wear testing of food has potential significance in benchtop testing. Practical Application Understanding of how high‐protein bar formulations impact their mechanical behaviors can help streamline their formulation development and scaling from bench to industrial production. Processing ability may be predicted with a quick wear test, providing a rapid testing method that requires little sample for evaluating bar formulations.

With the growth of the high‐protein bar market, predictive models for good processing ability would assist bar manufactures in development of bar formulations. The objective of this study was to create predictive models for high‐protein bar model formulations based on empirical testing and instrumental data. The predictive models generated had relatively high accuracy rates (> 85%). However, three misclassifications were seen for oil‐ and shortening‐based formulations, leaving gray areas of predictive values and indicating that data from additional formulations is needed to improve model accuracy. Model validation testing showed that cold flow was best for predicting processing ability of oil‐based formulations. For shortening‐based formulations, wear rate and G3′/G1′ at 4% strain and 10 rad/s best predicted processing ability. These models provide valuable information about ingredient ranges and instrumental tests that could be used to assist in the determination of processing ability. Practical applications The results of this study may be used by high‐protein bar manufacturers and manufacturers of similar products to determine the processing ability of novel formulations with a rapid test that requires only a small amount of sample. There are no similar methods currently used except for manipulating samples by hand. Judging processing ability from hand manipulation requires significant experience working with the product, whereas the tests used to create data for the models outlined in this article can be performed by inexperienced personnel to rapidly screen novel formulations.