Award Abstract # 2235992
NSF Convergence Accelerator Track J: Dairy Protein Product Research and Innovation Hub

NSF Org: ITE
Innovation and Technology Ecosystems
Recipient: BOISE STATE UNIVERSITY
Initial Amendment Date: December 9, 2022
Latest Amendment Date: December 9, 2022
Award Number: 2235992
Award Instrument: Standard Grant
Program Manager: Michael Reksulak
mreksula@nsf.gov
 (703)292-8326
ITE
 Innovation and Technology Ecosystems
TIP
 Directorate for Technology, Innovation, and Partnerships
Start Date: December 15, 2022
End Date: November 30, 2024 (Estimated)
Total Intended Award Amount: $750,000.00
Total Awarded Amount to Date: $750,000.00
Funds Obligated to Date: FY 2023 = $750,000.00
History of Investigator:
  • Owen McDougal (Principal Investigator)
    owenmcdougal@boisestate.edu
  • Kumar Mallikarjunan (Co-Principal Investigator)
  • Gulhan Unlu (Co-Principal Investigator)
  • Tim Andersen (Co-Principal Investigator)
  • Prateek Sharma (Co-Principal Investigator)
Recipient Sponsored Research Office: Boise State University
1910 UNIVERSITY DR
BOISE
ID  US  83725-0001
(208)426-1574
Sponsor Congressional District: 02
Primary Place of Performance: Boise State University
1910 UNIVERSITY DR
BOISE
ID  US  83725-0001
Primary Place of Performance
Congressional District:
02
Unique Entity Identifier (UEI): HYWTVM5HNFM3
Parent UEI: HYWTVM5HNFM3
NSF Program(s): Convergence Accelerator Resrch
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s): 131Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.084

ABSTRACT

The world population is expected to reach 10 billion by 2050. A critical challenge facing humanity is growing demand for nutrient-dense foods with longer shelf-life and environmental resilience to reach regions of the world most impacted by extreme weather conditions, geopolitical turmoil, and mass migration. Milk is nutrient-dense, containing vitamins and minerals, fat, and protein content used to produce a range of products that are widely consumed across the world by people of all ages, from infants to seniors. However, current dairy product manufacturing methods are rate limited, and use outdated processing practices that suffer from critical efficiency shortcomings in monitoring protein integrity, separation science, and spray drying of protein powders. This project will address the knowledge gap currently preventing adoption of state-of-the-art technological solutions by creating a roadmap for the implementation of intelligent sensing and advanced manufacturing technologies aimed at efficient production of high-value products for consumers that address nutrition security at a domestic and global level.

The project team's use-inspired approach targets farmers and rural communities, dairy processors, and consumers of food products containing dairy protein powder ingredients. Dairy is the single largest component of the Idaho agricultural economy, being driven predominantly by farmers and processors in rural counties, where underserved minority populations are increasing at a rapid rate in a state that is among the fastest growing in the United States. This project will focus on educational programs and workforce development for these underserved minority populations through land grant university extension outreach programs, partnership with dairy marketing and communication organizations (Dairy West), and organizations dedicated to the training and workforce development pipeline for students to careers in dairy processing (BUILD Dairy). University programs including the Vertically Integrated Project curriculum and BUILD Dairy-sponsored projects, offer students training essential for their employment in high-paying, benefit-eligible positions in rural communities throughout Idaho and the United States.

The goal of this Convergence Accelerator is to modernize the dairy processing industry by fusing artificial intelligence, chemometric sensing, and advanced manufacturing tools to achieve transformative efficiency, quality, and quantity gains in the production of shelf-stable, nutrient-dense, protein powder products. To achieve this convergence goal, a team of academic researchers and industry stakeholders with exceptional credentials, experience, and knowledge in food and dairy chemistry, computer science/artificial intelligence, microbiology, rheology, food process engineering, and food process technology has been assembled.

