2015 NirSensors

According to a study by the FAO, one third of all agricultural goods produced worldwide (1.3 billion tons per year) are currently spoiled, which corresponds to a total economic loss of 750 billion USD [1]. Losses of up to 50% are particularly high in the case of fruit and vegetables. At the same time, more than 800 million people worldwide suffer from malnutrition [1].

Drying is probably the most important and at the same time the most energy-intensive method of food preservation. It alone, across all sectors, is responsible for 15-25% of global energy consumption.  Process efficiency averages 35-45% but may well be as low as 10% [2]. In other words, up to 10 times more energy is used for drying than theoretically needed. One of the biggest problems in this context is the almost always lack of knowledge of the current water content of a product, which usually leads to over-drying. This, in turn, leads to unnecessary deterioration of quality, an increase in energy demand, and a reduction in sales weight, which can represent a significant economic loss.

In conventional drying applications, process settings, technologies and control systems are based on empirical values, some of which are several decades old and have never been critically scrutinized, neither in terms of product quality, nor in terms of the wider implications in terms of resource efficiency and sustainability. The quality of the product is usually ensured by pre-sorting or purchasing the highest quality raw materials, rather than aiming to optimize the process itself.

While in other sectors, most notably the chemical industry as a direct result of the first oil crisis, increasing price pressure and stricter legislation made it necessary to significantly increase efficiency in production at the system level decades ago, this hardly played a role in the food and beverage industry until recently. It is only due to the drastic rise in food, water and energy prices, increasing disposal costs as well as stricter regulations on the one hand and the increased expectations of consumers regarding sustainability and product characteristics on the other hand, that resource efficiency, together with the guarantee of the required product quality, has increasingly come into focus.

To effectively and sustainably increase resource and production efficiency,  processing operations must be subjected to consideration and optimization at the system level, for which an interdisciplinary approach is essential. A multitude of information from different disciplines (food chemistry, biology, physics, systems process engineering, process intensification, process integration, mechatronics, automation technology, etc.) must be collected, linked and implemented in appropriate processes, technologies, models and software tools as well as control and regulation strategies. In this context, it is extremely important to move away from the classical approach of independent consideration and optimization of basic operations and other elements of the overall process and to consciously investigate interactions and include them in system optimization. For this purpose, however, it is of central importance to understand the individual elements of the system in detail and to be able to represent them in models in order to be able to draw conclusions later on about the effects of the optimization of a part of the system on the efficiency of the overall system. 

The project described below, which is proposed in connection with the establishment of a junior research group, forms a central aspect of the research question described above and the cornerstone for further work on the overall concept. The proposed project will contribute to both product quality assurance and more efficient use of resources and reduction of processing time (smaller equipment) in the production of dried food products by developing hardware and software to optimize drying processes. The development of an adaptive control system is proposed,  which incorporates both raw material properties and the changes the product undergoes during processing to (a) stop the process exactly when the target water content is reached, thereby reducing energy demand, drying time, and quality losses; (b) utilize raw material that is currently rejected; (c) produce higher quality products than is currently possible; (d) respond more quickly to changes in consumer expectations regarding product quality.

Globally, the results of this project have the potential to contribute to increased food safety in the following ways: (a) the hardware and software developed can be made available to SMEs  as a low cost alternative to previously very expensive NIR sensors for water content determination. This offers the potential to significantly reduce drying time and energy requirements and increase profits through better quality and higher sales weight; (b) Valuable information can be obtained on correlations between optical, chemical, mechanical and sensory properties as a basis for further research; (c) The development of a control system based on the evaluation and incorporation of image data, which has the potential to reduce losses by utilizing previously rejected raw materials.

Specifically, this approach is expected to increase raw material efficiency by at least 20% and throughput by at least  30% , reduce energy consumption by at least 30% through optimal control, and simultaneously produce higher quality products.

References

[1] FAO (2013). The state of food insecurity in the world - The multiple dimensions of food security.

[2] Mujumdar, A.S. (2007) Handbook of Industrial Drying, CRC/Taylor & Francis.