Curbing food waste with quality control

Technology as an effective solution to food waste

Food waste occurs at all levels within the food chain, including food processing and manufacturing companies. Some of the causes that contribute to waste include: overproduction, strict quality standards and inefficient processes. Technology plays a crucial role in addressing these causes. Thus, you can use technology for several purposes:

Data analytics and advanced modeling can help accurately predict demand, thus preventing overproduction.

Improved packaging and preservation technologies extend the shelf life of food, while advanced logistics and tracking provide better traceability and prevent spoilage.

Producers can also utilize by-products and residual streams by applying technologies such as fermentation and converting by-products into valuable ingredients.

Start with control

To reduce food waste, having control over the process is essential. This control begins with gaining insight into current performance and identifying potential bottlenecks. For this, collecting and making the best use of data is crucial. Measuring and analyzing valuable data not only provides solutions to combat food waste, but also provides other benefits, such as:

improving machine performance

prevention of errors

reducing costs and energy consumption

An essential approach to reducing food waste is to avoid "bad" quality food. Unnecessary waste often results from inefficient processes and improperly adjusted machinery. With constant quality control, we can prevent poorly produced food from going to waste.

Vision AI contributes to continuous quality control by recognizing, categorizing, and sorting products based on specific visual characteristics, such as apples with rotten spots. The system mimics specific human tasks. An essential feature of an AI-integrated system is that it generates data to improve itself. This enables it to recognize situations and prevent problems, thereby also reducing food waste.

With efficient steps such as production process mapping, real-time monitoring and concrete improvement suggestions, food producers can gain control over waste and deliver consistent quality.

In practice

At QING, we continue to develop our technologies and strategies to reduce food waste. We have been working on a variety of projects that apply technology to reduce it. Some examples include:

An automated inline measurement system that serves as a replacement for destructive sample inspection, eliminating food waste.

Smart algorithms are deployed for more accurate sorting of products, resulting in maximum value and minimum waste per product.

Automated cutting processes for food products make you completely independent of operator quality, which leads to less waste.

AI-vision is used for objective and continuous quality inspection of unique food products. This minimizes waste through timely defect detection and prevents subsequent rejection of entire batches.

In the video below, we demonstrate the power of Vision AI for quality control of baguettes. In the bakery and confectionery industry, traditional vision systems are used to check the length, width and height of a product. However, when it comes to the quality of a product, such as a baguette, there is much more that needs to be checked. A system without Vision AI is then not enough. Vision AI can also check the following aspects: Shape accuracy, deviations and recognition of cracks.

Together against food waste

The Netherlands is committed to Sustainable Development Goal (SDG) 12.3 of the US to halve food waste by 2030 compared to 2015. That means we in the Netherlands need to start wasting 1 billion kilograms of food per year less. That's the same amount of food for a year for the entire province of North Holland.

The Foundation Together Against Food Waste is committed to achieving this objective. They do not do this alone, but in cooperation with many other stakeholders. QING also contributes to this and is a proud stakeholder of this initiative.

By making the most of technologies and data, we can collectively fight food waste and have a positive impact on the environment, economy and food security.

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