The quality of biological raw materials varies widely because of seasonality, climate, differences between varieties and so on. When these raw materials are used in the food industry, this can often lead to the quality of the finished product also becoming unstable. Customers have clear expectations about a product's taste and consistency, and it is important for the industry to meet these expectations. Controlling production by means of statistics and data modelling helps to stabilise product quality.
Involved in many areas of research
Data modelling is used to perform scientific research throughout the entire process, from planning, through execution and statistical analysis to presentation. It is Nofima's goal to be at the forefront of the development of statistical and mathematical methods, so that we can exploit the potential created by new and more powerful measurement techniques.
We have a long tradition of data modelling and statistics here at Nofima and they have been in a state of continual development. Ever since the 1970s, Nofima has been combining chemical ideas with statistical and mathematical calculation techniques, which have contributed to establishing companies and creating software programmes. This is a field that provides the necessary research basis upon which other areas of research depend, even though this may not occur to the customer.
Because of the increased use of instrumentation and data tools there has been a huge increase in the volume of measured data. So it is necessary to find methods which can distil the essence out of all these numbers, enabling us to concentrate on what is important. Multivariate data analyses are methods for converting huge quantities of data from instruments, experiments and processes into information that can be interpreted. By using designed research, we are able to get the greatest possible amount of information out of a limited number of tests. This is quick, efficient and cost saving.
The methods thus developed can be used for:
- better utilisation of raw materials
- reducing wastage
- reducing variations in the production process
- more environmentally friendly production
- efficient product development of, for example, food for better health