Federal grant · project grant (b)
Awards Issued Prior to January 20, 2025, Were Funded Under Previous Administrations and May Not Reflect the Priorities and Policies of the Current Administration. Snacks Are Enjoyed by Both Children and Adults. However, the Growing Prevalence of Metabolic Syndrome Has Been Attributed to Physical Inactivity, Unhealthy Eating Habits, and Obesogenic Environments Such as the Availability of Calorie-dense Nutrient-poor Snacks. With Increasing Consumer Appeal for Ready-to-eat (RTE) Products Including Snacks With Nutritional, Sensorial, and Healthful Properties, Consumers Are Drawn to Plant-based Food (PBF) Products. One Strategy Is to Leverage the Increasing Interest in Plant-based Products, That Also Meet Consumer Demand for Food and Nutrition Security, Sustainability, and Healthier Options. Alternatives Like Lentil and Quinoa Have Received Relatively Little Attention as Ingredients for Food Application Due in Part to the Many Limitations in Their Nutritional Profile, Functionality, and Sensory Properties. It Is Still Unclear How They Impact Gut Microbiota and Health. Our Overarching Goal Is to Improve the Acceptability and Economic Value of Lentil and Quinoa by Designing Alternative Processing Conditions That Develop Value-added Ingredients and Products With Enhanced Nutritional, Techno-functional Bioactive, and Sensory Properties. This Project Is a Collaboration Between Pis at Delaware State University, and Alabama A&m University With Support From Researchers at Ncat, Umd, Usda-ars-errc, and Infraready Products LTD, Canada. Our Project Proposes to: (1) Determine Effect of Processing on Key Ingredients Properties; (2) Develop and Characterize Formulated Puffed Snacks; and (3) Assess Impact of Metabolites on Gut Microbiota and Ameliorating Effect on Obesity. We Will Demonstrate the Quality and Value of These Snack Products Through in Vitro, Consumer Studies, Animal Models to Validate Their Nutritional and Health Impact, Consumer Acceptability Compared to Traditional Counterparts. We Will Incorporate Immersive Machine Learning Training Simultaneously With STUDENTS' Experiential Research, That Will Improve STUDENTS' Employability, and Equip Pis With Resources to Translate Research to Commercial Innovation.
Committed
$499,993
Paid out
$129.4K
26%
Committed, not yet paid
$370.6K
74%
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