Design and test of a cost-effective hyperspectral camera for food quality assessment

Hyperspectral imaging (HSI) is a valuable tool for assessing the quality of agrifood products due to its ability to obtain simultaneously spatial and spectral information, that can be modelled to predict physical and chemical features. Although HSI technique can gather a lot of data, a single device is sometimes insufficient to cover each important points of the supply chain that companies need to monitor. Thus, distributed systems are necessary, but most companies cannot afford the associated costs. Hence research is moving towards the development of hyperspectral solutions that are cost-effective for distributed stand-alone applications. As a result, an HSI camera prototype was developed based on previous research by Salazar and Mendez (2020). The system can get spectral information between 400 and 1000 nm within a 41x41 pixel spatial surface. The prototype has been assembled using low-cost optical and electronic components (i.e., lenses, transmissive holographic diffraction gratings, a Raspberry Pi 3b+, and a Raspberry Pi NoIr camera) and elements 3D printed using a photopolymer resin (e.g., the external case, holders).