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Understanding and measuring the impact of process inputs on "degree-of-cook" in starch-based systems

Bhimalingeswarappa Geera, University of Nebraska - Lincoln

Abstract

Starch-based food processing requires the application of varying amounts of thermal energy and shear in the presence of moisture. "Degree-of-cook" is a generic term given to changes in starch's native state resulting from process inputs. Degree-of-cook is often considered a quality parameter, because of its influence on product quality. However, there is a lack of degree-of-cook methods that are sensitive, reliable, easy to interpret, and applicable to a broad range of products and/or processes. The objectives of this work were to (1) use starch analysis methods to provide a better understanding of the effects of process variables on starch changes, and (2) evaluate the appropriateness of these methods to quantify starch native state changes, in response to process variables in pure starch and whole ground corn systems cooked in high moisture (>70%) and low-to-medium (20-40%) moisture environments.^ Degree-of-cook methods, modeled for dilute pure starch systems, were primarily influenced by cook temperature and sonication energy, while cook time was shown to have a nominal effect. In dilute whole ground corn systems, however, cook time was shown to influence starch structural changes. The effect of sonication energy on changes in starch structure and functionality was dependent on gelatinization state in both pure starch and whole ground corn systems.^ The effect of varying barrel temperature and screw speed inputs on changes to starch structure and functionality, in extrusion systems processed at low-to-medium moisture levels, was dependent on moisture content. Process inputs at medium moisture contents appeared to be too gentle to cause significant molecular fragmentation of starch polymers, even at the highest barrel temperature and screw speed.^ Water absorption and water solubility indices, rapid visco-analysis, and starch susceptibility to amyloglucosidase methods were able to detect differences in starch structure and functionality across a broad range of process variables and moisture contents. These methods had reasonable predictive R2 values, and were found to be applicable for both pure (corn starch) and starch-based ingredient (whole ground corn) systems. These methods have potential application as diagnostic tools to monitor and maintain product quality, to assist in process scale-up, and to expedite the reverse-engineering of competitor's products.^

Subject Area

Agriculture, Food Science and Technology|Engineering, Agricultural

Recommended Citation

Geera, Bhimalingeswarappa, "Understanding and measuring the impact of process inputs on "degree-of-cook" in starch-based systems" (2009). ETD collection for University of Nebraska - Lincoln. AAI3378800.
http://digitalcommons.unl.edu/dissertations/AAI3378800

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