1. Ashim K. Datta Biological and Environmental Engineering
Food manufacturing: improving quality and safety by combining data-driven with mechanistic understanding
Ashim K. Datta
Biological and Environmental Engineering

2. Food Manufacturing  Improve quality  Improve safety
 Novel product/process
 Reduce waste/ Sustainability
 Reduce cost
Food manufacturing encompasses procurement, processing, distribution, storage and consumption.
Primary goals are to improve quality and safety, develop new products while reducing waste and cost.

3. Complex systems approach combining data-driven with mechanistic understanding
Composition and Structure
Raw material properties
Processed material properties
Changes during packaging and distribution
Energy use databases
Waste generated databases
Food con-sumption databases
Mechanistic
Knowledge-base
Of property-
composition
Mechanistic process
models
Important stages of food manufacturing that can be integrated in a complex systems approach;
Data and knowledge bases (circles) are at various stages of availability.
The current USDA composition database has 200,000+ foods
Physical properties are many and the relationships between the properties and composition/structure are also complex and numerous.
Processing methods are many that transforms the food material in a very complex manner for which significant mechanistic understanding exists.
Because of many processing possibilities, processed material properties of importance to the consumer, i.e., quality (texture, color, sensory) and safety (microbiological and chemical) can have very large possibilities.
My career has been to try to build mechanistic/engineering models that describe the changes that a food undergoes. It is a system level approach that can bring in a lot of the details but it is at the individual food product scale.
Energy use and waste generated are also of critical interests that depend on the processing conditions—large databases already exist on these
Using complex systems approaches that combine data-driven with mechanistic models and couple various scales, sensitivity of the ingredients and processing methods on food quality, energy use, environmental footprint, and microbiological and chemical risk on the population can be seen at the individual industry level or at the population level.
While I work at this scale, I want to build in a way they can be linked into the larger systems level approach that would help decision making in industry and by public planners toward risk management, efficiency and sustainability.
Food composition databases
Thermo-physical property databases
Food safety databases
Food risk databases
Life cycle analysis databases

4. usda nifa funded project on “computer-aided food manufacturing for everyone”
Properties Knowledge Base for most foods
Thermophysical
Electromagnetic
Colloidal, Texture
High pressure
Fruits/veg storage
Process Apps for complete process sim of most used processes
Drying
Frying
Baking
Sterilization
Shelf-life
Visualization lib for most complex processes
Microwave drying
High pressure processing
UV processing
I am happy to say a decent size grant has been funded where a team of us from several universities will be working with a number of food industries in building three tools—
1) a property predictor that provides the properties needed for a particular type of processing by doing all the calculations in the background.
2) Process simulations apps that provide what-if scenarios in product and process development
3) Scientific visualization of complex food processes