Source: CORNELL UNIVERSITY submitted to
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
Funding Source
Reporting Frequency
Accession No.
Grant No.
Project No.
Proposal No.
Multistate No.
Program Code
Project Start Date
May 1, 2018
Project End Date
Apr 30, 2022
Grant Year
Project Director
Datta, A.
Recipient Organization
Performing Department
Bio and Envir Engineering
Non Technical Summary
Achieving improved food quality and safety often involves significant trial-and-error. Food manufacturing, like other manufacturing, strives to reduce this product/process development expense while reducing time-to market, and achieving high-quality innovation. We propose a three-pronged approach to enable these goals, whereby we develop three food-specific, user-friendly, and effective computing technologies that complement each other. The overall goal of these tools are to perform "what if" scenarios more efficiently than trial-and-error. 1) The first tool, an extensive knowledge base, will provide access to the widest possible range of food properties to anyone, at any time, and anywhere through a web-based interface. Available data will be made readily accessible and supplemented with prediction capabilities when data are not available; 2) The second tool will be the building of high level computing apps that can quickly simulate food processes, such as drying or frying, helping to guide food manufacturers toward the best strategy for quality, but get there faster; 3) The third tool will build a visualization library for the most complex food processes that will assist food manufacturers gain insight and thus help provide pathways to improving them. These tools should be useful for large, medium and small industries, making food manufacturing more agile, efficient and competitive. In education, the tools will enable students to discover new relationships between food materials and properties and provide much greater insight into complex processes.
Animal Health Component
Research Effort Categories

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
Knowledge Area
402 - Engineering Systems and Equipment;

Subject Of Investigation
5010 - Food;

Field Of Science
2020 - Engineering;
Goals / Objectives
Our long-term goal is to increase the efficiency of new food product/process development by building a comprehensive Knowledge Base of properties, generic process-simulation apps, and a process-visualization database that can be used by everyone. We will also fully integrate the tools in formal classroom education and industrial extension for capacity-building.Objectives in reaching this goal are:Develop a Knowledge Base of properties with a web interface. We will develop a crowd-sourced, interactive, web-based tool for food properties data and prediction models by building prediction frameworks for a number of properties.Develop simulation apps for the most widely used food processes. Building on our previously developed process/quality modeling frameworks, we will develop multiple general-purpose easy-to-use apps, each covering a group of processes, and build a crowdsourced container website to make them available to others. Develop instructional modules around these apps to introduce them to industry and in formal education, and collect assessment data to improve the introduction and functionality of the apps.Develop visualizations of highly complex food processes. For a set of complex processes for which direct app development is currently suboptimal, we will develop realistic visualizations and build a crowdsourced container website to make the visualizations available to others.
Project Methods
Build the structure for a queryable database. Build a web-based interface in which users will be able to search for the property they need for a given food material. Populate the database with research properties data and their prediction equations to distill the most accurate and reliable data for initial inclusion. The web interface would also provide appropriate means for crowdsourcing additional data from other researchers as well as evaluating the data.Developing the simulation apps will involve 1) working with industry to identify processes that will have the greatest impact and controls inside the processes and foods that are most relevant to them, 2) building the simulations, 3) building the apps from the simulations, and 4) deploying the apps on a server to be used by industry. With industry input, we will focus initially on common processes such as drying, frying, baking, and sterilization.Visualizations are intended for really complex processes outside the realm of app use due to computational challenges (numerical, CPU time, memory issues). The visualization library will also include videos from many imaging applications and other experimental work. Initially, to demonstrate the possibilities, we will do visualizations of the most complex of the processes we have already simulated, like microwave drying and puffing--complexities come from multiple physics (electromagnetics/transport/solid mechanics), their coupling, strong changes in properties, and large deformation.