Hyperspectral imaging has long been recognized for its ability to evaluate the freshness and consistency of food products and highlight their impurities. And a recent study in Catalonia, Spain, applied this vision technique to a local staple of southern Europe — the hazelnut. Hyperspectral imaging is a technique that combines imaging and spectroscopy to obtain the spectrum for each pixel in an image and reveal far more bands than those that can be captured within the visible range. This capability allows for the unique spectral characteristics of the components within an image. The research team gathered chemical and spatial information and examined the oxidation of hazelnuts, which ultimately leads to rancidity. Batches are typically stored in various ways after they are dried: in cool, dry air; nitrogen; or vacuum packaging. While many common evaluation methods are inherently destructive, this study — published in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy — used a near-infrared line-mapping hyperspectral camera with 320 sensors and a spatial resolution of ~300 µm to scan the product in its packaging. Then, principal component analysis was applied to the images to remove extraneous data points. Jokin Ezenarro Garate, a postdoctoral researcher at Universitat Rovira i Virgili in Spain and one of the principal authors of the study, explained that vacuum storage was determined to be the most effective storage method to reduce oxidation. According to Verified Market Reports, the market size of hyperspectral imaging in food and agriculture is valued at $12.3 billion and is projected to grow at a compound annual growth rate of 9.3%, reaching $25.7 billion by 2033. Two of the features in this edition focus on hyperspectral imaging. Steve Kinney of Smart Vision Lights writes here that traditional multispectral lighting can be adapted through analytical methods to reveal hyperspectral data. And here, Trond Løke from HySpex by NEO discusses how sensors can help autonomous drones gather hyperspectral data that reveals mineral deposits or forest diversity. The value of hyperspectral imaging can be found in the natural environment and in the monitoring of important manufacturing processes — from food production to semiconductor chip fabrication. Enjoy the issue!