The specific deliverables are: (1) Develop artificial intelligence-based chemometric solutions to automate the use of near-infrared spectroscopy for the real-time analysis of proteins in milk during processing to improve the quality of dairy products and reduce waste; (2) Implement and optimize operating conditions for advanced manufacturing pulsed electric field and extruder equipment into dairy facilities to improve processing efficiency, product quality, reduce waste, conserve energy, and expand capacity; and (3) Converge sciences, engineering, computer science, food science, nutrition, dairy farming, supply chain management, and workforce training to develop innovative protein products for early childhood development, adolescent and adult nutrition, and senior care that are shelf-stable, nutrient-dense, and impactful to a global market.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

Note:  When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

Can, Handan and Chanumolu, Sree K. and Nielsen, Barbara D. and Alvarez, Sophie and Naldrett, Michael J. and Ünlü, Gülhan and Otu, Hasan H. "Integration of Meta-Multi-Omics Data Using Probabilistic Graphs and External Knowledge" Cells , v.12 , 2023 https://doi.org/10.3390/cells12151998 Citation Details
Palmer, Katelynn and Parhi, Ashutos and Shetty, Abhishek and Sunkesula, Venkateswarlu and Sharma, Prateek "Development of methodology for assessing flowability of milk protein powders using shear failure testing device" Journal of Food Engineering , v.348 , 2023 https://doi.org/10.1016/j.jfoodeng.2023.111450 Citation Details

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Dairy NutriSols brings together a team of experts across disciplines to modernize food processing. Our goal is to adapt modern data analytics and emerging technologies to our existing food system to improve efficiencies, reduce costs, and produce higher-quality food products. Large-scale adoption promises a world where technology application improves product quality, reduces waste, and yields a healthier global population. 

 

Dairy NutriSols takes a use-inspired approach. This means that academic experts work directly with food industry partners to match possible solutions with actual challenges. This method increases rates of adoption and allows the team to create affordable, practical solutions that can then be scaled broadly across the food manufacturing sector. Since the inception of this NSF Convergence Accelerator (CA) project, the Dairy NutriSols convergence science team has refined its objectives and deliverables to best meet the needs of the industry with sustainable and applicable solutions. The refined objectives can be categorized as follows:

  1. Technology Application - Instead of developing new technologies, Dairy NutriSols aims to apply proven technologies in novel ways. 

    1. AI/Big Data: Harnessing the power of artificial intelligence models, the team is using chemometrics, the science of extracting information from chemical systems, to improve dairy product quality and reduce waste by monitoring protein quality in real-time. 

    2. Resource Optimization: Pulse electric field is a non-thermal food processing treatment broadly used for pathogen reduction and extraction of bioactives. Applying it at various stages of food production holds promise for improving food manufacturing efficiency which leads to cost savings, reduced energy use, and improved functionality. 

    3. Food Transformation: Extrusion technology uses heat, pressure, and constraints to create materials of a specific shape/texture. While extrusion is broadly used in food manufacturing (think cheese puffs and cereal), Dairy NutriSols is using extrusion to upcycle by-products into value-added novel ingredients and testing nutrient values in extruded products to reduce waste and improve quality. 

  2. Future-Proofing: Dairy NutriSols aims to go beyond developing science for the sake of science, to the application of scientific knowledge for industry adoption and societal benefit - contributing to a food-secure future. 

    1. Sustainability: Finding sustainable solutions to food production at scale is top of mind for manufacturers. They are interested in doing more with less while reducing waste and emissions. Finding ways to up-cycle the byproducts of food manufacturing, much like the dairy industry did with cheese whey 20 years ago, offers great potential to create new products and eliminate waste. 

    2. Workforce Development: Solving for a more innovative and sustainable food system, requires people to be excited about careers in the food industry. Dairy NutriSols partners with industry leaders to develop interest among young people and offer training for new and existing employees.


For each of the objectives described above, Dairy NutriSols is working with an industry partner to fine-tune solutions for adoption. Once optimized, the team will work toward product commercialization and broader, scalable adoption across dairy and food manufacturing. Applying data analytics and emerging technologies can modernize food processing, enabling the dairy industry to achieve critical sustainability goals. Increased efficiency will result in energy and cost savings, foster product innovation, and significantly enhance sustainability by reducing waste and improving the industry’s environmental footprint. This efficiency also benefits society by making nutritious products more accessible and affordable, especially for underserved communities and those facing nutrition insecurity.

 

 


Last Modified: 03/17/2025
Modified by: Owen McDougal

Please report errors in award information by writing to: awardsearch@nsf.gov.

Print this page

Back to Top of page