2015 NirSensors

According to a study by the FAO, a third of all agricultural goods produced worldwide (1.3 billion tons per year) currently spoil, which corresponds to a total economic loss of USD 750 billion [1]. The losses are particularly high for fruit and vegetables, at up to 50%. 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 most energy-intensive method of food preservation. It alone is responsible for 15-25% of global energy consumption across all sectors, while process efficiency averages 35-45% but can be as low as 10% [2]. In other words, up to 10 times more energy is used for drying than would theoretically be necessary. One of the biggest problems in this context is the almost constant lack of knowledge of the current water content of a product, which usually leads to overdrying. This in turn leads to an unnecessary deterioration in quality, an increase in energy requirements and a reduction in sales weight, which can represent a significant economic loss.

In conventional drying applications, the process settings, technologies and control systems are based on empirical values, some of which are several decades old and have never been critically scrutinized, either in terms of product quality or the wider implications in terms of resource efficiency and sustainability. The quality of the product is usually ensured by pre-sorting or purchasing raw materials of the highest quality instead of striving to optimize the process itself.

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

In order to effectively and sustainably increase resource and production efficiency, manufacturing processes must be examined and optimized at system level, which requires an interdisciplinary approach. A large amount 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. Here it is extremely important to move away from the classic approach of independent consideration and optimization of basic operations and other elements of the overall process and to consciously examine interactions and include them in system optimization. For this, however, it is of central importance to understand the individual elements of the system in detail and to be able to depict them in models in order to be able to draw conclusions 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 being applied for 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. By developing hardware and software to optimize drying processes, the proposed project will contribute to ensuring product quality as well as to more efficient use of resources and shorter processing times (smaller systems) in the production of dried foods. The development of an adaptive control system is proposed that takes into account both the raw material properties and the changes that the product undergoes during processing in order to (a) stop the process exactly when the target water content is reached, thereby reducing energy consumption, drying time and quality losses; (b) utilize raw material that is currently rejected; (c) produce products of higher quality 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 increasing 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 to increase profits through better quality and higher sales weight; (b) valuable information can be gained 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 integration of image data and thus has the potential to reduce losses by using 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 requirements by at least 30% through optimal control and at the same time 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