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Nouvelles sur l’optique, la lumière,

la technologie d’analyse optique et plus

Branch detection in green beans using reflection spectroscopy

In this post we present an application case of spectroscopy in the fruits and vegetables industry. The combination of reflectance spectroscopy measurements in the visible and near infrared (NIR) spectrum and an artificial neural network is employed to distinguish between branches (foreign bodies, a relevant problem in the agrifood sector) and green beans for two different types of beans: round (Phaseolus vulgaris) and flat (Phaseolus coccineus). Good results are achieved, especially in the visible spectrum, demonstrating the potential of spectroscopy.

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Of light and plants

One of the first biology lessons we are taught in school is that plants need sunlight to perform photosynthesis to “feed” themselves and live. Nevertheless, the relationship between plants and light is more complex. In this post we will describe how different wavelengths, from ultraviolet to far red, are employed to control the growth or the flowering of plants.

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NIR spectroscopy and Machine Learning

Near infrared spectroscopy (NIR) is employed in the agrifood industry to recover information about the chemical composition and quality parameters of different products in a non-invasive, fast and accurate way. However, the relationships between the spectral measurements and the quality parameters are not trivial, and different machine learning methods are employed for modeling them. In this post, an overview of the commonly employed calibration methods based on machine learning will be provided.

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Scientific cameras for spectroscopy

With the increasing importance of hyperspectral and multispectral imaging, the use of cameras in spectroscopic applications has also grown. In this post we will describe the process by which a camera generates an image after being exposed to a light source as well as the main existing types of cameras (silicon-based CCDs, CMOS sensors and InGaAs sensors), including their characteristics, advantages and disadvantages.

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LiDAR: working principle and main applications

LiDAR (light detection and ranging) is a technology that appeared in the 1960s, shortly after the invention of the laser. The main advantages of LiDAR is that it can provide precise position over large areas and that it is fast, collecting information with a speed and a degree of detail that it would not be possible otherwise. In this post we will explain its working principle, the main types of LiDARs and the most important applications.

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NIR spectroscopy applied to meat

NIR spectroscopy applied to meat

Meat and meat products are an important source of protein, vitamins and minerals in the human diet. Therefore, quality control is one of the essential stages in their processing. Spectroscopy has emerged as an alternative to conventional quality study methods thanks to its speed, simplicity and ability to detect internal attributes. This post will address the applications of spectroscopy for the study of quality parameters in meat.

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NIR spectroscopy applied to fruits and vegetables

Near infrared spectroscopy (NIR), which covers approximately 780 to 2500 nm, has many applications in the fruit and vegetables industry, and can be used to measure moisture, soluble solids content, water content, stiffness or presence of internal damage, among other parameters. In this post, the use of NIR spectroscopy for the measurement of different attributes in fruits and vegetables is reviewed.

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NIR spectroscopy applied to the wine industry

NIR spectroscopy applied to the wine industry

Wine industry requires cheap, effective and fast measurement methods, which have led to the use of near infrared (NIR) spectroscopy as a technique for measuring quality parameters throughout the production process of this industry, from grapes to wine. Currently, the main application of NIR spectroscopy in the wine industry is associated to the measurement of alcohol. However, NIR technology offers much more possibilities, as it is detailed in this post.

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Hyperspectral and multispectral imaging

Hyperspectral imaging (HSI) and multispectral imaging (MSI) are optical spectroscopy imaging techniques. They have gained importance in the last years in the world of spectroscopy, but do you really know in what they consist? In this post, we will define them, explain the different types of acquisition systems that are employed and describe their main elements, as well as mentioning their applications.

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